diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..189fdc5f98e76500e7a626f3b51e1074e5e43cc9
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16349, "bytes_utf8": 16349, "lines": 456, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 415, "bytes_utf8": 415, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16685, "cached_input_tokens": 12032, "output_tokens": 339, "reasoning_output_tokens": 229}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..8fd0be3ae6fa6f172b6b143d9e83c420b4919431
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_084bdbd6ba92f76a",
+    "api_calls": 0,
+    "input_tokens": 16685,
+    "cached_input_tokens": 12032,
+    "output_tokens": 339,
+    "total_tokens": 17024,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 10073.23,
+    "sql_execution_elapsed_ms_total": 1.15,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..872d29dee71be5f6fcb0735816eb5ca377e0403b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:29:51.935586+00:00",
+  "ended_at": "2026-05-19T15:30:02.008835+00:00",
+  "elapsed_ms": 10073.23,
+  "prompt_metrics": {
+    "chars": 16349,
+    "bytes_utf8": 16349,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 781,
+    "bytes_utf8": 781,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 415,
+      "bytes_utf8": 415,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16685,
+      "cached_input_tokens": 12032,
+      "output_tokens": 339,
+      "reasoning_output_tokens": 229
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..a78f7cbc5ba39d3c32ddbf711ec7c4225f545a4b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_h2o_group_sum",
+    "template_name": "Grouped Numeric Sum",
+    "primary_family": "subgroup_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=Location_Type, measure_col=Productivity_Score.",
+  "planned_template_id": "tpl_h2o_group_sum",
+  "bindings": {
+    "group_col": "Location_Type",
+    "measure_col": "Productivity_Score",
+    "top_k": 19,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 94.8,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..48d0375fb3845f077dc4d086784293af59a3a6fe
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40db-923b-7b70-974f-2e2c6f4fae52"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"Location_Type\\\", SUM(CAST(\\\"Productivity_Score\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"m1\\\"\\nGROUP BY \\\"Location_Type\\\"\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Applied the provided Grouped Numeric Sum template with group_col=\\\"Location_Type\\\" and measure_col=\\\"Productivity_Score\\\". Cast \\\"Productivity_Score\\\" to REAL because the schema stores it as TEXT.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16685,"cached_input_tokens":12032,"output_tokens":339,"reasoning_output_tokens":229}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..fd06c650601abbb20ffd85976183c387138f9e57
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_h2o_group_sum\nSELECT \"Location_Type\", SUM(CAST(\"Productivity_Score\" AS REAL)) AS \"total_measure\"\nFROM \"m1\"\nGROUP BY \"Location_Type\"\nORDER BY \"total_measure\" DESC;","notes":"Applied the provided Grouped Numeric Sum template with group_col=\"Location_Type\" and measure_col=\"Productivity_Score\". Cast \"Productivity_Score\" to REAL because the schema stores it as TEXT."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..4c9b4275c0c3d3fcf35bab7515093c8655bc5c54
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16899, "bytes_utf8": 16899, "lines": 456, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 632, "bytes_utf8": 632, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16827, "cached_input_tokens": 15744, "output_tokens": 421, "reasoning_output_tokens": 246}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..588f7152237e899b09e299403ce03dd8a4e417f7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_0978a623dc7f6b02",
+    "api_calls": 0,
+    "input_tokens": 16827,
+    "cached_input_tokens": 15744,
+    "output_tokens": 421,
+    "total_tokens": 17248,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 11770.09,
+    "sql_execution_elapsed_ms_total": 1.57,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..fb463f3e8cdb890b22a923aab2fe83193e66479f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:47:01.625725+00:00",
+  "ended_at": "2026-05-19T15:47:13.395852+00:00",
+  "elapsed_ms": 11770.09,
+  "prompt_metrics": {
+    "chars": 16899,
+    "bytes_utf8": 16899,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1003,
+    "bytes_utf8": 1003,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 632,
+      "bytes_utf8": 632,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16827,
+      "cached_input_tokens": 15744,
+      "output_tokens": 421,
+      "reasoning_output_tokens": 246
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..4f8f6cffbace1280e37ad48c70bb32f9ca3e5c47
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_tpch_relative_total_threshold",
+    "template_name": "Relative-to-Total Extreme Threshold",
+    "primary_family": "tail_rarity_structure",
+    "portability": "partial",
+    "sql_skeleton": "WITH grouped AS (\n    SELECT {group_col}, SUM({measure_col}) AS group_value\n    FROM {table}\n    GROUP BY {group_col}\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=Location_Type, measure_col=WFH_Days_Per_Week.",
+  "planned_template_id": "tpl_tpch_relative_total_threshold",
+  "bindings": {
+    "group_col": "Location_Type",
+    "measure_col": "WFH_Days_Per_Week",
+    "top_k": 12,
+    "top_n": 3,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 4.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "WITH grouped AS (\n    SELECT {group_col}, SUM({measure_col}) AS group_value\n    FROM {table}\n    GROUP BY {group_col}\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..7941019f3dc201c08ad563922d82b46e825588fe
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40eb-4870-7e40-ae2d-b7ae088e12db"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n    SELECT \\\"Location_Type\\\", SUM(CAST(\\\"WFH_Days_Per_Week\\\" AS REAL)) AS group_value\\n    FROM \\\"m1\\\"\\n    GROUP BY \\\"Location_Type\\\"\\n), total AS (\\n    SELECT SUM(group_value) AS total_value\\n    FROM grouped\\n)\\nSELECT g.\\\"Location_Type\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.1\\nORDER BY g.group_value DESC;\",\"notes\":\"Applied the planned template with group_col=\\\"Location_Type\\\" and measure_col=\\\"WFH_Days_Per_Week\\\". Cast \\\"WFH_Days_Per_Week\\\" from TEXT to REAL for SQLite aggregation.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16827,"cached_input_tokens":15744,"output_tokens":421,"reasoning_output_tokens":246}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e5e28128170c3dd2f05a1759bfdf9b81a95d01e0
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tpch_relative_total_threshold\nWITH grouped AS (\n    SELECT \"Location_Type\", SUM(CAST(\"WFH_Days_Per_Week\" AS REAL)) AS group_value\n    FROM \"m1\"\n    GROUP BY \"Location_Type\"\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.\"Location_Type\", g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * 0.1\nORDER BY g.group_value DESC;","notes":"Applied the planned template with group_col=\"Location_Type\" and measure_col=\"WFH_Days_Per_Week\". Cast \"WFH_Days_Per_Week\" from TEXT to REAL for SQLite aggregation."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..fccc5c2c3b7b2d9b8fc2d9d696d57283cc203675
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16496, "bytes_utf8": 16496, "lines": 454, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 584, "bytes_utf8": 584, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16734, "cached_input_tokens": 15744, "output_tokens": 518, "reasoning_output_tokens": 362}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..3f14d054bb4fa183830346cd430e8d84107bce96
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_10b98eafb0959930",
+    "api_calls": 0,
+    "input_tokens": 16734,
+    "cached_input_tokens": 15744,
+    "output_tokens": 518,
+    "total_tokens": 17252,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 18236.41,
+    "sql_execution_elapsed_ms_total": 2.56,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..738dc23571490074e973de92f1d5fcab7eb298db
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:46:43.382613+00:00",
+  "ended_at": "2026-05-19T15:47:01.619062+00:00",
+  "elapsed_ms": 18236.41,
+  "prompt_metrics": {
+    "chars": 16496,
+    "bytes_utf8": 16496,
+    "lines": 454,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1293,
+    "bytes_utf8": 1293,
+    "lines": 5,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 584,
+      "bytes_utf8": 584,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16734,
+      "cached_input_tokens": 15744,
+      "output_tokens": 518,
+      "reasoning_output_tokens": 362
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..bc3f22a1328bd7b119cebd7235e4230c868c2679
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,454 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_quantile_tail_slice",
+    "template_name": "Quantile Tail Slice",
+    "primary_family": "tail_rarity_structure",
+    "portability": "partial",
+    "sql_skeleton": "WITH buckets AS (\n    SELECT {measure_col},\n           NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n    FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;",
+    "required_roles": [
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=Stress_Level.",
+  "planned_template_id": "tpl_m4_quantile_tail_slice",
+  "bindings": {
+    "measure_col": "Stress_Level",
+    "top_k": 13,
+    "top_n": 3,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 7.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "WITH buckets AS (\n    SELECT {measure_col},\n           NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n    FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e733ce32f1eae847fd90068cd8329bfbec43c2fe
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,5 @@
+{"type":"thread.started","thread_id":"019e40eb-01c1-7722-96a3-7b2eb771fbee"}
+{"type":"turn.started"}
+{"type":"error","message":"Reconnecting... 2/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 2000000, Requested 17369. Please try again in 521ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_quantile_tail_slice\\nWITH buckets AS (\\n    SELECT\\n        CAST(\\\"Stress_Level\\\" AS REAL) AS \\\"Stress_Level\\\",\\n        NTILE(10) OVER (ORDER BY CAST(\\\"Stress_Level\\\" AS REAL) DESC) AS \\\"tail_bucket\\\"\\n    FROM \\\"m1\\\"\\n)\\nSELECT \\\"Stress_Level\\\"\\nFROM buckets\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY \\\"Stress_Level\\\" DESC;\",\"notes\":\"Used the requested Quantile Tail Slice template with measure_col bound to \\\"Stress_Level\\\" and num_tiles=10. Cast \\\"Stress_Level\\\" from TEXT to REAL so the tail bucket and descending order are numeric, not lexicographic.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16734,"cached_input_tokens":15744,"output_tokens":518,"reasoning_output_tokens":362}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..c69313ed3504138bff74e27d4fedb4a13fd610a5
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_m4_quantile_tail_slice\nWITH buckets AS (\n    SELECT\n        CAST(\"Stress_Level\" AS REAL) AS \"Stress_Level\",\n        NTILE(10) OVER (ORDER BY CAST(\"Stress_Level\" AS REAL) DESC) AS \"tail_bucket\"\n    FROM \"m1\"\n)\nSELECT \"Stress_Level\"\nFROM buckets\nWHERE \"tail_bucket\" = 1\nORDER BY \"Stress_Level\" DESC;","notes":"Used the requested Quantile Tail Slice template with measure_col bound to \"Stress_Level\" and num_tiles=10. Cast \"Stress_Level\" from TEXT to REAL so the tail bucket and descending order are numeric, not lexicographic."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..18b2f7eb023a508e139004b3e36b7a10c64f7507
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:06:22.712207+00:00",
+  "ended_at": "2026-05-19T16:06:26.989445+00:00",
+  "elapsed_ms": 4277.21,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16245,
+    "bytes_utf8": 16245,
+    "lines": 454,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_attempt_2.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..3259cc70a0ac3a617ff05d03f69417d5818b2d57
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_attempt_2.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:06:27.992388+00:00",
+  "ended_at": "2026-05-19T16:06:30.860455+00:00",
+  "elapsed_ms": 2868.02,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16245,
+    "bytes_utf8": 16245,
+    "lines": 454,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_2.txt",
+  "response_path": "cli/sql_response_attempt_2.txt",
+  "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_2.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b091af966e6fd652baa1a40d82347660cf9d42fc
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,454 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_threshold_rarity_cdf",
+    "template_name": "Threshold Rarity CDF",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};",
+    "required_roles": [
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=Age.",
+  "planned_template_id": "tpl_threshold_rarity_cdf",
+  "bindings": {
+    "measure_col": "Age",
+    "top_k": 12,
+    "top_n": 3,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 41.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_prompt_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b091af966e6fd652baa1a40d82347660cf9d42fc
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_prompt_attempt_2.txt
@@ -0,0 +1,454 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_threshold_rarity_cdf",
+    "template_name": "Threshold Rarity CDF",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};",
+    "required_roles": [
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=Age.",
+  "planned_template_id": "tpl_threshold_rarity_cdf",
+  "bindings": {
+    "measure_col": "Age",
+    "top_k": 12,
+    "top_n": 3,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 41.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..fcff87f2267e49f59815320a089c03502a5d94d7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fd-000d-7260-87ee-eb6638054cb8"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..c530b6861aff5bce9ce3f8cb88175649bd488691
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_response_attempt_1.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fd-000d-7260-87ee-eb6638054cb8"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_response_attempt_2.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..4cdf1dc6904fe83a8adae9fab2ca4e29e37a69ba
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_response_attempt_2.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fd-14a2-7b60-a523-f2e3f5160dc1"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_response_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..7b129ca541467f38b7d863093180b58bc0f0eff5
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_response_attempt_2.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fd-14a2-7b60-a523-f2e3f5160dc1"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_stderr_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_125f5b1eba679c5e/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_125f5b1eba679c5e/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..fe7faf514aff88dae4446b69fa015dd36bb79ca6
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_125f5b1eba679c5e/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16783, "bytes_utf8": 16783, "lines": 458, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 686, "bytes_utf8": 686, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16810, "cached_input_tokens": 15744, "output_tokens": 704, "reasoning_output_tokens": 516}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_125f5b1eba679c5e/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_125f5b1eba679c5e/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..cded8b70bf8dac2217ea10ec5abc225c8d4cdbbd
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_125f5b1eba679c5e/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tpcds_within_group_share\nSELECT\n  \"Team_Collaboration_Frequency\",\n  \"Quality_Score\",\n  SUM(CAST(\"Years_Experience\" AS REAL)) AS total_measure,\n  SUM(CAST(\"Years_Experience\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"Years_Experience\" AS REAL))) OVER (PARTITION BY \"Team_Collaboration_Frequency\") AS share_within_group\nFROM \"m1\"\nGROUP BY \"Team_Collaboration_Frequency\", \"Quality_Score\"\nORDER BY share_within_group DESC;","notes":"Used the fixed template bindings exactly: group_col=Team_Collaboration_Frequency, item_col=Quality_Score, measure_col=Years_Experience. Cast Years_Experience to REAL because the SQLite schema stores it as TEXT."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..b950cab0a0c8bfbf60a73eb995b8e9fae8b8a5fc
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:04:10.842074+00:00",
+  "ended_at": "2026-05-19T16:04:15.271782+00:00",
+  "elapsed_ms": 4429.68,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16660,
+    "bytes_utf8": 16660,
+    "lines": 459,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_attempt_2.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..35bc7082863362eb5716d3cb4f4618abed6b7c39
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_attempt_2.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:04:16.273658+00:00",
+  "ended_at": "2026-05-19T16:04:19.394508+00:00",
+  "elapsed_ms": 3120.82,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16660,
+    "bytes_utf8": 16660,
+    "lines": 459,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_2.txt",
+  "response_path": "cli/sql_response_attempt_2.txt",
+  "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_2.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..0f9f91a23bd91de83333b6affb5ac6c44483be4a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,459 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_group_condition_rate",
+    "template_name": "Grouped Condition Rate",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;",
+    "required_roles": [
+      "group_col",
+      "condition_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=Survey_Date, condition_col=Internet_Speed_Category.",
+  "planned_template_id": "tpl_m4_group_condition_rate",
+  "bindings": {
+    "group_col": "Survey_Date",
+    "condition_col": "Internet_Speed_Category",
+    "condition_value": "Very Fast (100+ Mbps)",
+    "positive_value": "Very Fast (100+ Mbps)",
+    "negative_value": "Fast (50-100 Mbps)",
+    "top_k": 10,
+    "top_n": 3,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 4.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_prompt_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..0f9f91a23bd91de83333b6affb5ac6c44483be4a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_prompt_attempt_2.txt
@@ -0,0 +1,459 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_group_condition_rate",
+    "template_name": "Grouped Condition Rate",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;",
+    "required_roles": [
+      "group_col",
+      "condition_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=Survey_Date, condition_col=Internet_Speed_Category.",
+  "planned_template_id": "tpl_m4_group_condition_rate",
+  "bindings": {
+    "group_col": "Survey_Date",
+    "condition_col": "Internet_Speed_Category",
+    "condition_value": "Very Fast (100+ Mbps)",
+    "positive_value": "Very Fast (100+ Mbps)",
+    "negative_value": "Fast (50-100 Mbps)",
+    "top_k": 10,
+    "top_n": 3,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 4.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..1a9639de3dc5e987386f6577e53c4513101c9aa6
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fa-fcf1-7880-8df7-f2dd6fa927bd"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..7a38437f6a2d34befa60302355d8f1757d6422c3
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_response_attempt_1.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fa-fcf1-7880-8df7-f2dd6fa927bd"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_response_attempt_2.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..1cc40ea4e88863a1721b621e48861adbeba13666
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_response_attempt_2.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fb-123c-74f3-bd28-6fd76a646857"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_response_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..7b2cae7f11afaec06b3a95ffcc9c28c3f9879879
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_response_attempt_2.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fb-123c-74f3-bd28-6fd76a646857"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_stderr_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..ba701a8de2d164aa4e838d6dcbfa9799f2d1fb27
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:11:01.104498+00:00",
+  "ended_at": "2026-05-19T16:11:04.442167+00:00",
+  "elapsed_ms": 3337.64,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16424,
+    "bytes_utf8": 16424,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_attempt_2.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..7a96faf1092ac09e91f749b73257c5846e50826b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_attempt_2.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:11:05.443960+00:00",
+  "ended_at": "2026-05-19T16:11:08.370180+00:00",
+  "elapsed_ms": 2926.19,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16424,
+    "bytes_utf8": 16424,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_2.txt",
+  "response_path": "cli/sql_response_attempt_2.txt",
+  "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_2.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..6d49d340bf1dd8a1cb49c8d7072b556d4f95bd9e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_window_partition_avg",
+    "template_name": "Window Partition Average",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Window Partition Average to probe direction_consistency with semantic role ranked_signal_view. Focus on group_col=Has_Children, measure_col=Work_Life_Balance.",
+  "planned_template_id": "tpl_m4_window_partition_avg",
+  "bindings": {
+    "group_col": "Has_Children",
+    "measure_col": "Work_Life_Balance",
+    "top_k": 14,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 8.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_prompt_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..6d49d340bf1dd8a1cb49c8d7072b556d4f95bd9e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_prompt_attempt_2.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_window_partition_avg",
+    "template_name": "Window Partition Average",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Window Partition Average to probe direction_consistency with semantic role ranked_signal_view. Focus on group_col=Has_Children, measure_col=Work_Life_Balance.",
+  "planned_template_id": "tpl_m4_window_partition_avg",
+  "bindings": {
+    "group_col": "Has_Children",
+    "measure_col": "Work_Life_Balance",
+    "top_k": 14,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 8.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..35fec5ef4cae6ce3e129941e55588eec54bde17d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4101-3f94-7f61-a51c-5a2f54b9dda6"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..88d81720e05d6ef4c5601a140ff35838105bf548
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_response_attempt_1.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4101-3f94-7f61-a51c-5a2f54b9dda6"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_response_attempt_2.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..8d284761b50e35c79a11f150d89aac0bbed90c2f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_response_attempt_2.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4101-5062-73f0-af23-d79354d3ea57"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_response_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..741fc1b0c0f2788fbf46929048680fa69580d71c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_response_attempt_2.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4101-5062-73f0-af23-d79354d3ea57"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_stderr_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..86a9bb098587e3d421ef78dec2b0a8509243a108
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/conversation.jsonl
@@ -0,0 +1,4 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16528, "bytes_utf8": 16528, "lines": 456, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "status": "failed", "error": "AI CLI command failed with exit code 1: "}
+{"attempt": 2, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_2.txt", "metrics": {"chars": 16528, "bytes_utf8": 16528, "lines": 456, "estimated_tokens": null}}
+{"attempt": 2, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_2.txt", "raw_content_path": "cli/sql_response_attempt_2.raw.txt", "stderr_path": "cli/sql_stderr_attempt_2.txt", "metrics": {"chars": 2106, "bytes_utf8": 2106, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16729, "cached_input_tokens": 15744, "output_tokens": 3116, "reasoning_output_tokens": 2388}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..007518c01083cd35e28d73dafcd1d79d415c6346
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 2,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_17bd5a0052c8c6ae",
+    "api_calls": 0,
+    "input_tokens": 16729,
+    "cached_input_tokens": 15744,
+    "output_tokens": 3116,
+    "total_tokens": 19845,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 2,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 49495.78,
+    "sql_execution_elapsed_ms_total": 8.63,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..af8ce40fc3f0966ab073181448a95c69c720dbb8
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:54:37.316723+00:00",
+  "ended_at": "2026-05-19T15:54:40.262868+00:00",
+  "elapsed_ms": 2946.11,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16528,
+    "bytes_utf8": 16528,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/sql_attempt_2.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..bb243be52660f854f1b647e63ed5f822f9ac1eec
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/sql_attempt_2.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:54:41.266541+00:00",
+  "ended_at": "2026-05-19T15:55:27.816253+00:00",
+  "elapsed_ms": 46549.67,
+  "prompt_metrics": {
+    "chars": 16528,
+    "bytes_utf8": 16528,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 2817,
+    "bytes_utf8": 2817,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 2106,
+      "bytes_utf8": 2106,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16729,
+      "cached_input_tokens": 15744,
+      "output_tokens": 3116,
+      "reasoning_output_tokens": 2388
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_2.txt",
+  "response_path": "cli/sql_response_attempt_2.txt",
+  "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_2.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/sql_prompt_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..f2a4646d854200d2a6bb7efed094bf52438fb953
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/sql_prompt_attempt_2.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=Education_Level, measure_col=WFH_Days_Per_Week.",
+  "planned_template_id": "tpl_grouped_percentile_point",
+  "bindings": {
+    "group_col": "Education_Level",
+    "measure_col": "WFH_Days_Per_Week",
+    "top_k": 16,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 4.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..27c51510946247c69d9623f441add451bb6c6841
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/sql_response_attempt_1.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f2-3c9b-7a62-8563-c0a4a6676932"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/sql_response_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..4b7402681ee7735cb927d8206f28093f211f6d2c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/sql_response_attempt_2.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_grouped_percentile_point\nWITH \"ordered\" AS (\n  SELECT\n    \"Education_Level\" AS \"group_col\",\n    CAST(\"WFH_Days_Per_Week\" AS REAL) AS \"measure_value\",\n    ROW_NUMBER() OVER (\n      PARTITION BY \"Education_Level\"\n      ORDER BY CAST(\"WFH_Days_Per_Week\" AS REAL)\n    ) AS \"rn\",\n    COUNT(*) OVER (\n      PARTITION BY \"Education_Level\"\n    ) AS \"cnt\"\n  FROM \"m1\"\n  WHERE \"Education_Level\" IS NOT NULL\n    AND \"WFH_Days_Per_Week\" IS NOT NULL\n    AND TRIM(\"Education_Level\") <> ''\n    AND TRIM(\"WFH_Days_Per_Week\") <> ''\n),\n\"targets\" AS (\n  SELECT DISTINCT\n    \"group_col\",\n    \"cnt\",\n    (1.0 + (\"cnt\" - 1) * 0.9) AS \"pos\",\n    CAST((1.0 + (\"cnt\" - 1) * 0.9) AS INT) AS \"lower_rn\",\n    CASE\n      WHEN (1.0 + (\"cnt\" - 1) * 0.9) = CAST((1.0 + (\"cnt\" - 1) * 0.9) AS INT)\n        THEN CAST((1.0 + (\"cnt\" - 1) * 0.9) AS INT)\n      ELSE CAST((1.0 + (\"cnt\" - 1) * 0.9) AS INT) + 1\n    END AS \"upper_rn\"\n  FROM \"ordered\"\n  WHERE \"cnt\" >= 5\n),\n\"bounds\" AS (\n  SELECT\n    \"t\".\"group_col\",\n    \"t\".\"pos\",\n    \"t\".\"lower_rn\",\n    \"t\".\"upper_rn\",\n    \"lo\".\"measure_value\" AS \"lower_val\",\n    \"hi\".\"measure_value\" AS \"upper_val\"\n  FROM \"targets\" AS \"t\"\n  JOIN \"ordered\" AS \"lo\"\n    ON \"lo\".\"group_col\" = \"t\".\"group_col\"\n   AND \"lo\".\"rn\" = \"t\".\"lower_rn\"\n  JOIN \"ordered\" AS \"hi\"\n    ON \"hi\".\"group_col\" = \"t\".\"group_col\"\n   AND \"hi\".\"rn\" = \"t\".\"upper_rn\"\n)\nSELECT\n  \"group_col\" AS \"Education_Level\",\n  CASE\n    WHEN \"lower_rn\" = \"upper_rn\" THEN \"lower_val\"\n    ELSE \"lower_val\" + (\"pos\" - \"lower_rn\") * (\"upper_val\" - \"lower_val\")\n  END AS \"percentile_measure\"\nFROM \"bounds\"\nORDER BY \"percentile_measure\" DESC, \"Education_Level\" ASC;","notes":"Emulates SQLite-compatible grouped PERCENTILE_CONT(0.9) for \"WFH_Days_Per_Week\" by \"Education_Level\" using window functions, casts the text measure to REAL, excludes null/blank values, and applies the bound minimum group size of 5."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/sql_stderr_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1bf8fc06dacea1e9/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1bf8fc06dacea1e9/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..fdf316d1a9c35b372dbf46a1783324d331c5f7db
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1bf8fc06dacea1e9/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16505, "bytes_utf8": 16505, "lines": 454, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 624, "bytes_utf8": 624, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16736, "cached_input_tokens": 12032, "output_tokens": 453, "reasoning_output_tokens": 282}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1bf8fc06dacea1e9/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1bf8fc06dacea1e9/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..71c790a9ca40deb77c077a12e2809bf7b77cbef2
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1bf8fc06dacea1e9/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_1bf8fc06dacea1e9",
+    "api_calls": 0,
+    "input_tokens": 16736,
+    "cached_input_tokens": 12032,
+    "output_tokens": 453,
+    "total_tokens": 17189,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 16279.34,
+    "sql_execution_elapsed_ms_total": 3.95,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1bf8fc06dacea1e9/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1bf8fc06dacea1e9/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1bf8fc06dacea1e9/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..ef417f21dd79f1ea2e2d927c796792bd92ca7067
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1bf8fc06dacea1e9/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:46:27.093087+00:00",
+  "ended_at": "2026-05-19T15:46:43.372463+00:00",
+  "elapsed_ms": 16279.34,
+  "prompt_metrics": {
+    "chars": 16505,
+    "bytes_utf8": 16505,
+    "lines": 454,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1342,
+    "bytes_utf8": 1342,
+    "lines": 5,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 624,
+      "bytes_utf8": 624,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16736,
+      "cached_input_tokens": 12032,
+      "output_tokens": 453,
+      "reasoning_output_tokens": 282
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1bf8fc06dacea1e9/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1bf8fc06dacea1e9/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..3213df7c02bd02b9cbe202fe221fed223dc3c4ea
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1bf8fc06dacea1e9/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,454 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_quantile_tail_slice",
+    "template_name": "Quantile Tail Slice",
+    "primary_family": "tail_rarity_structure",
+    "portability": "partial",
+    "sql_skeleton": "WITH buckets AS (\n    SELECT {measure_col},\n           NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n    FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;",
+    "required_roles": [
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=Job_Satisfaction.",
+  "planned_template_id": "tpl_m4_quantile_tail_slice",
+  "bindings": {
+    "measure_col": "Job_Satisfaction",
+    "top_k": 12,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 100.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "WITH buckets AS (\n    SELECT {measure_col},\n           NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n    FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1bf8fc06dacea1e9/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1bf8fc06dacea1e9/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..964d8d8df8cc8787a48194c7f4a292cf5851744e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1bf8fc06dacea1e9/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,5 @@
+{"type":"thread.started","thread_id":"019e40ea-c1b3-75f2-a69c-d52f7fbee048"}
+{"type":"turn.started"}
+{"type":"error","message":"Reconnecting... 2/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 2000000, Requested 17371. Please try again in 521ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_quantile_tail_slice\\nWITH \\\"buckets\\\" AS (\\n    SELECT\\n        CAST(\\\"Job_Satisfaction\\\" AS REAL) AS \\\"Job_Satisfaction\\\",\\n        NTILE(10) OVER (ORDER BY CAST(\\\"Job_Satisfaction\\\" AS REAL) DESC) AS \\\"tail_bucket\\\"\\n    FROM \\\"m1\\\"\\n    WHERE \\\"Job_Satisfaction\\\" IS NOT NULL\\n)\\nSELECT \\\"Job_Satisfaction\\\"\\nFROM \\\"buckets\\\"\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY \\\"Job_Satisfaction\\\" DESC;\",\"notes\":\"Uses the requested Quantile Tail Slice template on \\\"Job_Satisfaction\\\", casting from TEXT to REAL so NTILE(10) and descending sort operate numerically; returns the top decile tail values.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16736,"cached_input_tokens":12032,"output_tokens":453,"reasoning_output_tokens":282}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1bf8fc06dacea1e9/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1bf8fc06dacea1e9/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..2cb9100c8e55f252458f22d617538c596ff47131
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1bf8fc06dacea1e9/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_m4_quantile_tail_slice\nWITH \"buckets\" AS (\n    SELECT\n        CAST(\"Job_Satisfaction\" AS REAL) AS \"Job_Satisfaction\",\n        NTILE(10) OVER (ORDER BY CAST(\"Job_Satisfaction\" AS REAL) DESC) AS \"tail_bucket\"\n    FROM \"m1\"\n    WHERE \"Job_Satisfaction\" IS NOT NULL\n)\nSELECT \"Job_Satisfaction\"\nFROM \"buckets\"\nWHERE \"tail_bucket\" = 1\nORDER BY \"Job_Satisfaction\" DESC;","notes":"Uses the requested Quantile Tail Slice template on \"Job_Satisfaction\", casting from TEXT to REAL so NTILE(10) and descending sort operate numerically; returns the top decile tail values."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1bf8fc06dacea1e9/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1bf8fc06dacea1e9/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1cb01cf428f528f7/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1cb01cf428f528f7/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..d3f3e4de60540fc7b8c2124e7813e42d4e977a1f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1cb01cf428f528f7/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16336, "bytes_utf8": 16336, "lines": 456, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 366, "bytes_utf8": 366, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16681, "cached_input_tokens": 15744, "output_tokens": 413, "reasoning_output_tokens": 317}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1cb01cf428f528f7/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1cb01cf428f528f7/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..f293fd526bae4514c2673a82615aaa597a559276
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1cb01cf428f528f7/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_1cb01cf428f528f7",
+    "api_calls": 0,
+    "input_tokens": 16681,
+    "cached_input_tokens": 15744,
+    "output_tokens": 413,
+    "total_tokens": 17094,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 20926.91,
+    "sql_execution_elapsed_ms_total": 2.63,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1cb01cf428f528f7/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1cb01cf428f528f7/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1cb01cf428f528f7/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..b79ae4660e64331278162b05a5000745fd436281
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1cb01cf428f528f7/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:31:29.559462+00:00",
+  "ended_at": "2026-05-19T15:31:50.486405+00:00",
+  "elapsed_ms": 20926.91,
+  "prompt_metrics": {
+    "chars": 16336,
+    "bytes_utf8": 16336,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1726,
+    "bytes_utf8": 1726,
+    "lines": 7,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 366,
+      "bytes_utf8": 366,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16681,
+      "cached_input_tokens": 15744,
+      "output_tokens": 413,
+      "reasoning_output_tokens": 317
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1cb01cf428f528f7/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1cb01cf428f528f7/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..a0aff2390193da91c286c5e8ff7e160010f12ca9
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1cb01cf428f528f7/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_h2o_group_sum",
+    "template_name": "Grouped Numeric Sum",
+    "primary_family": "subgroup_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=Industry, measure_col=Efficiency_Rating.",
+  "planned_template_id": "tpl_h2o_group_sum",
+  "bindings": {
+    "group_col": "Industry",
+    "measure_col": "Efficiency_Rating",
+    "top_k": 13,
+    "top_n": 3,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 95.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1cb01cf428f528f7/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1cb01cf428f528f7/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..f85feb2f556c1c0b7d50261fbff152adc114e08f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1cb01cf428f528f7/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,7 @@
+{"type":"thread.started","thread_id":"019e40dd-0fb2-7202-b9b2-dcc3a4812a8a"}
+{"type":"turn.started"}
+{"type":"error","message":"Reconnecting... 2/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1984058, Requested 17316. Please try again in 41ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"error","message":"Reconnecting... 3/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1990246, Requested 17316. Please try again in 226ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"error","message":"Reconnecting... 4/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 2000000, Requested 17316. Please try again in 519ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"Industry\\\", SUM(CAST(\\\"Efficiency_Rating\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"m1\\\"\\nGROUP BY \\\"Industry\\\"\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Applied the grouped numeric sum template with \\\"Industry\\\" as the grouping column and cast \\\"Efficiency_Rating\\\" to REAL because the schema stores it as TEXT.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16681,"cached_input_tokens":15744,"output_tokens":413,"reasoning_output_tokens":317}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1cb01cf428f528f7/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1cb01cf428f528f7/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b8977958345a405959affa0b4295e49386476308
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1cb01cf428f528f7/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_h2o_group_sum\nSELECT \"Industry\", SUM(CAST(\"Efficiency_Rating\" AS REAL)) AS \"total_measure\"\nFROM \"m1\"\nGROUP BY \"Industry\"\nORDER BY \"total_measure\" DESC;","notes":"Applied the grouped numeric sum template with \"Industry\" as the grouping column and cast \"Efficiency_Rating\" to REAL because the schema stores it as TEXT."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1cb01cf428f528f7/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1cb01cf428f528f7/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1d2af5a89f2cdef4/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1d2af5a89f2cdef4/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..7c45fb3e2d10d05617f83e811090ed380f3b7533
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1d2af5a89f2cdef4/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:05:04.248410+00:00",
+  "ended_at": "2026-05-19T16:05:07.692882+00:00",
+  "elapsed_ms": 3444.44,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16639,
+    "bytes_utf8": 16639,
+    "lines": 459,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1d2af5a89f2cdef4/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1d2af5a89f2cdef4/cli/sql_attempt_2.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..46056d8a3653f7629a234bae37290b6e4da49aec
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1d2af5a89f2cdef4/cli/sql_attempt_2.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:05:08.694696+00:00",
+  "ended_at": "2026-05-19T16:05:12.054355+00:00",
+  "elapsed_ms": 3359.62,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16639,
+    "bytes_utf8": 16639,
+    "lines": 459,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_2.txt",
+  "response_path": "cli/sql_response_attempt_2.txt",
+  "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_2.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1d2af5a89f2cdef4/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1d2af5a89f2cdef4/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..7d8e90bcf55a027464ec860737114655294ad8a6
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1d2af5a89f2cdef4/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,459 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_group_condition_rate",
+    "template_name": "Grouped Condition Rate",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;",
+    "required_roles": [
+      "group_col",
+      "condition_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=Gender, condition_col=Team_Collaboration_Frequency.",
+  "planned_template_id": "tpl_m4_group_condition_rate",
+  "bindings": {
+    "group_col": "Gender",
+    "condition_col": "Team_Collaboration_Frequency",
+    "condition_value": "Few times per week",
+    "positive_value": "Daily",
+    "negative_value": "Few times per week",
+    "top_k": 17,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 98.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1d2af5a89f2cdef4/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1d2af5a89f2cdef4/cli/sql_prompt_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..7d8e90bcf55a027464ec860737114655294ad8a6
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1d2af5a89f2cdef4/cli/sql_prompt_attempt_2.txt
@@ -0,0 +1,459 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_group_condition_rate",
+    "template_name": "Grouped Condition Rate",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;",
+    "required_roles": [
+      "group_col",
+      "condition_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=Gender, condition_col=Team_Collaboration_Frequency.",
+  "planned_template_id": "tpl_m4_group_condition_rate",
+  "bindings": {
+    "group_col": "Gender",
+    "condition_col": "Team_Collaboration_Frequency",
+    "condition_value": "Few times per week",
+    "positive_value": "Daily",
+    "negative_value": "Few times per week",
+    "top_k": 17,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 98.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1d2af5a89f2cdef4/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1d2af5a89f2cdef4/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..8940226c26e46ec7119cb64826056d6c646c119d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1d2af5a89f2cdef4/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fb-cd6e-7dc3-a480-697a48631795"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1d2af5a89f2cdef4/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1d2af5a89f2cdef4/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..9a468ded8673689666587f3ad0b830a92dbc95b6
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1d2af5a89f2cdef4/cli/sql_response_attempt_1.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fb-cd6e-7dc3-a480-697a48631795"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1d2af5a89f2cdef4/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1d2af5a89f2cdef4/cli/sql_response_attempt_2.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e06260eaf36c3cc63ca0be42d9c292091a7a086f
--- /dev/null
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@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fb-dee3-7190-ace0-b6e73eae612a"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1d2af5a89f2cdef4/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1d2af5a89f2cdef4/cli/sql_response_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..7ab4bbd90e4155636bb496e8a2638c9c4a174406
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1d2af5a89f2cdef4/cli/sql_response_attempt_2.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fb-dee3-7190-ace0-b6e73eae612a"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1d2af5a89f2cdef4/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1d2af5a89f2cdef4/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1d2af5a89f2cdef4/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1d2af5a89f2cdef4/cli/sql_stderr_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1e7ab5b666473593/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1e7ab5b666473593/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..be5f65f685a14023dda2a36b3338ceccad92beda
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1e7ab5b666473593/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16346, "bytes_utf8": 16346, "lines": 456, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 405, "bytes_utf8": 405, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16683, "cached_input_tokens": 12032, "output_tokens": 237, "reasoning_output_tokens": 137}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1e7ab5b666473593/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1e7ab5b666473593/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..5660b8c2d9fe2c0631c5a8169ec795d93ae2002c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1e7ab5b666473593/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_1e7ab5b666473593",
+    "api_calls": 0,
+    "input_tokens": 16683,
+    "cached_input_tokens": 12032,
+    "output_tokens": 237,
+    "total_tokens": 16920,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 7688.91,
+    "sql_execution_elapsed_ms_total": 1.14,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1e7ab5b666473593/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1e7ab5b666473593/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1e7ab5b666473593/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..573183cfa631f19a060ee851e683658b7747ebd6
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1e7ab5b666473593/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:28:36.781528+00:00",
+  "ended_at": "2026-05-19T15:28:44.470465+00:00",
+  "elapsed_ms": 7688.91,
+  "prompt_metrics": {
+    "chars": 16346,
+    "bytes_utf8": 16346,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 759,
+    "bytes_utf8": 759,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 405,
+      "bytes_utf8": 405,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16683,
+      "cached_input_tokens": 12032,
+      "output_tokens": 237,
+      "reasoning_output_tokens": 137
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1e7ab5b666473593/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1e7ab5b666473593/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..feaa4001ac6e5072cf32b67476e7cffd1ef76362
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1e7ab5b666473593/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_h2o_group_sum",
+    "template_name": "Grouped Numeric Sum",
+    "primary_family": "subgroup_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=Education_Level, measure_col=Years_Experience.",
+  "planned_template_id": "tpl_h2o_group_sum",
+  "bindings": {
+    "group_col": "Education_Level",
+    "measure_col": "Years_Experience",
+    "top_k": 11,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 7.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1e7ab5b666473593/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1e7ab5b666473593/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e3d8a2e21a4af33785eb510d713dcc28ca210236
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1e7ab5b666473593/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40da-6cbc-7e53-ba32-0298821296b3"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"Education_Level\\\", SUM(CAST(\\\"Years_Experience\\\" AS REAL)) AS total_measure\\nFROM \\\"m1\\\"\\nGROUP BY \\\"Education_Level\\\"\\nORDER BY total_measure DESC;\",\"notes\":\"Used the provided grouped numeric sum template with group_col=\\\"Education_Level\\\" and measure_col=\\\"Years_Experience\\\". CAST to REAL because the schema stores numeric fields as TEXT in SQLite.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16683,"cached_input_tokens":12032,"output_tokens":237,"reasoning_output_tokens":137}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1e7ab5b666473593/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1e7ab5b666473593/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..bda40555f293338e236e7d84df1894788e192562
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1e7ab5b666473593/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_h2o_group_sum\nSELECT \"Education_Level\", SUM(CAST(\"Years_Experience\" AS REAL)) AS total_measure\nFROM \"m1\"\nGROUP BY \"Education_Level\"\nORDER BY total_measure DESC;","notes":"Used the provided grouped numeric sum template with group_col=\"Education_Level\" and measure_col=\"Years_Experience\". CAST to REAL because the schema stores numeric fields as TEXT in SQLite."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1e7ab5b666473593/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1e7ab5b666473593/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2309a5c59929db44/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2309a5c59929db44/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..8880e341756b73e372d1b531b700fce1746ecf5b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2309a5c59929db44/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16661, "bytes_utf8": 16661, "lines": 460, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 490, "bytes_utf8": 490, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16787, "cached_input_tokens": 15744, "output_tokens": 435, "reasoning_output_tokens": 296}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2309a5c59929db44/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2309a5c59929db44/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..af787dc849cf860135427ccb590d907f6400f95f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2309a5c59929db44/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_2309a5c59929db44",
+    "api_calls": 0,
+    "input_tokens": 16787,
+    "cached_input_tokens": 15744,
+    "output_tokens": 435,
+    "total_tokens": 17222,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 13813.3,
+    "sql_execution_elapsed_ms_total": 0.89,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2309a5c59929db44/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2309a5c59929db44/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2309a5c59929db44/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..9d3a6bec27f59b0a1876278d8d74c9bb370fd422
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2309a5c59929db44/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:43:59.813928+00:00",
+  "ended_at": "2026-05-19T15:44:13.627256+00:00",
+  "elapsed_ms": 13813.3,
+  "prompt_metrics": {
+    "chars": 16661,
+    "bytes_utf8": 16661,
+    "lines": 460,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 857,
+    "bytes_utf8": 857,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 490,
+      "bytes_utf8": 490,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16787,
+      "cached_input_tokens": 15744,
+      "output_tokens": 435,
+      "reasoning_output_tokens": 296
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2309a5c59929db44/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2309a5c59929db44/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..4e5e326f24e2134843c90ed6eb584078ccaaabc9
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2309a5c59929db44/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,460 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_c2_filtered_group_count_2d",
+    "template_name": "Filtered Two-Dimensional Group Count",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;",
+    "required_roles": [
+      "group_col",
+      "group_col_2",
+      "predicate_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Filtered Two-Dimensional Group Count to probe slice_level_consistency with semantic role count_distribution. Focus on group_col=Has_Children, group_col_2=Work_Life_Balance.",
+  "planned_template_id": "tpl_c2_filtered_group_count_2d",
+  "bindings": {
+    "group_col": "Has_Children",
+    "group_col_2": "Work_Life_Balance",
+    "predicate_col": "Work_Life_Balance",
+    "predicate_op": ">=",
+    "predicate_value": 8.0,
+    "top_k": 10,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 8.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2309a5c59929db44/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2309a5c59929db44/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..a49197ddac0674941ab746350ef180a8638ab4f6
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2309a5c59929db44/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40e8-824a-7f21-a1e1-2b08a06e82ea"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_c2_filtered_group_count_2d\\nSELECT \\\"Has_Children\\\", \\\"Work_Life_Balance\\\", COUNT(*) AS row_count\\nFROM \\\"m1\\\"\\nWHERE CAST(\\\"Work_Life_Balance\\\" AS REAL) >= 8.0\\nGROUP BY \\\"Has_Children\\\", \\\"Work_Life_Balance\\\"\\nORDER BY row_count DESC;\",\"notes\":\"Used the provided filtered two-dimensional group count template with group_col=\\\"Has_Children\\\", group_col_2=\\\"Work_Life_Balance\\\", and a numeric cast on \\\"Work_Life_Balance\\\" because the schema stores it as TEXT.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16787,"cached_input_tokens":15744,"output_tokens":435,"reasoning_output_tokens":296}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2309a5c59929db44/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2309a5c59929db44/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..d263a2b03f8500f6294762bd07e552ec42fad115
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2309a5c59929db44/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_c2_filtered_group_count_2d\nSELECT \"Has_Children\", \"Work_Life_Balance\", COUNT(*) AS row_count\nFROM \"m1\"\nWHERE CAST(\"Work_Life_Balance\" AS REAL) >= 8.0\nGROUP BY \"Has_Children\", \"Work_Life_Balance\"\nORDER BY row_count DESC;","notes":"Used the provided filtered two-dimensional group count template with group_col=\"Has_Children\", group_col_2=\"Work_Life_Balance\", and a numeric cast on \"Work_Life_Balance\" because the schema stores it as TEXT."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2309a5c59929db44/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2309a5c59929db44/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..9d7c386e8cafa4f19622c2fcef19e610d373f06d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:08:19.666934+00:00",
+  "ended_at": "2026-05-19T16:08:22.704425+00:00",
+  "elapsed_ms": 3037.46,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16308,
+    "bytes_utf8": 16308,
+    "lines": 454,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_attempt_2.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..39b25f2037f265f44df15b48dc1f665b72b1bcf9
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_attempt_2.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:08:23.706647+00:00",
+  "ended_at": "2026-05-19T16:08:27.044206+00:00",
+  "elapsed_ms": 3337.53,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16308,
+    "bytes_utf8": 16308,
+    "lines": 454,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_2.txt",
+  "response_path": "cli/sql_response_attempt_2.txt",
+  "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_2.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..60bacfe7620483194b7da869297bab90b8d43d8a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,454 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_tail_low_support_group_count_v2",
+    "template_name": "Low-Support Group Count",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT\n    {group_col},\n    COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};",
+    "required_roles": [
+      "group_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Low-Support Group Count to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=Job_Level.",
+  "planned_template_id": "tpl_tail_low_support_group_count_v2",
+  "bindings": {
+    "group_col": "Job_Level",
+    "top_k": 10,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 8.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT\n    {group_col},\n    COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_prompt_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..60bacfe7620483194b7da869297bab90b8d43d8a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_prompt_attempt_2.txt
@@ -0,0 +1,454 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_tail_low_support_group_count_v2",
+    "template_name": "Low-Support Group Count",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT\n    {group_col},\n    COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};",
+    "required_roles": [
+      "group_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Low-Support Group Count to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=Job_Level.",
+  "planned_template_id": "tpl_tail_low_support_group_count_v2",
+  "bindings": {
+    "group_col": "Job_Level",
+    "top_k": 10,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 8.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT\n    {group_col},\n    COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..d49cd510ddb121125c4727db8e22168f48e1fbe0
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fe-c8d8-7132-8096-500cfe21b66c"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..6e65d69ff034cad20096377a376e33fa1ecf18af
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_response_attempt_1.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fe-c8d8-7132-8096-500cfe21b66c"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_response_attempt_2.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..84c85a751cc9ac03c450dd2c87b49f6ae86e73d8
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_response_attempt_2.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fe-d89d-7ee0-98f1-339efa8a71fd"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_response_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..21d7166bfe4fd031a0769ae59bf741b82ab2b11a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_response_attempt_2.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fe-d89d-7ee0-98f1-339efa8a71fd"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_23265d90fe56bf1b/cli/sql_stderr_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_249b31099d1e3aec/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_249b31099d1e3aec/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..ec300f9edb22a17ea25d0ea6d3a5ebd78c2467cc
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_249b31099d1e3aec/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16503, "bytes_utf8": 16503, "lines": 456, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 1717, "bytes_utf8": 1717, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16719, "cached_input_tokens": 15744, "output_tokens": 3655, "reasoning_output_tokens": 3106}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_249b31099d1e3aec/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_249b31099d1e3aec/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..bd376a8499f7b3cbfda31eeea21a48219bfd8d08
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_249b31099d1e3aec/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_249b31099d1e3aec",
+    "api_calls": 0,
+    "input_tokens": 16719,
+    "cached_input_tokens": 15744,
+    "output_tokens": 3655,
+    "total_tokens": 20374,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 53276.48,
+    "sql_execution_elapsed_ms_total": 6.15,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_249b31099d1e3aec/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_249b31099d1e3aec/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_249b31099d1e3aec/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..5a0d16c6479ca14380305bb55363797e8ec2a823
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_249b31099d1e3aec/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:51:59.625443+00:00",
+  "ended_at": "2026-05-19T15:52:52.901954+00:00",
+  "elapsed_ms": 53276.48,
+  "prompt_metrics": {
+    "chars": 16503,
+    "bytes_utf8": 16503,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 2317,
+    "bytes_utf8": 2317,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 1717,
+      "bytes_utf8": 1717,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16719,
+      "cached_input_tokens": 15744,
+      "output_tokens": 3655,
+      "reasoning_output_tokens": 3106
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_249b31099d1e3aec/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_249b31099d1e3aec/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..891353dba0f1941ea1b5b213ed5e9cca37e5b5b6
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_249b31099d1e3aec/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=Response_Quality, measure_col=Age.",
+  "planned_template_id": "tpl_grouped_percentile_point",
+  "bindings": {
+    "group_col": "Response_Quality",
+    "measure_col": "Age",
+    "top_k": 19,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 38.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_249b31099d1e3aec/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_249b31099d1e3aec/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b88d2d6d7bf8ba3ae123fbcaa5edaf20f6bfcbb3
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_249b31099d1e3aec/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40ef-d49c-7903-82e2-3e544537f434"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ordered\\\" AS (\\n  SELECT\\n    \\\"Response_Quality\\\",\\n    CAST(\\\"Age\\\" AS REAL) AS \\\"age_value\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"Response_Quality\\\"\\n      ORDER BY CAST(\\\"Age\\\" AS REAL)\\n    ) AS \\\"rn\\\",\\n    COUNT(*) OVER (\\n      PARTITION BY \\\"Response_Quality\\\"\\n    ) AS \\\"cnt\\\"\\n  FROM \\\"m1\\\"\\n  WHERE \\\"Age\\\" IS NOT NULL\\n),\\n\\\"positions\\\" AS (\\n  SELECT DISTINCT\\n    \\\"Response_Quality\\\",\\n    (((\\\"cnt\\\" - 1) * 0.9) + 1.0) AS \\\"pos\\\"\\n  FROM \\\"ordered\\\"\\n),\\n\\\"bounds\\\" AS (\\n  SELECT\\n    \\\"Response_Quality\\\",\\n    \\\"pos\\\",\\n    CAST(\\\"pos\\\" AS INTEGER) AS \\\"lower_rn\\\",\\n    CAST(\\\"pos\\\" AS INTEGER) + CASE\\n      WHEN \\\"pos\\\" > CAST(\\\"pos\\\" AS INTEGER) THEN 1\\n      ELSE 0\\n    END AS \\\"upper_rn\\\"\\n  FROM \\\"positions\\\"\\n)\\nSELECT\\n  b.\\\"Response_Quality\\\",\\n  CASE\\n    WHEN b.\\\"lower_rn\\\" = b.\\\"upper_rn\\\" THEN\\n      MAX(CASE WHEN o.\\\"rn\\\" = b.\\\"lower_rn\\\" THEN o.\\\"age_value\\\" END)\\n    ELSE\\n      MAX(CASE WHEN o.\\\"rn\\\" = b.\\\"lower_rn\\\" THEN o.\\\"age_value\\\" END) +\\n      (b.\\\"pos\\\" - b.\\\"lower_rn\\\") * (\\n        MAX(CASE WHEN o.\\\"rn\\\" = b.\\\"upper_rn\\\" THEN o.\\\"age_value\\\" END) -\\n        MAX(CASE WHEN o.\\\"rn\\\" = b.\\\"lower_rn\\\" THEN o.\\\"age_value\\\" END)\\n      )\\n  END AS \\\"percentile_measure\\\"\\nFROM \\\"bounds\\\" AS b\\nJOIN \\\"ordered\\\" AS o\\n  ON o.\\\"Response_Quality\\\" = b.\\\"Response_Quality\\\"\\nGROUP BY\\n  b.\\\"Response_Quality\\\",\\n  b.\\\"pos\\\",\\n  b.\\\"lower_rn\\\",\\n  b.\\\"upper_rn\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\",\"notes\":\"Emulates PERCENTILE_CONT(0.9) for each \\\"Response_Quality\\\" group in SQLite using window functions and linear interpolation, casting \\\"Age\\\" from TEXT to REAL and excluding NULL ages.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16719,"cached_input_tokens":15744,"output_tokens":3655,"reasoning_output_tokens":3106}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_249b31099d1e3aec/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_249b31099d1e3aec/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..ae8882ffbe281d912caa8cc51e101d08aa147d05
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_249b31099d1e3aec/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_grouped_percentile_point\nWITH \"ordered\" AS (\n  SELECT\n    \"Response_Quality\",\n    CAST(\"Age\" AS REAL) AS \"age_value\",\n    ROW_NUMBER() OVER (\n      PARTITION BY \"Response_Quality\"\n      ORDER BY CAST(\"Age\" AS REAL)\n    ) AS \"rn\",\n    COUNT(*) OVER (\n      PARTITION BY \"Response_Quality\"\n    ) AS \"cnt\"\n  FROM \"m1\"\n  WHERE \"Age\" IS NOT NULL\n),\n\"positions\" AS (\n  SELECT DISTINCT\n    \"Response_Quality\",\n    (((\"cnt\" - 1) * 0.9) + 1.0) AS \"pos\"\n  FROM \"ordered\"\n),\n\"bounds\" AS (\n  SELECT\n    \"Response_Quality\",\n    \"pos\",\n    CAST(\"pos\" AS INTEGER) AS \"lower_rn\",\n    CAST(\"pos\" AS INTEGER) + CASE\n      WHEN \"pos\" > CAST(\"pos\" AS INTEGER) THEN 1\n      ELSE 0\n    END AS \"upper_rn\"\n  FROM \"positions\"\n)\nSELECT\n  b.\"Response_Quality\",\n  CASE\n    WHEN b.\"lower_rn\" = b.\"upper_rn\" THEN\n      MAX(CASE WHEN o.\"rn\" = b.\"lower_rn\" THEN o.\"age_value\" END)\n    ELSE\n      MAX(CASE WHEN o.\"rn\" = b.\"lower_rn\" THEN o.\"age_value\" END) +\n      (b.\"pos\" - b.\"lower_rn\") * (\n        MAX(CASE WHEN o.\"rn\" = b.\"upper_rn\" THEN o.\"age_value\" END) -\n        MAX(CASE WHEN o.\"rn\" = b.\"lower_rn\" THEN o.\"age_value\" END)\n      )\n  END AS \"percentile_measure\"\nFROM \"bounds\" AS b\nJOIN \"ordered\" AS o\n  ON o.\"Response_Quality\" = b.\"Response_Quality\"\nGROUP BY\n  b.\"Response_Quality\",\n  b.\"pos\",\n  b.\"lower_rn\",\n  b.\"upper_rn\"\nORDER BY \"percentile_measure\" DESC;","notes":"Emulates PERCENTILE_CONT(0.9) for each \"Response_Quality\" group in SQLite using window functions and linear interpolation, casting \"Age\" from TEXT to REAL and excluding NULL ages."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_249b31099d1e3aec/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_249b31099d1e3aec/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_262723f1965435fa/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_262723f1965435fa/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..5a7a0595475e4348dd0ee75e23f0bab21990e659
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_262723f1965435fa/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16503, "bytes_utf8": 16503, "lines": 456, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 1939, "bytes_utf8": 1939, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16719, "cached_input_tokens": 12032, "output_tokens": 2402, "reasoning_output_tokens": 1762}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_262723f1965435fa/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_262723f1965435fa/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..e05f08fba25825ef8a8ee571bdfc3db18d97889c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_262723f1965435fa/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_262723f1965435fa",
+    "api_calls": 0,
+    "input_tokens": 16719,
+    "cached_input_tokens": 12032,
+    "output_tokens": 2402,
+    "total_tokens": 19121,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 38864.12,
+    "sql_execution_elapsed_ms_total": 8.69,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_262723f1965435fa/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_262723f1965435fa/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_262723f1965435fa/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..6ca8c643badf59f52a7ed7e1b01319c948000d5d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_262723f1965435fa/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:51:20.747024+00:00",
+  "ended_at": "2026-05-19T15:51:59.611186+00:00",
+  "elapsed_ms": 38864.12,
+  "prompt_metrics": {
+    "chars": 16503,
+    "bytes_utf8": 16503,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 2556,
+    "bytes_utf8": 2556,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 1939,
+      "bytes_utf8": 1939,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16719,
+      "cached_input_tokens": 12032,
+      "output_tokens": 2402,
+      "reasoning_output_tokens": 1762
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_262723f1965435fa/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_262723f1965435fa/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..cadee13d067f3d6dbd875c4db6c6d797e1c8194b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_262723f1965435fa/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=Response_Quality, measure_col=Age.",
+  "planned_template_id": "tpl_grouped_percentile_point",
+  "bindings": {
+    "group_col": "Response_Quality",
+    "measure_col": "Age",
+    "top_k": 14,
+    "top_n": 3,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 41.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_262723f1965435fa/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_262723f1965435fa/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..911e7060275effa85abdcc458eb208c4f264136d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_262723f1965435fa/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40ef-3cb7-7572-a1ea-96302e7af9fe"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ordered\\\" AS (\\n  SELECT\\n    \\\"Response_Quality\\\",\\n    CAST(\\\"Age\\\" AS REAL) AS \\\"age_value\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"Response_Quality\\\"\\n      ORDER BY CAST(\\\"Age\\\" AS REAL)\\n    ) AS \\\"rn\\\",\\n    COUNT(*) OVER (\\n      PARTITION BY \\\"Response_Quality\\\"\\n    ) AS \\\"cnt\\\"\\n  FROM \\\"m1\\\"\\n  WHERE \\\"Age\\\" IS NOT NULL\\n    AND TRIM(\\\"Age\\\") <> ''\\n),\\n\\\"params\\\" AS (\\n  SELECT\\n    \\\"Response_Quality\\\",\\n    (1.0 + 0.95 * (\\\"cnt\\\" - 1)) AS \\\"pos\\\",\\n    CAST(1.0 + 0.95 * (\\\"cnt\\\" - 1) AS INTEGER) AS \\\"lower_rn\\\",\\n    CASE\\n      WHEN (1.0 + 0.95 * (\\\"cnt\\\" - 1)) > CAST(1.0 + 0.95 * (\\\"cnt\\\" - 1) AS INTEGER)\\n      THEN CAST(1.0 + 0.95 * (\\\"cnt\\\" - 1) AS INTEGER) + 1\\n      ELSE CAST(1.0 + 0.95 * (\\\"cnt\\\" - 1) AS INTEGER)\\n    END AS \\\"upper_rn\\\"\\n  FROM \\\"ordered\\\"\\n  GROUP BY \\\"Response_Quality\\\", \\\"cnt\\\"\\n),\\n\\\"bounds\\\" AS (\\n  SELECT\\n    p.\\\"Response_Quality\\\",\\n    p.\\\"pos\\\",\\n    p.\\\"lower_rn\\\",\\n    p.\\\"upper_rn\\\",\\n    MAX(CASE WHEN o.\\\"rn\\\" = p.\\\"lower_rn\\\" THEN o.\\\"age_value\\\" END) AS \\\"lower_value\\\",\\n    MAX(CASE WHEN o.\\\"rn\\\" = p.\\\"upper_rn\\\" THEN o.\\\"age_value\\\" END) AS \\\"upper_value\\\"\\n  FROM \\\"params\\\" AS p\\n  JOIN \\\"ordered\\\" AS o\\n    ON o.\\\"Response_Quality\\\" = p.\\\"Response_Quality\\\"\\n  GROUP BY\\n    p.\\\"Response_Quality\\\",\\n    p.\\\"pos\\\",\\n    p.\\\"lower_rn\\\",\\n    p.\\\"upper_rn\\\"\\n)\\nSELECT\\n  \\\"Response_Quality\\\",\\n  CASE\\n    WHEN \\\"lower_rn\\\" = \\\"upper_rn\\\" THEN \\\"lower_value\\\"\\n    ELSE \\\"lower_value\\\" + (\\\"pos\\\" - \\\"lower_rn\\\") * (\\\"upper_value\\\" - \\\"lower_value\\\")\\n  END AS \\\"percentile_measure\\\"\\nFROM \\\"bounds\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\",\"notes\":\"SQLite does not support PERCENTILE_CONT, so this emulates the 95th percentile continuously per Response_Quality with window functions and linear interpolation. Age is cast from TEXT to REAL because the schema stores numeric fields as TEXT.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16719,"cached_input_tokens":12032,"output_tokens":2402,"reasoning_output_tokens":1762}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_262723f1965435fa/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_262723f1965435fa/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..4d42be979dd1f6c4e0cce3530a5c9f8ee91af99b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_262723f1965435fa/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_grouped_percentile_point\nWITH \"ordered\" AS (\n  SELECT\n    \"Response_Quality\",\n    CAST(\"Age\" AS REAL) AS \"age_value\",\n    ROW_NUMBER() OVER (\n      PARTITION BY \"Response_Quality\"\n      ORDER BY CAST(\"Age\" AS REAL)\n    ) AS \"rn\",\n    COUNT(*) OVER (\n      PARTITION BY \"Response_Quality\"\n    ) AS \"cnt\"\n  FROM \"m1\"\n  WHERE \"Age\" IS NOT NULL\n    AND TRIM(\"Age\") <> ''\n),\n\"params\" AS (\n  SELECT\n    \"Response_Quality\",\n    (1.0 + 0.95 * (\"cnt\" - 1)) AS \"pos\",\n    CAST(1.0 + 0.95 * (\"cnt\" - 1) AS INTEGER) AS \"lower_rn\",\n    CASE\n      WHEN (1.0 + 0.95 * (\"cnt\" - 1)) > CAST(1.0 + 0.95 * (\"cnt\" - 1) AS INTEGER)\n      THEN CAST(1.0 + 0.95 * (\"cnt\" - 1) AS INTEGER) + 1\n      ELSE CAST(1.0 + 0.95 * (\"cnt\" - 1) AS INTEGER)\n    END AS \"upper_rn\"\n  FROM \"ordered\"\n  GROUP BY \"Response_Quality\", \"cnt\"\n),\n\"bounds\" AS (\n  SELECT\n    p.\"Response_Quality\",\n    p.\"pos\",\n    p.\"lower_rn\",\n    p.\"upper_rn\",\n    MAX(CASE WHEN o.\"rn\" = p.\"lower_rn\" THEN o.\"age_value\" END) AS \"lower_value\",\n    MAX(CASE WHEN o.\"rn\" = p.\"upper_rn\" THEN o.\"age_value\" END) AS \"upper_value\"\n  FROM \"params\" AS p\n  JOIN \"ordered\" AS o\n    ON o.\"Response_Quality\" = p.\"Response_Quality\"\n  GROUP BY\n    p.\"Response_Quality\",\n    p.\"pos\",\n    p.\"lower_rn\",\n    p.\"upper_rn\"\n)\nSELECT\n  \"Response_Quality\",\n  CASE\n    WHEN \"lower_rn\" = \"upper_rn\" THEN \"lower_value\"\n    ELSE \"lower_value\" + (\"pos\" - \"lower_rn\") * (\"upper_value\" - \"lower_value\")\n  END AS \"percentile_measure\"\nFROM \"bounds\"\nORDER BY \"percentile_measure\" DESC;","notes":"SQLite does not support PERCENTILE_CONT, so this emulates the 95th percentile continuously per Response_Quality with window functions and linear interpolation. Age is cast from TEXT to REAL because the schema stores numeric fields as TEXT."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_262723f1965435fa/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_262723f1965435fa/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2994e13b03622d40/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2994e13b03622d40/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..8d9b5ec93e87e3829c02867e23fb756485e5b79e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2994e13b03622d40/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,458 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_tpcds_within_group_share",
+    "template_name": "Within-Group Share of Total",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;",
+    "required_roles": [
+      "group_col",
+      "item_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=Industry, measure_col=Job_Satisfaction.",
+  "planned_template_id": "tpl_tpcds_within_group_share",
+  "bindings": {
+    "group_col": "Industry",
+    "measure_col": "Job_Satisfaction",
+    "item_col": "Years_Experience",
+    "top_k": 10,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 100.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2994e13b03622d40/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2994e13b03622d40/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..c668676577f8a6555f67927dd4a61349c2f85744
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2994e13b03622d40/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40df-d3f1-76c2-996a-ce0a06473784"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n  \\\"Industry\\\",\\n  \\\"Years_Experience\\\",\\n  SUM(CAST(\\\"Job_Satisfaction\\\" AS REAL)) AS total_measure,\\n  SUM(CAST(\\\"Job_Satisfaction\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"Job_Satisfaction\\\" AS REAL))) OVER (PARTITION BY \\\"Industry\\\") AS share_within_group\\nFROM \\\"m1\\\"\\nGROUP BY \\\"Industry\\\", \\\"Years_Experience\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Uses the provided template with bound roles group_col=\\\"Industry\\\", item_col=\\\"Years_Experience\\\", and measure_col=\\\"Job_Satisfaction\\\". \\\"Job_Satisfaction\\\" is cast to REAL because the SQLite schema stores it as TEXT.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16800,"cached_input_tokens":12032,"output_tokens":677,"reasoning_output_tokens":504}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2994e13b03622d40/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2994e13b03622d40/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..fed3769049f6c6530ce207112eb2df2bade04ce0
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:06:45.600162+00:00",
+  "ended_at": "2026-05-19T16:06:48.458244+00:00",
+  "elapsed_ms": 2858.05,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16276,
+    "bytes_utf8": 16276,
+    "lines": 454,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_attempt_2.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..2e6eab96b4048664cbde8f8c258dcb9d3bfa041a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_attempt_2.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:06:49.461745+00:00",
+  "ended_at": "2026-05-19T16:06:52.693747+00:00",
+  "elapsed_ms": 3231.95,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16276,
+    "bytes_utf8": 16276,
+    "lines": 454,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_2.txt",
+  "response_path": "cli/sql_response_attempt_2.txt",
+  "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_2.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..a4df97d5536552bfdd07c6abb246a6d25792e659
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,454 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_threshold_rarity_cdf",
+    "template_name": "Threshold Rarity CDF",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};",
+    "required_roles": [
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=Work_Hours_Per_Week.",
+  "planned_template_id": "tpl_threshold_rarity_cdf",
+  "bindings": {
+    "measure_col": "Work_Hours_Per_Week",
+    "top_k": 10,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 46.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_prompt_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..a4df97d5536552bfdd07c6abb246a6d25792e659
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_prompt_attempt_2.txt
@@ -0,0 +1,454 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_threshold_rarity_cdf",
+    "template_name": "Threshold Rarity CDF",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};",
+    "required_roles": [
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=Work_Hours_Per_Week.",
+  "planned_template_id": "tpl_threshold_rarity_cdf",
+  "bindings": {
+    "measure_col": "Work_Hours_Per_Week",
+    "top_k": 10,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 46.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..f48eb524bf15b46fd333de4cdddc0d5bf9f431d7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fd-5984-76a2-a102-b31749b83c81"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..2db6161476bf528d6740d1b13cc03a4af1ddd30f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_response_attempt_1.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fd-5984-76a2-a102-b31749b83c81"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_response_attempt_2.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..02b690614175c5b763420bf8863e2888f08c4912
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_response_attempt_2.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fd-687a-7781-b2ec-887a8eaeec9d"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_response_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b1e402a6b53636900620efa788e7e035c770e52e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_response_attempt_2.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fd-687a-7781-b2ec-887a8eaeec9d"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2c286ffbbcad8c6c/cli/sql_stderr_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..84c891e3d1ab7ef41282b316366fa69475ae1c36
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:06:38.694310+00:00",
+  "ended_at": "2026-05-19T16:06:41.648201+00:00",
+  "elapsed_ms": 2953.86,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16272,
+    "bytes_utf8": 16272,
+    "lines": 454,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_attempt_2.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..99949ab05a75dd42c1c39bc7f7d26cfe6c87fab9
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_attempt_2.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:06:42.650058+00:00",
+  "ended_at": "2026-05-19T16:06:45.597431+00:00",
+  "elapsed_ms": 2947.34,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16272,
+    "bytes_utf8": 16272,
+    "lines": 454,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_2.txt",
+  "response_path": "cli/sql_response_attempt_2.txt",
+  "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_2.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..03e752dae5ce82fecbed4369f38f3e0fd7e0f784
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,454 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_threshold_rarity_cdf",
+    "template_name": "Threshold Rarity CDF",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};",
+    "required_roles": [
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=WFH_Days_Per_Week.",
+  "planned_template_id": "tpl_threshold_rarity_cdf",
+  "bindings": {
+    "measure_col": "WFH_Days_Per_Week",
+    "top_k": 14,
+    "top_n": 5,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 4.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_prompt_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..03e752dae5ce82fecbed4369f38f3e0fd7e0f784
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_prompt_attempt_2.txt
@@ -0,0 +1,454 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_threshold_rarity_cdf",
+    "template_name": "Threshold Rarity CDF",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};",
+    "required_roles": [
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=WFH_Days_Per_Week.",
+  "planned_template_id": "tpl_threshold_rarity_cdf",
+  "bindings": {
+    "measure_col": "WFH_Days_Per_Week",
+    "top_k": 14,
+    "top_n": 5,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 4.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..232352862b8cf3ca8db1af40c6ecea6fc0f008ab
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fd-3e52-7860-889e-1b892a973ecd"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b7ad40b64f2d866db904b1bbed86d67348197b1e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_response_attempt_1.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fd-3e52-7860-889e-1b892a973ecd"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_response_attempt_2.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..178dec9b8673e3fa3a5c8af53ce511d41f08d630
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_response_attempt_2.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fd-4dcb-7ed2-b839-73835fdb2f2c"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_response_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..63f9471bbb730abdd118e926eda041c27272dbc3
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_response_attempt_2.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fd-4dcb-7ed2-b839-73835fdb2f2c"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_3fda77aad7fdc9e0/cli/sql_stderr_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_46d699e8f5e6e4e1/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_46d699e8f5e6e4e1/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..1a4c52cd41ba8491c044c59321d0945729905893
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_46d699e8f5e6e4e1/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16632, "bytes_utf8": 16632, "lines": 459, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 421, "bytes_utf8": 421, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16760, "cached_input_tokens": 12032, "output_tokens": 375, "reasoning_output_tokens": 257}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_46d699e8f5e6e4e1/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_46d699e8f5e6e4e1/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..e5f4d5ca973bf80fc92c85bb58c1d7f96cd6fd9a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_46d699e8f5e6e4e1/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_46d699e8f5e6e4e1",
+    "api_calls": 0,
+    "input_tokens": 16760,
+    "cached_input_tokens": 12032,
+    "output_tokens": 375,
+    "total_tokens": 17135,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 9661.34,
+    "sql_execution_elapsed_ms_total": 3.04,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_46d699e8f5e6e4e1/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_46d699e8f5e6e4e1/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_46d699e8f5e6e4e1/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..ebc85a6c23b16b62a70a43e4eac39a5e5294e631
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_46d699e8f5e6e4e1/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:03:24.423930+00:00",
+  "ended_at": "2026-05-19T16:03:34.085303+00:00",
+  "elapsed_ms": 9661.34,
+  "prompt_metrics": {
+    "chars": 16632,
+    "bytes_utf8": 16632,
+    "lines": 459,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 776,
+    "bytes_utf8": 776,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 421,
+      "bytes_utf8": 421,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16760,
+      "cached_input_tokens": 12032,
+      "output_tokens": 375,
+      "reasoning_output_tokens": 257
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_46d699e8f5e6e4e1/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_46d699e8f5e6e4e1/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..1f1844edef03383b7b08c9475d77e3371b60f8c3
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_46d699e8f5e6e4e1/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,459 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_group_condition_rate",
+    "template_name": "Grouped Condition Rate",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;",
+    "required_roles": [
+      "group_col",
+      "condition_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=Stress_Level, condition_col=Company_Size.",
+  "planned_template_id": "tpl_m4_group_condition_rate",
+  "bindings": {
+    "group_col": "Stress_Level",
+    "condition_col": "Company_Size",
+    "condition_value": "Large (1001-5000)",
+    "positive_value": "Large (1001-5000)",
+    "negative_value": "Medium (201-1000)",
+    "top_k": 13,
+    "top_n": 5,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 41.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_46d699e8f5e6e4e1/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_46d699e8f5e6e4e1/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..c10fe45ceb430a8aa8b9e62eb0bf40b78d2f0bd3
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_46d699e8f5e6e4e1/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fa-47a7-7723-81e9-06b45a0ec018"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"Stress_Level\\\",\\n       AVG(CASE WHEN \\\"Company_Size\\\" = 'Large (1001-5000)' THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"m1\\\"\\nGROUP BY \\\"Stress_Level\\\"\\nORDER BY \\\"condition_rate\\\" DESC;\",\"notes\":\"Computes the within-group proportion of rows with Company_Size = 'Large (1001-5000)' for each Stress_Level, following the Grouped Condition Rate template.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16760,"cached_input_tokens":12032,"output_tokens":375,"reasoning_output_tokens":257}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_46d699e8f5e6e4e1/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_46d699e8f5e6e4e1/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b4ecf8c7ee10b8da82ed615ff73837d0e83978f3
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_46d699e8f5e6e4e1/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_m4_group_condition_rate\nSELECT \"Stress_Level\",\n       AVG(CASE WHEN \"Company_Size\" = 'Large (1001-5000)' THEN 1 ELSE 0 END) AS \"condition_rate\"\nFROM \"m1\"\nGROUP BY \"Stress_Level\"\nORDER BY \"condition_rate\" DESC;","notes":"Computes the within-group proportion of rows with Company_Size = 'Large (1001-5000)' for each Stress_Level, following the Grouped Condition Rate template."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_46d699e8f5e6e4e1/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_46d699e8f5e6e4e1/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4a5dec0ab4741835/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4a5dec0ab4741835/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..30a409ac13c71d5dba51f8324bef997b27fe176b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4a5dec0ab4741835/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16780, "bytes_utf8": 16780, "lines": 458, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 826, "bytes_utf8": 826, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16811, "cached_input_tokens": 12032, "output_tokens": 744, "reasoning_output_tokens": 516}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4a5dec0ab4741835/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4a5dec0ab4741835/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..550677936f5f134830f2141df40645e01bf8c3ed
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4a5dec0ab4741835/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_4a5dec0ab4741835",
+    "api_calls": 0,
+    "input_tokens": 16811,
+    "cached_input_tokens": 12032,
+    "output_tokens": 744,
+    "total_tokens": 17555,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 13801.51,
+    "sql_execution_elapsed_ms_total": 6.16,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4a5dec0ab4741835/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4a5dec0ab4741835/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4a5dec0ab4741835/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..73b64f614a894e0596d7104bf46bd04ce54b5396
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4a5dec0ab4741835/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:35:35.198661+00:00",
+  "ended_at": "2026-05-19T15:35:49.000209+00:00",
+  "elapsed_ms": 13801.51,
+  "prompt_metrics": {
+    "chars": 16780,
+    "bytes_utf8": 16780,
+    "lines": 458,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1224,
+    "bytes_utf8": 1224,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 826,
+      "bytes_utf8": 826,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16811,
+      "cached_input_tokens": 12032,
+      "output_tokens": 744,
+      "reasoning_output_tokens": 516
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4a5dec0ab4741835/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4a5dec0ab4741835/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..2ea193f4a31a307d9ca99ea96e3a53a771b35546
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4a5dec0ab4741835/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,458 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_tpcds_within_group_share",
+    "template_name": "Within-Group Share of Total",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;",
+    "required_roles": [
+      "group_col",
+      "item_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=Internet_Speed_Category, measure_col=Work_Life_Balance.",
+  "planned_template_id": "tpl_tpcds_within_group_share",
+  "bindings": {
+    "group_col": "Internet_Speed_Category",
+    "measure_col": "Work_Life_Balance",
+    "item_col": "Productivity_Score",
+    "top_k": 12,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 8.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4a5dec0ab4741835/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4a5dec0ab4741835/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..7717273cdadaf46ecf54bb18ac7ebbcf5b2feffb
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4a5dec0ab4741835/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40e0-cf1d-79f3-a53b-5c97f3f345fd"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n  \\\"Internet_Speed_Category\\\",\\n  \\\"Productivity_Score\\\",\\n  SUM(CAST(\\\"Work_Life_Balance\\\" AS REAL)) AS total_measure,\\n  SUM(CAST(\\\"Work_Life_Balance\\\" AS REAL)) * 100.0\\n    / SUM(SUM(CAST(\\\"Work_Life_Balance\\\" AS REAL))) OVER (PARTITION BY \\\"Internet_Speed_Category\\\") AS share_within_group\\nFROM \\\"m1\\\"\\nWHERE \\\"Internet_Speed_Category\\\" IS NOT NULL\\n  AND \\\"Productivity_Score\\\" IS NOT NULL\\n  AND \\\"Work_Life_Balance\\\" IS NOT NULL\\nGROUP BY \\\"Internet_Speed_Category\\\", \\\"Productivity_Score\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Uses the requested template with group_col=\\\"Internet_Speed_Category\\\", item_col=\\\"Productivity_Score\\\", and measure_col=\\\"Work_Life_Balance\\\". CAST is applied because the schema stores these fields as TEXT in SQLite.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16811,"cached_input_tokens":12032,"output_tokens":744,"reasoning_output_tokens":516}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4a5dec0ab4741835/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4a5dec0ab4741835/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..5c62ff00931afa3ed75a73191531c89042ddd5e7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4a5dec0ab4741835/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tpcds_within_group_share\nSELECT\n  \"Internet_Speed_Category\",\n  \"Productivity_Score\",\n  SUM(CAST(\"Work_Life_Balance\" AS REAL)) AS total_measure,\n  SUM(CAST(\"Work_Life_Balance\" AS REAL)) * 100.0\n    / SUM(SUM(CAST(\"Work_Life_Balance\" AS REAL))) OVER (PARTITION BY \"Internet_Speed_Category\") AS share_within_group\nFROM \"m1\"\nWHERE \"Internet_Speed_Category\" IS NOT NULL\n  AND \"Productivity_Score\" IS NOT NULL\n  AND \"Work_Life_Balance\" IS NOT NULL\nGROUP BY \"Internet_Speed_Category\", \"Productivity_Score\"\nORDER BY share_within_group DESC;","notes":"Uses the requested template with group_col=\"Internet_Speed_Category\", item_col=\"Productivity_Score\", and measure_col=\"Work_Life_Balance\". CAST is applied because the schema stores these fields as TEXT in SQLite."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4a5dec0ab4741835/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4a5dec0ab4741835/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4c4a3b6b2b1121b9/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4c4a3b6b2b1121b9/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..5a97f5eec2ede6d1e33c72d458f0a2b69a34125e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4c4a3b6b2b1121b9/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16787, "bytes_utf8": 16787, "lines": 458, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 749, "bytes_utf8": 749, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16812, "cached_input_tokens": 12032, "output_tokens": 466, "reasoning_output_tokens": 269}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4c4a3b6b2b1121b9/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4c4a3b6b2b1121b9/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..8756e8b968d53f207ca51af81a6c509b6108bde6
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4c4a3b6b2b1121b9/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_4c4a3b6b2b1121b9",
+    "api_calls": 0,
+    "input_tokens": 16812,
+    "cached_input_tokens": 12032,
+    "output_tokens": 466,
+    "total_tokens": 17278,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 10865.21,
+    "sql_execution_elapsed_ms_total": 6.33,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4c4a3b6b2b1121b9/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4c4a3b6b2b1121b9/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4c4a3b6b2b1121b9/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..d35d44d38f06ddbaa51716d3968d503c1205902d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4c4a3b6b2b1121b9/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:35:49.011344+00:00",
+  "ended_at": "2026-05-19T15:35:59.876590+00:00",
+  "elapsed_ms": 10865.21,
+  "prompt_metrics": {
+    "chars": 16787,
+    "bytes_utf8": 16787,
+    "lines": 458,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1129,
+    "bytes_utf8": 1129,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 749,
+      "bytes_utf8": 749,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16812,
+      "cached_input_tokens": 12032,
+      "output_tokens": 466,
+      "reasoning_output_tokens": 269
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4c4a3b6b2b1121b9/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4c4a3b6b2b1121b9/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e07563c04ba41eb895e3b5d5c8af603a47d2f6a7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4c4a3b6b2b1121b9/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,458 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_tpcds_within_group_share",
+    "template_name": "Within-Group Share of Total",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;",
+    "required_roles": [
+      "group_col",
+      "item_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=Internet_Speed_Category, measure_col=Work_Life_Balance.",
+  "planned_template_id": "tpl_tpcds_within_group_share",
+  "bindings": {
+    "group_col": "Internet_Speed_Category",
+    "measure_col": "Work_Life_Balance",
+    "item_col": "Productivity_Score",
+    "top_k": 17,
+    "top_n": 7,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 7.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4c4a3b6b2b1121b9/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4c4a3b6b2b1121b9/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..79a27ed9e6917a89011f30710c23a7ba1253f849
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4c4a3b6b2b1121b9/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40e1-0520-7081-af44-e9208d837712"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"Internet_Speed_Category\\\", \\\"Productivity_Score\\\",\\n       SUM(CAST(\\\"Work_Life_Balance\\\" AS REAL)) AS total_measure,\\n       SUM(CAST(\\\"Work_Life_Balance\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"Work_Life_Balance\\\" AS REAL))) OVER (PARTITION BY \\\"Internet_Speed_Category\\\") AS share_within_group\\nFROM \\\"m1\\\"\\nGROUP BY \\\"Internet_Speed_Category\\\", \\\"Productivity_Score\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Used the required Within-Group Share of Total template with bound roles: group_col=\\\"Internet_Speed_Category\\\", item_col=\\\"Productivity_Score\\\", measure_col=\\\"Work_Life_Balance\\\". CAST to REAL is applied because the schema stores numeric-looking fields as TEXT in SQLite.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16812,"cached_input_tokens":12032,"output_tokens":466,"reasoning_output_tokens":269}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4c4a3b6b2b1121b9/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4c4a3b6b2b1121b9/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..3dc48773bdb16fc24d4eeca9bb99f578a8376666
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4c4a3b6b2b1121b9/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tpcds_within_group_share\nSELECT \"Internet_Speed_Category\", \"Productivity_Score\",\n       SUM(CAST(\"Work_Life_Balance\" AS REAL)) AS total_measure,\n       SUM(CAST(\"Work_Life_Balance\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"Work_Life_Balance\" AS REAL))) OVER (PARTITION BY \"Internet_Speed_Category\") AS share_within_group\nFROM \"m1\"\nGROUP BY \"Internet_Speed_Category\", \"Productivity_Score\"\nORDER BY share_within_group DESC;","notes":"Used the required Within-Group Share of Total template with bound roles: group_col=\"Internet_Speed_Category\", item_col=\"Productivity_Score\", measure_col=\"Work_Life_Balance\". CAST to REAL is applied because the schema stores numeric-looking fields as TEXT in SQLite."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4c4a3b6b2b1121b9/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_4c4a3b6b2b1121b9/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5347a3fe8acac887/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5347a3fe8acac887/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..be46af6781aa199ef4a0a8f21bc083a998f56fa4
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5347a3fe8acac887/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16758, "bytes_utf8": 16758, "lines": 458, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 712, "bytes_utf8": 712, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16810, "cached_input_tokens": 15744, "output_tokens": 718, "reasoning_output_tokens": 516}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5347a3fe8acac887/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5347a3fe8acac887/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..98e104b606db7872a3c452ad2a025ce5aa69e097
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5347a3fe8acac887/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_5347a3fe8acac887",
+    "api_calls": 0,
+    "input_tokens": 16810,
+    "cached_input_tokens": 15744,
+    "output_tokens": 718,
+    "total_tokens": 17528,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 14230.7,
+    "sql_execution_elapsed_ms_total": 8.34,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5347a3fe8acac887/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5347a3fe8acac887/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5347a3fe8acac887/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..22e51b3cdefa0a4f76b7689468ebf3f49f9592a1
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5347a3fe8acac887/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:37:18.997531+00:00",
+  "ended_at": "2026-05-19T15:37:33.228267+00:00",
+  "elapsed_ms": 14230.7,
+  "prompt_metrics": {
+    "chars": 16758,
+    "bytes_utf8": 16758,
+    "lines": 458,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1105,
+    "bytes_utf8": 1105,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 712,
+      "bytes_utf8": 712,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16810,
+      "cached_input_tokens": 15744,
+      "output_tokens": 718,
+      "reasoning_output_tokens": 516
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5347a3fe8acac887/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5347a3fe8acac887/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..fab1e0969c2c8c002f6b8f45a99737c62d36efdc
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5347a3fe8acac887/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,458 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_tpcds_within_group_share",
+    "template_name": "Within-Group Share of Total",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;",
+    "required_roles": [
+      "group_col",
+      "item_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=Stress_Level, measure_col=WFH_Days_Per_Week.",
+  "planned_template_id": "tpl_tpcds_within_group_share",
+  "bindings": {
+    "group_col": "Stress_Level",
+    "measure_col": "WFH_Days_Per_Week",
+    "item_col": "Innovation_Score",
+    "top_k": 15,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 4.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5347a3fe8acac887/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5347a3fe8acac887/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..a12d7664981638941b39bf665c0ba538600f4c10
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5347a3fe8acac887/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40e2-6491-76e1-ad8e-d1c823b7e6e9"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"Stress_Level\\\", \\\"Innovation_Score\\\",\\n       SUM(CAST(NULLIF(\\\"WFH_Days_Per_Week\\\", '') AS REAL)) AS \\\"total_measure\\\",\\n       SUM(CAST(NULLIF(\\\"WFH_Days_Per_Week\\\", '') AS REAL)) * 100.0\\n         / SUM(SUM(CAST(NULLIF(\\\"WFH_Days_Per_Week\\\", '') AS REAL))) OVER (PARTITION BY \\\"Stress_Level\\\") AS \\\"share_within_group\\\"\\nFROM \\\"m1\\\"\\nGROUP BY \\\"Stress_Level\\\", \\\"Innovation_Score\\\"\\nORDER BY \\\"share_within_group\\\" DESC;\",\"notes\":\"Applied the Within-Group Share of Total template with group_col=\\\"Stress_Level\\\", item_col=\\\"Innovation_Score\\\", and measure_col=\\\"WFH_Days_Per_Week\\\". The measure is cast from TEXT to REAL for SQLite aggregation.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16810,"cached_input_tokens":15744,"output_tokens":718,"reasoning_output_tokens":516}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5347a3fe8acac887/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5347a3fe8acac887/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..95a64864b6c6b25bdbec51d620b48c9f4c6c9d2c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5347a3fe8acac887/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tpcds_within_group_share\nSELECT \"Stress_Level\", \"Innovation_Score\",\n       SUM(CAST(NULLIF(\"WFH_Days_Per_Week\", '') AS REAL)) AS \"total_measure\",\n       SUM(CAST(NULLIF(\"WFH_Days_Per_Week\", '') AS REAL)) * 100.0\n         / SUM(SUM(CAST(NULLIF(\"WFH_Days_Per_Week\", '') AS REAL))) OVER (PARTITION BY \"Stress_Level\") AS \"share_within_group\"\nFROM \"m1\"\nGROUP BY \"Stress_Level\", \"Innovation_Score\"\nORDER BY \"share_within_group\" DESC;","notes":"Applied the Within-Group Share of Total template with group_col=\"Stress_Level\", item_col=\"Innovation_Score\", and measure_col=\"WFH_Days_Per_Week\". The measure is cast from TEXT to REAL for SQLite aggregation."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5347a3fe8acac887/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5347a3fe8acac887/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..16b2181d921bbabc12badf9b7166e33e4ee846cd
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:09:59.821554+00:00",
+  "ended_at": "2026-05-19T16:10:04.000368+00:00",
+  "elapsed_ms": 4178.78,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16433,
+    "bytes_utf8": 16433,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_attempt_2.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..5458ac11cf6107e50f2ba6c814e17b194bddcada
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_attempt_2.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:10:05.003125+00:00",
+  "ended_at": "2026-05-19T16:10:07.946947+00:00",
+  "elapsed_ms": 2943.78,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16433,
+    "bytes_utf8": 16433,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_2.txt",
+  "response_path": "cli/sql_response_attempt_2.txt",
+  "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_2.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..d8b7a707205cf5e5949550309d1eac2db539412b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_window_partition_avg",
+    "template_name": "Window Partition Average",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Window Partition Average to probe direction_consistency with semantic role ranked_signal_view. Focus on group_col=Response_Quality, measure_col=Meetings_Per_Week.",
+  "planned_template_id": "tpl_m4_window_partition_avg",
+  "bindings": {
+    "group_col": "Response_Quality",
+    "measure_col": "Meetings_Per_Week",
+    "top_k": 10,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 10.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_prompt_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..d8b7a707205cf5e5949550309d1eac2db539412b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_prompt_attempt_2.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_window_partition_avg",
+    "template_name": "Window Partition Average",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Window Partition Average to probe direction_consistency with semantic role ranked_signal_view. Focus on group_col=Response_Quality, measure_col=Meetings_Per_Week.",
+  "planned_template_id": "tpl_m4_window_partition_avg",
+  "bindings": {
+    "group_col": "Response_Quality",
+    "measure_col": "Meetings_Per_Week",
+    "top_k": 10,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 10.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..6c11b1e2ce2d1f74186eb09e50413eef7ff43395
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4100-5002-7372-9a7d-387e6ff8c783"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..c357fed9018e676cff91a9ecea4e56ee5cc625fc
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_response_attempt_1.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4100-5002-7372-9a7d-387e6ff8c783"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_response_attempt_2.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..a891a37e84acb824c33a588bb9c4bebf27603847
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_response_attempt_2.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4100-6457-7133-9436-d475b06f3c51"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_response_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b930ef38e5801f52b4fb47f25eaa67599852e12c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_response_attempt_2.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4100-6457-7133-9436-d475b06f3c51"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_54ba1dab53703388/cli/sql_stderr_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_62f33e22c3fbc6af/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_62f33e22c3fbc6af/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..2afa2209626b7e66a6f595d712ba82178f7e9b90
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_62f33e22c3fbc6af/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16242, "bytes_utf8": 16242, "lines": 454, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 303, "bytes_utf8": 303, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16654, "cached_input_tokens": 15744, "output_tokens": 205, "reasoning_output_tokens": 124}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_62f33e22c3fbc6af/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_62f33e22c3fbc6af/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..09a544a959f7adadacaefcaefc9d972945395bf7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_62f33e22c3fbc6af/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_62f33e22c3fbc6af",
+    "api_calls": 0,
+    "input_tokens": 16654,
+    "cached_input_tokens": 15744,
+    "output_tokens": 205,
+    "total_tokens": 16859,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 14646.23,
+    "sql_execution_elapsed_ms_total": 0.92,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_62f33e22c3fbc6af/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_62f33e22c3fbc6af/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_62f33e22c3fbc6af/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..536a2ca056aae77648a4966e3fcd7da21e628947
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_62f33e22c3fbc6af/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:33:22.859902+00:00",
+  "ended_at": "2026-05-19T15:33:37.506159+00:00",
+  "elapsed_ms": 14646.23,
+  "prompt_metrics": {
+    "chars": 16242,
+    "bytes_utf8": 16242,
+    "lines": 454,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1327,
+    "bytes_utf8": 1327,
+    "lines": 6,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 303,
+      "bytes_utf8": 303,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16654,
+      "cached_input_tokens": 15744,
+      "output_tokens": 205,
+      "reasoning_output_tokens": 124
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_62f33e22c3fbc6af/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_62f33e22c3fbc6af/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b571dd29de5c974ce70ca3bf810acdc4b1fd6df4
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_62f33e22c3fbc6af/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,454 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_clickbench_group_count",
+    "template_name": "Grouped Count by Category",
+    "primary_family": "subgroup_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;",
+    "required_roles": [
+      "group_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=Education_Level.",
+  "planned_template_id": "tpl_clickbench_group_count",
+  "bindings": {
+    "group_col": "Education_Level",
+    "top_k": 13,
+    "top_n": 5,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 98.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_62f33e22c3fbc6af/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_62f33e22c3fbc6af/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..2a2ef94578ec54cd7f1f54b1917b490d806cbce7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_62f33e22c3fbc6af/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,6 @@
+{"type":"thread.started","thread_id":"019e40de-ca41-7a63-a3e0-055992e7574a"}
+{"type":"turn.started"}
+{"type":"error","message":"Reconnecting... 2/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1997799, Requested 17289. Please try again in 452ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"error","message":"Reconnecting... 3/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1987910, Requested 17289. Please try again in 155ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"Education_Level\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"m1\\\"\\nGROUP BY \\\"Education_Level\\\"\\nORDER BY \\\"row_count\\\" DESC;\",\"notes\":\"Uses the provided grouped-count template with group_col bound to \\\"Education_Level\\\" on the single table \\\"m1\\\".\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16654,"cached_input_tokens":15744,"output_tokens":205,"reasoning_output_tokens":124}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_62f33e22c3fbc6af/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_62f33e22c3fbc6af/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..ecc249da2c0cc1ce574a9d231341dea31ed8effc
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_62f33e22c3fbc6af/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_clickbench_group_count\nSELECT \"Education_Level\", COUNT(*) AS \"row_count\"\nFROM \"m1\"\nGROUP BY \"Education_Level\"\nORDER BY \"row_count\" DESC;","notes":"Uses the provided grouped-count template with group_col bound to \"Education_Level\" on the single table \"m1\"."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_62f33e22c3fbc6af/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_62f33e22c3fbc6af/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_6cdd84097e92fbfc/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_6cdd84097e92fbfc/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..06db0e893fe08fc4e6ca3ff2c24e5f380afcfe9e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_6cdd84097e92fbfc/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16894, "bytes_utf8": 16894, "lines": 456, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 701, "bytes_utf8": 701, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16821, "cached_input_tokens": 15744, "output_tokens": 593, "reasoning_output_tokens": 399}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_6cdd84097e92fbfc/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_6cdd84097e92fbfc/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..d7ca672b29baf24e42171bfec81fb8a30af7a977
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_6cdd84097e92fbfc/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_6cdd84097e92fbfc",
+    "api_calls": 0,
+    "input_tokens": 16821,
+    "cached_input_tokens": 15744,
+    "output_tokens": 593,
+    "total_tokens": 17414,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 11798.35,
+    "sql_execution_elapsed_ms_total": 3.12,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_6cdd84097e92fbfc/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_6cdd84097e92fbfc/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_6cdd84097e92fbfc/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..5f756347cb556b61f6ef629df59fc54427275bd0
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_6cdd84097e92fbfc/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:47:47.436472+00:00",
+  "ended_at": "2026-05-19T15:47:59.234883+00:00",
+  "elapsed_ms": 11798.35,
+  "prompt_metrics": {
+    "chars": 16894,
+    "bytes_utf8": 16894,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1100,
+    "bytes_utf8": 1100,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 701,
+      "bytes_utf8": 701,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16821,
+      "cached_input_tokens": 15744,
+      "output_tokens": 593,
+      "reasoning_output_tokens": 399
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_6cdd84097e92fbfc/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_6cdd84097e92fbfc/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..89f97854b59ba5294703bdcf91b26b3d2b1066bd
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_6cdd84097e92fbfc/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_tpch_relative_total_threshold",
+    "template_name": "Relative-to-Total Extreme Threshold",
+    "primary_family": "tail_rarity_structure",
+    "portability": "partial",
+    "sql_skeleton": "WITH grouped AS (\n    SELECT {group_col}, SUM({measure_col}) AS group_value\n    FROM {table}\n    GROUP BY {group_col}\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=Job_Level, measure_col=Productivity_Score.",
+  "planned_template_id": "tpl_tpch_relative_total_threshold",
+  "bindings": {
+    "group_col": "Job_Level",
+    "measure_col": "Productivity_Score",
+    "top_k": 14,
+    "top_n": 5,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 98.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "WITH grouped AS (\n    SELECT {group_col}, SUM({measure_col}) AS group_value\n    FROM {table}\n    GROUP BY {group_col}\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_6cdd84097e92fbfc/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_6cdd84097e92fbfc/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..f8277faeefe9caa9e582775797ac31ef555028a9
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_6cdd84097e92fbfc/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40eb-fbfa-7df3-8c09-f190f45e1788"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n  SELECT\\n    \\\"Job_Level\\\",\\n    SUM(CAST(\\\"Productivity_Score\\\" AS REAL)) AS \\\"group_value\\\"\\n  FROM \\\"m1\\\"\\n  GROUP BY \\\"Job_Level\\\"\\n), total AS (\\n  SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n  FROM grouped\\n)\\nSELECT\\n  g.\\\"Job_Level\\\",\\n  g.\\\"group_value\\\"\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.1\\nORDER BY g.\\\"group_value\\\" DESC;\",\"notes\":\"Used the provided Relative-to-Total Extreme Threshold template with group_col=\\\"Job_Level\\\" and measure_col=\\\"Productivity_Score\\\". CAST to REAL is applied because the schema stores numeric fields as TEXT in SQLite.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16821,"cached_input_tokens":15744,"output_tokens":593,"reasoning_output_tokens":399}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_6cdd84097e92fbfc/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_6cdd84097e92fbfc/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..1f15591fabd2cd916ab4baf510aba2b625591069
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_6cdd84097e92fbfc/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tpch_relative_total_threshold\nWITH grouped AS (\n  SELECT\n    \"Job_Level\",\n    SUM(CAST(\"Productivity_Score\" AS REAL)) AS \"group_value\"\n  FROM \"m1\"\n  GROUP BY \"Job_Level\"\n), total AS (\n  SELECT SUM(\"group_value\") AS \"total_value\"\n  FROM grouped\n)\nSELECT\n  g.\"Job_Level\",\n  g.\"group_value\"\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.\"group_value\" > t.\"total_value\" * 0.1\nORDER BY g.\"group_value\" DESC;","notes":"Used the provided Relative-to-Total Extreme Threshold template with group_col=\"Job_Level\" and measure_col=\"Productivity_Score\". CAST to REAL is applied because the schema stores numeric fields as TEXT in SQLite."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_6cdd84097e92fbfc/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_6cdd84097e92fbfc/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_72e06c3ae6c87d9c/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_72e06c3ae6c87d9c/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..ee0aae2b25e14b1746b4b6f56139ac452c881ff3
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_72e06c3ae6c87d9c/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16347, "bytes_utf8": 16347, "lines": 456, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 418, "bytes_utf8": 418, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16691, "cached_input_tokens": 12032, "output_tokens": 316, "reasoning_output_tokens": 200}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_72e06c3ae6c87d9c/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_72e06c3ae6c87d9c/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..e622cbe4aacfe5da736e57af634891379ac961d9
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_72e06c3ae6c87d9c/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_72e06c3ae6c87d9c",
+    "api_calls": 0,
+    "input_tokens": 16691,
+    "cached_input_tokens": 12032,
+    "output_tokens": 316,
+    "total_tokens": 17007,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 15180.32,
+    "sql_execution_elapsed_ms_total": 0.96,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_72e06c3ae6c87d9c/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_72e06c3ae6c87d9c/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_72e06c3ae6c87d9c/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..0511386e92e916776804a8442ea3a67131f015b2
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_72e06c3ae6c87d9c/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:29:12.187111+00:00",
+  "ended_at": "2026-05-19T15:29:27.367467+00:00",
+  "elapsed_ms": 15180.32,
+  "prompt_metrics": {
+    "chars": 16347,
+    "bytes_utf8": 16347,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 780,
+    "bytes_utf8": 780,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 418,
+      "bytes_utf8": 418,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16691,
+      "cached_input_tokens": 12032,
+      "output_tokens": 316,
+      "reasoning_output_tokens": 200
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_72e06c3ae6c87d9c/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_72e06c3ae6c87d9c/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..a6d47fb59b9929ba525de020f0e59f7e26ac37db
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_72e06c3ae6c87d9c/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_h2o_group_sum",
+    "template_name": "Grouped Numeric Sum",
+    "primary_family": "subgroup_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=Has_Children, measure_col=Work_Hours_Per_Week.",
+  "planned_template_id": "tpl_h2o_group_sum",
+  "bindings": {
+    "group_col": "Has_Children",
+    "measure_col": "Work_Hours_Per_Week",
+    "top_k": 13,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 46.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_72e06c3ae6c87d9c/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_72e06c3ae6c87d9c/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..8cd6c3599fb92ed88be7babe0a5d22886737e81d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_72e06c3ae6c87d9c/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40da-f714-7570-b088-41acf416c7cd"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"Has_Children\\\", SUM(CAST(\\\"Work_Hours_Per_Week\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"m1\\\"\\nGROUP BY \\\"Has_Children\\\"\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Uses the planned grouped-sum template with group_col=\\\"Has_Children\\\" and measure_col=\\\"Work_Hours_Per_Week\\\". CAST to REAL is added because the schema stores numeric-looking fields as TEXT in SQLite.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16691,"cached_input_tokens":12032,"output_tokens":316,"reasoning_output_tokens":200}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_72e06c3ae6c87d9c/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_72e06c3ae6c87d9c/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..6f132f2f113d1656449a3276b0afa4e6d4ce17f8
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_72e06c3ae6c87d9c/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_h2o_group_sum\nSELECT \"Has_Children\", SUM(CAST(\"Work_Hours_Per_Week\" AS REAL)) AS \"total_measure\"\nFROM \"m1\"\nGROUP BY \"Has_Children\"\nORDER BY \"total_measure\" DESC;","notes":"Uses the planned grouped-sum template with group_col=\"Has_Children\" and measure_col=\"Work_Hours_Per_Week\". CAST to REAL is added because the schema stores numeric-looking fields as TEXT in SQLite."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_72e06c3ae6c87d9c/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_72e06c3ae6c87d9c/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..bfe735e096dbe7058c7ce8e3001de247e4395c87
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:06:15.686783+00:00",
+  "ended_at": "2026-05-19T16:06:18.840411+00:00",
+  "elapsed_ms": 3153.6,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16271,
+    "bytes_utf8": 16271,
+    "lines": 454,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_attempt_2.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..9efa20b69ffc25018ecf87414f8b808740f113bb
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_attempt_2.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:06:19.842310+00:00",
+  "ended_at": "2026-05-19T16:06:22.709198+00:00",
+  "elapsed_ms": 2866.86,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16271,
+    "bytes_utf8": 16271,
+    "lines": 454,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_2.txt",
+  "response_path": "cli/sql_response_attempt_2.txt",
+  "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_2.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..fc3ac4674b88abc3218e6b165366d7a97d8bdd8f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,454 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_threshold_rarity_cdf",
+    "template_name": "Threshold Rarity CDF",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};",
+    "required_roles": [
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=Work_Life_Balance.",
+  "planned_template_id": "tpl_threshold_rarity_cdf",
+  "bindings": {
+    "measure_col": "Work_Life_Balance",
+    "top_k": 11,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 8.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_prompt_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..fc3ac4674b88abc3218e6b165366d7a97d8bdd8f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_prompt_attempt_2.txt
@@ -0,0 +1,454 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_threshold_rarity_cdf",
+    "template_name": "Threshold Rarity CDF",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};",
+    "required_roles": [
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=Work_Life_Balance.",
+  "planned_template_id": "tpl_threshold_rarity_cdf",
+  "bindings": {
+    "measure_col": "Work_Life_Balance",
+    "top_k": 11,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 8.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e44b5d30854e79bbecdcc8986c3fa6120d3ca7c2
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fc-e47a-7563-8050-bb61a7b940e5"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..7def26eef1cab58125ecbe6cd5d662fa9141ffb8
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_response_attempt_1.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fc-e47a-7563-8050-bb61a7b940e5"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_response_attempt_2.raw.txt
new file mode 100644
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+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_response_attempt_2.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fc-f4c5-7032-8f17-00e9c3f51110"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_response_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..07ef4823e545f7558b54bb081463e1e8f3f45240
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_response_attempt_2.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fc-f4c5-7032-8f17-00e9c3f51110"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_73c62cb142f70357/cli/sql_stderr_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..cd14c814277cc1b38851b59bd5304518455b5e17
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/conversation.jsonl
@@ -0,0 +1,4 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16533, "bytes_utf8": 16533, "lines": 456, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "status": "failed", "error": "AI CLI command failed with exit code 1: "}
+{"attempt": 2, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_2.txt", "metrics": {"chars": 16533, "bytes_utf8": 16533, "lines": 456, "estimated_tokens": null}}
+{"attempt": 2, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_2.txt", "raw_content_path": "cli/sql_response_attempt_2.raw.txt", "stderr_path": "cli/sql_stderr_attempt_2.txt", "metrics": {"chars": 1931, "bytes_utf8": 1931, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16729, "cached_input_tokens": 15744, "output_tokens": 1166, "reasoning_output_tokens": 516}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..7a6176d368c089d850349178e8d1254262b24999
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 2,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_760a40094161b4fe",
+    "api_calls": 0,
+    "input_tokens": 16729,
+    "cached_input_tokens": 15744,
+    "output_tokens": 1166,
+    "total_tokens": 17895,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 2,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 33186.19,
+    "sql_execution_elapsed_ms_total": 11.23,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..de59837d7858a7592dd3d357f6f17c265d41131e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:56:04.252312+00:00",
+  "ended_at": "2026-05-19T15:56:07.582320+00:00",
+  "elapsed_ms": 3329.97,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16533,
+    "bytes_utf8": 16533,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_attempt_2.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..b70f620507161d5e80f52f7e0cb48b00abe92377
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_attempt_2.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:56:08.584850+00:00",
+  "ended_at": "2026-05-19T15:56:38.441118+00:00",
+  "elapsed_ms": 29856.22,
+  "prompt_metrics": {
+    "chars": 16533,
+    "bytes_utf8": 16533,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 2530,
+    "bytes_utf8": 2530,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 1931,
+      "bytes_utf8": 1931,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16729,
+      "cached_input_tokens": 15744,
+      "output_tokens": 1166,
+      "reasoning_output_tokens": 516
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_2.txt",
+  "response_path": "cli/sql_response_attempt_2.txt",
+  "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_2.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..d054aabb2df54a0e05cb7b96fbc3d172e455ca03
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=Marital_Status, measure_col=Work_Hours_Per_Week.",
+  "planned_template_id": "tpl_grouped_percentile_point",
+  "bindings": {
+    "group_col": "Marital_Status",
+    "measure_col": "Work_Hours_Per_Week",
+    "top_k": 17,
+    "top_n": 7,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 45.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_prompt_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..d054aabb2df54a0e05cb7b96fbc3d172e455ca03
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_prompt_attempt_2.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=Marital_Status, measure_col=Work_Hours_Per_Week.",
+  "planned_template_id": "tpl_grouped_percentile_point",
+  "bindings": {
+    "group_col": "Marital_Status",
+    "measure_col": "Work_Hours_Per_Week",
+    "top_k": 17,
+    "top_n": 7,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 45.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b908963ba6feb480eaa29f20c845f5f74845c09d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f3-9037-72a0-bd35-d8cc15d70753"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..add7ba70b7f3679f6366ddf97e4a1f56cd33fc18
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_response_attempt_1.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f3-9037-72a0-bd35-d8cc15d70753"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_response_attempt_2.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..85b852c7ab604925fe3b3679e11381ccb7793ca2
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_response_attempt_2.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f3-a126-73d3-8b40-2944c0887094"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n  SELECT\\n    \\\"Marital_Status\\\" AS \\\"group_col\\\",\\n    CAST(\\\"Work_Hours_Per_Week\\\" AS REAL) AS \\\"measure_value\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"Marital_Status\\\"\\n      ORDER BY CAST(\\\"Work_Hours_Per_Week\\\" AS REAL)\\n    ) AS \\\"rn\\\",\\n    COUNT(*) OVER (\\n      PARTITION BY \\\"Marital_Status\\\"\\n    ) AS \\\"cnt\\\"\\n  FROM \\\"m1\\\"\\n  WHERE \\\"Marital_Status\\\" IS NOT NULL\\n    AND \\\"Work_Hours_Per_Week\\\" IS NOT NULL\\n),\\n\\\"positions\\\" AS (\\n  SELECT DISTINCT\\n    \\\"group_col\\\",\\n    \\\"cnt\\\",\\n    (1.0 + (\\\"cnt\\\" - 1) * 0.95) AS \\\"pos\\\",\\n    CAST((1.0 + (\\\"cnt\\\" - 1) * 0.95) AS INTEGER) AS \\\"lower_rn\\\",\\n    CASE\\n      WHEN (1.0 + (\\\"cnt\\\" - 1) * 0.95) = CAST((1.0 + (\\\"cnt\\\" - 1) * 0.95) AS INTEGER)\\n        THEN CAST((1.0 + (\\\"cnt\\\" - 1) * 0.95) AS INTEGER)\\n      ELSE CAST((1.0 + (\\\"cnt\\\" - 1) * 0.95) AS INTEGER) + 1\\n    END AS \\\"upper_rn\\\"\\n  FROM \\\"ranked\\\"\\n)\\nSELECT\\n  p.\\\"group_col\\\" AS \\\"Marital_Status\\\",\\n  CASE\\n    WHEN p.\\\"lower_rn\\\" = p.\\\"upper_rn\\\" THEN MAX(CASE WHEN r.\\\"rn\\\" = p.\\\"lower_rn\\\" THEN r.\\\"measure_value\\\" END)\\n    ELSE\\n      MAX(CASE WHEN r.\\\"rn\\\" = p.\\\"lower_rn\\\" THEN r.\\\"measure_value\\\" END) +\\n      (p.\\\"pos\\\" - p.\\\"lower_rn\\\") * (\\n        MAX(CASE WHEN r.\\\"rn\\\" = p.\\\"upper_rn\\\" THEN r.\\\"measure_value\\\" END) -\\n        MAX(CASE WHEN r.\\\"rn\\\" = p.\\\"lower_rn\\\" THEN r.\\\"measure_value\\\" END)\\n      )\\n  END AS \\\"percentile_measure\\\"\\nFROM \\\"positions\\\" AS p\\nJOIN \\\"ranked\\\" AS r\\n  ON r.\\\"group_col\\\" = p.\\\"group_col\\\"\\nGROUP BY p.\\\"group_col\\\", p.\\\"cnt\\\", p.\\\"pos\\\", p.\\\"lower_rn\\\", p.\\\"upper_rn\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\",\"notes\":\"SQLite-compatible emulation of the 95th percentile for \\\"Work_Hours_Per_Week\\\" by \\\"Marital_Status\\\", using linear interpolation to mirror PERCENTILE_CONT behavior. Casts the TEXT measure column to REAL and excludes NULL group/measure values.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16729,"cached_input_tokens":15744,"output_tokens":1166,"reasoning_output_tokens":516}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_response_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..4c5f79019136bb1b74d2126b44cca1c8ca8371c1
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_response_attempt_2.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_grouped_percentile_point\nWITH \"ranked\" AS (\n  SELECT\n    \"Marital_Status\" AS \"group_col\",\n    CAST(\"Work_Hours_Per_Week\" AS REAL) AS \"measure_value\",\n    ROW_NUMBER() OVER (\n      PARTITION BY \"Marital_Status\"\n      ORDER BY CAST(\"Work_Hours_Per_Week\" AS REAL)\n    ) AS \"rn\",\n    COUNT(*) OVER (\n      PARTITION BY \"Marital_Status\"\n    ) AS \"cnt\"\n  FROM \"m1\"\n  WHERE \"Marital_Status\" IS NOT NULL\n    AND \"Work_Hours_Per_Week\" IS NOT NULL\n),\n\"positions\" AS (\n  SELECT DISTINCT\n    \"group_col\",\n    \"cnt\",\n    (1.0 + (\"cnt\" - 1) * 0.95) AS \"pos\",\n    CAST((1.0 + (\"cnt\" - 1) * 0.95) AS INTEGER) AS \"lower_rn\",\n    CASE\n      WHEN (1.0 + (\"cnt\" - 1) * 0.95) = CAST((1.0 + (\"cnt\" - 1) * 0.95) AS INTEGER)\n        THEN CAST((1.0 + (\"cnt\" - 1) * 0.95) AS INTEGER)\n      ELSE CAST((1.0 + (\"cnt\" - 1) * 0.95) AS INTEGER) + 1\n    END AS \"upper_rn\"\n  FROM \"ranked\"\n)\nSELECT\n  p.\"group_col\" AS \"Marital_Status\",\n  CASE\n    WHEN p.\"lower_rn\" = p.\"upper_rn\" THEN MAX(CASE WHEN r.\"rn\" = p.\"lower_rn\" THEN r.\"measure_value\" END)\n    ELSE\n      MAX(CASE WHEN r.\"rn\" = p.\"lower_rn\" THEN r.\"measure_value\" END) +\n      (p.\"pos\" - p.\"lower_rn\") * (\n        MAX(CASE WHEN r.\"rn\" = p.\"upper_rn\" THEN r.\"measure_value\" END) -\n        MAX(CASE WHEN r.\"rn\" = p.\"lower_rn\" THEN r.\"measure_value\" END)\n      )\n  END AS \"percentile_measure\"\nFROM \"positions\" AS p\nJOIN \"ranked\" AS r\n  ON r.\"group_col\" = p.\"group_col\"\nGROUP BY p.\"group_col\", p.\"cnt\", p.\"pos\", p.\"lower_rn\", p.\"upper_rn\"\nORDER BY \"percentile_measure\" DESC;","notes":"SQLite-compatible emulation of the 95th percentile for \"Work_Hours_Per_Week\" by \"Marital_Status\", using linear interpolation to mirror PERCENTILE_CONT behavior. Casts the TEXT measure column to REAL and excludes NULL group/measure values."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_760a40094161b4fe/cli/sql_stderr_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7644ac366e675269/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7644ac366e675269/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..18fb62840d5f5baed3288cacae73a5c2998fe10f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7644ac366e675269/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16223, "bytes_utf8": 16223, "lines": 454, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 288, "bytes_utf8": 288, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16652, "cached_input_tokens": 12032, "output_tokens": 183, "reasoning_output_tokens": 108}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7644ac366e675269/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7644ac366e675269/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..70962f8db34c6118e6b706b0325225e0e7651c0d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7644ac366e675269/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_7644ac366e675269",
+    "api_calls": 0,
+    "input_tokens": 16652,
+    "cached_input_tokens": 12032,
+    "output_tokens": 183,
+    "total_tokens": 16835,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 7796.46,
+    "sql_execution_elapsed_ms_total": 1.49,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7644ac366e675269/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7644ac366e675269/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7644ac366e675269/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..081af3b5c30c62daac1e1d111551126a1fd53d89
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7644ac366e675269/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:33:15.055217+00:00",
+  "ended_at": "2026-05-19T15:33:22.851706+00:00",
+  "elapsed_ms": 7796.46,
+  "prompt_metrics": {
+    "chars": 16223,
+    "bytes_utf8": 16223,
+    "lines": 454,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 642,
+    "bytes_utf8": 642,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 288,
+      "bytes_utf8": 288,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16652,
+      "cached_input_tokens": 12032,
+      "output_tokens": 183,
+      "reasoning_output_tokens": 108
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7644ac366e675269/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7644ac366e675269/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..4bc570cf86d8b1bc0e6cecfa4bc4b056edfe2661
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7644ac366e675269/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,454 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_clickbench_group_count",
+    "template_name": "Grouped Count by Category",
+    "primary_family": "subgroup_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;",
+    "required_roles": [
+      "group_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=Gender.",
+  "planned_template_id": "tpl_clickbench_group_count",
+  "bindings": {
+    "group_col": "Gender",
+    "top_k": 12,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 46.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7644ac366e675269/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7644ac366e675269/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..500a6119bc47ea7352fcc0fc72addcdf1ad2dc2a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7644ac366e675269/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40de-abe2-7503-a3b4-6af0a61cd062"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"Gender\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"m1\\\"\\nGROUP BY \\\"Gender\\\"\\nORDER BY \\\"row_count\\\" DESC;\",\"notes\":\"Uses the provided grouped-count template with group_col bound to \\\"Gender\\\" to measure subgroup count distribution.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16652,"cached_input_tokens":12032,"output_tokens":183,"reasoning_output_tokens":108}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7644ac366e675269/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7644ac366e675269/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..6adbb9e70dd1a1db6ff73e4f62568180b24796f0
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7644ac366e675269/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_clickbench_group_count\nSELECT \"Gender\", COUNT(*) AS \"row_count\"\nFROM \"m1\"\nGROUP BY \"Gender\"\nORDER BY \"row_count\" DESC;","notes":"Uses the provided grouped-count template with group_col bound to \"Gender\" to measure subgroup count distribution."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7644ac366e675269/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7644ac366e675269/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_76edc40b3c5fcfd0/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_76edc40b3c5fcfd0/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..d0cbc1f9c2cfac2f0cd7358272a2f091a315e5af
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_76edc40b3c5fcfd0/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16756, "bytes_utf8": 16756, "lines": 458, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 685, "bytes_utf8": 685, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16805, "cached_input_tokens": 12032, "output_tokens": 708, "reasoning_output_tokens": 516}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_76edc40b3c5fcfd0/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_76edc40b3c5fcfd0/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..f9e2ba3160b2b445774040311835cff9db91adf8
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_76edc40b3c5fcfd0/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_76edc40b3c5fcfd0",
+    "api_calls": 0,
+    "input_tokens": 16805,
+    "cached_input_tokens": 12032,
+    "output_tokens": 708,
+    "total_tokens": 17513,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 13948.55,
+    "sql_execution_elapsed_ms_total": 9.57,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_76edc40b3c5fcfd0/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_76edc40b3c5fcfd0/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_76edc40b3c5fcfd0/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..1190764d5c2e2c38fa4cdc359adce11c31677c07
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_76edc40b3c5fcfd0/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:35:59.890016+00:00",
+  "ended_at": "2026-05-19T15:36:13.838605+00:00",
+  "elapsed_ms": 13948.55,
+  "prompt_metrics": {
+    "chars": 16756,
+    "bytes_utf8": 16756,
+    "lines": 458,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1083,
+    "bytes_utf8": 1083,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 685,
+      "bytes_utf8": 685,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16805,
+      "cached_input_tokens": 12032,
+      "output_tokens": 708,
+      "reasoning_output_tokens": 516
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_76edc40b3c5fcfd0/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_76edc40b3c5fcfd0/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..61e1d428b9b88dae4f2aa86cf5f9a1de8c0616f2
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_76edc40b3c5fcfd0/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,458 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_tpcds_within_group_share",
+    "template_name": "Within-Group Share of Total",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;",
+    "required_roles": [
+      "group_col",
+      "item_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=Manager_Support_Level, measure_col=Age.",
+  "planned_template_id": "tpl_tpcds_within_group_share",
+  "bindings": {
+    "group_col": "Manager_Support_Level",
+    "measure_col": "Age",
+    "item_col": "Task_Completion_Rate",
+    "top_k": 13,
+    "top_n": 3,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 41.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_76edc40b3c5fcfd0/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_76edc40b3c5fcfd0/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b5364d64017994c925ff7b2a78219f8774fdb984
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_76edc40b3c5fcfd0/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40e1-2f7d-7b62-9428-6eb01586d919"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n  \\\"Manager_Support_Level\\\",\\n  \\\"Task_Completion_Rate\\\",\\n  SUM(CAST(\\\"Age\\\" AS REAL)) AS \\\"total_measure\\\",\\n  SUM(CAST(\\\"Age\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"Age\\\" AS REAL))) OVER (PARTITION BY \\\"Manager_Support_Level\\\") AS \\\"share_within_group\\\"\\nFROM \\\"m1\\\"\\nGROUP BY \\\"Manager_Support_Level\\\", \\\"Task_Completion_Rate\\\"\\nORDER BY \\\"share_within_group\\\" DESC;\",\"notes\":\"Used the provided Within-Group Share of Total template with bound roles: group_col=\\\"Manager_Support_Level\\\", item_col=\\\"Task_Completion_Rate\\\", measure_col=\\\"Age\\\". Cast \\\"Age\\\" to REAL because the SQLite schema stores numeric fields as TEXT.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16805,"cached_input_tokens":12032,"output_tokens":708,"reasoning_output_tokens":516}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_76edc40b3c5fcfd0/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_76edc40b3c5fcfd0/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..4d4df7499cac81d36584669584a2f1f0c1509cd5
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_76edc40b3c5fcfd0/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tpcds_within_group_share\nSELECT\n  \"Manager_Support_Level\",\n  \"Task_Completion_Rate\",\n  SUM(CAST(\"Age\" AS REAL)) AS \"total_measure\",\n  SUM(CAST(\"Age\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"Age\" AS REAL))) OVER (PARTITION BY \"Manager_Support_Level\") AS \"share_within_group\"\nFROM \"m1\"\nGROUP BY \"Manager_Support_Level\", \"Task_Completion_Rate\"\nORDER BY \"share_within_group\" DESC;","notes":"Used the provided Within-Group Share of Total template with bound roles: group_col=\"Manager_Support_Level\", item_col=\"Task_Completion_Rate\", measure_col=\"Age\". Cast \"Age\" to REAL because the SQLite schema stores numeric fields as TEXT."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_76edc40b3c5fcfd0/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_76edc40b3c5fcfd0/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_77ca51d9786db7c5/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_77ca51d9786db7c5/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..3010add1dd21c55a84ee042f334480680426277a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_77ca51d9786db7c5/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16332, "bytes_utf8": 16332, "lines": 456, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 406, "bytes_utf8": 406, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16683, "cached_input_tokens": 12032, "output_tokens": 356, "reasoning_output_tokens": 249}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_77ca51d9786db7c5/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_77ca51d9786db7c5/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..92e17549c42033cf887557fb6836400992f3eb0a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_77ca51d9786db7c5/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_77ca51d9786db7c5",
+    "api_calls": 0,
+    "input_tokens": 16683,
+    "cached_input_tokens": 12032,
+    "output_tokens": 356,
+    "total_tokens": 17039,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 20172.19,
+    "sql_execution_elapsed_ms_total": 1.11,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_77ca51d9786db7c5/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_77ca51d9786db7c5/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_77ca51d9786db7c5/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..36b52fd7f166dd1f04be4a58f8939d0c728c2a0f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_77ca51d9786db7c5/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:30:25.275162+00:00",
+  "ended_at": "2026-05-19T15:30:45.447383+00:00",
+  "elapsed_ms": 20172.19,
+  "prompt_metrics": {
+    "chars": 16332,
+    "bytes_utf8": 16332,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1764,
+    "bytes_utf8": 1764,
+    "lines": 7,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 406,
+      "bytes_utf8": 406,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16683,
+      "cached_input_tokens": 12032,
+      "output_tokens": 356,
+      "reasoning_output_tokens": 249
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_77ca51d9786db7c5/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_77ca51d9786db7c5/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..66a481a7fc91d7eb3f9dbf4ef390d53595b3d120
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_77ca51d9786db7c5/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_h2o_group_sum",
+    "template_name": "Grouped Numeric Sum",
+    "primary_family": "subgroup_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=Job_Level, measure_col=Quality_Score.",
+  "planned_template_id": "tpl_h2o_group_sum",
+  "bindings": {
+    "group_col": "Job_Level",
+    "measure_col": "Quality_Score",
+    "top_k": 11,
+    "top_n": 5,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 96.225,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_77ca51d9786db7c5/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_77ca51d9786db7c5/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..3510b0210f58c46c4f687aea1bcc7accde315ef7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_77ca51d9786db7c5/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,7 @@
+{"type":"thread.started","thread_id":"019e40dc-148a-7ac3-8fa4-dfdac94c1139"}
+{"type":"turn.started"}
+{"type":"error","message":"Reconnecting... 2/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1984625, Requested 17318. Please try again in 58ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"error","message":"Reconnecting... 3/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1982900, Requested 17318. Please try again in 6ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"error","message":"Reconnecting... 4/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1992546, Requested 17318. Please try again in 295ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"Job_Level\\\", SUM(CAST(\\\"Quality_Score\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"m1\\\"\\nGROUP BY \\\"Job_Level\\\"\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Used the required Grouped Numeric Sum template with group_col=\\\"Job_Level\\\" and measure_col=\\\"Quality_Score\\\". CAST to REAL is included because the SQLite schema stores numeric-looking fields as TEXT.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16683,"cached_input_tokens":12032,"output_tokens":356,"reasoning_output_tokens":249}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_77ca51d9786db7c5/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_77ca51d9786db7c5/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..d980f4d7f2c74b82adaf4d176dbef809d2daf829
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_77ca51d9786db7c5/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_h2o_group_sum\nSELECT \"Job_Level\", SUM(CAST(\"Quality_Score\" AS REAL)) AS \"total_measure\"\nFROM \"m1\"\nGROUP BY \"Job_Level\"\nORDER BY \"total_measure\" DESC;","notes":"Used the required Grouped Numeric Sum template with group_col=\"Job_Level\" and measure_col=\"Quality_Score\". CAST to REAL is included because the SQLite schema stores numeric-looking fields as TEXT."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_77ca51d9786db7c5/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_77ca51d9786db7c5/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7c50fcbb8b0ad962/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7c50fcbb8b0ad962/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..69a3edf72def77ab6da8fe13b54154173e59832a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7c50fcbb8b0ad962/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16906, "bytes_utf8": 16906, "lines": 456, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 669, "bytes_utf8": 669, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16823, "cached_input_tokens": 12032, "output_tokens": 619, "reasoning_output_tokens": 445}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7c50fcbb8b0ad962/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7c50fcbb8b0ad962/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..e581b32e1a6c0eee06f2d53c831e2b35bf6631ac
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7c50fcbb8b0ad962/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_7c50fcbb8b0ad962",
+    "api_calls": 0,
+    "input_tokens": 16823,
+    "cached_input_tokens": 12032,
+    "output_tokens": 619,
+    "total_tokens": 17442,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 16125.38,
+    "sql_execution_elapsed_ms_total": 1.29,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7c50fcbb8b0ad962/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7c50fcbb8b0ad962/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7c50fcbb8b0ad962/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..750b759a9b0ab46a917e9f793d45a6e073acafb9
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7c50fcbb8b0ad962/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:48:29.427419+00:00",
+  "ended_at": "2026-05-19T15:48:45.552832+00:00",
+  "elapsed_ms": 16125.38,
+  "prompt_metrics": {
+    "chars": 16906,
+    "bytes_utf8": 16906,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1036,
+    "bytes_utf8": 1036,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 669,
+      "bytes_utf8": 669,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16823,
+      "cached_input_tokens": 12032,
+      "output_tokens": 619,
+      "reasoning_output_tokens": 445
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7c50fcbb8b0ad962/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7c50fcbb8b0ad962/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..bf301e25196529f4ef0ce0c0f3b911081777f1d8
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7c50fcbb8b0ad962/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_tpch_relative_total_threshold",
+    "template_name": "Relative-to-Total Extreme Threshold",
+    "primary_family": "tail_rarity_structure",
+    "portability": "partial",
+    "sql_skeleton": "WITH grouped AS (\n    SELECT {group_col}, SUM({measure_col}) AS group_value\n    FROM {table}\n    GROUP BY {group_col}\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=Company_Size, measure_col=Task_Completion_Rate.",
+  "planned_template_id": "tpl_tpch_relative_total_threshold",
+  "bindings": {
+    "group_col": "Company_Size",
+    "measure_col": "Task_Completion_Rate",
+    "top_k": 15,
+    "top_n": 7,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 92.1,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "WITH grouped AS (\n    SELECT {group_col}, SUM({measure_col}) AS group_value\n    FROM {table}\n    GROUP BY {group_col}\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7c50fcbb8b0ad962/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7c50fcbb8b0ad962/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..5ab901280175d3ee7362c38d1d521866cd90a8fe
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7c50fcbb8b0ad962/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40ec-9fa0-7fb3-9a3c-f40ce379e755"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n    SELECT \\\"Company_Size\\\", SUM(CAST(NULLIF(\\\"Task_Completion_Rate\\\", '') AS REAL)) AS group_value\\n    FROM \\\"m1\\\"\\n    GROUP BY \\\"Company_Size\\\"\\n), total AS (\\n    SELECT SUM(group_value) AS total_value\\n    FROM grouped\\n)\\nSELECT g.\\\"Company_Size\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.05\\nORDER BY g.group_value DESC;\",\"notes\":\"Uses the required template with group_col=\\\"Company_Size\\\" and measure_col=\\\"Task_Completion_Rate\\\". Casts the TEXT measure to REAL and treats empty strings as NULL for SQLite-safe aggregation.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16823,"cached_input_tokens":12032,"output_tokens":619,"reasoning_output_tokens":445}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7c50fcbb8b0ad962/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7c50fcbb8b0ad962/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..4991ac93df04da715607801111ac4d0ac36d4e01
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7c50fcbb8b0ad962/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tpch_relative_total_threshold\nWITH grouped AS (\n    SELECT \"Company_Size\", SUM(CAST(NULLIF(\"Task_Completion_Rate\", '') AS REAL)) AS group_value\n    FROM \"m1\"\n    GROUP BY \"Company_Size\"\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.\"Company_Size\", g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * 0.05\nORDER BY g.group_value DESC;","notes":"Uses the required template with group_col=\"Company_Size\" and measure_col=\"Task_Completion_Rate\". Casts the TEXT measure to REAL and treats empty strings as NULL for SQLite-safe aggregation."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7c50fcbb8b0ad962/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7c50fcbb8b0ad962/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..e56dac6d6b3a8c0e916bbb9eea5e21098274f33e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:11:15.729623+00:00",
+  "ended_at": "2026-05-19T16:11:20.675546+00:00",
+  "elapsed_ms": 4945.9,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16404,
+    "bytes_utf8": 16404,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_attempt_2.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..fff040e7062c4a5f889f91218662c616f4a962c3
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_attempt_2.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:11:21.678179+00:00",
+  "ended_at": "2026-05-19T16:11:24.795969+00:00",
+  "elapsed_ms": 3117.75,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16404,
+    "bytes_utf8": 16404,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_2.txt",
+  "response_path": "cli/sql_response_attempt_2.txt",
+  "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_2.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..ef85554efb6939034e90cb3dce5a55dad843e458
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_window_partition_avg",
+    "template_name": "Window Partition Average",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Window Partition Average to probe slice_level_consistency with semantic role filtered_stable_view. Focus on group_col=Location_Type, measure_col=Age.",
+  "planned_template_id": "tpl_m4_window_partition_avg",
+  "bindings": {
+    "group_col": "Location_Type",
+    "measure_col": "Age",
+    "top_k": 10,
+    "top_n": 3,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 41.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_prompt_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..ef85554efb6939034e90cb3dce5a55dad843e458
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_prompt_attempt_2.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_window_partition_avg",
+    "template_name": "Window Partition Average",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Window Partition Average to probe slice_level_consistency with semantic role filtered_stable_view. Focus on group_col=Location_Type, measure_col=Age.",
+  "planned_template_id": "tpl_m4_window_partition_avg",
+  "bindings": {
+    "group_col": "Location_Type",
+    "measure_col": "Age",
+    "top_k": 10,
+    "top_n": 3,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 41.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..d3b9b8da9c3ed919fa7209ea2889f363b18ef995
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4101-78ad-7403-88ce-d10e6a9e7e6a"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..f724fcc352b85d8300014fde652679cddfcb4a3e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_response_attempt_1.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4101-78ad-7403-88ce-d10e6a9e7e6a"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_response_attempt_2.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b20e910d7515caf497a4946c7cd20e7b5a0db421
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_response_attempt_2.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4101-8fc7-7581-9983-7c7e5508184e"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_response_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..460a8c76542577f714f3a2e1722c6592bdbc5655
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_response_attempt_2.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4101-8fc7-7581-9983-7c7e5508184e"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_7d0126f9d97d03ed/cli/sql_stderr_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8b72a0ea47b83634/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8b72a0ea47b83634/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..83c7aeda119db8b3ec02d0f5fb1caff071da44e5
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8b72a0ea47b83634/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16232, "bytes_utf8": 16232, "lines": 454, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 305, "bytes_utf8": 305, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16654, "cached_input_tokens": 12032, "output_tokens": 241, "reasoning_output_tokens": 165}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8b72a0ea47b83634/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8b72a0ea47b83634/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..df630273de162035bd82651ef0680bf26bd3a6ca
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8b72a0ea47b83634/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_8b72a0ea47b83634",
+    "api_calls": 0,
+    "input_tokens": 16654,
+    "cached_input_tokens": 12032,
+    "output_tokens": 241,
+    "total_tokens": 16895,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 9107.72,
+    "sql_execution_elapsed_ms_total": 1.78,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8b72a0ea47b83634/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8b72a0ea47b83634/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8b72a0ea47b83634/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..2001c6f221247567dd520cb0377db7ebc104de9f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8b72a0ea47b83634/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:32:51.766123+00:00",
+  "ended_at": "2026-05-19T15:33:00.873869+00:00",
+  "elapsed_ms": 9107.72,
+  "prompt_metrics": {
+    "chars": 16232,
+    "bytes_utf8": 16232,
+    "lines": 454,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 651,
+    "bytes_utf8": 651,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 305,
+      "bytes_utf8": 305,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16654,
+      "cached_input_tokens": 12032,
+      "output_tokens": 241,
+      "reasoning_output_tokens": 165
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8b72a0ea47b83634/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8b72a0ea47b83634/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..be5c89545b5c37c96b71bd31236b87625fe25d82
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8b72a0ea47b83634/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,454 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_clickbench_group_count",
+    "template_name": "Grouped Count by Category",
+    "primary_family": "subgroup_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;",
+    "required_roles": [
+      "group_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=Survey_Date.",
+  "planned_template_id": "tpl_clickbench_group_count",
+  "bindings": {
+    "group_col": "Survey_Date",
+    "top_k": 10,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 7.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8b72a0ea47b83634/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8b72a0ea47b83634/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..7a28bbc6370a1c090780cd66d422b5d7526eb38b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8b72a0ea47b83634/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40de-50c4-7502-a820-85c491ebf454"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"Survey_Date\\\", COUNT(*) AS row_count\\nFROM \\\"m1\\\"\\nGROUP BY \\\"Survey_Date\\\"\\nORDER BY row_count DESC;\",\"notes\":\"Uses the planned grouped-count template with group_col bound to \\\"Survey_Date\\\" to inspect count distribution across survey dates.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16654,"cached_input_tokens":12032,"output_tokens":241,"reasoning_output_tokens":165}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8b72a0ea47b83634/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8b72a0ea47b83634/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..d94b89a40bf9bcd71beef3fe683ff65568ccc69b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8b72a0ea47b83634/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_clickbench_group_count\nSELECT \"Survey_Date\", COUNT(*) AS row_count\nFROM \"m1\"\nGROUP BY \"Survey_Date\"\nORDER BY row_count DESC;","notes":"Uses the planned grouped-count template with group_col bound to \"Survey_Date\" to inspect count distribution across survey dates."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8b72a0ea47b83634/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8b72a0ea47b83634/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8c8663f240755a7f/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8c8663f240755a7f/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..1583076dbb34782d010491986f58644f5c84ef7e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8c8663f240755a7f/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16668, "bytes_utf8": 16668, "lines": 460, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 500, "bytes_utf8": 500, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16785, "cached_input_tokens": 15744, "output_tokens": 383, "reasoning_output_tokens": 249}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8c8663f240755a7f/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8c8663f240755a7f/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..4385c9676c09fc50128ebcb48e1020251e52745d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8c8663f240755a7f/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_8c8663f240755a7f",
+    "api_calls": 0,
+    "input_tokens": 16785,
+    "cached_input_tokens": 15744,
+    "output_tokens": 383,
+    "total_tokens": 17168,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 9716.86,
+    "sql_execution_elapsed_ms_total": 2.46,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8c8663f240755a7f/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8c8663f240755a7f/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8c8663f240755a7f/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..9391c8fbf126cc9dff6bdc153bce78359cde4cd9
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8c8663f240755a7f/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:42:58.700306+00:00",
+  "ended_at": "2026-05-19T15:43:08.417197+00:00",
+  "elapsed_ms": 9716.86,
+  "prompt_metrics": {
+    "chars": 16668,
+    "bytes_utf8": 16668,
+    "lines": 460,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 863,
+    "bytes_utf8": 863,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 500,
+      "bytes_utf8": 500,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16785,
+      "cached_input_tokens": 15744,
+      "output_tokens": 383,
+      "reasoning_output_tokens": 249
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8c8663f240755a7f/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8c8663f240755a7f/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..5a1079ca4fd5eafe262ca7b07c5781885fc82d42
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8c8663f240755a7f/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,460 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_c2_filtered_group_count_2d",
+    "template_name": "Filtered Two-Dimensional Group Count",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;",
+    "required_roles": [
+      "group_col",
+      "group_col_2",
+      "predicate_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Filtered Two-Dimensional Group Count to probe slice_level_consistency with semantic role count_distribution. Focus on group_col=Has_Children, group_col_2=Home_Office_Quality.",
+  "planned_template_id": "tpl_c2_filtered_group_count_2d",
+  "bindings": {
+    "group_col": "Has_Children",
+    "group_col_2": "Home_Office_Quality",
+    "predicate_col": "Efficiency_Rating",
+    "predicate_op": ">=",
+    "predicate_value": 95.0,
+    "top_k": 10,
+    "top_n": 5,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 95.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8c8663f240755a7f/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8c8663f240755a7f/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..909a5f11bcdccb276e875c0faf3df1e024290a1a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8c8663f240755a7f/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40e7-9395-7830-baff-883bfb36f952"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_c2_filtered_group_count_2d\\nSELECT \\\"Has_Children\\\", \\\"Home_Office_Quality\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"m1\\\"\\nWHERE CAST(\\\"Efficiency_Rating\\\" AS REAL) >= 95.0\\nGROUP BY \\\"Has_Children\\\", \\\"Home_Office_Quality\\\"\\nORDER BY \\\"row_count\\\" DESC;\",\"notes\":\"Applied the required filtered two-dimensional group count template with bound roles Has_Children, Home_Office_Quality, and Efficiency_Rating. Cast Efficiency_Rating to REAL because the schema stores it as TEXT.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16785,"cached_input_tokens":15744,"output_tokens":383,"reasoning_output_tokens":249}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8c8663f240755a7f/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8c8663f240755a7f/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b31cd0a1cd0cb9c04ab362d065b46ef8c1deaaf8
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8c8663f240755a7f/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_c2_filtered_group_count_2d\nSELECT \"Has_Children\", \"Home_Office_Quality\", COUNT(*) AS \"row_count\"\nFROM \"m1\"\nWHERE CAST(\"Efficiency_Rating\" AS REAL) >= 95.0\nGROUP BY \"Has_Children\", \"Home_Office_Quality\"\nORDER BY \"row_count\" DESC;","notes":"Applied the required filtered two-dimensional group count template with bound roles Has_Children, Home_Office_Quality, and Efficiency_Rating. Cast Efficiency_Rating to REAL because the schema stores it as TEXT."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8c8663f240755a7f/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8c8663f240755a7f/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8f7e110b469cd788/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8f7e110b469cd788/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..44211d071ef7d43ee47c9b71d3c42eb43fd6d389
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8f7e110b469cd788/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16523, "bytes_utf8": 16523, "lines": 456, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 994, "bytes_utf8": 994, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16721, "cached_input_tokens": 12032, "output_tokens": 806, "reasoning_output_tokens": 516}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8f7e110b469cd788/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8f7e110b469cd788/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..0b81b054cf064989ac2849f9fd3f38497df45062
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8f7e110b469cd788/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_8f7e110b469cd788",
+    "api_calls": 0,
+    "input_tokens": 16721,
+    "cached_input_tokens": 12032,
+    "output_tokens": 806,
+    "total_tokens": 17527,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 17620.01,
+    "sql_execution_elapsed_ms_total": 5.52,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8f7e110b469cd788/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8f7e110b469cd788/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8f7e110b469cd788/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..e88a1212267faeacd70c46aeb653921df9ed5979
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8f7e110b469cd788/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:00:45.655307+00:00",
+  "ended_at": "2026-05-19T16:01:03.275350+00:00",
+  "elapsed_ms": 17620.01,
+  "prompt_metrics": {
+    "chars": 16523,
+    "bytes_utf8": 16523,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1459,
+    "bytes_utf8": 1459,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 994,
+      "bytes_utf8": 994,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16721,
+      "cached_input_tokens": 12032,
+      "output_tokens": 806,
+      "reasoning_output_tokens": 516
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8f7e110b469cd788/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8f7e110b469cd788/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..7c4284e48110fa42ce4188ec33bf3d2c8f304e22
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8f7e110b469cd788/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=Company_Size, measure_col=Efficiency_Rating.",
+  "planned_template_id": "tpl_grouped_percentile_point",
+  "bindings": {
+    "group_col": "Company_Size",
+    "measure_col": "Efficiency_Rating",
+    "top_k": 17,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 95.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8f7e110b469cd788/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8f7e110b469cd788/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..55348d00488d32f7700f31a8ad43da4d58bae6ed
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8f7e110b469cd788/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f7-db68-7553-aa66-34b859ca488c"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n  SELECT\\n    \\\"Company_Size\\\",\\n    CAST(\\\"Efficiency_Rating\\\" AS REAL) AS \\\"measure\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"Company_Size\\\"\\n      ORDER BY CAST(\\\"Efficiency_Rating\\\" AS REAL)\\n    ) AS \\\"rn\\\",\\n    COUNT(*) OVER (PARTITION BY \\\"Company_Size\\\") AS \\\"cnt\\\"\\n  FROM \\\"m1\\\"\\n  WHERE \\\"Company_Size\\\" IS NOT NULL\\n    AND \\\"Efficiency_Rating\\\" IS NOT NULL\\n),\\n\\\"picked\\\" AS (\\n  SELECT\\n    \\\"Company_Size\\\",\\n    \\\"measure\\\",\\n    \\\"rn\\\",\\n    CAST((0.9 * \\\"cnt\\\") + 0.9999999999 AS INTEGER) AS \\\"target_rn\\\"\\n  FROM \\\"ranked\\\"\\n)\\nSELECT\\n  \\\"Company_Size\\\",\\n  \\\"measure\\\" AS \\\"percentile_measure\\\"\\nFROM \\\"picked\\\"\\nWHERE \\\"rn\\\" = \\\"target_rn\\\"\\nORDER BY \\\"percentile_measure\\\" DESC, \\\"Company_Size\\\" ASC;\",\"notes\":\"SQLite does not support PERCENTILE_CONT, so this uses a nearest-rank 90th percentile per Company_Size via window functions, casting \\\"Efficiency_Rating\\\" from TEXT to REAL.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16721,"cached_input_tokens":12032,"output_tokens":806,"reasoning_output_tokens":516}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8f7e110b469cd788/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8f7e110b469cd788/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..c07589ff1f2a547f2d790b987f8cb6013cd4c806
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8f7e110b469cd788/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_grouped_percentile_point\nWITH \"ranked\" AS (\n  SELECT\n    \"Company_Size\",\n    CAST(\"Efficiency_Rating\" AS REAL) AS \"measure\",\n    ROW_NUMBER() OVER (\n      PARTITION BY \"Company_Size\"\n      ORDER BY CAST(\"Efficiency_Rating\" AS REAL)\n    ) AS \"rn\",\n    COUNT(*) OVER (PARTITION BY \"Company_Size\") AS \"cnt\"\n  FROM \"m1\"\n  WHERE \"Company_Size\" IS NOT NULL\n    AND \"Efficiency_Rating\" IS NOT NULL\n),\n\"picked\" AS (\n  SELECT\n    \"Company_Size\",\n    \"measure\",\n    \"rn\",\n    CAST((0.9 * \"cnt\") + 0.9999999999 AS INTEGER) AS \"target_rn\"\n  FROM \"ranked\"\n)\nSELECT\n  \"Company_Size\",\n  \"measure\" AS \"percentile_measure\"\nFROM \"picked\"\nWHERE \"rn\" = \"target_rn\"\nORDER BY \"percentile_measure\" DESC, \"Company_Size\" ASC;","notes":"SQLite does not support PERCENTILE_CONT, so this uses a nearest-rank 90th percentile per Company_Size via window functions, casting \"Efficiency_Rating\" from TEXT to REAL."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8f7e110b469cd788/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_8f7e110b469cd788/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_964a68cdf278d439/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_964a68cdf278d439/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..7401b752ecbd1b715cb2c605ee8d613fd213d93b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_964a68cdf278d439/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16755, "bytes_utf8": 16755, "lines": 458, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 748, "bytes_utf8": 748, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16805, "cached_input_tokens": 12032, "output_tokens": 726, "reasoning_output_tokens": 516}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_964a68cdf278d439/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_964a68cdf278d439/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..c63b5c6bed990a9d5b62840a71b576e01ff56245
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_964a68cdf278d439/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_964a68cdf278d439",
+    "api_calls": 0,
+    "input_tokens": 16805,
+    "cached_input_tokens": 12032,
+    "output_tokens": 726,
+    "total_tokens": 17531,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 17825.06,
+    "sql_execution_elapsed_ms_total": 5.12,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_964a68cdf278d439/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_964a68cdf278d439/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_964a68cdf278d439/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..5ed54a6f8a09f212f6a9b116767f7f265fe9b7f8
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_964a68cdf278d439/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:33:52.969758+00:00",
+  "ended_at": "2026-05-19T15:34:10.794852+00:00",
+  "elapsed_ms": 17825.06,
+  "prompt_metrics": {
+    "chars": 16755,
+    "bytes_utf8": 16755,
+    "lines": 458,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1477,
+    "bytes_utf8": 1477,
+    "lines": 5,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 748,
+      "bytes_utf8": 748,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16805,
+      "cached_input_tokens": 12032,
+      "output_tokens": 726,
+      "reasoning_output_tokens": 516
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_964a68cdf278d439/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_964a68cdf278d439/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..7dd2e420db89536d749762d958084c20519ec73a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_964a68cdf278d439/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,458 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_tpcds_within_group_share",
+    "template_name": "Within-Group Share of Total",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;",
+    "required_roles": [
+      "group_col",
+      "item_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=Company_Size, measure_col=Commute_Time_Minutes.",
+  "planned_template_id": "tpl_tpcds_within_group_share",
+  "bindings": {
+    "group_col": "Company_Size",
+    "measure_col": "Commute_Time_Minutes",
+    "item_col": "Age",
+    "top_k": 14,
+    "top_n": 3,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 38.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_964a68cdf278d439/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_964a68cdf278d439/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..492f9b9a5bd2e6c5f0c88e18ac8cfdef6656f100
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_964a68cdf278d439/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,5 @@
+{"type":"thread.started","thread_id":"019e40df-3ff3-78a0-9278-25588a673b65"}
+{"type":"turn.started"}
+{"type":"error","message":"Reconnecting... 2/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1983265, Requested 17440. Please try again in 21ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n  \\\"Company_Size\\\",\\n  \\\"Age\\\",\\n  SUM(CAST(\\\"Commute_Time_Minutes\\\" AS REAL)) AS total_measure,\\n  SUM(CAST(\\\"Commute_Time_Minutes\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"Commute_Time_Minutes\\\" AS REAL))) OVER (PARTITION BY \\\"Company_Size\\\") AS share_within_group\\nFROM \\\"m1\\\"\\nWHERE \\\"Company_Size\\\" IS NOT NULL\\n  AND \\\"Age\\\" IS NOT NULL\\n  AND \\\"Commute_Time_Minutes\\\" IS NOT NULL\\nGROUP BY \\\"Company_Size\\\", \\\"Age\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Used the requested Within-Group Share of Total template with group_col=\\\"Company_Size\\\", item_col=\\\"Age\\\", and measure_col=\\\"Commute_Time_Minutes\\\". CAST to REAL is needed because the schema stores numeric fields as TEXT.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16805,"cached_input_tokens":12032,"output_tokens":726,"reasoning_output_tokens":516}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_964a68cdf278d439/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_964a68cdf278d439/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..eeae758806aa6b837faa0fe9aa9d625b62a5a239
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_964a68cdf278d439/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tpcds_within_group_share\nSELECT\n  \"Company_Size\",\n  \"Age\",\n  SUM(CAST(\"Commute_Time_Minutes\" AS REAL)) AS total_measure,\n  SUM(CAST(\"Commute_Time_Minutes\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"Commute_Time_Minutes\" AS REAL))) OVER (PARTITION BY \"Company_Size\") AS share_within_group\nFROM \"m1\"\nWHERE \"Company_Size\" IS NOT NULL\n  AND \"Age\" IS NOT NULL\n  AND \"Commute_Time_Minutes\" IS NOT NULL\nGROUP BY \"Company_Size\", \"Age\"\nORDER BY share_within_group DESC;","notes":"Used the requested Within-Group Share of Total template with group_col=\"Company_Size\", item_col=\"Age\", and measure_col=\"Commute_Time_Minutes\". CAST to REAL is needed because the schema stores numeric fields as TEXT."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_964a68cdf278d439/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_964a68cdf278d439/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..c1b0f95c56dd9a3f3d7e6972d7ce9e980d947ad1
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:10:22.789116+00:00",
+  "ended_at": "2026-05-19T16:10:27.653151+00:00",
+  "elapsed_ms": 4864.0,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16423,
+    "bytes_utf8": 16423,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_attempt_2.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..72e913e589d955147f3dbd2bc9308ceee31651d2
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_attempt_2.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:10:28.655757+00:00",
+  "ended_at": "2026-05-19T16:10:31.701906+00:00",
+  "elapsed_ms": 3046.11,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16423,
+    "bytes_utf8": 16423,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_2.txt",
+  "response_path": "cli/sql_response_attempt_2.txt",
+  "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_2.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..8dc8b6977f4c9bf1d438b8e02460f6fc00e1631b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_window_partition_avg",
+    "template_name": "Window Partition Average",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Window Partition Average to probe slice_level_consistency with semantic role ranked_signal_view. Focus on group_col=Gender, measure_col=Commute_Time_Minutes.",
+  "planned_template_id": "tpl_m4_window_partition_avg",
+  "bindings": {
+    "group_col": "Gender",
+    "measure_col": "Commute_Time_Minutes",
+    "top_k": 16,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 33.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_prompt_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..8dc8b6977f4c9bf1d438b8e02460f6fc00e1631b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_prompt_attempt_2.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_window_partition_avg",
+    "template_name": "Window Partition Average",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Window Partition Average to probe slice_level_consistency with semantic role ranked_signal_view. Focus on group_col=Gender, measure_col=Commute_Time_Minutes.",
+  "planned_template_id": "tpl_m4_window_partition_avg",
+  "bindings": {
+    "group_col": "Gender",
+    "measure_col": "Commute_Time_Minutes",
+    "top_k": 16,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 33.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..06da76149504707af7e9ab340de7faa664562937
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4100-a9d8-7be3-9534-67e1d9eacd52"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..05cf3077c182e683106e1e4ff34a0e76e042ad10
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_response_attempt_1.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4100-a9d8-7be3-9534-67e1d9eacd52"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_response_attempt_2.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..89be0590b080c83198bb95c995c121d4fc5bd1f5
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_response_attempt_2.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4100-c0d0-77a3-b454-37a60efb6236"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_response_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..5f4a3e83301b4af5b1e432bcca9cbc51b5236a65
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_response_attempt_2.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4100-c0d0-77a3-b454-37a60efb6236"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_9d795e59b326498f/cli/sql_stderr_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a09417f47adcbf76/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a09417f47adcbf76/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..595bb9ec5e8bbd7f9d9a3956443f6bea4fca81f0
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a09417f47adcbf76/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16790, "bytes_utf8": 16790, "lines": 458, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 823, "bytes_utf8": 823, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16811, "cached_input_tokens": 15744, "output_tokens": 638, "reasoning_output_tokens": 416}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a09417f47adcbf76/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a09417f47adcbf76/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..0ccc37e6126ffe96e613598c63a568f3390ebd51
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a09417f47adcbf76/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_a09417f47adcbf76",
+    "api_calls": 0,
+    "input_tokens": 16811,
+    "cached_input_tokens": 15744,
+    "output_tokens": 638,
+    "total_tokens": 17449,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 13399.44,
+    "sql_execution_elapsed_ms_total": 9.34,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a09417f47adcbf76/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a09417f47adcbf76/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a09417f47adcbf76/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..eae268c345ce0eb7541e3f606540a249fd60e67f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a09417f47adcbf76/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:36:42.566355+00:00",
+  "ended_at": "2026-05-19T15:36:55.965838+00:00",
+  "elapsed_ms": 13399.44,
+  "prompt_metrics": {
+    "chars": 16790,
+    "bytes_utf8": 16790,
+    "lines": 458,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1220,
+    "bytes_utf8": 1220,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 823,
+      "bytes_utf8": 823,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16811,
+      "cached_input_tokens": 15744,
+      "output_tokens": 638,
+      "reasoning_output_tokens": 416
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a09417f47adcbf76/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a09417f47adcbf76/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..a496c81dddf6ee8c6b1bbb6776a9b1961ebaecbc
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a09417f47adcbf76/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,458 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_tpcds_within_group_share",
+    "template_name": "Within-Group Share of Total",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;",
+    "required_roles": [
+      "group_col",
+      "item_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=Team_Collaboration_Frequency, measure_col=Years_Experience.",
+  "planned_template_id": "tpl_tpcds_within_group_share",
+  "bindings": {
+    "group_col": "Team_Collaboration_Frequency",
+    "measure_col": "Years_Experience",
+    "item_col": "Quality_Score",
+    "top_k": 19,
+    "top_n": 5,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 5.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a09417f47adcbf76/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a09417f47adcbf76/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..f545ea5f398d84266df7a1da6471ef0d7f8de2d4
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a09417f47adcbf76/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40e1-d650-76d0-9fb1-ead511946540"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n  \\\"Team_Collaboration_Frequency\\\",\\n  \\\"Quality_Score\\\",\\n  SUM(CAST(\\\"Years_Experience\\\" AS REAL)) AS total_measure,\\n  SUM(CAST(\\\"Years_Experience\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"Years_Experience\\\" AS REAL))) OVER (PARTITION BY \\\"Team_Collaboration_Frequency\\\") AS share_within_group\\nFROM \\\"m1\\\"\\nWHERE \\\"Team_Collaboration_Frequency\\\" IS NOT NULL\\n  AND \\\"Quality_Score\\\" IS NOT NULL\\n  AND \\\"Years_Experience\\\" IS NOT NULL\\nGROUP BY \\\"Team_Collaboration_Frequency\\\", \\\"Quality_Score\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Uses the requested template with group_col=\\\"Team_Collaboration_Frequency\\\", item_col=\\\"Quality_Score\\\", and measure_col=\\\"Years_Experience\\\". CAST is applied because the schema stores numeric fields as TEXT in SQLite.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16811,"cached_input_tokens":15744,"output_tokens":638,"reasoning_output_tokens":416}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a09417f47adcbf76/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a09417f47adcbf76/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..a11458b68ce7800f5e52427235db3ec34d504168
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a09417f47adcbf76/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tpcds_within_group_share\nSELECT\n  \"Team_Collaboration_Frequency\",\n  \"Quality_Score\",\n  SUM(CAST(\"Years_Experience\" AS REAL)) AS total_measure,\n  SUM(CAST(\"Years_Experience\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"Years_Experience\" AS REAL))) OVER (PARTITION BY \"Team_Collaboration_Frequency\") AS share_within_group\nFROM \"m1\"\nWHERE \"Team_Collaboration_Frequency\" IS NOT NULL\n  AND \"Quality_Score\" IS NOT NULL\n  AND \"Years_Experience\" IS NOT NULL\nGROUP BY \"Team_Collaboration_Frequency\", \"Quality_Score\"\nORDER BY share_within_group DESC;","notes":"Uses the requested template with group_col=\"Team_Collaboration_Frequency\", item_col=\"Quality_Score\", and measure_col=\"Years_Experience\". CAST is applied because the schema stores numeric fields as TEXT in SQLite."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a09417f47adcbf76/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a09417f47adcbf76/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a3405e74ec685e5f/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a3405e74ec685e5f/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..a57ae0de244db6f71f08c3175a8a235a76c13639
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a3405e74ec685e5f/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:06:00.796573+00:00",
+  "ended_at": "2026-05-19T16:06:03.962662+00:00",
+  "elapsed_ms": 3166.06,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16271,
+    "bytes_utf8": 16271,
+    "lines": 454,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a3405e74ec685e5f/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a3405e74ec685e5f/cli/sql_attempt_2.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..3bd585fb12bbf512fd0bff753297c8b83451ed8d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a3405e74ec685e5f/cli/sql_attempt_2.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:06:04.964535+00:00",
+  "ended_at": "2026-05-19T16:06:08.059668+00:00",
+  "elapsed_ms": 3095.1,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16271,
+    "bytes_utf8": 16271,
+    "lines": 454,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_2.txt",
+  "response_path": "cli/sql_response_attempt_2.txt",
+  "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_2.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a3405e74ec685e5f/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a3405e74ec685e5f/cli/sql_prompt_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..32c2ae04278952e177cab3549b1e971aff19c290
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a3405e74ec685e5f/cli/sql_prompt_attempt_2.txt
@@ -0,0 +1,454 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_threshold_rarity_cdf",
+    "template_name": "Threshold Rarity CDF",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};",
+    "required_roles": [
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=Job_Satisfaction.",
+  "planned_template_id": "tpl_threshold_rarity_cdf",
+  "bindings": {
+    "measure_col": "Job_Satisfaction",
+    "top_k": 14,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 100.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a3405e74ec685e5f/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a3405e74ec685e5f/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e12fba9bcfb5ab961db15d89ae8235d44d686be9
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a3405e74ec685e5f/cli/sql_response_attempt_1.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fc-aabc-72d0-bdd0-b75c5eed0cd3"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a3405e74ec685e5f/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a3405e74ec685e5f/cli/sql_response_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..f238148c2a4898360dac1e719e0b066ad9be3209
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a3405e74ec685e5f/cli/sql_response_attempt_2.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fc-bac6-7d52-9ff0-cac53cfef1eb"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a3405e74ec685e5f/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_a3405e74ec685e5f/cli/sql_stderr_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ae154c66cfcfc8db/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ae154c66cfcfc8db/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..81e8e6a1bdafe061e4dd8e6404e3745abd3f46c5
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ae154c66cfcfc8db/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16912, "bytes_utf8": 16912, "lines": 456, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 701, "bytes_utf8": 701, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16825, "cached_input_tokens": 12032, "output_tokens": 510, "reasoning_output_tokens": 328}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ae154c66cfcfc8db/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ae154c66cfcfc8db/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..d030b36f5f141e327aed8bd34df4d0a0e534a974
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ae154c66cfcfc8db/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_ae154c66cfcfc8db",
+    "api_calls": 0,
+    "input_tokens": 16825,
+    "cached_input_tokens": 12032,
+    "output_tokens": 510,
+    "total_tokens": 17335,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 11044.77,
+    "sql_execution_elapsed_ms_total": 1.2,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ae154c66cfcfc8db/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ae154c66cfcfc8db/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ae154c66cfcfc8db/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..c25cfe1c4d25d4cc75c3edc35bcd7c1336947c3a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ae154c66cfcfc8db/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:49:34.088819+00:00",
+  "ended_at": "2026-05-19T15:49:45.133627+00:00",
+  "elapsed_ms": 11044.77,
+  "prompt_metrics": {
+    "chars": 16912,
+    "bytes_utf8": 16912,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1068,
+    "bytes_utf8": 1068,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 701,
+      "bytes_utf8": 701,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16825,
+      "cached_input_tokens": 12032,
+      "output_tokens": 510,
+      "reasoning_output_tokens": 328
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ae154c66cfcfc8db/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ae154c66cfcfc8db/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..14f25b999b8dd2afcfd85631e4d1e71731d0c2a1
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ae154c66cfcfc8db/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_tpch_relative_total_threshold",
+    "template_name": "Relative-to-Total Extreme Threshold",
+    "primary_family": "tail_rarity_structure",
+    "portability": "partial",
+    "sql_skeleton": "WITH grouped AS (\n    SELECT {group_col}, SUM({measure_col}) AS group_value\n    FROM {table}\n    GROUP BY {group_col}\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=Home_Office_Quality, measure_col=Innovation_Score.",
+  "planned_template_id": "tpl_tpch_relative_total_threshold",
+  "bindings": {
+    "group_col": "Home_Office_Quality",
+    "measure_col": "Innovation_Score",
+    "top_k": 17,
+    "top_n": 5,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 80.9,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "WITH grouped AS (\n    SELECT {group_col}, SUM({measure_col}) AS group_value\n    FROM {table}\n    GROUP BY {group_col}\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ae154c66cfcfc8db/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ae154c66cfcfc8db/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e0eb6c47ab680aa8835802b9985a61829859254c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ae154c66cfcfc8db/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40ed-9c37-7323-9daa-26387a7b0bb8"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n    SELECT \\\"Home_Office_Quality\\\", SUM(CAST(\\\"Innovation_Score\\\" AS REAL)) AS group_value\\n    FROM \\\"m1\\\"\\n    GROUP BY \\\"Home_Office_Quality\\\"\\n), total AS (\\n    SELECT SUM(group_value) AS total_value\\n    FROM grouped\\n)\\nSELECT g.\\\"Home_Office_Quality\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.05\\nORDER BY g.group_value DESC;\",\"notes\":\"Applied the planned Relative-to-Total Extreme Threshold template with group_col=\\\"Home_Office_Quality\\\" and measure_col=\\\"Innovation_Score\\\". CAST to REAL is used because the schema stores numeric-looking values as TEXT.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16825,"cached_input_tokens":12032,"output_tokens":510,"reasoning_output_tokens":328}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ae154c66cfcfc8db/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ae154c66cfcfc8db/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..a3eb1cafd2ddd8515a54750763771b78940cec7b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ae154c66cfcfc8db/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tpch_relative_total_threshold\nWITH grouped AS (\n    SELECT \"Home_Office_Quality\", SUM(CAST(\"Innovation_Score\" AS REAL)) AS group_value\n    FROM \"m1\"\n    GROUP BY \"Home_Office_Quality\"\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.\"Home_Office_Quality\", g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * 0.05\nORDER BY g.group_value DESC;","notes":"Applied the planned Relative-to-Total Extreme Threshold template with group_col=\"Home_Office_Quality\" and measure_col=\"Innovation_Score\". CAST to REAL is used because the schema stores numeric-looking values as TEXT."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ae154c66cfcfc8db/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ae154c66cfcfc8db/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b0f40efb5992b84c/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b0f40efb5992b84c/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..7757816c47e7659ee5832197463b13daa664b069
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b0f40efb5992b84c/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 17196, "bytes_utf8": 17196, "lines": 459, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 763, "bytes_utf8": 763, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16903, "cached_input_tokens": 12032, "output_tokens": 611, "reasoning_output_tokens": 407}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b0f40efb5992b84c/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b0f40efb5992b84c/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..607b6b98b4638e94755c6e7281619a3642d4cc5f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b0f40efb5992b84c/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_b0f40efb5992b84c",
+    "api_calls": 0,
+    "input_tokens": 16903,
+    "cached_input_tokens": 12032,
+    "output_tokens": 611,
+    "total_tokens": 17514,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 17093.01,
+    "sql_execution_elapsed_ms_total": 1.09,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b0f40efb5992b84c/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b0f40efb5992b84c/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b0f40efb5992b84c/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..89ca672c7d401a50634a0d581c5d9278f73b52a2
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b0f40efb5992b84c/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:40:41.183198+00:00",
+  "ended_at": "2026-05-19T15:40:58.276229+00:00",
+  "elapsed_ms": 17093.01,
+  "prompt_metrics": {
+    "chars": 17196,
+    "bytes_utf8": 17196,
+    "lines": 459,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1466,
+    "bytes_utf8": 1466,
+    "lines": 5,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 763,
+      "bytes_utf8": 763,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16903,
+      "cached_input_tokens": 12032,
+      "output_tokens": 611,
+      "reasoning_output_tokens": 407
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b0f40efb5992b84c/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b0f40efb5992b84c/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..2f8af1db5252356df00f316581fe9af9fbba6dd0
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b0f40efb5992b84c/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,459 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_group_ratio_two_conditions",
+    "template_name": "Grouped Ratio of Two Conditions",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "yes",
+    "sql_skeleton": "WITH grouped AS (\n    SELECT {group_col},\n           SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n           SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n    FROM {table}\n    GROUP BY {group_col}\n)\nSELECT {group_col},\n       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;",
+    "required_roles": [
+      "group_col",
+      "condition_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=Has_Children, condition_col=Team_Collaboration_Frequency.",
+  "planned_template_id": "tpl_m4_group_ratio_two_conditions",
+  "bindings": {
+    "group_col": "Has_Children",
+    "condition_col": "Team_Collaboration_Frequency",
+    "condition_value": "Daily",
+    "positive_value": "Daily",
+    "negative_value": "Few times per week",
+    "top_k": 12,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 10.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "WITH grouped AS (\n    SELECT {group_col},\n           SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n           SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n    FROM {table}\n    GROUP BY {group_col}\n)\nSELECT {group_col},\n       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b0f40efb5992b84c/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b0f40efb5992b84c/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..911c49b11be0010300ea84c830cd5ad3f7a489af
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b0f40efb5992b84c/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,5 @@
+{"type":"thread.started","thread_id":"019e40e5-7a71-7be1-9902-f0feff711a01"}
+{"type":"turn.started"}
+{"type":"error","message":"Reconnecting... 2/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1983575, Requested 17538. Please try again in 33ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n    SELECT\\n        \\\"Has_Children\\\",\\n        SUM(CASE WHEN \\\"Team_Collaboration_Frequency\\\" = 'Daily' THEN 1 ELSE 0 END) AS numerator_count,\\n        SUM(CASE WHEN \\\"Team_Collaboration_Frequency\\\" = 'Few times per week' THEN 1 ELSE 0 END) AS denominator_count\\n    FROM \\\"m1\\\"\\n    GROUP BY \\\"Has_Children\\\"\\n)\\nSELECT\\n    \\\"Has_Children\\\",\\n    CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\",\"notes\":\"Uses the planned grouped ratio template with group_col=\\\"Has_Children\\\" and condition_col=\\\"Team_Collaboration_Frequency\\\", computing the ratio of 'Daily' to 'Few times per week' within each group.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16903,"cached_input_tokens":12032,"output_tokens":611,"reasoning_output_tokens":407}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b0f40efb5992b84c/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b0f40efb5992b84c/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..db33a861250d896606525819d711e22434fbaebe
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b0f40efb5992b84c/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_m4_group_ratio_two_conditions\nWITH grouped AS (\n    SELECT\n        \"Has_Children\",\n        SUM(CASE WHEN \"Team_Collaboration_Frequency\" = 'Daily' THEN 1 ELSE 0 END) AS numerator_count,\n        SUM(CASE WHEN \"Team_Collaboration_Frequency\" = 'Few times per week' THEN 1 ELSE 0 END) AS denominator_count\n    FROM \"m1\"\n    GROUP BY \"Has_Children\"\n)\nSELECT\n    \"Has_Children\",\n    CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;","notes":"Uses the planned grouped ratio template with group_col=\"Has_Children\" and condition_col=\"Team_Collaboration_Frequency\", computing the ratio of 'Daily' to 'Few times per week' within each group."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b0f40efb5992b84c/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b0f40efb5992b84c/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..ea2f32c40d0526c72c90fa30057973f42f167c16
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:10:53.260083+00:00",
+  "ended_at": "2026-05-19T16:10:57.037167+00:00",
+  "elapsed_ms": 3777.05,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16422,
+    "bytes_utf8": 16422,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_attempt_2.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..25ccf0134514cf6c7d980b40e93712d2ad6385d0
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_attempt_2.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:10:58.038941+00:00",
+  "ended_at": "2026-05-19T16:11:01.101479+00:00",
+  "elapsed_ms": 3062.51,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16422,
+    "bytes_utf8": 16422,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_2.txt",
+  "response_path": "cli/sql_response_attempt_2.txt",
+  "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_2.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..892a400d76c6403b34333bcca0aa15104c2e51ea
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_window_partition_avg",
+    "template_name": "Window Partition Average",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Window Partition Average to probe slice_level_consistency with semantic role ranked_signal_view. Focus on group_col=Marital_Status, measure_col=Stress_Level.",
+  "planned_template_id": "tpl_m4_window_partition_avg",
+  "bindings": {
+    "group_col": "Marital_Status",
+    "measure_col": "Stress_Level",
+    "top_k": 18,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 7.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_prompt_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..892a400d76c6403b34333bcca0aa15104c2e51ea
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_prompt_attempt_2.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_window_partition_avg",
+    "template_name": "Window Partition Average",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Window Partition Average to probe slice_level_consistency with semantic role ranked_signal_view. Focus on group_col=Marital_Status, measure_col=Stress_Level.",
+  "planned_template_id": "tpl_m4_window_partition_avg",
+  "bindings": {
+    "group_col": "Marital_Status",
+    "measure_col": "Stress_Level",
+    "top_k": 18,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 7.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..4b9d81df06a05c8b1d76cfeeff3e84feaf768471
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4101-20b6-7c12-a6eb-a2e6116c9239"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..43cdb59e71d0241646edb7b6db128544e7c015b2
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_response_attempt_1.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4101-20b6-7c12-a6eb-a2e6116c9239"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_response_attempt_2.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..0dacd1a4d3d5a7396b02a0d4b02c4ad074e9b468
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_response_attempt_2.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4101-3392-7cd1-a5a0-48b607d64774"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_response_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..67b7f759128470dde6a5fe19b0a225e7b14d3477
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_response_attempt_2.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4101-3392-7cd1-a5a0-48b607d64774"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b562a878d4acaa92/cli/sql_stderr_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b80ca91cec049995/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b80ca91cec049995/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..426db886598b746ee9ea2919c02ac07890227041
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b80ca91cec049995/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16752, "bytes_utf8": 16752, "lines": 458, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 774, "bytes_utf8": 774, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16804, "cached_input_tokens": 12032, "output_tokens": 679, "reasoning_output_tokens": 458}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b80ca91cec049995/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b80ca91cec049995/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..c3a69b29a87b8118b2ac18e9de00496c8f062670
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b80ca91cec049995/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_b80ca91cec049995",
+    "api_calls": 0,
+    "input_tokens": 16804,
+    "cached_input_tokens": 12032,
+    "output_tokens": 679,
+    "total_tokens": 17483,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 20074.86,
+    "sql_execution_elapsed_ms_total": 5.35,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b80ca91cec049995/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b80ca91cec049995/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b80ca91cec049995/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..c42f24897b478d6a88bb54dbc11014f262de668a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b80ca91cec049995/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:34:10.808895+00:00",
+  "ended_at": "2026-05-19T15:34:30.883800+00:00",
+  "elapsed_ms": 20074.86,
+  "prompt_metrics": {
+    "chars": 16752,
+    "bytes_utf8": 16752,
+    "lines": 458,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1509,
+    "bytes_utf8": 1509,
+    "lines": 5,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 774,
+      "bytes_utf8": 774,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16804,
+      "cached_input_tokens": 12032,
+      "output_tokens": 679,
+      "reasoning_output_tokens": 458
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b80ca91cec049995/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b80ca91cec049995/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..04c485066ebd332ce101b32c55f861afd0f4249d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b80ca91cec049995/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,458 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_tpcds_within_group_share",
+    "template_name": "Within-Group Share of Total",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;",
+    "required_roles": [
+      "group_col",
+      "item_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=Company_Size, measure_col=Commute_Time_Minutes.",
+  "planned_template_id": "tpl_tpcds_within_group_share",
+  "bindings": {
+    "group_col": "Company_Size",
+    "measure_col": "Commute_Time_Minutes",
+    "item_col": "Age",
+    "top_k": 19,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 33.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b80ca91cec049995/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b80ca91cec049995/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..6ad431868cbf19202bddd24dcb77ef32c6a302f4
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b80ca91cec049995/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,5 @@
+{"type":"thread.started","thread_id":"019e40df-857b-74f3-addd-c791c6f77a3e"}
+{"type":"turn.started"}
+{"type":"error","message":"Reconnecting... 2/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1984379, Requested 17439. Please try again in 54ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n  \\\"Company_Size\\\",\\n  \\\"Age\\\",\\n  SUM(CAST(\\\"Commute_Time_Minutes\\\" AS REAL)) AS total_measure,\\n  SUM(CAST(\\\"Commute_Time_Minutes\\\" AS REAL)) * 100.0\\n    / SUM(SUM(CAST(\\\"Commute_Time_Minutes\\\" AS REAL))) OVER (PARTITION BY \\\"Company_Size\\\") AS share_within_group\\nFROM \\\"m1\\\"\\nWHERE \\\"Company_Size\\\" IS NOT NULL\\n  AND \\\"Age\\\" IS NOT NULL\\n  AND \\\"Commute_Time_Minutes\\\" IS NOT NULL\\n  AND TRIM(\\\"Commute_Time_Minutes\\\") <> ''\\nGROUP BY \\\"Company_Size\\\", \\\"Age\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Applied the Within-Group Share of Total template with group_col=\\\"Company_Size\\\", item_col=\\\"Age\\\", and measure_col=\\\"Commute_Time_Minutes\\\", casting the TEXT measure to REAL for SQLite aggregation.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16804,"cached_input_tokens":12032,"output_tokens":679,"reasoning_output_tokens":458}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b80ca91cec049995/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b80ca91cec049995/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..6f4e034a292eb1cb6af8211a03ff3004f37562b1
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b80ca91cec049995/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tpcds_within_group_share\nSELECT\n  \"Company_Size\",\n  \"Age\",\n  SUM(CAST(\"Commute_Time_Minutes\" AS REAL)) AS total_measure,\n  SUM(CAST(\"Commute_Time_Minutes\" AS REAL)) * 100.0\n    / SUM(SUM(CAST(\"Commute_Time_Minutes\" AS REAL))) OVER (PARTITION BY \"Company_Size\") AS share_within_group\nFROM \"m1\"\nWHERE \"Company_Size\" IS NOT NULL\n  AND \"Age\" IS NOT NULL\n  AND \"Commute_Time_Minutes\" IS NOT NULL\n  AND TRIM(\"Commute_Time_Minutes\") <> ''\nGROUP BY \"Company_Size\", \"Age\"\nORDER BY share_within_group DESC;","notes":"Applied the Within-Group Share of Total template with group_col=\"Company_Size\", item_col=\"Age\", and measure_col=\"Commute_Time_Minutes\", casting the TEXT measure to REAL for SQLite aggregation."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b80ca91cec049995/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b80ca91cec049995/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b88b57c0a6139d5b/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b88b57c0a6139d5b/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..fbe7493ce51a0eb41701836c18d22e1d06f4e37a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b88b57c0a6139d5b/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16644, "bytes_utf8": 16644, "lines": 460, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 476, "bytes_utf8": 476, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16777, "cached_input_tokens": 15744, "output_tokens": 545, "reasoning_output_tokens": 418}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b88b57c0a6139d5b/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b88b57c0a6139d5b/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..84f90ad49999c349ebe6f2418f68d6259e84d5ef
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b88b57c0a6139d5b/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_b88b57c0a6139d5b",
+    "api_calls": 0,
+    "input_tokens": 16777,
+    "cached_input_tokens": 15744,
+    "output_tokens": 545,
+    "total_tokens": 17322,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 10760.92,
+    "sql_execution_elapsed_ms_total": 1.28,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b88b57c0a6139d5b/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b88b57c0a6139d5b/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b88b57c0a6139d5b/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..abe567cbceef87379e47209013d505c287098da9
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b88b57c0a6139d5b/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:42:47.932649+00:00",
+  "ended_at": "2026-05-19T15:42:58.693614+00:00",
+  "elapsed_ms": 10760.92,
+  "prompt_metrics": {
+    "chars": 16644,
+    "bytes_utf8": 16644,
+    "lines": 460,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 851,
+    "bytes_utf8": 851,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 476,
+      "bytes_utf8": 476,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16777,
+      "cached_input_tokens": 15744,
+      "output_tokens": 545,
+      "reasoning_output_tokens": 418
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b88b57c0a6139d5b/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b88b57c0a6139d5b/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..169737e54482712fc051c30eb6e402cec4b686f7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b88b57c0a6139d5b/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,460 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_c2_filtered_group_count_2d",
+    "template_name": "Filtered Two-Dimensional Group Count",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;",
+    "required_roles": [
+      "group_col",
+      "group_col_2",
+      "predicate_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Filtered Two-Dimensional Group Count to probe slice_level_consistency with semantic role count_distribution. Focus on group_col=Has_Children, group_col_2=Industry.",
+  "planned_template_id": "tpl_c2_filtered_group_count_2d",
+  "bindings": {
+    "group_col": "Has_Children",
+    "group_col_2": "Industry",
+    "predicate_col": "Innovation_Score",
+    "predicate_op": ">=",
+    "predicate_value": 84.2,
+    "top_k": 14,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 84.2,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b88b57c0a6139d5b/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b88b57c0a6139d5b/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..39e4ed0ffab019a6bdc2392065705b1fd110b66c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b88b57c0a6139d5b/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40e7-698b-7662-a55c-874b3f1554f7"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_c2_filtered_group_count_2d\\nSELECT \\\"Has_Children\\\", \\\"Industry\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"m1\\\"\\nWHERE CAST(\\\"Innovation_Score\\\" AS REAL) >= 84.2\\nGROUP BY \\\"Has_Children\\\", \\\"Industry\\\"\\nORDER BY \\\"row_count\\\" DESC;\",\"notes\":\"Used the planned filtered two-dimensional group count template with \\\"Has_Children\\\" and \\\"Industry\\\". CAST(\\\"Innovation_Score\\\" AS REAL) is applied because the SQLite schema stores this numeric field as TEXT.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16777,"cached_input_tokens":15744,"output_tokens":545,"reasoning_output_tokens":418}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b88b57c0a6139d5b/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b88b57c0a6139d5b/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..51c1be997994562fe09d40a688bd4d9b419f261b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b88b57c0a6139d5b/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_c2_filtered_group_count_2d\nSELECT \"Has_Children\", \"Industry\", COUNT(*) AS \"row_count\"\nFROM \"m1\"\nWHERE CAST(\"Innovation_Score\" AS REAL) >= 84.2\nGROUP BY \"Has_Children\", \"Industry\"\nORDER BY \"row_count\" DESC;","notes":"Used the planned filtered two-dimensional group count template with \"Has_Children\" and \"Industry\". CAST(\"Innovation_Score\" AS REAL) is applied because the SQLite schema stores this numeric field as TEXT."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b88b57c0a6139d5b/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_b88b57c0a6139d5b/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bd80cb4008dd9070/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bd80cb4008dd9070/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..2c8cbd96b0cfd1be495811306e882c56e40c9ba3
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bd80cb4008dd9070/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16350, "bytes_utf8": 16350, "lines": 456, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 404, "bytes_utf8": 404, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16691, "cached_input_tokens": 12032, "output_tokens": 410, "reasoning_output_tokens": 301}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bd80cb4008dd9070/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bd80cb4008dd9070/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..b7f5cda8f41759068822a7957b89adc02b777e6b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bd80cb4008dd9070/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_bd80cb4008dd9070",
+    "api_calls": 0,
+    "input_tokens": 16691,
+    "cached_input_tokens": 12032,
+    "output_tokens": 410,
+    "total_tokens": 17101,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 14605.36,
+    "sql_execution_elapsed_ms_total": 1.97,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bd80cb4008dd9070/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bd80cb4008dd9070/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bd80cb4008dd9070/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..9c798ee658041a3ec35c4c2fcdc0d5da9bd8b7ad
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bd80cb4008dd9070/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:29:27.372013+00:00",
+  "ended_at": "2026-05-19T15:29:41.977405+00:00",
+  "elapsed_ms": 14605.36,
+  "prompt_metrics": {
+    "chars": 16350,
+    "bytes_utf8": 16350,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1091,
+    "bytes_utf8": 1091,
+    "lines": 5,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 404,
+      "bytes_utf8": 404,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16691,
+      "cached_input_tokens": 12032,
+      "output_tokens": 410,
+      "reasoning_output_tokens": 301
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bd80cb4008dd9070/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bd80cb4008dd9070/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..bc8eac08dcfeda3a33856227eb9dbb7bfc1f73e8
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bd80cb4008dd9070/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_h2o_group_sum",
+    "template_name": "Grouped Numeric Sum",
+    "primary_family": "subgroup_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=Has_Children, measure_col=Work_Hours_Per_Week.",
+  "planned_template_id": "tpl_h2o_group_sum",
+  "bindings": {
+    "group_col": "Has_Children",
+    "measure_col": "Work_Hours_Per_Week",
+    "top_k": 18,
+    "top_n": 7,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 45.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bd80cb4008dd9070/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bd80cb4008dd9070/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..8f1e44530c72b39b99c39bd987ef3d58f51ed291
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bd80cb4008dd9070/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,5 @@
+{"type":"thread.started","thread_id":"019e40db-325d-7181-89c2-2b4aaff6a613"}
+{"type":"turn.started"}
+{"type":"error","message":"Reconnecting... 2/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1998131, Requested 17326. Please try again in 463ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"Has_Children\\\", SUM(CAST(\\\"Work_Hours_Per_Week\\\" AS REAL)) AS total_measure\\nFROM \\\"m1\\\"\\nGROUP BY \\\"Has_Children\\\"\\nORDER BY total_measure DESC;\",\"notes\":\"Used the required grouped numeric sum template with group_col=\\\"Has_Children\\\" and measure_col=\\\"Work_Hours_Per_Week\\\". CAST to REAL is included because the schema stores numeric values as TEXT.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16691,"cached_input_tokens":12032,"output_tokens":410,"reasoning_output_tokens":301}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bd80cb4008dd9070/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bd80cb4008dd9070/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b43056d59fce9d08766839d360b6b6dafb9ead1b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bd80cb4008dd9070/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_h2o_group_sum\nSELECT \"Has_Children\", SUM(CAST(\"Work_Hours_Per_Week\" AS REAL)) AS total_measure\nFROM \"m1\"\nGROUP BY \"Has_Children\"\nORDER BY total_measure DESC;","notes":"Used the required grouped numeric sum template with group_col=\"Has_Children\" and measure_col=\"Work_Hours_Per_Week\". CAST to REAL is included because the schema stores numeric values as TEXT."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bd80cb4008dd9070/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bd80cb4008dd9070/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bdbfc29aa9bd9eb0/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bdbfc29aa9bd9eb0/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..420f460f54111feb1bbd0160c03bcf08c6e8a179
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bdbfc29aa9bd9eb0/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16604, "bytes_utf8": 16604, "lines": 459, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 435, "bytes_utf8": 435, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16745, "cached_input_tokens": 12032, "output_tokens": 339, "reasoning_output_tokens": 227}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bdbfc29aa9bd9eb0/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bdbfc29aa9bd9eb0/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..d47c59a1150d867dbcdf35675d336847119d3b44
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bdbfc29aa9bd9eb0/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_bdbfc29aa9bd9eb0",
+    "api_calls": 0,
+    "input_tokens": 16745,
+    "cached_input_tokens": 12032,
+    "output_tokens": 339,
+    "total_tokens": 17084,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 8873.61,
+    "sql_execution_elapsed_ms_total": 1.98,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bdbfc29aa9bd9eb0/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bdbfc29aa9bd9eb0/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bdbfc29aa9bd9eb0/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..603708168d0a0ae9d9bb4437b4c5b7462e40a7c6
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bdbfc29aa9bd9eb0/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:05:23.999741+00:00",
+  "ended_at": "2026-05-19T16:05:32.873386+00:00",
+  "elapsed_ms": 8873.61,
+  "prompt_metrics": {
+    "chars": 16604,
+    "bytes_utf8": 16604,
+    "lines": 459,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 798,
+    "bytes_utf8": 798,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 435,
+      "bytes_utf8": 435,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16745,
+      "cached_input_tokens": 12032,
+      "output_tokens": 339,
+      "reasoning_output_tokens": 227
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bdbfc29aa9bd9eb0/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bdbfc29aa9bd9eb0/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..0f28291b176cc6231247873b7d691a9149f79204
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bdbfc29aa9bd9eb0/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,459 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_group_condition_rate",
+    "template_name": "Grouped Condition Rate",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;",
+    "required_roles": [
+      "group_col",
+      "condition_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Condition Rate to probe direction_consistency with semantic role within_group_proportion. Focus on group_col=Education_Level, condition_col=Response_Quality.",
+  "planned_template_id": "tpl_m4_group_condition_rate",
+  "bindings": {
+    "group_col": "Education_Level",
+    "condition_col": "Response_Quality",
+    "condition_value": "Medium",
+    "positive_value": "High",
+    "negative_value": "Medium",
+    "top_k": 18,
+    "top_n": 7,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 96.1,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bdbfc29aa9bd9eb0/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bdbfc29aa9bd9eb0/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..cf002f13a062c72cfa109f33d7e59bfc6d2b7b06
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bdbfc29aa9bd9eb0/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fc-1aba-7512-bfcc-7f56c22da55c"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"Education_Level\\\",\\n       AVG(CASE WHEN \\\"Response_Quality\\\" = 'Medium' THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"m1\\\"\\nGROUP BY \\\"Education_Level\\\"\\nORDER BY \\\"condition_rate\\\" DESC;\",\"notes\":\"Computes the within-group proportion of records with \\\"Response_Quality\\\" = 'Medium' for each \\\"Education_Level\\\", following the planned Grouped Condition Rate template.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16745,"cached_input_tokens":12032,"output_tokens":339,"reasoning_output_tokens":227}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bdbfc29aa9bd9eb0/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bdbfc29aa9bd9eb0/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..ebae574685412a0f5833f85a7207c9da9cb973b5
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bdbfc29aa9bd9eb0/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_m4_group_condition_rate\nSELECT \"Education_Level\",\n       AVG(CASE WHEN \"Response_Quality\" = 'Medium' THEN 1 ELSE 0 END) AS \"condition_rate\"\nFROM \"m1\"\nGROUP BY \"Education_Level\"\nORDER BY \"condition_rate\" DESC;","notes":"Computes the within-group proportion of records with \"Response_Quality\" = 'Medium' for each \"Education_Level\", following the planned Grouped Condition Rate template."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bdbfc29aa9bd9eb0/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_bdbfc29aa9bd9eb0/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c090316307136898/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c090316307136898/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..642b3a98be773cd926c533d80c515683f70ab1fd
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c090316307136898/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16513, "bytes_utf8": 16513, "lines": 456, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 1241, "bytes_utf8": 1241, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16719, "cached_input_tokens": 15744, "output_tokens": 2121, "reasoning_output_tokens": 1765}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c090316307136898/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c090316307136898/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..da4663cd861b78ae0dfde371da8b7eb0306e417a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c090316307136898/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_c090316307136898",
+    "api_calls": 0,
+    "input_tokens": 16719,
+    "cached_input_tokens": 15744,
+    "output_tokens": 2121,
+    "total_tokens": 18840,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 34162.79,
+    "sql_execution_elapsed_ms_total": 4.19,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c090316307136898/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c090316307136898/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c090316307136898/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..22cca486273fccf5ba546a8accd956ea9df913bd
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c090316307136898/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:57:54.149865+00:00",
+  "ended_at": "2026-05-19T15:58:28.312690+00:00",
+  "elapsed_ms": 34162.79,
+  "prompt_metrics": {
+    "chars": 16513,
+    "bytes_utf8": 16513,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1733,
+    "bytes_utf8": 1733,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 1241,
+      "bytes_utf8": 1241,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16719,
+      "cached_input_tokens": 15744,
+      "output_tokens": 2121,
+      "reasoning_output_tokens": 1765
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c090316307136898/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c090316307136898/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..28eaf6de0db04304808237c04e63a2e8bb2b6f82
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c090316307136898/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=Department, measure_col=Quality_Score.",
+  "planned_template_id": "tpl_grouped_percentile_point",
+  "bindings": {
+    "group_col": "Department",
+    "measure_col": "Quality_Score",
+    "top_k": 10,
+    "top_n": 5,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 96.225,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c090316307136898/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c090316307136898/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..aabd3f59ff888c2c401fdeee3e642306da95a34c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c090316307136898/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f5-3d90-7633-8625-5600ed128ba2"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n  SELECT\\n    \\\"Department\\\",\\n    CAST(\\\"Quality_Score\\\" AS REAL) AS \\\"quality_score\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"Department\\\"\\n      ORDER BY CAST(\\\"Quality_Score\\\" AS REAL)\\n    ) AS \\\"rn\\\",\\n    COUNT(*) OVER (\\n      PARTITION BY \\\"Department\\\"\\n    ) AS \\\"cnt\\\"\\n  FROM \\\"m1\\\"\\n  WHERE \\\"Department\\\" IS NOT NULL\\n    AND \\\"Quality_Score\\\" IS NOT NULL\\n),\\n\\\"cutoffs\\\" AS (\\n  SELECT\\n    \\\"Department\\\",\\n    \\\"quality_score\\\",\\n    \\\"rn\\\",\\n    \\\"cnt\\\",\\n    CAST((0.95 * \\\"cnt\\\") AS INTEGER)\\n      + CASE\\n          WHEN (0.95 * \\\"cnt\\\") > CAST((0.95 * \\\"cnt\\\") AS INTEGER) THEN 1\\n          ELSE 0\\n        END AS \\\"target_rn\\\"\\n  FROM \\\"ranked\\\"\\n  WHERE \\\"cnt\\\" >= 5\\n)\\nSELECT\\n  \\\"Department\\\",\\n  MIN(\\\"quality_score\\\") AS \\\"percentile_measure\\\"\\nFROM \\\"cutoffs\\\"\\nWHERE \\\"rn\\\" >= \\\"target_rn\\\"\\nGROUP BY \\\"Department\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\",\"notes\":\"SQLite does not support PERCENTILE_CONT, so this query uses a nearest-rank 95th percentile approximation per Department on CAST(\\\"Quality_Score\\\" AS REAL). It excludes NULL Department and Quality_Score values and keeps only departments with at least 5 rows.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16719,"cached_input_tokens":15744,"output_tokens":2121,"reasoning_output_tokens":1765}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c090316307136898/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c090316307136898/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..9c479ba65324944f10f15ba5fad7046342a0e556
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c090316307136898/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_grouped_percentile_point\nWITH \"ranked\" AS (\n  SELECT\n    \"Department\",\n    CAST(\"Quality_Score\" AS REAL) AS \"quality_score\",\n    ROW_NUMBER() OVER (\n      PARTITION BY \"Department\"\n      ORDER BY CAST(\"Quality_Score\" AS REAL)\n    ) AS \"rn\",\n    COUNT(*) OVER (\n      PARTITION BY \"Department\"\n    ) AS \"cnt\"\n  FROM \"m1\"\n  WHERE \"Department\" IS NOT NULL\n    AND \"Quality_Score\" IS NOT NULL\n),\n\"cutoffs\" AS (\n  SELECT\n    \"Department\",\n    \"quality_score\",\n    \"rn\",\n    \"cnt\",\n    CAST((0.95 * \"cnt\") AS INTEGER)\n      + CASE\n          WHEN (0.95 * \"cnt\") > CAST((0.95 * \"cnt\") AS INTEGER) THEN 1\n          ELSE 0\n        END AS \"target_rn\"\n  FROM \"ranked\"\n  WHERE \"cnt\" >= 5\n)\nSELECT\n  \"Department\",\n  MIN(\"quality_score\") AS \"percentile_measure\"\nFROM \"cutoffs\"\nWHERE \"rn\" >= \"target_rn\"\nGROUP BY \"Department\"\nORDER BY \"percentile_measure\" DESC;","notes":"SQLite does not support PERCENTILE_CONT, so this query uses a nearest-rank 95th percentile approximation per Department on CAST(\"Quality_Score\" AS REAL). It excludes NULL Department and Quality_Score values and keeps only departments with at least 5 rows."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c090316307136898/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c090316307136898/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c157c1bffc2a5f53/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c157c1bffc2a5f53/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..00a4fcba64909fa436bf77a99a3fae7723668eb1
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c157c1bffc2a5f53/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16905, "bytes_utf8": 16905, "lines": 456, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 1005, "bytes_utf8": 1005, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16825, "cached_input_tokens": 15744, "output_tokens": 803, "reasoning_output_tokens": 516}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c157c1bffc2a5f53/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c157c1bffc2a5f53/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..b753e26fba00f72122c26d393990391684fc7279
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c157c1bffc2a5f53/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_c157c1bffc2a5f53",
+    "api_calls": 0,
+    "input_tokens": 16825,
+    "cached_input_tokens": 15744,
+    "output_tokens": 803,
+    "total_tokens": 17628,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 17704.06,
+    "sql_execution_elapsed_ms_total": 4.79,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c157c1bffc2a5f53/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c157c1bffc2a5f53/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c157c1bffc2a5f53/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..7efc055b19690fd2b78885315398bf0ab88c3572
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c157c1bffc2a5f53/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:48:11.703292+00:00",
+  "ended_at": "2026-05-19T15:48:29.407394+00:00",
+  "elapsed_ms": 17704.06,
+  "prompt_metrics": {
+    "chars": 16905,
+    "bytes_utf8": 16905,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1465,
+    "bytes_utf8": 1465,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 1005,
+      "bytes_utf8": 1005,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16825,
+      "cached_input_tokens": 15744,
+      "output_tokens": 803,
+      "reasoning_output_tokens": 516
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c157c1bffc2a5f53/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c157c1bffc2a5f53/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..3028e5dc075093e096485ff6ea4fce703026b2cb
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c157c1bffc2a5f53/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_tpch_relative_total_threshold",
+    "template_name": "Relative-to-Total Extreme Threshold",
+    "primary_family": "tail_rarity_structure",
+    "portability": "partial",
+    "sql_skeleton": "WITH grouped AS (\n    SELECT {group_col}, SUM({measure_col}) AS group_value\n    FROM {table}\n    GROUP BY {group_col}\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=Company_Size, measure_col=Task_Completion_Rate.",
+  "planned_template_id": "tpl_tpch_relative_total_threshold",
+  "bindings": {
+    "group_col": "Company_Size",
+    "measure_col": "Task_Completion_Rate",
+    "top_k": 10,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 96.1,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "WITH grouped AS (\n    SELECT {group_col}, SUM({measure_col}) AS group_value\n    FROM {table}\n    GROUP BY {group_col}\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c157c1bffc2a5f53/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c157c1bffc2a5f53/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..fa6fdf53bf99f3ee06fae32a535274f9cdad26d6
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c157c1bffc2a5f53/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40ec-5a33-7121-a706-6d143a5b47ca"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH \\\"grouped\\\" AS (\\n    SELECT\\n        \\\"Company_Size\\\",\\n        SUM(CAST(\\\"Task_Completion_Rate\\\" AS REAL)) AS \\\"group_value\\\"\\n    FROM \\\"m1\\\"\\n    WHERE \\\"Company_Size\\\" IS NOT NULL\\n      AND \\\"Company_Size\\\" <> ''\\n      AND \\\"Task_Completion_Rate\\\" IS NOT NULL\\n      AND \\\"Task_Completion_Rate\\\" <> ''\\n    GROUP BY \\\"Company_Size\\\"\\n),\\n\\\"total\\\" AS (\\n    SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n    FROM \\\"grouped\\\"\\n)\\nSELECT\\n    \\\"g\\\".\\\"Company_Size\\\",\\n    \\\"g\\\".\\\"group_value\\\"\\nFROM \\\"grouped\\\" AS \\\"g\\\"\\nCROSS JOIN \\\"total\\\" AS \\\"t\\\"\\nWHERE \\\"g\\\".\\\"group_value\\\" > \\\"t\\\".\\\"total_value\\\" * 0.1\\nORDER BY \\\"g\\\".\\\"group_value\\\" DESC;\",\"notes\":\"Applied the planned Relative-to-Total Extreme Threshold template with group_col=Company_Size, measure_col=Task_Completion_Rate, and fraction_threshold=0.1. Added null/empty filtering and CAST(... AS REAL) because Task_Completion_Rate is stored as TEXT in the SQLite schema.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16825,"cached_input_tokens":15744,"output_tokens":803,"reasoning_output_tokens":516}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c157c1bffc2a5f53/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c157c1bffc2a5f53/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..0b1bb9afbaa9f96fd4ee8e333380c079fb07a130
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c157c1bffc2a5f53/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tpch_relative_total_threshold\nWITH \"grouped\" AS (\n    SELECT\n        \"Company_Size\",\n        SUM(CAST(\"Task_Completion_Rate\" AS REAL)) AS \"group_value\"\n    FROM \"m1\"\n    WHERE \"Company_Size\" IS NOT NULL\n      AND \"Company_Size\" <> ''\n      AND \"Task_Completion_Rate\" IS NOT NULL\n      AND \"Task_Completion_Rate\" <> ''\n    GROUP BY \"Company_Size\"\n),\n\"total\" AS (\n    SELECT SUM(\"group_value\") AS \"total_value\"\n    FROM \"grouped\"\n)\nSELECT\n    \"g\".\"Company_Size\",\n    \"g\".\"group_value\"\nFROM \"grouped\" AS \"g\"\nCROSS JOIN \"total\" AS \"t\"\nWHERE \"g\".\"group_value\" > \"t\".\"total_value\" * 0.1\nORDER BY \"g\".\"group_value\" DESC;","notes":"Applied the planned Relative-to-Total Extreme Threshold template with group_col=Company_Size, measure_col=Task_Completion_Rate, and fraction_threshold=0.1. Added null/empty filtering and CAST(... AS REAL) because Task_Completion_Rate is stored as TEXT in the SQLite schema."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c157c1bffc2a5f53/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c157c1bffc2a5f53/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c29800b3f1b40fad/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c29800b3f1b40fad/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..337152789a180e12bf3aaf205bcb1d82be76a7c1
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c29800b3f1b40fad/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16234, "bytes_utf8": 16234, "lines": 454, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 294, "bytes_utf8": 294, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16654, "cached_input_tokens": 12032, "output_tokens": 209, "reasoning_output_tokens": 128}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c29800b3f1b40fad/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c29800b3f1b40fad/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..bb7a219a3479dca11901b96aa75580fe5a642428
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c29800b3f1b40fad/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_c29800b3f1b40fad",
+    "api_calls": 0,
+    "input_tokens": 16654,
+    "cached_input_tokens": 12032,
+    "output_tokens": 209,
+    "total_tokens": 16863,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 17230.75,
+    "sql_execution_elapsed_ms_total": 2.59,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c29800b3f1b40fad/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c29800b3f1b40fad/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c29800b3f1b40fad/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..8b8e24a617c1ececd2dd3065adf46388c12e107f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c29800b3f1b40fad/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:32:09.796738+00:00",
+  "ended_at": "2026-05-19T15:32:27.027534+00:00",
+  "elapsed_ms": 17230.75,
+  "prompt_metrics": {
+    "chars": 16234,
+    "bytes_utf8": 16234,
+    "lines": 454,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1650,
+    "bytes_utf8": 1650,
+    "lines": 7,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 294,
+      "bytes_utf8": 294,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16654,
+      "cached_input_tokens": 12032,
+      "output_tokens": 209,
+      "reasoning_output_tokens": 128
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c29800b3f1b40fad/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c29800b3f1b40fad/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..19c2be2b811c695164713063ccd0b71d7c4f721e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c29800b3f1b40fad/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,454 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_clickbench_group_count",
+    "template_name": "Grouped Count by Category",
+    "primary_family": "subgroup_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;",
+    "required_roles": [
+      "group_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=Stress_Level.",
+  "planned_template_id": "tpl_clickbench_group_count",
+  "bindings": {
+    "group_col": "Stress_Level",
+    "top_k": 13,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 8.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c29800b3f1b40fad/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c29800b3f1b40fad/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..5f6cc524aab852b2bbd8ec2206d1b1df1c225975
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c29800b3f1b40fad/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,7 @@
+{"type":"thread.started","thread_id":"019e40dd-acf4-7690-8221-2ee011f836d6"}
+{"type":"turn.started"}
+{"type":"error","message":"Reconnecting... 2/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1984215, Requested 17289. Please try again in 45ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"error","message":"Reconnecting... 3/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1989716, Requested 17289. Please try again in 210ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"error","message":"Reconnecting... 4/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 2000000, Requested 17289. Please try again in 518ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"Stress_Level\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"m1\\\"\\nGROUP BY \\\"Stress_Level\\\"\\nORDER BY \\\"row_count\\\" DESC;\",\"notes\":\"Uses the required grouped-count template with group_col bound to \\\"Stress_Level\\\" on the single table \\\"m1\\\".\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16654,"cached_input_tokens":12032,"output_tokens":209,"reasoning_output_tokens":128}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c29800b3f1b40fad/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c29800b3f1b40fad/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..1608f5792fc8e67865be7fb13e3d9a07a483d8b5
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c29800b3f1b40fad/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_clickbench_group_count\nSELECT \"Stress_Level\", COUNT(*) AS \"row_count\"\nFROM \"m1\"\nGROUP BY \"Stress_Level\"\nORDER BY \"row_count\" DESC;","notes":"Uses the required grouped-count template with group_col bound to \"Stress_Level\" on the single table \"m1\"."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c29800b3f1b40fad/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c29800b3f1b40fad/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c38da853d6c799f6/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c38da853d6c799f6/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..454f5dff9c866e3ae43125ede124899dd3827a90
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c38da853d6c799f6/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16885, "bytes_utf8": 16885, "lines": 456, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 702, "bytes_utf8": 702, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16819, "cached_input_tokens": 15744, "output_tokens": 471, "reasoning_output_tokens": 277}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c38da853d6c799f6/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c38da853d6c799f6/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..5cf4336208817fb67c8645c198616f9a5d7c91eb
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c38da853d6c799f6/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_c38da853d6c799f6",
+    "api_calls": 0,
+    "input_tokens": 16819,
+    "cached_input_tokens": 15744,
+    "output_tokens": 471,
+    "total_tokens": 17290,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 18086.43,
+    "sql_execution_elapsed_ms_total": 2.68,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c38da853d6c799f6/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c38da853d6c799f6/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c38da853d6c799f6/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..4781a0d9f13dfc707dc02290b87dde4d90bb4113
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c38da853d6c799f6/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:48:59.778214+00:00",
+  "ended_at": "2026-05-19T15:49:17.864683+00:00",
+  "elapsed_ms": 18086.43,
+  "prompt_metrics": {
+    "chars": 16885,
+    "bytes_utf8": 16885,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1783,
+    "bytes_utf8": 1783,
+    "lines": 6,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 702,
+      "bytes_utf8": 702,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16819,
+      "cached_input_tokens": 15744,
+      "output_tokens": 471,
+      "reasoning_output_tokens": 277
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c38da853d6c799f6/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c38da853d6c799f6/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..ce6baefc5e91a314550398922a141877f8e98641
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c38da853d6c799f6/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_tpch_relative_total_threshold",
+    "template_name": "Relative-to-Total Extreme Threshold",
+    "primary_family": "tail_rarity_structure",
+    "portability": "partial",
+    "sql_skeleton": "WITH grouped AS (\n    SELECT {group_col}, SUM({measure_col}) AS group_value\n    FROM {table}\n    GROUP BY {group_col}\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=Industry, measure_col=Quality_Score.",
+  "planned_template_id": "tpl_tpch_relative_total_threshold",
+  "bindings": {
+    "group_col": "Industry",
+    "measure_col": "Quality_Score",
+    "top_k": 16,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 93.6,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "WITH grouped AS (\n    SELECT {group_col}, SUM({measure_col}) AS group_value\n    FROM {table}\n    GROUP BY {group_col}\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c38da853d6c799f6/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c38da853d6c799f6/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..172264cba0245b8aa48575f468f31678ddf21bf3
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c38da853d6c799f6/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,6 @@
+{"type":"thread.started","thread_id":"019e40ed-15f5-7522-b0e4-09ea225416cc"}
+{"type":"turn.started"}
+{"type":"error","message":"Reconnecting... 2/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 2000000, Requested 17454. Please try again in 523ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"error","message":"Reconnecting... 3/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1985309, Requested 17454. Please try again in 82ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH \\\"grouped\\\" AS (\\n    SELECT \\\"Industry\\\", SUM(CAST(\\\"Quality_Score\\\" AS REAL)) AS \\\"group_value\\\"\\n    FROM \\\"m1\\\"\\n    GROUP BY \\\"Industry\\\"\\n),\\n\\\"total\\\" AS (\\n    SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n    FROM \\\"grouped\\\"\\n)\\nSELECT g.\\\"Industry\\\", g.\\\"group_value\\\"\\nFROM \\\"grouped\\\" AS g\\nCROSS JOIN \\\"total\\\" AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.05\\nORDER BY g.\\\"group_value\\\" DESC;\",\"notes\":\"Used the required Relative-to-Total Extreme Threshold template with group_col=\\\"Industry\\\" and measure_col=\\\"Quality_Score\\\". CAST to REAL is included because the schema stores numeric-looking values as TEXT.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16819,"cached_input_tokens":15744,"output_tokens":471,"reasoning_output_tokens":277}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c38da853d6c799f6/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c38da853d6c799f6/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..c98d8f1ff9776465aafdebce08b32e9f55dd96d9
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c38da853d6c799f6/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tpch_relative_total_threshold\nWITH \"grouped\" AS (\n    SELECT \"Industry\", SUM(CAST(\"Quality_Score\" AS REAL)) AS \"group_value\"\n    FROM \"m1\"\n    GROUP BY \"Industry\"\n),\n\"total\" AS (\n    SELECT SUM(\"group_value\") AS \"total_value\"\n    FROM \"grouped\"\n)\nSELECT g.\"Industry\", g.\"group_value\"\nFROM \"grouped\" AS g\nCROSS JOIN \"total\" AS t\nWHERE g.\"group_value\" > t.\"total_value\" * 0.05\nORDER BY g.\"group_value\" DESC;","notes":"Used the required Relative-to-Total Extreme Threshold template with group_col=\"Industry\" and measure_col=\"Quality_Score\". CAST to REAL is included because the schema stores numeric-looking values as TEXT."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c38da853d6c799f6/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c38da853d6c799f6/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c5d752a9ffd5e1d6/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c5d752a9ffd5e1d6/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..0482639dcbeb2b136103e808593632a9dc0ba888
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c5d752a9ffd5e1d6/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16898, "bytes_utf8": 16898, "lines": 456, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 782, "bytes_utf8": 782, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16821, "cached_input_tokens": 15744, "output_tokens": 586, "reasoning_output_tokens": 384}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c5d752a9ffd5e1d6/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c5d752a9ffd5e1d6/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..e58f586b3ec805afc2f846d51c9644bb72456dc9
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c5d752a9ffd5e1d6/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_c5d752a9ffd5e1d6",
+    "api_calls": 0,
+    "input_tokens": 16821,
+    "cached_input_tokens": 15744,
+    "output_tokens": 586,
+    "total_tokens": 17407,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 12450.78,
+    "sql_execution_elapsed_ms_total": 1.93,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c5d752a9ffd5e1d6/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c5d752a9ffd5e1d6/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c5d752a9ffd5e1d6/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..a78d34cd2b79d947710fb9fbc220ef4950352853
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c5d752a9ffd5e1d6/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:50:56.886293+00:00",
+  "ended_at": "2026-05-19T15:51:09.337101+00:00",
+  "elapsed_ms": 12450.78,
+  "prompt_metrics": {
+    "chars": 16898,
+    "bytes_utf8": 16898,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1167,
+    "bytes_utf8": 1167,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 782,
+      "bytes_utf8": 782,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16821,
+      "cached_input_tokens": 15744,
+      "output_tokens": 586,
+      "reasoning_output_tokens": 384
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c5d752a9ffd5e1d6/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c5d752a9ffd5e1d6/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..1f8a9fbf317309a33dc397258f6476b5d528f90a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c5d752a9ffd5e1d6/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_tpch_relative_total_threshold",
+    "template_name": "Relative-to-Total Extreme Threshold",
+    "primary_family": "tail_rarity_structure",
+    "portability": "partial",
+    "sql_skeleton": "WITH grouped AS (\n    SELECT {group_col}, SUM({measure_col}) AS group_value\n    FROM {table}\n    GROUP BY {group_col}\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=Stress_Level, measure_col=Job_Satisfaction.",
+  "planned_template_id": "tpl_tpch_relative_total_threshold",
+  "bindings": {
+    "group_col": "Stress_Level",
+    "measure_col": "Job_Satisfaction",
+    "top_k": 11,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 100.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "WITH grouped AS (\n    SELECT {group_col}, SUM({measure_col}) AS group_value\n    FROM {table}\n    GROUP BY {group_col}\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c5d752a9ffd5e1d6/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c5d752a9ffd5e1d6/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b98bb05d0d9391ef2a80951959f8fa3b98ca09bc
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c5d752a9ffd5e1d6/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40ee-df97-7220-86fb-0de4cfba4340"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold.\\nWITH grouped AS (\\n    SELECT\\n        \\\"Stress_Level\\\",\\n        SUM(CAST(\\\"Job_Satisfaction\\\" AS REAL)) AS group_value\\n    FROM \\\"m1\\\"\\n    WHERE \\\"Stress_Level\\\" IS NOT NULL\\n      AND \\\"Job_Satisfaction\\\" IS NOT NULL\\n    GROUP BY \\\"Stress_Level\\\"\\n), total AS (\\n    SELECT SUM(group_value) AS total_value\\n    FROM grouped\\n)\\nSELECT\\n    g.\\\"Stress_Level\\\",\\n    g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.1\\nORDER BY g.group_value DESC;\",\"notes\":\"Used the planned Relative-to-Total Extreme Threshold template with group_col=\\\"Stress_Level\\\" and measure_col=\\\"Job_Satisfaction\\\". Cast \\\"Job_Satisfaction\\\" to REAL because the SQLite schema stores it as TEXT.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16821,"cached_input_tokens":15744,"output_tokens":586,"reasoning_output_tokens":384}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c5d752a9ffd5e1d6/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c5d752a9ffd5e1d6/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e858c14ede26a7432e4d4db541e3c1394e3a4b5b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c5d752a9ffd5e1d6/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tpch_relative_total_threshold.\nWITH grouped AS (\n    SELECT\n        \"Stress_Level\",\n        SUM(CAST(\"Job_Satisfaction\" AS REAL)) AS group_value\n    FROM \"m1\"\n    WHERE \"Stress_Level\" IS NOT NULL\n      AND \"Job_Satisfaction\" IS NOT NULL\n    GROUP BY \"Stress_Level\"\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT\n    g.\"Stress_Level\",\n    g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * 0.1\nORDER BY g.group_value DESC;","notes":"Used the planned Relative-to-Total Extreme Threshold template with group_col=\"Stress_Level\" and measure_col=\"Job_Satisfaction\". Cast \"Job_Satisfaction\" to REAL because the SQLite schema stores it as TEXT."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c5d752a9ffd5e1d6/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_c5d752a9ffd5e1d6/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_cedf08d47958fc8f/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_cedf08d47958fc8f/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..374591baccdb09aed8a4f5fb0eaa4ea26528d525
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_cedf08d47958fc8f/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=Industry, measure_col=Meetings_Per_Week.",
+  "planned_template_id": "tpl_grouped_percentile_point",
+  "bindings": {
+    "group_col": "Industry",
+    "measure_col": "Meetings_Per_Week",
+    "top_k": 13,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 10.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_cedf08d47958fc8f/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_cedf08d47958fc8f/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..7464d8928b09f05009232df313d37f027c29d948
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_cedf08d47958fc8f/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f8-2045-74d0-99a6-e9582e7745ff"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n  SELECT\\n    \\\"Industry\\\",\\n    CAST(\\\"Meetings_Per_Week\\\" AS REAL) AS \\\"measure_value\\\",\\n    COUNT(*) OVER (PARTITION BY \\\"Industry\\\") AS \\\"group_size\\\",\\n    CUME_DIST() OVER (\\n      PARTITION BY \\\"Industry\\\"\\n      ORDER BY CAST(\\\"Meetings_Per_Week\\\" AS REAL)\\n    ) AS \\\"cume_dist_value\\\"\\n  FROM \\\"m1\\\"\\n  WHERE \\\"Industry\\\" IS NOT NULL\\n    AND \\\"Meetings_Per_Week\\\" IS NOT NULL\\n),\\n\\\"percentiles\\\" AS (\\n  SELECT\\n    \\\"Industry\\\",\\n    MIN(\\\"measure_value\\\") AS \\\"percentile_measure\\\",\\n    MAX(\\\"group_size\\\") AS \\\"group_size\\\"\\n  FROM \\\"ranked\\\"\\n  WHERE \\\"cume_dist_value\\\" >= 0.9\\n  GROUP BY \\\"Industry\\\"\\n)\\nSELECT\\n  \\\"Industry\\\",\\n  \\\"percentile_measure\\\"\\nFROM \\\"percentiles\\\"\\nWHERE \\\"group_size\\\" >= 5\\nORDER BY \\\"percentile_measure\\\" DESC\\nLIMIT 13;\",\"notes\":\"SQLite does not support PERCENTILE_CONT, so this uses a CUME_DIST-based discrete 90th-percentile surrogate for \\\"Meetings_Per_Week\\\" within each \\\"Industry\\\", filters out groups with fewer than 5 rows, and ranks the results descending.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16723,"cached_input_tokens":12032,"output_tokens":2901,"reasoning_output_tokens":2588}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_cf451603badf73b4/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_cf451603badf73b4/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..cebf076b4764bd8a6a552d51008fad8ddd3fd397
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_cf451603badf73b4/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16623, "bytes_utf8": 16623, "lines": 459, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 482, "bytes_utf8": 482, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16753, "cached_input_tokens": 12032, "output_tokens": 314, "reasoning_output_tokens": 188}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_cf451603badf73b4/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_cf451603badf73b4/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..eece6e7afce19b897edccf781aa12e29c0e742e3
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_cf451603badf73b4/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_cf451603badf73b4",
+    "api_calls": 0,
+    "input_tokens": 16753,
+    "cached_input_tokens": 12032,
+    "output_tokens": 314,
+    "total_tokens": 17067,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 9396.85,
+    "sql_execution_elapsed_ms_total": 1.15,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_cf451603badf73b4/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_cf451603badf73b4/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_cf451603badf73b4/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..27efc841d4b7c41597d99145a404d43ca1e212f3
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_cf451603badf73b4/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:03:15.021968+00:00",
+  "ended_at": "2026-05-19T16:03:24.418843+00:00",
+  "elapsed_ms": 9396.85,
+  "prompt_metrics": {
+    "chars": 16623,
+    "bytes_utf8": 16623,
+    "lines": 459,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 841,
+    "bytes_utf8": 841,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 482,
+      "bytes_utf8": 482,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16753,
+      "cached_input_tokens": 12032,
+      "output_tokens": 314,
+      "reasoning_output_tokens": 188
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_cf451603badf73b4/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_cf451603badf73b4/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..07a4c87ffc5c260b02998450db98340061a640e2
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_cf451603badf73b4/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,459 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_group_condition_rate",
+    "template_name": "Grouped Condition Rate",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;",
+    "required_roles": [
+      "group_col",
+      "condition_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Condition Rate to probe direction_consistency with semantic role within_group_proportion. Focus on group_col=Team_Collaboration_Frequency, condition_col=Job_Level.",
+  "planned_template_id": "tpl_m4_group_condition_rate",
+  "bindings": {
+    "group_col": "Team_Collaboration_Frequency",
+    "condition_col": "Job_Level",
+    "condition_value": "Mid-Level",
+    "positive_value": "Junior",
+    "negative_value": "Mid-Level",
+    "top_k": 17,
+    "top_n": 5,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 8.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_cf451603badf73b4/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_cf451603badf73b4/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e5fcac6d752c1e89bdb1fae3cffb6c9f6b101bec
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_cf451603badf73b4/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fa-22cb-7923-a35b-7c618bf6b220"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"Team_Collaboration_Frequency\\\",\\n       AVG(CASE WHEN \\\"Job_Level\\\" = 'Mid-Level' THEN 1 ELSE 0 END) AS condition_rate\\nFROM \\\"m1\\\"\\nGROUP BY \\\"Team_Collaboration_Frequency\\\"\\nORDER BY condition_rate DESC;\",\"notes\":\"Uses the Grouped Condition Rate template with group_col=\\\"Team_Collaboration_Frequency\\\" and condition_col=\\\"Job_Level\\\", measuring the within-group proportion of rows where \\\"Job_Level\\\" = 'Mid-Level'.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16753,"cached_input_tokens":12032,"output_tokens":314,"reasoning_output_tokens":188}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_cf451603badf73b4/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_cf451603badf73b4/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..a6ffe1a2a572d873370a8de68a1716f034848edf
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_cf451603badf73b4/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_m4_group_condition_rate\nSELECT \"Team_Collaboration_Frequency\",\n       AVG(CASE WHEN \"Job_Level\" = 'Mid-Level' THEN 1 ELSE 0 END) AS condition_rate\nFROM \"m1\"\nGROUP BY \"Team_Collaboration_Frequency\"\nORDER BY condition_rate DESC;","notes":"Uses the Grouped Condition Rate template with group_col=\"Team_Collaboration_Frequency\" and condition_col=\"Job_Level\", measuring the within-group proportion of rows where \"Job_Level\" = 'Mid-Level'."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_cf451603badf73b4/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_cf451603badf73b4/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..c35224c8f0ce38fc8176eb2ee0aa56a7cde3f1f5
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/conversation.jsonl
@@ -0,0 +1,4 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16513, "bytes_utf8": 16513, "lines": 456, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "status": "failed", "error": "AI CLI command failed with exit code 1: "}
+{"attempt": 2, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_2.txt", "metrics": {"chars": 16513, "bytes_utf8": 16513, "lines": 456, "estimated_tokens": null}}
+{"attempt": 2, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_2.txt", "raw_content_path": "cli/sql_response_attempt_2.raw.txt", "stderr_path": "cli/sql_stderr_attempt_2.txt", "metrics": {"chars": 1836, "bytes_utf8": 1836, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16721, "cached_input_tokens": 15744, "output_tokens": 1124, "reasoning_output_tokens": 516}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..f05fa0dc8884954ce23dd7335fd37435a9129bfd
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 2,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_d0aa13aa38e488cc",
+    "api_calls": 0,
+    "input_tokens": 16721,
+    "cached_input_tokens": 15744,
+    "output_tokens": 1124,
+    "total_tokens": 17845,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 2,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 22435.79,
+    "sql_execution_elapsed_ms_total": 6.09,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..2c73239c1c1ccb4f8a1d53b9bed26ac2d6c74df6
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:58:48.183557+00:00",
+  "ended_at": "2026-05-19T15:58:51.100501+00:00",
+  "elapsed_ms": 2916.91,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16513,
+    "bytes_utf8": 16513,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_attempt_2.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..b4ecb1a001860d3878b980018ee9496a279aa9fe
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_attempt_2.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:58:52.103407+00:00",
+  "ended_at": "2026-05-19T15:59:11.622329+00:00",
+  "elapsed_ms": 19518.88,
+  "prompt_metrics": {
+    "chars": 16513,
+    "bytes_utf8": 16513,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 2455,
+    "bytes_utf8": 2455,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 1836,
+      "bytes_utf8": 1836,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16721,
+      "cached_input_tokens": 15744,
+      "output_tokens": 1124,
+      "reasoning_output_tokens": 516
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_2.txt",
+  "response_path": "cli/sql_response_attempt_2.txt",
+  "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_2.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..c990a466f5a9f97ea8f752212d412a18cad2ecf3
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=Job_Level, measure_col=Innovation_Score.",
+  "planned_template_id": "tpl_grouped_percentile_point",
+  "bindings": {
+    "group_col": "Job_Level",
+    "measure_col": "Innovation_Score",
+    "top_k": 11,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 84.2,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_prompt_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..c990a466f5a9f97ea8f752212d412a18cad2ecf3
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_prompt_attempt_2.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=Job_Level, measure_col=Innovation_Score.",
+  "planned_template_id": "tpl_grouped_percentile_point",
+  "bindings": {
+    "group_col": "Job_Level",
+    "measure_col": "Innovation_Score",
+    "top_k": 11,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 84.2,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..593b355ec28358a104a3f9565a1cba4fa4533abc
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f6-1087-73b3-9f60-f19272ddd5e3"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..cb142bcb6f6df312b9f25fe8de753075b78ae92c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_response_attempt_1.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f6-1087-73b3-9f60-f19272ddd5e3"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_response_attempt_2.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..08d4a73231fc583ebd32d2758a9e573d4ed021e3
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_response_attempt_2.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f6-1fc5-7e73-a9d8-35d4fc970221"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ordered\\\" AS (\\n  SELECT\\n    \\\"Job_Level\\\",\\n    CAST(\\\"Innovation_Score\\\" AS REAL) AS \\\"measure_value\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"Job_Level\\\"\\n      ORDER BY CAST(\\\"Innovation_Score\\\" AS REAL)\\n    ) AS \\\"rn\\\",\\n    COUNT(*) OVER (\\n      PARTITION BY \\\"Job_Level\\\"\\n    ) AS \\\"cnt\\\"\\n  FROM \\\"m1\\\"\\n  WHERE \\\"Job_Level\\\" IS NOT NULL\\n    AND \\\"Innovation_Score\\\" IS NOT NULL\\n),\\n\\\"positions\\\" AS (\\n  SELECT DISTINCT\\n    \\\"Job_Level\\\",\\n    \\\"cnt\\\",\\n    ((\\\"cnt\\\" - 1) * 0.9) AS \\\"raw_pos\\\",\\n    CAST(((\\\"cnt\\\" - 1) * 0.9) AS INTEGER) + 1 AS \\\"lower_rn\\\",\\n    CASE\\n      WHEN ((\\\"cnt\\\" - 1) * 0.9) = CAST(((\\\"cnt\\\" - 1) * 0.9) AS INTEGER) THEN CAST(((\\\"cnt\\\" - 1) * 0.9) AS INTEGER) + 1\\n      ELSE CAST(((\\\"cnt\\\" - 1) * 0.9) AS INTEGER) + 2\\n    END AS \\\"upper_rn\\\"\\n  FROM \\\"ordered\\\"\\n),\\n\\\"picked\\\" AS (\\n  SELECT\\n    o.\\\"Job_Level\\\",\\n    p.\\\"raw_pos\\\",\\n    p.\\\"lower_rn\\\",\\n    p.\\\"upper_rn\\\",\\n    MAX(CASE WHEN o.\\\"rn\\\" = p.\\\"lower_rn\\\" THEN o.\\\"measure_value\\\" END) AS \\\"lower_value\\\",\\n    MAX(CASE WHEN o.\\\"rn\\\" = p.\\\"upper_rn\\\" THEN o.\\\"measure_value\\\" END) AS \\\"upper_value\\\"\\n  FROM \\\"ordered\\\" AS o\\n  JOIN \\\"positions\\\" AS p\\n    ON o.\\\"Job_Level\\\" = p.\\\"Job_Level\\\"\\n  GROUP BY\\n    o.\\\"Job_Level\\\",\\n    p.\\\"raw_pos\\\",\\n    p.\\\"lower_rn\\\",\\n    p.\\\"upper_rn\\\"\\n)\\nSELECT\\n  \\\"Job_Level\\\",\\n  CASE\\n    WHEN \\\"lower_rn\\\" = \\\"upper_rn\\\" THEN \\\"lower_value\\\"\\n    ELSE \\\"lower_value\\\" + (\\\"raw_pos\\\" - CAST(\\\"raw_pos\\\" AS INTEGER)) * (\\\"upper_value\\\" - \\\"lower_value\\\")\\n  END AS \\\"percentile_measure\\\"\\nFROM \\\"picked\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\",\"notes\":\"Emulates PERCENTILE_CONT(0.9) per \\\"Job_Level\\\" in SQLite using window functions and linear interpolation, with \\\"Innovation_Score\\\" cast from TEXT to REAL.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16721,"cached_input_tokens":15744,"output_tokens":1124,"reasoning_output_tokens":516}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_response_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..7149359f91e4fd6140af46e082365aa2bd491f62
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_response_attempt_2.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_grouped_percentile_point\nWITH \"ordered\" AS (\n  SELECT\n    \"Job_Level\",\n    CAST(\"Innovation_Score\" AS REAL) AS \"measure_value\",\n    ROW_NUMBER() OVER (\n      PARTITION BY \"Job_Level\"\n      ORDER BY CAST(\"Innovation_Score\" AS REAL)\n    ) AS \"rn\",\n    COUNT(*) OVER (\n      PARTITION BY \"Job_Level\"\n    ) AS \"cnt\"\n  FROM \"m1\"\n  WHERE \"Job_Level\" IS NOT NULL\n    AND \"Innovation_Score\" IS NOT NULL\n),\n\"positions\" AS (\n  SELECT DISTINCT\n    \"Job_Level\",\n    \"cnt\",\n    ((\"cnt\" - 1) * 0.9) AS \"raw_pos\",\n    CAST(((\"cnt\" - 1) * 0.9) AS INTEGER) + 1 AS \"lower_rn\",\n    CASE\n      WHEN ((\"cnt\" - 1) * 0.9) = CAST(((\"cnt\" - 1) * 0.9) AS INTEGER) THEN CAST(((\"cnt\" - 1) * 0.9) AS INTEGER) + 1\n      ELSE CAST(((\"cnt\" - 1) * 0.9) AS INTEGER) + 2\n    END AS \"upper_rn\"\n  FROM \"ordered\"\n),\n\"picked\" AS (\n  SELECT\n    o.\"Job_Level\",\n    p.\"raw_pos\",\n    p.\"lower_rn\",\n    p.\"upper_rn\",\n    MAX(CASE WHEN o.\"rn\" = p.\"lower_rn\" THEN o.\"measure_value\" END) AS \"lower_value\",\n    MAX(CASE WHEN o.\"rn\" = p.\"upper_rn\" THEN o.\"measure_value\" END) AS \"upper_value\"\n  FROM \"ordered\" AS o\n  JOIN \"positions\" AS p\n    ON o.\"Job_Level\" = p.\"Job_Level\"\n  GROUP BY\n    o.\"Job_Level\",\n    p.\"raw_pos\",\n    p.\"lower_rn\",\n    p.\"upper_rn\"\n)\nSELECT\n  \"Job_Level\",\n  CASE\n    WHEN \"lower_rn\" = \"upper_rn\" THEN \"lower_value\"\n    ELSE \"lower_value\" + (\"raw_pos\" - CAST(\"raw_pos\" AS INTEGER)) * (\"upper_value\" - \"lower_value\")\n  END AS \"percentile_measure\"\nFROM \"picked\"\nORDER BY \"percentile_measure\" DESC;","notes":"Emulates PERCENTILE_CONT(0.9) per \"Job_Level\" in SQLite using window functions and linear interpolation, with \"Innovation_Score\" cast from TEXT to REAL."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d0aa13aa38e488cc/cli/sql_stderr_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d1812e90e549c4d7/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d1812e90e549c4d7/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..fb17d0cad7ff7ec471f577432ac43a61de7bafe8
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d1812e90e549c4d7/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 17181, "bytes_utf8": 17181, "lines": 459, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 759, "bytes_utf8": 759, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16896, "cached_input_tokens": 15744, "output_tokens": 560, "reasoning_output_tokens": 370}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d1812e90e549c4d7/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d1812e90e549c4d7/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..1cbac7127c4b8f85084491f1e933079bc856ac74
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d1812e90e549c4d7/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_d1812e90e549c4d7",
+    "api_calls": 0,
+    "input_tokens": 16896,
+    "cached_input_tokens": 15744,
+    "output_tokens": 560,
+    "total_tokens": 17456,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 14854.22,
+    "sql_execution_elapsed_ms_total": 1.71,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d1812e90e549c4d7/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d1812e90e549c4d7/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d1812e90e549c4d7/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..c349e3cb44f59b58dbf09a0cb83fd6b76f4f8a5e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d1812e90e549c4d7/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:42:23.841255+00:00",
+  "ended_at": "2026-05-19T15:42:38.695505+00:00",
+  "elapsed_ms": 14854.22,
+  "prompt_metrics": {
+    "chars": 17181,
+    "bytes_utf8": 17181,
+    "lines": 459,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1128,
+    "bytes_utf8": 1128,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 759,
+      "bytes_utf8": 759,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16896,
+      "cached_input_tokens": 15744,
+      "output_tokens": 560,
+      "reasoning_output_tokens": 370
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d1812e90e549c4d7/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d1812e90e549c4d7/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..4c0cf758bb91901b87d44088ef69f5066891bdf1
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d1812e90e549c4d7/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,459 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_group_ratio_two_conditions",
+    "template_name": "Grouped Ratio of Two Conditions",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "yes",
+    "sql_skeleton": "WITH grouped AS (\n    SELECT {group_col},\n           SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n           SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n    FROM {table}\n    GROUP BY {group_col}\n)\nSELECT {group_col},\n       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;",
+    "required_roles": [
+      "group_col",
+      "condition_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=Internet_Speed_Category, condition_col=Location_Type.",
+  "planned_template_id": "tpl_m4_group_ratio_two_conditions",
+  "bindings": {
+    "group_col": "Internet_Speed_Category",
+    "condition_col": "Location_Type",
+    "condition_value": "Suburban",
+    "positive_value": "Suburban",
+    "negative_value": "Urban",
+    "top_k": 14,
+    "top_n": 3,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 4.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "WITH grouped AS (\n    SELECT {group_col},\n           SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n           SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n    FROM {table}\n    GROUP BY {group_col}\n)\nSELECT {group_col},\n       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d1812e90e549c4d7/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d1812e90e549c4d7/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..de5e0cbe2a55d97b684b84f2d641fa9f7bba755c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d1812e90e549c4d7/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40e7-0b6a-7e23-acb0-800c74b5e424"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n    SELECT \\\"Internet_Speed_Category\\\",\\n           SUM(CASE WHEN \\\"Location_Type\\\" = 'Suburban' THEN 1 ELSE 0 END) AS numerator_count,\\n           SUM(CASE WHEN \\\"Location_Type\\\" = 'Urban' THEN 1 ELSE 0 END) AS denominator_count\\n    FROM \\\"m1\\\"\\n    GROUP BY \\\"Internet_Speed_Category\\\"\\n)\\nSELECT \\\"Internet_Speed_Category\\\",\\n       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\",\"notes\":\"Instantiated the grouped ratio template with group_col=\\\"Internet_Speed_Category\\\" and condition_col=\\\"Location_Type\\\", using 'Suburban' as the numerator condition and 'Urban' as the denominator condition.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16896,"cached_input_tokens":15744,"output_tokens":560,"reasoning_output_tokens":370}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d1812e90e549c4d7/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d1812e90e549c4d7/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..2b8a3b34ece1aee268127e8ec830437a78d6b30a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d1812e90e549c4d7/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_m4_group_ratio_two_conditions\nWITH grouped AS (\n    SELECT \"Internet_Speed_Category\",\n           SUM(CASE WHEN \"Location_Type\" = 'Suburban' THEN 1 ELSE 0 END) AS numerator_count,\n           SUM(CASE WHEN \"Location_Type\" = 'Urban' THEN 1 ELSE 0 END) AS denominator_count\n    FROM \"m1\"\n    GROUP BY \"Internet_Speed_Category\"\n)\nSELECT \"Internet_Speed_Category\",\n       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;","notes":"Instantiated the grouped ratio template with group_col=\"Internet_Speed_Category\" and condition_col=\"Location_Type\", using 'Suburban' as the numerator condition and 'Urban' as the denominator condition."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d1812e90e549c4d7/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d1812e90e549c4d7/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d4bbf84268ee27df/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d4bbf84268ee27df/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..efe56b86541d45e298cd16ae47cef452b907bcc3
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d4bbf84268ee27df/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16348, "bytes_utf8": 16348, "lines": 456, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 404, "bytes_utf8": 404, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16685, "cached_input_tokens": 12032, "output_tokens": 393, "reasoning_output_tokens": 286}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d4bbf84268ee27df/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d4bbf84268ee27df/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..bd2cf7ca36e8fe80c521464eef7008ac203f7fee
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d4bbf84268ee27df/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_d4bbf84268ee27df",
+    "api_calls": 0,
+    "input_tokens": 16685,
+    "cached_input_tokens": 12032,
+    "output_tokens": 393,
+    "total_tokens": 17078,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 9943.39,
+    "sql_execution_elapsed_ms_total": 1.16,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d4bbf84268ee27df/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d4bbf84268ee27df/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d4bbf84268ee27df/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..d3d1b477c2986403350637eaeb97b549ae89243e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d4bbf84268ee27df/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:29:41.987057+00:00",
+  "ended_at": "2026-05-19T15:29:51.930478+00:00",
+  "elapsed_ms": 9943.39,
+  "prompt_metrics": {
+    "chars": 16348,
+    "bytes_utf8": 16348,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 762,
+    "bytes_utf8": 762,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 404,
+      "bytes_utf8": 404,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16685,
+      "cached_input_tokens": 12032,
+      "output_tokens": 393,
+      "reasoning_output_tokens": 286
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d4bbf84268ee27df/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d4bbf84268ee27df/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..4eb74e5b02cad73073c245ec7c14167ca8175bd4
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d4bbf84268ee27df/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_h2o_group_sum",
+    "template_name": "Grouped Numeric Sum",
+    "primary_family": "subgroup_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=Location_Type, measure_col=Productivity_Score.",
+  "planned_template_id": "tpl_h2o_group_sum",
+  "bindings": {
+    "group_col": "Location_Type",
+    "measure_col": "Productivity_Score",
+    "top_k": 14,
+    "top_n": 3,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 98.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d4bbf84268ee27df/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d4bbf84268ee27df/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..83541ff4a9c34a048d866042336ea622fd0e0a3e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d4bbf84268ee27df/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40db-6b6f-7511-a2fa-0f6200092bd1"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"Location_Type\\\", SUM(CAST(\\\"Productivity_Score\\\" AS REAL)) AS total_measure\\nFROM \\\"m1\\\"\\nGROUP BY \\\"Location_Type\\\"\\nORDER BY total_measure DESC;\",\"notes\":\"Used the planned grouped-sum template with group_col=\\\"Location_Type\\\" and measure_col=\\\"Productivity_Score\\\". Casted \\\"Productivity_Score\\\" to REAL because the SQLite schema stores it as TEXT.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16685,"cached_input_tokens":12032,"output_tokens":393,"reasoning_output_tokens":286}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d4bbf84268ee27df/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d4bbf84268ee27df/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..84e5019e5a7330b1d4ce4a02d9162ceb6081efed
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d4bbf84268ee27df/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_h2o_group_sum\nSELECT \"Location_Type\", SUM(CAST(\"Productivity_Score\" AS REAL)) AS total_measure\nFROM \"m1\"\nGROUP BY \"Location_Type\"\nORDER BY total_measure DESC;","notes":"Used the planned grouped-sum template with group_col=\"Location_Type\" and measure_col=\"Productivity_Score\". Casted \"Productivity_Score\" to REAL because the SQLite schema stores it as TEXT."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d4bbf84268ee27df/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d4bbf84268ee27df/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d5258be445612f80/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d5258be445612f80/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..84580bd33b12c1c51655304cda5d3473ed5f6c46
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d5258be445612f80/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16686, "bytes_utf8": 16686, "lines": 460, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 521, "bytes_utf8": 521, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16787, "cached_input_tokens": 12032, "output_tokens": 455, "reasoning_output_tokens": 322}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d5258be445612f80/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d5258be445612f80/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..94e681bfe5449aa075f95eb52a0dff854d0d8062
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d5258be445612f80/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_d5258be445612f80",
+    "api_calls": 0,
+    "input_tokens": 16787,
+    "cached_input_tokens": 12032,
+    "output_tokens": 455,
+    "total_tokens": 17242,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 12585.72,
+    "sql_execution_elapsed_ms_total": 1.52,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d5258be445612f80/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d5258be445612f80/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d5258be445612f80/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..c5991b026e0e68d5362930944bc8976292168e17
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d5258be445612f80/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:43:31.761059+00:00",
+  "ended_at": "2026-05-19T15:43:44.346810+00:00",
+  "elapsed_ms": 12585.72,
+  "prompt_metrics": {
+    "chars": 16686,
+    "bytes_utf8": 16686,
+    "lines": 460,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 888,
+    "bytes_utf8": 888,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 521,
+      "bytes_utf8": 521,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16787,
+      "cached_input_tokens": 12032,
+      "output_tokens": 455,
+      "reasoning_output_tokens": 322
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d5258be445612f80/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d5258be445612f80/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..374dea9ca0f42beb295b531cca71f1de045d5a0e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d5258be445612f80/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,460 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_c2_filtered_group_count_2d",
+    "template_name": "Filtered Two-Dimensional Group Count",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;",
+    "required_roles": [
+      "group_col",
+      "group_col_2",
+      "predicate_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Filtered Two-Dimensional Group Count to probe slice_level_consistency with semantic role count_distribution. Focus on group_col=Has_Children, group_col_2=Team_Collaboration_Frequency.",
+  "planned_template_id": "tpl_c2_filtered_group_count_2d",
+  "bindings": {
+    "group_col": "Has_Children",
+    "group_col_2": "Team_Collaboration_Frequency",
+    "predicate_col": "Job_Satisfaction",
+    "predicate_op": ">=",
+    "predicate_value": 100.0,
+    "top_k": 13,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 100.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d5258be445612f80/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d5258be445612f80/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..68d005e2366b4124685d243f36ad00b218ecabae
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d5258be445612f80/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40e8-14ba-7c53-b0ac-6b3b1154ee3d"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_c2_filtered_group_count_2d\\nSELECT \\\"Has_Children\\\", \\\"Team_Collaboration_Frequency\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"m1\\\"\\nWHERE CAST(\\\"Job_Satisfaction\\\" AS REAL) >= 100.0\\nGROUP BY \\\"Has_Children\\\", \\\"Team_Collaboration_Frequency\\\"\\nORDER BY \\\"row_count\\\" DESC;\",\"notes\":\"Used the required filtered two-dimensional group count template with the bound grouping columns. Cast \\\"Job_Satisfaction\\\" to REAL because the schema snapshot types it as TEXT while the predicate value is numeric.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16787,"cached_input_tokens":12032,"output_tokens":455,"reasoning_output_tokens":322}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d5258be445612f80/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d5258be445612f80/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..110b7b243be07dc2564bb97e11d3cd038c1902ea
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d5258be445612f80/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_c2_filtered_group_count_2d\nSELECT \"Has_Children\", \"Team_Collaboration_Frequency\", COUNT(*) AS \"row_count\"\nFROM \"m1\"\nWHERE CAST(\"Job_Satisfaction\" AS REAL) >= 100.0\nGROUP BY \"Has_Children\", \"Team_Collaboration_Frequency\"\nORDER BY \"row_count\" DESC;","notes":"Used the required filtered two-dimensional group count template with the bound grouping columns. Cast \"Job_Satisfaction\" to REAL because the schema snapshot types it as TEXT while the predicate value is numeric."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d5258be445612f80/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d5258be445612f80/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..3f9a8f92400afdb1ffeb45bb74d8576a8f2576ac
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:11:08.372910+00:00",
+  "ended_at": "2026-05-19T16:11:11.587359+00:00",
+  "elapsed_ms": 3214.42,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16429,
+    "bytes_utf8": 16429,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_attempt_2.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..088cfb380abe2df3075cb7922c539a38ea7e7aac
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_attempt_2.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:11:12.590351+00:00",
+  "ended_at": "2026-05-19T16:11:15.726961+00:00",
+  "elapsed_ms": 3136.58,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16429,
+    "bytes_utf8": 16429,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_2.txt",
+  "response_path": "cli/sql_response_attempt_2.txt",
+  "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_2.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..05d877f02fe54d0322744a9db37512f87f7d7fbd
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_window_partition_avg",
+    "template_name": "Window Partition Average",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Window Partition Average to probe direction_consistency with semantic role filtered_stable_view. Focus on group_col=Has_Children, measure_col=Work_Life_Balance.",
+  "planned_template_id": "tpl_m4_window_partition_avg",
+  "bindings": {
+    "group_col": "Has_Children",
+    "measure_col": "Work_Life_Balance",
+    "top_k": 19,
+    "top_n": 7,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 7.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_prompt_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..05d877f02fe54d0322744a9db37512f87f7d7fbd
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_prompt_attempt_2.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_window_partition_avg",
+    "template_name": "Window Partition Average",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Window Partition Average to probe direction_consistency with semantic role filtered_stable_view. Focus on group_col=Has_Children, measure_col=Work_Life_Balance.",
+  "planned_template_id": "tpl_m4_window_partition_avg",
+  "bindings": {
+    "group_col": "Has_Children",
+    "measure_col": "Work_Life_Balance",
+    "top_k": 19,
+    "top_n": 7,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 7.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..9e0433eb4354efdb904d1fb060306eb36e320989
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4101-5bdf-7961-a23b-f8a23752f0d3"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..ad0bbc9a4c804a776e815ebfebca5a3f834ce4d1
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_response_attempt_1.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4101-5bdf-7961-a23b-f8a23752f0d3"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_response_attempt_2.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..f9ad0bedc13f317daa6bfd4eb3c363137abd9ef9
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_response_attempt_2.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4101-6c4a-7c81-ade4-5b0b57b97f3e"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_response_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..8f41e1197efd702afcc681d8d564a321190ccdc6
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_response_attempt_2.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4101-6c4a-7c81-ade4-5b0b57b97f3e"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_d9ca320d964dd0cf/cli/sql_stderr_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..7b54182080b843b785699f868a512adc1f04d033
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:10:45.570651+00:00",
+  "ended_at": "2026-05-19T16:10:48.927125+00:00",
+  "elapsed_ms": 3356.44,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16423,
+    "bytes_utf8": 16423,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_attempt_2.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..f7cd3f33ddd8242b56b9fca98a385bfde27e8508
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_attempt_2.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:10:49.928797+00:00",
+  "ended_at": "2026-05-19T16:10:53.255775+00:00",
+  "elapsed_ms": 3326.95,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16423,
+    "bytes_utf8": 16423,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_2.txt",
+  "response_path": "cli/sql_response_attempt_2.txt",
+  "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_2.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..c1cc9e4426e19a8ec4fe68cb2a1fc875fd15e22d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_window_partition_avg",
+    "template_name": "Window Partition Average",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Window Partition Average to probe slice_level_consistency with semantic role filtered_stable_view. Focus on group_col=Marital_Status, measure_col=Stress_Level.",
+  "planned_template_id": "tpl_m4_window_partition_avg",
+  "bindings": {
+    "group_col": "Marital_Status",
+    "measure_col": "Stress_Level",
+    "top_k": 13,
+    "top_n": 5,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 7.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_prompt_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..c1cc9e4426e19a8ec4fe68cb2a1fc875fd15e22d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_prompt_attempt_2.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_window_partition_avg",
+    "template_name": "Window Partition Average",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Window Partition Average to probe slice_level_consistency with semantic role filtered_stable_view. Focus on group_col=Marital_Status, measure_col=Stress_Level.",
+  "planned_template_id": "tpl_m4_window_partition_avg",
+  "bindings": {
+    "group_col": "Marital_Status",
+    "measure_col": "Stress_Level",
+    "top_k": 13,
+    "top_n": 5,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 7.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..9dea33752ce271d392cdd163301808e34442a0c3
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4101-02c7-74b0-84a2-179e0367fffa"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..2417ed53d5cd3b50996452585b9659a2d418cb13
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_response_attempt_1.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4101-02c7-74b0-84a2-179e0367fffa"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_response_attempt_2.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..1acca5aafec9f88bcd64ca0a80dbd6cca7e91a2f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_response_attempt_2.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4101-13cc-7cb0-adac-5afc8ba983c1"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_response_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..ae3c32af5df4087f6cd025f03a890e5f18c91254
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_response_attempt_2.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4101-13cc-7cb0-adac-5afc8ba983c1"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_dc319b160933f964/cli/sql_stderr_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..ad9821746ab7331e76430ee9fc5ff2a783711537
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/conversation.jsonl
@@ -0,0 +1,4 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16516, "bytes_utf8": 16516, "lines": 456, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "status": "failed", "error": "AI CLI command failed with exit code 1: "}
+{"attempt": 2, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_2.txt", "metrics": {"chars": 16516, "bytes_utf8": 16516, "lines": 456, "estimated_tokens": null}}
+{"attempt": 2, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_2.txt", "raw_content_path": "cli/sql_response_attempt_2.raw.txt", "stderr_path": "cli/sql_stderr_attempt_2.txt", "metrics": {"chars": 1918, "bytes_utf8": 1918, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16723, "cached_input_tokens": 12032, "output_tokens": 3486, "reasoning_output_tokens": 2847}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..d5fdd1dc7e1b493df658a0710100262676548d4d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 2,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_e020021a868a8665",
+    "api_calls": 0,
+    "input_tokens": 16723,
+    "cached_input_tokens": 12032,
+    "output_tokens": 3486,
+    "total_tokens": 20209,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 2,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 55824.43,
+    "sql_execution_elapsed_ms_total": 8.63,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..a9d15a79bc90b74dc0e4c5c728578890b291a92f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:01:45.217467+00:00",
+  "ended_at": "2026-05-19T16:01:48.578973+00:00",
+  "elapsed_ms": 3361.46,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16516,
+    "bytes_utf8": 16516,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_attempt_2.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..f7582556c23bdaeb02f681d9811c3cd5cdac6403
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_attempt_2.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:01:49.581959+00:00",
+  "ended_at": "2026-05-19T16:02:42.044983+00:00",
+  "elapsed_ms": 52462.97,
+  "prompt_metrics": {
+    "chars": 16516,
+    "bytes_utf8": 16516,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 2513,
+    "bytes_utf8": 2513,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 1918,
+      "bytes_utf8": 1918,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16723,
+      "cached_input_tokens": 12032,
+      "output_tokens": 3486,
+      "reasoning_output_tokens": 2847
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_2.txt",
+  "response_path": "cli/sql_response_attempt_2.txt",
+  "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_2.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..396f613e1c34dff7c1e223666a1763d2836c2bae
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=Industry, measure_col=Meetings_Per_Week.",
+  "planned_template_id": "tpl_grouped_percentile_point",
+  "bindings": {
+    "group_col": "Industry",
+    "measure_col": "Meetings_Per_Week",
+    "top_k": 18,
+    "top_n": 5,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 9.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_prompt_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..396f613e1c34dff7c1e223666a1763d2836c2bae
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_prompt_attempt_2.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=Industry, measure_col=Meetings_Per_Week.",
+  "planned_template_id": "tpl_grouped_percentile_point",
+  "bindings": {
+    "group_col": "Industry",
+    "measure_col": "Meetings_Per_Week",
+    "top_k": 18,
+    "top_n": 5,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 9.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..9ea2719677b36f7e49284ff3e0911703c3206def
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f8-c432-7ba1-9283-4901b7500dff"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..f0af9b855976e06a725123ffb54c3edeacba9323
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_response_attempt_1.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f8-c432-7ba1-9283-4901b7500dff"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_response_attempt_2.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..3631661ad55c6fc81dcd048ba7d94c9dabb2f3cb
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_response_attempt_2.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f8-d52b-7643-a81c-7fa42fbb8531"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ordered\\\" AS (\\n  SELECT\\n    \\\"Industry\\\",\\n    CAST(\\\"Meetings_Per_Week\\\" AS REAL) AS \\\"measure_value\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"Industry\\\"\\n      ORDER BY CAST(\\\"Meetings_Per_Week\\\" AS REAL)\\n    ) AS \\\"rn\\\",\\n    COUNT(*) OVER (\\n      PARTITION BY \\\"Industry\\\"\\n    ) AS \\\"n\\\"\\n  FROM \\\"m1\\\"\\n  WHERE \\\"Industry\\\" IS NOT NULL\\n    AND \\\"Meetings_Per_Week\\\" IS NOT NULL\\n    AND TRIM(\\\"Meetings_Per_Week\\\") <> ''\\n),\\n\\\"bounds\\\" AS (\\n  SELECT\\n    \\\"Industry\\\",\\n    1.0 + 0.95 * (MAX(\\\"n\\\") - 1) AS \\\"pos\\\",\\n    CAST(1.0 + 0.95 * (MAX(\\\"n\\\") - 1) AS INTEGER) AS \\\"lower_rn\\\",\\n    CAST(1.0 + 0.95 * (MAX(\\\"n\\\") - 1) AS INTEGER) +\\n      CASE\\n        WHEN (1.0 + 0.95 * (MAX(\\\"n\\\") - 1)) > CAST(1.0 + 0.95 * (MAX(\\\"n\\\") - 1) AS INTEGER) THEN 1\\n        ELSE 0\\n      END AS \\\"upper_rn\\\"\\n  FROM \\\"ordered\\\"\\n  GROUP BY \\\"Industry\\\"\\n  HAVING MAX(\\\"n\\\") >= 5\\n)\\nSELECT\\n  b.\\\"Industry\\\",\\n  CASE\\n    WHEN b.\\\"lower_rn\\\" = b.\\\"upper_rn\\\" THEN\\n      MAX(CASE WHEN o.\\\"rn\\\" = b.\\\"lower_rn\\\" THEN o.\\\"measure_value\\\" END)\\n    ELSE\\n      MAX(CASE WHEN o.\\\"rn\\\" = b.\\\"lower_rn\\\" THEN o.\\\"measure_value\\\" END) +\\n      (b.\\\"pos\\\" - b.\\\"lower_rn\\\") * (\\n        MAX(CASE WHEN o.\\\"rn\\\" = b.\\\"upper_rn\\\" THEN o.\\\"measure_value\\\" END) -\\n        MAX(CASE WHEN o.\\\"rn\\\" = b.\\\"lower_rn\\\" THEN o.\\\"measure_value\\\" END)\\n      )\\n  END AS \\\"percentile_measure\\\"\\nFROM \\\"bounds\\\" AS b\\nJOIN \\\"ordered\\\" AS o\\n  ON o.\\\"Industry\\\" = b.\\\"Industry\\\"\\nGROUP BY\\n  b.\\\"Industry\\\",\\n  b.\\\"pos\\\",\\n  b.\\\"lower_rn\\\",\\n  b.\\\"upper_rn\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\",\"notes\":\"Emulates PERCENTILE_CONT(0.95) in SQLite using window functions and linear interpolation, casting \\\"Meetings_Per_Week\\\" from TEXT to REAL. NULL/blank measures are excluded, and industries with fewer than 5 rows are filtered out using the provided min_group_size.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16723,"cached_input_tokens":12032,"output_tokens":3486,"reasoning_output_tokens":2847}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_response_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..32d806cafb067582632c0759b99503f305932590
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_response_attempt_2.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_grouped_percentile_point\nWITH \"ordered\" AS (\n  SELECT\n    \"Industry\",\n    CAST(\"Meetings_Per_Week\" AS REAL) AS \"measure_value\",\n    ROW_NUMBER() OVER (\n      PARTITION BY \"Industry\"\n      ORDER BY CAST(\"Meetings_Per_Week\" AS REAL)\n    ) AS \"rn\",\n    COUNT(*) OVER (\n      PARTITION BY \"Industry\"\n    ) AS \"n\"\n  FROM \"m1\"\n  WHERE \"Industry\" IS NOT NULL\n    AND \"Meetings_Per_Week\" IS NOT NULL\n    AND TRIM(\"Meetings_Per_Week\") <> ''\n),\n\"bounds\" AS (\n  SELECT\n    \"Industry\",\n    1.0 + 0.95 * (MAX(\"n\") - 1) AS \"pos\",\n    CAST(1.0 + 0.95 * (MAX(\"n\") - 1) AS INTEGER) AS \"lower_rn\",\n    CAST(1.0 + 0.95 * (MAX(\"n\") - 1) AS INTEGER) +\n      CASE\n        WHEN (1.0 + 0.95 * (MAX(\"n\") - 1)) > CAST(1.0 + 0.95 * (MAX(\"n\") - 1) AS INTEGER) THEN 1\n        ELSE 0\n      END AS \"upper_rn\"\n  FROM \"ordered\"\n  GROUP BY \"Industry\"\n  HAVING MAX(\"n\") >= 5\n)\nSELECT\n  b.\"Industry\",\n  CASE\n    WHEN b.\"lower_rn\" = b.\"upper_rn\" THEN\n      MAX(CASE WHEN o.\"rn\" = b.\"lower_rn\" THEN o.\"measure_value\" END)\n    ELSE\n      MAX(CASE WHEN o.\"rn\" = b.\"lower_rn\" THEN o.\"measure_value\" END) +\n      (b.\"pos\" - b.\"lower_rn\") * (\n        MAX(CASE WHEN o.\"rn\" = b.\"upper_rn\" THEN o.\"measure_value\" END) -\n        MAX(CASE WHEN o.\"rn\" = b.\"lower_rn\" THEN o.\"measure_value\" END)\n      )\n  END AS \"percentile_measure\"\nFROM \"bounds\" AS b\nJOIN \"ordered\" AS o\n  ON o.\"Industry\" = b.\"Industry\"\nGROUP BY\n  b.\"Industry\",\n  b.\"pos\",\n  b.\"lower_rn\",\n  b.\"upper_rn\"\nORDER BY \"percentile_measure\" DESC;","notes":"Emulates PERCENTILE_CONT(0.95) in SQLite using window functions and linear interpolation, casting \"Meetings_Per_Week\" from TEXT to REAL. NULL/blank measures are excluded, and industries with fewer than 5 rows are filtered out using the provided min_group_size."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e020021a868a8665/cli/sql_stderr_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e1588fcccccc4ac0/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e1588fcccccc4ac0/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..54597e1911776ca1178096015832fe90e4aa31a7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e1588fcccccc4ac0/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16507, "bytes_utf8": 16507, "lines": 454, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 543, "bytes_utf8": 543, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16736, "cached_input_tokens": 15744, "output_tokens": 497, "reasoning_output_tokens": 356}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e1588fcccccc4ac0/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e1588fcccccc4ac0/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..f0a857c4e8d54a285ff2d3b27957ab71566dad5b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e1588fcccccc4ac0/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_e1588fcccccc4ac0",
+    "api_calls": 0,
+    "input_tokens": 16736,
+    "cached_input_tokens": 15744,
+    "output_tokens": 497,
+    "total_tokens": 17233,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 23612.82,
+    "sql_execution_elapsed_ms_total": 5.83,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e1588fcccccc4ac0/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e1588fcccccc4ac0/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e1588fcccccc4ac0/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..4f306a9a31fb5d397b6bd3b715726bcbb08f53ed
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e1588fcccccc4ac0/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:45:37.993814+00:00",
+  "ended_at": "2026-05-19T15:46:01.606677+00:00",
+  "elapsed_ms": 23612.82,
+  "prompt_metrics": {
+    "chars": 16507,
+    "bytes_utf8": 16507,
+    "lines": 454,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1900,
+    "bytes_utf8": 1900,
+    "lines": 7,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 543,
+      "bytes_utf8": 543,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16736,
+      "cached_input_tokens": 15744,
+      "output_tokens": 497,
+      "reasoning_output_tokens": 356
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e1588fcccccc4ac0/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e1588fcccccc4ac0/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b99ca33798f737a101c841b3ab6d1636c68bdce3
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e1588fcccccc4ac0/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,454 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_quantile_tail_slice",
+    "template_name": "Quantile Tail Slice",
+    "primary_family": "tail_rarity_structure",
+    "portability": "partial",
+    "sql_skeleton": "WITH buckets AS (\n    SELECT {measure_col},\n           NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n    FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;",
+    "required_roles": [
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=Efficiency_Rating.",
+  "planned_template_id": "tpl_m4_quantile_tail_slice",
+  "bindings": {
+    "measure_col": "Efficiency_Rating",
+    "top_k": 14,
+    "top_n": 3,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 95.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "WITH buckets AS (\n    SELECT {measure_col},\n           NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n    FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e1588fcccccc4ac0/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e1588fcccccc4ac0/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e51e04ea66c85a864580db7507eb1619ee0de588
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e1588fcccccc4ac0/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,7 @@
+{"type":"thread.started","thread_id":"019e40ea-01cd-7952-998e-5513585ea883"}
+{"type":"turn.started"}
+{"type":"error","message":"Reconnecting... 2/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1983908, Requested 17371. Please try again in 38ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"error","message":"Reconnecting... 3/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 2000000, Requested 17371. Please try again in 521ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"error","message":"Reconnecting... 4/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1994868, Requested 17371. Please try again in 367ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_quantile_tail_slice\\nWITH buckets AS (\\n    SELECT \\\"Efficiency_Rating\\\",\\n           NTILE(10) OVER (ORDER BY CAST(\\\"Efficiency_Rating\\\" AS REAL) DESC) AS tail_bucket\\n    FROM \\\"m1\\\"\\n)\\nSELECT \\\"Efficiency_Rating\\\"\\nFROM buckets\\nWHERE tail_bucket = 1\\nORDER BY CAST(\\\"Efficiency_Rating\\\" AS REAL) DESC;\",\"notes\":\"Applied the Quantile Tail Slice template with measure_col bound to \\\"Efficiency_Rating\\\" and num_tiles=10. Cast to REAL for correct numeric ordering because the SQLite column is stored as TEXT.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16736,"cached_input_tokens":15744,"output_tokens":497,"reasoning_output_tokens":356}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e1588fcccccc4ac0/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e1588fcccccc4ac0/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..76c6a8b470f9bc3b1d08b96532b4d5156d6a9aed
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e1588fcccccc4ac0/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_m4_quantile_tail_slice\nWITH buckets AS (\n    SELECT \"Efficiency_Rating\",\n           NTILE(10) OVER (ORDER BY CAST(\"Efficiency_Rating\" AS REAL) DESC) AS tail_bucket\n    FROM \"m1\"\n)\nSELECT \"Efficiency_Rating\"\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY CAST(\"Efficiency_Rating\" AS REAL) DESC;","notes":"Applied the Quantile Tail Slice template with measure_col bound to \"Efficiency_Rating\" and num_tiles=10. Cast to REAL for correct numeric ordering because the SQLite column is stored as TEXT."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e1588fcccccc4ac0/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e1588fcccccc4ac0/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e774d1fbfa96cb3f/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e774d1fbfa96cb3f/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..6afe1403993eab8bcaa7edd6385227cb8a3c9b48
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e774d1fbfa96cb3f/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16345, "bytes_utf8": 16345, "lines": 456, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 414, "bytes_utf8": 414, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16685, "cached_input_tokens": 12032, "output_tokens": 262, "reasoning_output_tokens": 156}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e774d1fbfa96cb3f/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e774d1fbfa96cb3f/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..7fa87bf01b4b95705a2dac94d79fd458526c75f1
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e774d1fbfa96cb3f/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_e774d1fbfa96cb3f",
+    "api_calls": 0,
+    "input_tokens": 16685,
+    "cached_input_tokens": 12032,
+    "output_tokens": 262,
+    "total_tokens": 16947,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 13193.89,
+    "sql_execution_elapsed_ms_total": 1.26,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e774d1fbfa96cb3f/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e774d1fbfa96cb3f/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e774d1fbfa96cb3f/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..1971147e2fd38c000d8d922fcd920b311f92c989
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e774d1fbfa96cb3f/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:30:02.013752+00:00",
+  "ended_at": "2026-05-19T15:30:15.207663+00:00",
+  "elapsed_ms": 13193.89,
+  "prompt_metrics": {
+    "chars": 16345,
+    "bytes_utf8": 16345,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1109,
+    "bytes_utf8": 1109,
+    "lines": 5,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 414,
+      "bytes_utf8": 414,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16685,
+      "cached_input_tokens": 12032,
+      "output_tokens": 262,
+      "reasoning_output_tokens": 156
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e774d1fbfa96cb3f/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e774d1fbfa96cb3f/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..9b5986238c9464098537820bcc59b6abf8651825
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e774d1fbfa96cb3f/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_h2o_group_sum",
+    "template_name": "Grouped Numeric Sum",
+    "primary_family": "subgroup_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=Department, measure_col=Task_Completion_Rate.",
+  "planned_template_id": "tpl_h2o_group_sum",
+  "bindings": {
+    "group_col": "Department",
+    "measure_col": "Task_Completion_Rate",
+    "top_k": 10,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 96.1,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e774d1fbfa96cb3f/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e774d1fbfa96cb3f/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..c50babe3a7f35225eb3d2c81bb629146a4574b62
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e774d1fbfa96cb3f/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,5 @@
+{"type":"thread.started","thread_id":"019e40db-b9b5-7c43-a3b9-6a68707b7530"}
+{"type":"turn.started"}
+{"type":"error","message":"Reconnecting... 2/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 2000000, Requested 17320. Please try again in 519ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"Department\\\", SUM(CAST(\\\"Task_Completion_Rate\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"m1\\\"\\nGROUP BY \\\"Department\\\"\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Used the provided grouped numeric sum template with group_col=\\\"Department\\\" and measure_col=\\\"Task_Completion_Rate\\\". CAST to REAL because the schema stores numeric-looking fields as TEXT in SQLite.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16685,"cached_input_tokens":12032,"output_tokens":262,"reasoning_output_tokens":156}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e774d1fbfa96cb3f/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e774d1fbfa96cb3f/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..eb06764a72ed8215f85b06fbf3d52a714babd56a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e774d1fbfa96cb3f/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_h2o_group_sum\nSELECT \"Department\", SUM(CAST(\"Task_Completion_Rate\" AS REAL)) AS \"total_measure\"\nFROM \"m1\"\nGROUP BY \"Department\"\nORDER BY \"total_measure\" DESC;","notes":"Used the provided grouped numeric sum template with group_col=\"Department\" and measure_col=\"Task_Completion_Rate\". CAST to REAL because the schema stores numeric-looking fields as TEXT in SQLite."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e774d1fbfa96cb3f/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_e774d1fbfa96cb3f/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ebe2f831ba81a22e/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ebe2f831ba81a22e/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..2bfcae5de8d838f1f0273201a159de99a7759300
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ebe2f831ba81a22e/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16917, "bytes_utf8": 16917, "lines": 456, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 745, "bytes_utf8": 745, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16829, "cached_input_tokens": 12032, "output_tokens": 487, "reasoning_output_tokens": 269}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ebe2f831ba81a22e/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ebe2f831ba81a22e/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..b04ed55ab29790d3e5b8c132f29efa7e040a1e3d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ebe2f831ba81a22e/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_ebe2f831ba81a22e",
+    "api_calls": 0,
+    "input_tokens": 16829,
+    "cached_input_tokens": 12032,
+    "output_tokens": 487,
+    "total_tokens": 17316,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 10586.68,
+    "sql_execution_elapsed_ms_total": 2.5,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ebe2f831ba81a22e/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ebe2f831ba81a22e/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ebe2f831ba81a22e/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..e16f501db0bd3762fb90b41373b8461084949965
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ebe2f831ba81a22e/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:50:04.085258+00:00",
+  "ended_at": "2026-05-19T15:50:14.671976+00:00",
+  "elapsed_ms": 10586.68,
+  "prompt_metrics": {
+    "chars": 16917,
+    "bytes_utf8": 16917,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1169,
+    "bytes_utf8": 1169,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 745,
+      "bytes_utf8": 745,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16829,
+      "cached_input_tokens": 12032,
+      "output_tokens": 487,
+      "reasoning_output_tokens": 269
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ebe2f831ba81a22e/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ebe2f831ba81a22e/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..24e16aca01776839ece53bde7c7177fa629afe45
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ebe2f831ba81a22e/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_tpch_relative_total_threshold",
+    "template_name": "Relative-to-Total Extreme Threshold",
+    "primary_family": "tail_rarity_structure",
+    "portability": "partial",
+    "sql_skeleton": "WITH grouped AS (\n    SELECT {group_col}, SUM({measure_col}) AS group_value\n    FROM {table}\n    GROUP BY {group_col}\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=Manager_Support_Level, measure_col=Meetings_Per_Week.",
+  "planned_template_id": "tpl_tpch_relative_total_threshold",
+  "bindings": {
+    "group_col": "Manager_Support_Level",
+    "measure_col": "Meetings_Per_Week",
+    "top_k": 14,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 10.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "WITH grouped AS (\n    SELECT {group_col}, SUM({measure_col}) AS group_value\n    FROM {table}\n    GROUP BY {group_col}\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ebe2f831ba81a22e/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ebe2f831ba81a22e/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..a7556690532382ad2a5c75c8b5db22d3c4562959
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ebe2f831ba81a22e/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40ee-1130-76b2-9ed5-52fda2bd75c6"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH \\\"grouped\\\" AS (\\n  SELECT\\n    \\\"Manager_Support_Level\\\",\\n    SUM(CAST(\\\"Meetings_Per_Week\\\" AS REAL)) AS \\\"group_value\\\"\\n  FROM \\\"m1\\\"\\n  GROUP BY \\\"Manager_Support_Level\\\"\\n),\\n\\\"total\\\" AS (\\n  SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n  FROM \\\"grouped\\\"\\n)\\nSELECT\\n  g.\\\"Manager_Support_Level\\\",\\n  g.\\\"group_value\\\"\\nFROM \\\"grouped\\\" AS g\\nCROSS JOIN \\\"total\\\" AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.1\\nORDER BY g.\\\"group_value\\\" DESC;\",\"notes\":\"Applied the planned template with group_col=\\\"Manager_Support_Level\\\" and measure_col=\\\"Meetings_Per_Week\\\". Cast \\\"Meetings_Per_Week\\\" to REAL because the schema stores numeric fields as TEXT in SQLite.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16829,"cached_input_tokens":12032,"output_tokens":487,"reasoning_output_tokens":269}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ebe2f831ba81a22e/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ebe2f831ba81a22e/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..7d7c66041854e65726d70fcc16a821c7fefdb812
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ebe2f831ba81a22e/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tpch_relative_total_threshold\nWITH \"grouped\" AS (\n  SELECT\n    \"Manager_Support_Level\",\n    SUM(CAST(\"Meetings_Per_Week\" AS REAL)) AS \"group_value\"\n  FROM \"m1\"\n  GROUP BY \"Manager_Support_Level\"\n),\n\"total\" AS (\n  SELECT SUM(\"group_value\") AS \"total_value\"\n  FROM \"grouped\"\n)\nSELECT\n  g.\"Manager_Support_Level\",\n  g.\"group_value\"\nFROM \"grouped\" AS g\nCROSS JOIN \"total\" AS t\nWHERE g.\"group_value\" > t.\"total_value\" * 0.1\nORDER BY g.\"group_value\" DESC;","notes":"Applied the planned template with group_col=\"Manager_Support_Level\" and measure_col=\"Meetings_Per_Week\". Cast \"Meetings_Per_Week\" to REAL because the schema stores numeric fields as TEXT in SQLite."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ebe2f831ba81a22e/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ebe2f831ba81a22e/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ee752d22424b17ce/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ee752d22424b17ce/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..344e107d27aa42856ab74547bf31bfa352d8c954
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ee752d22424b17ce/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16739, "bytes_utf8": 16739, "lines": 458, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 673, "bytes_utf8": 673, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16800, "cached_input_tokens": 15744, "output_tokens": 2016, "reasoning_output_tokens": 1817}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ee752d22424b17ce/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ee752d22424b17ce/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..d6160fefd367f6dda507e489ca7679914630fca3
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ee752d22424b17ce/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_ee752d22424b17ce",
+    "api_calls": 0,
+    "input_tokens": 16800,
+    "cached_input_tokens": 15744,
+    "output_tokens": 2016,
+    "total_tokens": 18816,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 31759.06,
+    "sql_execution_elapsed_ms_total": 3.47,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ee752d22424b17ce/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ee752d22424b17ce/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ee752d22424b17ce/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..186e5cc7734a89e7df4043cc9063ab09e9a8a3dc
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ee752d22424b17ce/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:39:27.276406+00:00",
+  "ended_at": "2026-05-19T15:39:59.035491+00:00",
+  "elapsed_ms": 31759.06,
+  "prompt_metrics": {
+    "chars": 16739,
+    "bytes_utf8": 16739,
+    "lines": 458,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1076,
+    "bytes_utf8": 1076,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 673,
+      "bytes_utf8": 673,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16800,
+      "cached_input_tokens": 15744,
+      "output_tokens": 2016,
+      "reasoning_output_tokens": 1817
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ee752d22424b17ce/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ee752d22424b17ce/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..193ccb4738207ed7826a5237a843ed2acf01a1e4
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ee752d22424b17ce/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,458 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_tpcds_within_group_share",
+    "template_name": "Within-Group Share of Total",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;",
+    "required_roles": [
+      "group_col",
+      "item_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=Gender, measure_col=Quality_Score.",
+  "planned_template_id": "tpl_tpcds_within_group_share",
+  "bindings": {
+    "group_col": "Gender",
+    "measure_col": "Quality_Score",
+    "item_col": "Survey_Date",
+    "top_k": 14,
+    "top_n": 5,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 96.225,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ee752d22424b17ce/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ee752d22424b17ce/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b7e84fc6758bd968ae8f31e61a86211cbb9d27e7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ee752d22424b17ce/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40e4-59da-7311-9305-6f8bbc9820d0"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n  \\\"Gender\\\",\\n  strftime('%Y-%m', \\\"Survey_Date\\\") AS \\\"Survey_Month\\\",\\n  SUM(CAST(\\\"Quality_Score\\\" AS REAL)) AS \\\"total_measure\\\",\\n  SUM(CAST(\\\"Quality_Score\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"Quality_Score\\\" AS REAL))) OVER (PARTITION BY \\\"Gender\\\") AS \\\"share_within_group\\\"\\nFROM \\\"m1\\\"\\nGROUP BY\\n  \\\"Gender\\\",\\n  strftime('%Y-%m', \\\"Survey_Date\\\")\\nORDER BY \\\"share_within_group\\\" DESC\\nLIMIT 14;\",\"notes\":\"Uses the planned within-group share template with \\\"Gender\\\" as the group, monthly buckets from \\\"Survey_Date\\\" as the item, and casts \\\"Quality_Score\\\" from TEXT to REAL before aggregation.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16800,"cached_input_tokens":15744,"output_tokens":2016,"reasoning_output_tokens":1817}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ee752d22424b17ce/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ee752d22424b17ce/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e6ba51639e2694233144b23e07d42f57add6c785
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ee752d22424b17ce/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tpcds_within_group_share\nSELECT\n  \"Gender\",\n  strftime('%Y-%m', \"Survey_Date\") AS \"Survey_Month\",\n  SUM(CAST(\"Quality_Score\" AS REAL)) AS \"total_measure\",\n  SUM(CAST(\"Quality_Score\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"Quality_Score\" AS REAL))) OVER (PARTITION BY \"Gender\") AS \"share_within_group\"\nFROM \"m1\"\nGROUP BY\n  \"Gender\",\n  strftime('%Y-%m', \"Survey_Date\")\nORDER BY \"share_within_group\" DESC\nLIMIT 14;","notes":"Uses the planned within-group share template with \"Gender\" as the group, monthly buckets from \"Survey_Date\" as the item, and casts \"Quality_Score\" from TEXT to REAL before aggregation."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ee752d22424b17ce/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_ee752d22424b17ce/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..cf07588c07373ed2a7901ba35b71d3d84f99b782
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:10:31.704759+00:00",
+  "ended_at": "2026-05-19T16:10:34.613594+00:00",
+  "elapsed_ms": 2908.81,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16430,
+    "bytes_utf8": 16430,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_attempt_2.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..246b315966779fcc29eb80e069c4f7f4fb6be667
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_attempt_2.metadata.json
@@ -0,0 +1,43 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:10:35.616242+00:00",
+  "ended_at": "2026-05-19T16:10:38.976499+00:00",
+  "elapsed_ms": 3360.21,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16430,
+    "bytes_utf8": 16430,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_2.txt",
+  "response_path": "cli/sql_response_attempt_2.txt",
+  "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_2.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..3b7b1e8cd84d1c5c0f4fd1889aa52328f83c5760
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_window_partition_avg",
+    "template_name": "Window Partition Average",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Window Partition Average to probe direction_consistency with semantic role ranked_signal_view. Focus on group_col=Education_Level, measure_col=Job_Satisfaction.",
+  "planned_template_id": "tpl_m4_window_partition_avg",
+  "bindings": {
+    "group_col": "Education_Level",
+    "measure_col": "Job_Satisfaction",
+    "top_k": 12,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 100.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_prompt_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..3b7b1e8cd84d1c5c0f4fd1889aa52328f83c5760
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_prompt_attempt_2.txt
@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_window_partition_avg",
+    "template_name": "Window Partition Average",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Window Partition Average to probe direction_consistency with semantic role ranked_signal_view. Focus on group_col=Education_Level, measure_col=Job_Satisfaction.",
+  "planned_template_id": "tpl_m4_window_partition_avg",
+  "bindings": {
+    "group_col": "Education_Level",
+    "measure_col": "Job_Satisfaction",
+    "top_k": 12,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 100.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..459f766808f35392240ce23dc181f7248a524d12
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4100-cc97-7501-b73e-0faadc893cb7"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e02dc4cef3c4d012a41731eda0d6d8ac41ee488e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_response_attempt_1.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4100-cc97-7501-b73e-0faadc893cb7"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_response_attempt_2.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..89cdca8a3341bec9a7ba90c127a7816d93eb8079
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_response_attempt_2.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4100-dbde-7273-8059-d8a0ed597505"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_response_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..f40875d10d3f338ad37d0882c74e313371e6a7e3
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_response_attempt_2.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4100-dbde-7273-8059-d8a0ed597505"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f608bb51497b2d1d/cli/sql_stderr_attempt_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f683d596c73a902d/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f683d596c73a902d/cli/conversation.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..1928b386992486ab2158b905dda9f67481c0e1bc
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f683d596c73a902d/cli/conversation.jsonl
@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16779, "bytes_utf8": 16779, "lines": 458, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 748, "bytes_utf8": 748, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16815, "cached_input_tokens": 15744, "output_tokens": 992, "reasoning_output_tokens": 777}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f683d596c73a902d/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f683d596c73a902d/cli/session_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..471a33b577da0b820d0d2f8de4dc8377865e51b5
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f683d596c73a902d/cli/session_summary.json
@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_f683d596c73a902d",
+    "api_calls": 0,
+    "input_tokens": 16815,
+    "cached_input_tokens": 15744,
+    "output_tokens": 992,
+    "total_tokens": 17807,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 17819.76,
+    "sql_execution_elapsed_ms_total": 2.73,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f683d596c73a902d/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f683d596c73a902d/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f683d596c73a902d/cli/sql_attempt_1.metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..74a06327f293f8519624cf9f22d4f0ff383c139f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f683d596c73a902d/cli/sql_attempt_1.metadata.json
@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:37:48.802450+00:00",
+  "ended_at": "2026-05-19T15:38:06.622240+00:00",
+  "elapsed_ms": 17819.76,
+  "prompt_metrics": {
+    "chars": 16779,
+    "bytes_utf8": 16779,
+    "lines": 458,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1131,
+    "bytes_utf8": 1131,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 748,
+      "bytes_utf8": 748,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16815,
+      "cached_input_tokens": 15744,
+      "output_tokens": 992,
+      "reasoning_output_tokens": 777
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f683d596c73a902d/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f683d596c73a902d/cli/sql_prompt_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..ad3f860c5cbe67343370806561d9d4bdcd1a3ccf
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f683d596c73a902d/cli/sql_prompt_attempt_1.txt
@@ -0,0 +1,458 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_tpcds_within_group_share",
+    "template_name": "Within-Group Share of Total",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;",
+    "required_roles": [
+      "group_col",
+      "item_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=Work_Life_Balance, measure_col=Work_Hours_Per_Week.",
+  "planned_template_id": "tpl_tpcds_within_group_share",
+  "bindings": {
+    "group_col": "Work_Life_Balance",
+    "measure_col": "Work_Hours_Per_Week",
+    "item_col": "Efficiency_Rating",
+    "top_k": 16,
+    "top_n": 7,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 45.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;"
+}
+
+Repair context:
+{}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f683d596c73a902d/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f683d596c73a902d/cli/sql_response_attempt_1.raw.txt
new file mode 100644
index 0000000000000000000000000000000000000000..d0940a82c99fb7d012cee56b375faf9c13a036a5
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f683d596c73a902d/cli/sql_response_attempt_1.raw.txt
@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40e2-d8f5-74a2-8954-481934ffe4bd"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n  \\\"Work_Life_Balance\\\",\\n  \\\"Efficiency_Rating\\\",\\n  SUM(CAST(\\\"Work_Hours_Per_Week\\\" AS REAL)) AS total_measure,\\n  SUM(CAST(\\\"Work_Hours_Per_Week\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"Work_Hours_Per_Week\\\" AS REAL))) OVER (PARTITION BY \\\"Work_Life_Balance\\\") AS share_within_group\\nFROM \\\"m1\\\"\\nGROUP BY \\\"Work_Life_Balance\\\", \\\"Efficiency_Rating\\\"\\nORDER BY share_within_group DESC\\nLIMIT 16;\",\"notes\":\"Applied the Within-Group Share of Total template with group_col=\\\"Work_Life_Balance\\\", item_col=\\\"Efficiency_Rating\\\", and measure_col=\\\"Work_Hours_Per_Week\\\". CAST to REAL is used because the schema stores numeric fields as TEXT. Added LIMIT 16 from the provided top_k binding.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16815,"cached_input_tokens":15744,"output_tokens":992,"reasoning_output_tokens":777}}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f683d596c73a902d/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f683d596c73a902d/cli/sql_response_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..d0b38ef0652325bbfd3baafd696e240a221f8657
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f683d596c73a902d/cli/sql_response_attempt_1.txt
@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tpcds_within_group_share\nSELECT\n  \"Work_Life_Balance\",\n  \"Efficiency_Rating\",\n  SUM(CAST(\"Work_Hours_Per_Week\" AS REAL)) AS total_measure,\n  SUM(CAST(\"Work_Hours_Per_Week\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"Work_Hours_Per_Week\" AS REAL))) OVER (PARTITION BY \"Work_Life_Balance\") AS share_within_group\nFROM \"m1\"\nGROUP BY \"Work_Life_Balance\", \"Efficiency_Rating\"\nORDER BY share_within_group DESC\nLIMIT 16;","notes":"Applied the Within-Group Share of Total template with group_col=\"Work_Life_Balance\", item_col=\"Efficiency_Rating\", and measure_col=\"Work_Hours_Per_Week\". CAST to REAL is used because the schema stores numeric fields as TEXT. Added LIMIT 16 from the provided top_k binding."}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f683d596c73a902d/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_f683d596c73a902d/cli/sql_stderr_attempt_1.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_0209729875e8a0e5/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_0209729875e8a0e5/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..20ab84df836eabf6c21b5f0a19b9aee6bacc02a1
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_0209729875e8a0e5/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=feature_10, measure_col=feature_11.
+Result preview: [{"feature_10": "1", "feature_12": "0", "total_measure": 2205.0, "share_within_group": 60.928433268858804}, {"feature_10": "5", "feature_12": "0", "total_measure": 2091.0, "share_within_group": 55.87920897915553}, {"feature_10": "97", "feature_12": "65", "total_measure": 278.0, "share_within_group": 52.851711026615966}, {"feature_10": "75", "feature_12": "50", "total_measure": 8797.0, "share_within_group": 51.804958483010424}, {"feature_10": "2", "feature_12": "0", "total_measure": 1386.0, "share_within_group": 51.06853352984525}] Results were truncated.
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_0209729875e8a0e5/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_0209729875e8a0e5/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..2f824890474ada91c004eaeed0adbd6d923ed731
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_0209729875e8a0e5/generated_sql.sql
@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: within_group_proportion
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_0209729875e8a0e5
+-- problem_id: v2p_n9_9a370f3cc95b7209
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+  "feature_10",
+  "feature_12",
+  SUM(CAST("feature_11" AS REAL)) AS total_measure,
+  SUM(CAST("feature_11" AS REAL)) * 100.0 / NULLIF(SUM(SUM(CAST("feature_11" AS REAL))) OVER (PARTITION BY "feature_10"), 0) AS share_within_group
+FROM "n9"
+GROUP BY "feature_10", "feature_12"
+ORDER BY share_within_group DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_0209729875e8a0e5/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_0209729875e8a0e5/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..a33536f719030201918e047b82958542b995ebaa
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_0209729875e8a0e5/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT\n  \"feature_10\",\n  \"feature_12\",\n  SUM(CAST(\"feature_11\" AS REAL)) AS total_measure,\n  SUM(CAST(\"feature_11\" AS REAL)) * 100.0 / NULLIF(SUM(SUM(CAST(\"feature_11\" AS REAL))) OVER (PARTITION BY \"feature_10\"), 0) AS share_within_group\nFROM \"n9\"\nGROUP BY \"feature_10\", \"feature_12\"\nORDER BY share_within_group DESC;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n  \\\"feature_10\\\",\\n  \\\"feature_12\\\",\\n  SUM(CAST(\\\"feature_11\\\" AS REAL)) AS total_measure,\\n  SUM(CAST(\\\"feature_11\\\" AS REAL)) * 100.0 / NULLIF(SUM(SUM(CAST(\\\"feature_11\\\" AS REAL))) OVER (PARTITION BY \\\"feature_10\\\"), 0) AS share_within_group\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_10\\\", \\\"feature_12\\\"\\nORDER BY share_within_group DESC;\", \"columns\": [\"feature_10\", \"feature_12\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"feature_10\": \"1\", \"feature_12\": \"0\", \"total_measure\": 2205.0, \"share_within_group\": 60.928433268858804}, {\"feature_10\": \"5\", \"feature_12\": \"0\", \"total_measure\": 2091.0, \"share_within_group\": 55.87920897915553}, {\"feature_10\": \"97\", \"feature_12\": \"65\", \"total_measure\": 278.0, \"share_within_group\": 52.851711026615966}, {\"feature_10\": \"75\", \"feature_12\": \"50\", \"total_measure\": 8797.0, \"share_within_group\": 51.804958483010424}, {\"feature_10\": \"2\", \"feature_12\": \"0\", \"total_measure\": 1386.0, \"share_within_group\": 51.06853352984525}, {\"feature_10\": \"99\", \"feature_12\": \"66\", \"total_measure\": 374.0, \"share_within_group\": 50.26881720430107}, {\"feature_10\": \"7\", \"feature_12\": \"0\", \"total_measure\": 1477.0, \"share_within_group\": 48.569549490299245}, {\"feature_10\": \"4\", \"feature_12\": \"0\", \"total_measure\": 1754.0, \"share_within_group\": 46.19436397155649}, {\"feature_10\": \"13\", \"feature_12\": \"0\", \"total_measure\": 1465.0, \"share_within_group\": 44.47480267152398}, {\"feature_10\": \"96\", \"feature_12\": \"64\", \"total_measure\": 429.0, \"share_within_group\": 43.59756097560975}, {\"feature_10\": \"6\", \"feature_12\": \"0\", \"total_measure\": 2046.0, \"share_within_group\": 42.8391959798995}, {\"feature_10\": \"3\", \"feature_12\": \"0\", \"total_measure\": 967.0, \"share_within_group\": 41.93408499566349}, {\"feature_10\": \"8\", \"feature_12\": \"0\", \"total_measure\": 1395.0, \"share_within_group\": 35.95360824742268}, {\"feature_10\": \"93\", \"feature_12\": \"62\", \"total_measure\": 266.0, \"share_within_group\": 35.945945945945944}, {\"feature_10\": \"12\", \"feature_12\": \"0\", \"total_measure\": 1200.0, \"share_within_group\": 35.10825043885313}, {\"feature_10\": \"15\", \"feature_12\": \"0\", \"total_measure\": 1170.0, \"share_within_group\": 33.304867634500425}, {\"feature_10\": \"14\", \"feature_12\": \"0\", \"total_measure\": 1139.0, \"share_within_group\": 33.081614870752254}, {\"feature_10\": \"9\", \"feature_12\": \"0\", \"total_measure\": 1032.0, \"share_within_group\": 31.705069124423964}, {\"feature_10\": \"94\", \"feature_12\": \"63\", \"total_measure\": 308.0, \"share_within_group\": 31.68724279835391}, {\"feature_10\": \"95\", \"feature_12\": \"62\", \"total_measure\": 252.0, \"share_within_group\": 29.200463499420625}, {\"feature_10\": \"10\", \"feature_12\": \"0\", \"total_measure\": 1110.0, \"share_within_group\": 28.913779630112007}, {\"feature_10\": \"16\", \"feature_12\": \"0\", \"total_measure\": 1188.0, \"share_within_group\": 28.709521507974866}, {\"feature_10\": \"76\", \"feature_12\": \"51\", \"total_measure\": 1679.0, \"share_within_group\": 28.666552842752264}, {\"feature_10\": \"100\", \"feature_12\": \"67\", \"total_measure\": 1404.0, \"share_within_group\": 27.945859872611464}, {\"feature_10\": \"11\", \"feature_12\": \"0\", \"total_measure\": 1012.0, \"share_within_group\": 27.817482133040134}, {\"feature_10\": \"98\", \"feature_12\": \"64\", \"total_measure\": 181.0, \"share_within_group\": 27.177177177177178}, {\"feature_10\": \"88\", \"feature_12\": \"58\", \"total_measure\": 499.0, \"share_within_group\": 26.166754063974828}, {\"feature_10\": \"87\", \"feature_12\": \"58\", \"total_measure\": 390.0, \"share_within_group\": 25.8792302587923}, {\"feature_10\": \"74\", \"feature_12\": \"49\", \"total_measure\": 2192.0, \"share_within_group\": 25.730719568024416}, {\"feature_10\": \"19\", \"feature_12\": \"0\", \"total_measure\": 912.0, \"share_within_group\": 24.082387113810405}, {\"feature_10\": \"23\", \"feature_12\": \"0\", \"total_measure\": 1037.0, \"share_within_group\": 22.871636524040582}, {\"feature_10\": \"80\", \"feature_12\": \"53\", \"total_measure\": 1005.0, \"share_within_group\": 22.794284418235428}, {\"feature_10\": \"20\", \"feature_12\": \"0\", \"total_measure\": 1000.0, \"share_within_group\": 22.44165170556553}, {\"feature_10\": \"83\", \"feature_12\": \"55\", \"total_measure\": 674.0, \"share_within_group\": 22.43675099866844}, {\"feature_10\": \"91\", \"feature_12\": \"61\", \"total_measure\": 415.0, \"share_within_group\": 22.240085744908896}, {\"feature_10\": \"90\", \"feature_12\": \"59\", \"total_measure\": 459.0, \"share_within_group\": 22.109826589595375}, {\"feature_10\": \"98\", \"feature_12\": \"65\", \"total_measure\": 147.0, \"share_within_group\": 22.07207207207207}, {\"feature_10\": \"87\", \"feature_12\": \"59\", \"total_measure\": 329.0, \"share_within_group\": 21.831453218314532}, {\"feature_10\": \"93\", \"feature_12\": \"63\", \"total_measure\": 160.0, \"share_within_group\": 21.62162162162162}, {\"feature_10\": \"92\", \"feature_12\": \"61\", \"total_measure\": 232.0, \"share_within_group\": 20.17391304347826}, {\"feature_10\": \"88\", \"feature_12\": \"59\", \"total_measure\": 381.0, \"share_within_group\": 19.9790246460409}, {\"feature_10\": \"82\", \"feature_12\": \"54\", \"total_measure\": 564.0, \"share_within_group\": 19.775596072931275}, {\"feature_10\": \"85\", \"feature_12\": \"57\", \"total_measure\": 458.0, \"share_within_group\": 19.53091684434968}, {\"feature_10\": \"95\", \"feature_12\": \"63\", \"total_measure\": 166.0, \"share_within_group\": 19.235225955967554}, {\"feature_10\": \"95\", \"feature_12\": \"65\", \"total_measure\": 166.0, \"share_within_group\": 19.235225955967554}, {\"feature_10\": \"60\", \"feature_12\": \"40\", \"total_measure\": 1324.0, \"share_within_group\": 18.98752330417324}, {\"feature_10\": \"76\", \"feature_12\": \"50\", \"total_measure\": 1106.0, \"share_within_group\": 18.883387399692676}, {\"feature_10\": \"21\", \"feature_12\": \"0\", \"total_measure\": 688.0, \"share_within_group\": 18.72108843537415}, {\"feature_10\": \"91\", \"feature_12\": \"57\", \"total_measure\": 342.0, \"share_within_group\": 18.327974276527332}, {\"feature_10\": \"81\", \"feature_12\": \"54\", \"total_measure\": 711.0, \"share_within_group\": 18.0640243902439}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 16.52}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_0209729875e8a0e5/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_0209729875e8a0e5/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..71f87e861141eb0609929e4a1d021bd70140c889
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_0209729875e8a0e5/run_manifest.json
@@ -0,0 +1,91 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:35:27.008640+00:00",
+  "ended_at": "2026-05-19T15:35:39.449170+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_0209729875e8a0e5",
+    "problem_id": "v2p_n9_9a370f3cc95b7209",
+    "dataset_id": "n9",
+    "template_id": "tpl_tpcds_within_group_share",
+    "template_name": "Within-Group Share of Total",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "dependency_strength_similarity",
+    "intended_facet_id": "pairwise_conditional_dependency",
+    "variant_semantic_role": "within_group_proportion",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=feature_10, measure_col=feature_11.",
+    "bindings": {
+      "group_col": "feature_10",
+      "measure_col": "feature_11",
+      "item_col": "feature_12",
+      "top_k": 11,
+      "top_n": 5,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 97.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "item_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;",
+    "notes": [
+      "default_facets=pairwise_conditional_dependency",
+      "template_selection_mode=rule",
+      "problem_index_within_template=3",
+      "sql_variant_index=1/2",
+      "binding_index=26"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 3,
+    "problem_index_within_template": 3,
+    "sql_variant_index": 1,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_0209729875e8a0e5.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_0209729875e8a0e5",
+    "api_calls": 0,
+    "input_tokens": 15060,
+    "cached_input_tokens": 13696,
+    "output_tokens": 595,
+    "total_tokens": 15655,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 12420.34,
+    "sql_execution_elapsed_ms_total": 16.52,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_0209729875e8a0e5/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_0209729875e8a0e5/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_0209729875e8a0e5/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..3b22823d6d5bf4b4d0251c72d453f8d2c52ba9f5
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_0209729875e8a0e5/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:35:39.431109+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 12420.34, "started_at": "2026-05-19T15:35:27.009928+00:00", "ended_at": "2026-05-19T15:35:39.430296+00:00", "prompt_metrics": {"chars": 9805, "bytes_utf8": 9805, "lines": 302, "estimated_tokens": null}, "response_metrics": {"chars": 566, "bytes_utf8": 566, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15060, "cached_input_tokens": 13696, "output_tokens": 595, "reasoning_output_tokens": 415}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n  \\\"feature_10\\\",\\n  \\\"feature_12\\\",\\n  SUM(CAST(\\\"feature_11\\\" AS REAL)) AS total_measure,\\n  SUM(CAST(\\\"feature_11\\\" AS REAL)) * 100.0 / NULLIF(SUM(SUM(CAST(\\\"feature_11\\\" AS REAL))) OVER (PARTITION BY \\\"feature_10\\\"), 0) AS share_within_group\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_10\\\", \\\"feature_12\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Uses the Within-Group Share of Total template with \\\"feature_10\\\" as group_col, \\\"feature_12\\\" as item_col, and summed numeric \\\"feature_11\\\" as measure_col.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_0209729875e8a0e5/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_0209729875e8a0e5/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..8f559b8b7f7c1894bd332a0062379470ba86064d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_0209729875e8a0e5/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_0209729875e8a0e5",
+  "api_calls": 0,
+  "input_tokens": 15060,
+  "cached_input_tokens": 13696,
+  "output_tokens": 595,
+  "total_tokens": 15655,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 12420.34,
+  "sql_execution_elapsed_ms_total": 16.52,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_0209729875e8a0e5/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_109b942301d57cc9/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_109b942301d57cc9/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..804d7379f5f6ab05435aff1543095868e2deae9b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_109b942301d57cc9/final_answer.txt
@@ -0,0 +1 @@
+{"row_count": null, "preview_rows": [{"feature_10": "0", "support": 2239, "avg_response": 91.2228673514962}, {"feature_10": "75", "support": 237, "avg_response": 71.44303797468355}, {"feature_10": "35", "support": 179, "avg_response": 75.71508379888269}, {"feature_10": "44", "support": 159, "avg_response": 85.75471698113208}, {"feature_10": "36", "support": 151, "avg_response": 78.68211920529801}]}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_109b942301d57cc9/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_109b942301d57cc9/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..9f9abe2b5c30db646842a180fa50dc0b41fcb14b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_109b942301d57cc9/generated_sql.sql
@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: high_cardinality_response_stability
+-- intended_facet_id: target_cardinality_cross_section
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_cardinality_high_card_response_stability
+-- query_record_id: v2q_n9_109b942301d57cc9
+-- problem_id: v2p_n9_4183abcb61c06446
+-- realization_mode: deterministic
+-- source_kind: deterministic
+SELECT
+    "feature_10",
+    COUNT(*) AS support,
+    AVG("feature_4") AS avg_response
+FROM "n9"
+GROUP BY "feature_10"
+HAVING COUNT(*) >= 5.0
+ORDER BY support DESC, avg_response DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_109b942301d57cc9/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_109b942301d57cc9/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..82e3d3216adfb0c9e93ea1b47fa9c0e89de389c5
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_109b942301d57cc9/query_results.jsonl
@@ -0,0 +1 @@
+{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: n9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: high_cardinality_response_stability\n-- intended_facet_id: target_cardinality_cross_section\n-- variant_semantic_role: focused_target_view\n-- template_id: tpl_cardinality_high_card_response_stability\n-- query_record_id: v2q_n9_109b942301d57cc9\n-- problem_id: v2p_n9_4183abcb61c06446\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n    \"feature_10\",\n    COUNT(*) AS support,\n    AVG(\"feature_4\") AS avg_response\nFROM \"n9\"\nGROUP BY \"feature_10\"\nHAVING COUNT(*) >= 5.0\nORDER BY support DESC, avg_response DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: n9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: high_cardinality_response_stability\\n-- intended_facet_id: target_cardinality_cross_section\\n-- variant_semantic_role: focused_target_view\\n-- template_id: tpl_cardinality_high_card_response_stability\\n-- query_record_id: v2q_n9_109b942301d57cc9\\n-- problem_id: v2p_n9_4183abcb61c06446\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n    \\\"feature_10\\\",\\n    COUNT(*) AS support,\\n    AVG(\\\"feature_4\\\") AS avg_response\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_10\\\"\\nHAVING COUNT(*) >= 5.0\\nORDER BY support DESC, avg_response DESC;\", \"columns\": [\"feature_10\", \"support\", \"avg_response\"], \"rows\": [{\"feature_10\": \"0\", \"support\": 2239, \"avg_response\": 91.2228673514962}, {\"feature_10\": \"75\", \"support\": 237, \"avg_response\": 71.44303797468355}, {\"feature_10\": \"35\", \"support\": 179, \"avg_response\": 75.71508379888269}, {\"feature_10\": \"44\", \"support\": 159, \"avg_response\": 85.75471698113208}, {\"feature_10\": \"36\", \"support\": 151, \"avg_response\": 78.68211920529801}, {\"feature_10\": \"45\", \"support\": 147, \"avg_response\": 85.15646258503402}, {\"feature_10\": \"43\", \"support\": 140, \"avg_response\": 85.48571428571428}, {\"feature_10\": \"34\", \"support\": 140, \"avg_response\": 77.35}, {\"feature_10\": \"42\", \"support\": 139, \"avg_response\": 83.92086330935251}, {\"feature_10\": \"40\", \"support\": 138, \"avg_response\": 82.94202898550725}, {\"feature_10\": \"41\", \"support\": 138, \"avg_response\": 81.34782608695652}, {\"feature_10\": \"38\", \"support\": 137, \"avg_response\": 80.17518248175182}, {\"feature_10\": \"48\", \"support\": 133, \"avg_response\": 87.24812030075188}, {\"feature_10\": \"49\", \"support\": 133, \"avg_response\": 86.0827067669173}, {\"feature_10\": \"29\", \"support\": 132, \"avg_response\": 78.5909090909091}, {\"feature_10\": \"30\", \"support\": 131, \"avg_response\": 75.56488549618321}, {\"feature_10\": \"47\", \"support\": 130, \"avg_response\": 88.03846153846153}, {\"feature_10\": \"46\", \"support\": 128, \"avg_response\": 84.8984375}, {\"feature_10\": \"16\", \"support\": 123, \"avg_response\": 86.65853658536585}, {\"feature_10\": \"50\", \"support\": 122, \"avg_response\": 87.43442622950819}, {\"feature_10\": \"39\", \"support\": 122, \"avg_response\": 84.07377049180327}, {\"feature_10\": \"32\", \"support\": 122, \"avg_response\": 79.65573770491804}, {\"feature_10\": \"37\", \"support\": 121, \"avg_response\": 78.66115702479338}, {\"feature_10\": \"12\", \"support\": 117, \"avg_response\": 90.03418803418803}, {\"feature_10\": \"25\", \"support\": 113, \"avg_response\": 77.99115044247787}, {\"feature_10\": \"24\", \"support\": 112, \"avg_response\": 81.58928571428571}, {\"feature_10\": \"20\", \"support\": 110, \"avg_response\": 84.66363636363636}, {\"feature_10\": \"22\", \"support\": 110, \"avg_response\": 83.72727272727273}, {\"feature_10\": \"31\", \"support\": 110, \"avg_response\": 82.84545454545454}, {\"feature_10\": \"74\", \"support\": 110, \"avg_response\": 76.98181818181818}, {\"feature_10\": \"27\", \"support\": 109, \"avg_response\": 80.1743119266055}, {\"feature_10\": \"19\", \"support\": 107, \"avg_response\": 85.01869158878505}, {\"feature_10\": \"33\", \"support\": 107, \"avg_response\": 77.3644859813084}, {\"feature_10\": \"15\", \"support\": 106, \"avg_response\": 88.0}, {\"feature_10\": \"6\", \"support\": 105, \"avg_response\": 90.61904761904762}, {\"feature_10\": \"23\", \"support\": 104, \"avg_response\": 85.33653846153847}, {\"feature_10\": \"17\", \"support\": 103, \"avg_response\": 83.1747572815534}, {\"feature_10\": \"28\", \"support\": 103, \"avg_response\": 80.64077669902913}, {\"feature_10\": \"13\", \"support\": 102, \"avg_response\": 90.41176470588235}, {\"feature_10\": \"52\", \"support\": 102, \"avg_response\": 85.93137254901961}, {\"feature_10\": \"60\", \"support\": 102, \"avg_response\": 83.94117647058823}, {\"feature_10\": \"10\", \"support\": 101, \"avg_response\": 88.34653465346534}, {\"feature_10\": \"51\", \"support\": 101, \"avg_response\": 87.1980198019802}, {\"feature_10\": \"64\", \"support\": 99, \"avg_response\": 81.78787878787878}, {\"feature_10\": \"8\", \"support\": 96, \"avg_response\": 89.22916666666667}, {\"feature_10\": \"14\", \"support\": 94, \"avg_response\": 87.29787234042553}, {\"feature_10\": \"62\", \"support\": 94, \"avg_response\": 81.75531914893617}, {\"feature_10\": \"4\", \"support\": 91, \"avg_response\": 91.47252747252747}, {\"feature_10\": \"5\", \"support\": 91, \"avg_response\": 91.14285714285714}, {\"feature_10\": \"18\", \"support\": 91, \"avg_response\": 84.73626373626374}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 5.28}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_109b942301d57cc9/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_109b942301d57cc9/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..92463ffa359f1868bb71b52ac4d7744dadf34e12
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_109b942301d57cc9/run_manifest.json
@@ -0,0 +1,60 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T16:10:15.896400+00:00",
+  "ended_at": "2026-05-19T16:10:15.902438+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_109b942301d57cc9",
+    "problem_id": "v2p_n9_4183abcb61c06446",
+    "dataset_id": "n9",
+    "template_id": "tpl_cardinality_high_card_response_stability",
+    "template_name": "High-Cardinality Response Stability",
+    "family_id": "cardinality_structure",
+    "canonical_subitem_id": "high_cardinality_response_stability",
+    "intended_facet_id": "target_cardinality_cross_section",
+    "variant_semantic_role": "focused_target_view",
+    "subitem_assignment_source": "template_fixed",
+    "source_kind": "deterministic",
+    "realization_mode": "deterministic",
+    "gate_priority": "deterministic",
+    "extended_family": true,
+    "question": "Use template High-Cardinality Response Stability to probe high_cardinality_response_stability with semantic role focused_target_view. Focus on measure_col=feature_4, key_col=feature_10.",
+    "bindings": {
+      "key_col": "feature_10",
+      "measure_col": "feature_4",
+      "min_support": 5
+    },
+    "binding_roles": [
+      "key_col",
+      "target_col"
+    ],
+    "coverage_target_min": "enumerate_all_applicable",
+    "runtime_sql_skeleton": "SELECT\n    {key_col},\n    COUNT(*) AS support,\n    AVG({measure_col}) AS avg_response\nFROM {table}\nGROUP BY {key_col}\nHAVING COUNT(*) >= {min_support}\nORDER BY support DESC, avg_response DESC;",
+    "notes": [
+      "default_facets=target_cardinality_cross_section",
+      "template_selection_mode=deterministic",
+      "problem_index_within_template=8",
+      "sql_variant_index=1/1"
+    ],
+    "template_selection_mode": "deterministic",
+    "selected_template_rank": 0,
+    "problem_index_within_template": 8,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_109b942301d57cc9.sql",
+  "usage_summary": {
+    "engine": "template",
+    "input_tokens": 0,
+    "cached_input_tokens": 0,
+    "output_tokens": 0,
+    "total_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "none"
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_109b942301d57cc9/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_109b942301d57cc9/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_109b942301d57cc9/usage_summary.json
@@ -0,0 +1,9 @@
+{
+  "engine": "template",
+  "input_tokens": 0,
+  "cached_input_tokens": 0,
+  "output_tokens": 0,
+  "total_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "none"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_15678180ad917562/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_15678180ad917562/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..8f86677e553b6d22cd535788039200f41f4188d7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_15678180ad917562/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=feature_1, measure_col=feature_3.
+Result preview: [{"feature_1": "1", "feature_4": "100", "total_measure": 1376.0, "share_within_group": 77.87209960384833}, {"feature_1": "14", "feature_4": "100", "total_measure": 2748.0, "share_within_group": 77.86908472655143}, {"feature_1": "15", "feature_4": "100", "total_measure": 2459.0, "share_within_group": 76.93992490613266}, {"feature_1": "16", "feature_4": "100", "total_measure": 2523.0, "share_within_group": 76.66362807657246}, {"feature_1": "26", "feature_4": "100", "total_measure": 2992.0, "share_within_group": 76.56090071647901}] Results were truncated.
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_15678180ad917562/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_15678180ad917562/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..99c0dca2f19a25bc8bb11fbf27a0be98d7270f32
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_15678180ad917562/generated_sql.sql
@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: within_group_proportion
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_15678180ad917562
+-- problem_id: v2p_n9_9f46d1163eb14383
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+  "feature_1",
+  "feature_4",
+  SUM(CAST("feature_3" AS REAL)) AS total_measure,
+  SUM(CAST("feature_3" AS REAL)) * 100.0 / SUM(SUM(CAST("feature_3" AS REAL))) OVER (PARTITION BY "feature_1") AS share_within_group
+FROM "n9"
+GROUP BY "feature_1", "feature_4"
+ORDER BY share_within_group DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_15678180ad917562/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_15678180ad917562/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..2b35bec44e7273779d61220eb36f4674907aa27a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_15678180ad917562/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT\n  \"feature_1\",\n  \"feature_4\",\n  SUM(CAST(\"feature_3\" AS REAL)) AS total_measure,\n  SUM(CAST(\"feature_3\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"feature_3\" AS REAL))) OVER (PARTITION BY \"feature_1\") AS share_within_group\nFROM \"n9\"\nGROUP BY \"feature_1\", \"feature_4\"\nORDER BY share_within_group DESC;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n  \\\"feature_1\\\",\\n  \\\"feature_4\\\",\\n  SUM(CAST(\\\"feature_3\\\" AS REAL)) AS total_measure,\\n  SUM(CAST(\\\"feature_3\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"feature_3\\\" AS REAL))) OVER (PARTITION BY \\\"feature_1\\\") AS share_within_group\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_1\\\", \\\"feature_4\\\"\\nORDER BY share_within_group DESC;\", \"columns\": [\"feature_1\", \"feature_4\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"feature_1\": \"1\", \"feature_4\": \"100\", \"total_measure\": 1376.0, \"share_within_group\": 77.87209960384833}, {\"feature_1\": \"14\", \"feature_4\": \"100\", \"total_measure\": 2748.0, \"share_within_group\": 77.86908472655143}, {\"feature_1\": \"15\", \"feature_4\": \"100\", \"total_measure\": 2459.0, \"share_within_group\": 76.93992490613266}, {\"feature_1\": \"16\", \"feature_4\": \"100\", \"total_measure\": 2523.0, \"share_within_group\": 76.66362807657246}, {\"feature_1\": \"26\", \"feature_4\": \"100\", \"total_measure\": 2992.0, \"share_within_group\": 76.56090071647901}, {\"feature_1\": \"10\", \"feature_4\": \"100\", \"total_measure\": 1605.0, \"share_within_group\": 73.99723374827109}, {\"feature_1\": \"13\", \"feature_4\": \"100\", \"total_measure\": 2403.0, \"share_within_group\": 72.62012692656391}, {\"feature_1\": \"2\", \"feature_4\": \"100\", \"total_measure\": 1962.0, \"share_within_group\": 72.1588819418904}, {\"feature_1\": \"44\", \"feature_4\": \"100\", \"total_measure\": 2950.0, \"share_within_group\": 70.79433645308376}, {\"feature_1\": \"5\", \"feature_4\": \"100\", \"total_measure\": 1537.0, \"share_within_group\": 69.17191719171917}, {\"feature_1\": \"36\", \"feature_4\": \"100\", \"total_measure\": 2810.0, \"share_within_group\": 68.85567262925754}, {\"feature_1\": \"35\", \"feature_4\": \"100\", \"total_measure\": 2908.0, \"share_within_group\": 68.76330101678884}, {\"feature_1\": \"3\", \"feature_4\": \"100\", \"total_measure\": 1115.0, \"share_within_group\": 68.7422934648582}, {\"feature_1\": \"20\", \"feature_4\": \"100\", \"total_measure\": 2460.0, \"share_within_group\": 68.69589500139625}, {\"feature_1\": \"52\", \"feature_4\": \"100\", \"total_measure\": 2248.0, \"share_within_group\": 68.47395674687786}, {\"feature_1\": \"17\", \"feature_4\": \"100\", \"total_measure\": 1956.0, \"share_within_group\": 67.49482401656314}, {\"feature_1\": \"9\", \"feature_4\": \"100\", \"total_measure\": 1648.0, \"share_within_group\": 67.34777278299958}, {\"feature_1\": \"37\", \"feature_4\": \"100\", \"total_measure\": 2035.0, \"share_within_group\": 67.16171617161716}, {\"feature_1\": \"40\", \"feature_4\": \"100\", \"total_measure\": 2521.0, \"share_within_group\": 65.96023024594453}, {\"feature_1\": \"32\", \"feature_4\": \"100\", \"total_measure\": 3439.0, \"share_within_group\": 65.78041315990819}, {\"feature_1\": \"47\", \"feature_4\": \"100\", \"total_measure\": 2265.0, \"share_within_group\": 65.61413673232909}, {\"feature_1\": \"30\", \"feature_4\": \"100\", \"total_measure\": 2816.0, \"share_within_group\": 65.54934823091247}, {\"feature_1\": \"29\", \"feature_4\": \"100\", \"total_measure\": 2684.0, \"share_within_group\": 65.47938521590632}, {\"feature_1\": \"54\", \"feature_4\": \"100\", \"total_measure\": 2633.0, \"share_within_group\": 65.07661888284726}, {\"feature_1\": \"34\", \"feature_4\": \"100\", \"total_measure\": 2448.0, \"share_within_group\": 64.79618845950239}, {\"feature_1\": \"41\", \"feature_4\": \"100\", \"total_measure\": 2561.0, \"share_within_group\": 64.443885254152}, {\"feature_1\": \"23\", \"feature_4\": \"100\", \"total_measure\": 2442.0, \"share_within_group\": 64.41572144552889}, {\"feature_1\": \"8\", \"feature_4\": \"100\", \"total_measure\": 1816.0, \"share_within_group\": 64.19229409685401}, {\"feature_1\": \"38\", \"feature_4\": \"100\", \"total_measure\": 3280.0, \"share_within_group\": 63.93762183235867}, {\"feature_1\": \"21\", \"feature_4\": \"100\", \"total_measure\": 2009.0, \"share_within_group\": 63.215859030837}, {\"feature_1\": \"31\", \"feature_4\": \"100\", \"total_measure\": 2315.0, \"share_within_group\": 63.18231441048035}, {\"feature_1\": \"6\", \"feature_4\": \"100\", \"total_measure\": 1675.0, \"share_within_group\": 63.0410237109522}, {\"feature_1\": \"28\", \"feature_4\": \"100\", \"total_measure\": 2226.0, \"share_within_group\": 62.04013377926422}, {\"feature_1\": \"33\", \"feature_4\": \"100\", \"total_measure\": 2569.0, \"share_within_group\": 61.064891846921796}, {\"feature_1\": \"99\", \"feature_4\": \"100\", \"total_measure\": 1122.0, \"share_within_group\": 60.1931330472103}, {\"feature_1\": \"18\", \"feature_4\": \"100\", \"total_measure\": 1611.0, \"share_within_group\": 60.17930519237953}, {\"feature_1\": \"24\", \"feature_4\": \"100\", \"total_measure\": 2377.0, \"share_within_group\": 59.889140841521794}, {\"feature_1\": \"39\", \"feature_4\": \"100\", \"total_measure\": 2309.0, \"share_within_group\": 59.22031290074378}, {\"feature_1\": \"55\", \"feature_4\": \"100\", \"total_measure\": 2369.0, \"share_within_group\": 58.40729783037475}, {\"feature_1\": \"97\", \"feature_4\": \"100\", \"total_measure\": 1501.0, \"share_within_group\": 58.38195254764683}, {\"feature_1\": \"25\", \"feature_4\": \"100\", \"total_measure\": 2314.0, \"share_within_group\": 58.09691187547075}, {\"feature_1\": \"4\", \"feature_4\": \"100\", \"total_measure\": 1489.0, \"share_within_group\": 57.870190439176056}, {\"feature_1\": \"12\", \"feature_4\": \"100\", \"total_measure\": 1920.0, \"share_within_group\": 57.43344301525576}, {\"feature_1\": \"51\", \"feature_4\": \"100\", \"total_measure\": 2062.0, \"share_within_group\": 57.27777777777778}, {\"feature_1\": \"94\", \"feature_4\": \"100\", \"total_measure\": 796.0, \"share_within_group\": 56.93848354792561}, {\"feature_1\": \"42\", \"feature_4\": \"100\", \"total_measure\": 2454.0, \"share_within_group\": 56.20705451213926}, {\"feature_1\": \"98\", \"feature_4\": \"100\", \"total_measure\": 987.0, \"share_within_group\": 55.54305008441193}, {\"feature_1\": \"11\", \"feature_4\": \"100\", \"total_measure\": 1459.0, \"share_within_group\": 55.39104024297646}, {\"feature_1\": \"65\", \"feature_4\": \"100\", \"total_measure\": 1383.0, \"share_within_group\": 54.968203497615264}, {\"feature_1\": \"27\", \"feature_4\": \"100\", \"total_measure\": 1944.0, \"share_within_group\": 54.745142213460994}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 19.11}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_15678180ad917562/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_15678180ad917562/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..431a2ad0de29466cb3b445b52b7e3ebaa0051292
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_15678180ad917562/run_manifest.json
@@ -0,0 +1,91 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:39:09.705114+00:00",
+  "ended_at": "2026-05-19T15:39:26.260092+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_15678180ad917562",
+    "problem_id": "v2p_n9_9f46d1163eb14383",
+    "dataset_id": "n9",
+    "template_id": "tpl_tpcds_within_group_share",
+    "template_name": "Within-Group Share of Total",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "dependency_strength_similarity",
+    "intended_facet_id": "pairwise_conditional_dependency",
+    "variant_semantic_role": "within_group_proportion",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=feature_1, measure_col=feature_3.",
+    "bindings": {
+      "group_col": "feature_1",
+      "measure_col": "feature_3",
+      "item_col": "feature_4",
+      "top_k": 14,
+      "top_n": 5,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 58.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "item_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;",
+    "notes": [
+      "default_facets=pairwise_conditional_dependency",
+      "template_selection_mode=rule",
+      "problem_index_within_template=11",
+      "sql_variant_index=1/2",
+      "binding_index=34"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 3,
+    "problem_index_within_template": 11,
+    "sql_variant_index": 1,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_15678180ad917562.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_15678180ad917562",
+    "api_calls": 0,
+    "input_tokens": 15060,
+    "cached_input_tokens": 13696,
+    "output_tokens": 691,
+    "total_tokens": 15751,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 16531.47,
+    "sql_execution_elapsed_ms_total": 19.11,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_15678180ad917562/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_15678180ad917562/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_15678180ad917562/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..69b17feb33ed72b447e0c9602e468e791e677b94
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_15678180ad917562/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:39:26.239130+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 16531.47, "started_at": "2026-05-19T15:39:09.706235+00:00", "ended_at": "2026-05-19T15:39:26.237735+00:00", "prompt_metrics": {"chars": 9800, "bytes_utf8": 9800, "lines": 302, "estimated_tokens": null}, "response_metrics": {"chars": 576, "bytes_utf8": 576, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15060, "cached_input_tokens": 13696, "output_tokens": 691, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n  \\\"feature_1\\\",\\n  \\\"feature_4\\\",\\n  SUM(CAST(\\\"feature_3\\\" AS REAL)) AS total_measure,\\n  SUM(CAST(\\\"feature_3\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"feature_3\\\" AS REAL))) OVER (PARTITION BY \\\"feature_1\\\") AS share_within_group\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_1\\\", \\\"feature_4\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Used the planned template with group_col=\\\"feature_1\\\", item_col=\\\"feature_4\\\", and measure_col=\\\"feature_3\\\". CAST was added because the schema stores feature columns as TEXT in SQLite.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_15678180ad917562/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_15678180ad917562/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..edcc8ee44289e404d4ec25348b49f9341efc7510
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_15678180ad917562/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_15678180ad917562",
+  "api_calls": 0,
+  "input_tokens": 15060,
+  "cached_input_tokens": 13696,
+  "output_tokens": 691,
+  "total_tokens": 15751,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 16531.47,
+  "sql_execution_elapsed_ms_total": 19.11,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_15678180ad917562/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_1d9d55c5f7ad11f7/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_1d9d55c5f7ad11f7/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..6b9f701a56366b7e02c1c52b660d2ed0721dd270
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_1d9d55c5f7ad11f7/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=feature_11, measure_col=feature_15.
+Result preview: [{"feature_11": "0", "group_value": 123045.0}, {"feature_11": "100", "group_value": 56070.0}]
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_1d9d55c5f7ad11f7/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_1d9d55c5f7ad11f7/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..3cf8dde43a6c02cc51d58cc9ea973ba99fbefa70
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_1d9d55c5f7ad11f7/generated_sql.sql
@@ -0,0 +1,26 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: filtered_stable_view
+-- template_id: tpl_tpch_relative_total_threshold
+-- query_record_id: v2q_n9_1d9d55c5f7ad11f7
+-- problem_id: v2p_n9_ce269b9d7d7d7ee3
+-- realization_mode: agent
+-- source_kind: agent
+WITH "grouped" AS (
+  SELECT "feature_11", SUM(CAST("feature_15" AS REAL)) AS "group_value"
+  FROM "n9"
+  GROUP BY "feature_11"
+), "total" AS (
+  SELECT SUM("group_value") AS "total_value"
+  FROM "grouped"
+)
+SELECT g."feature_11", g."group_value"
+FROM "grouped" AS g
+CROSS JOIN "total" AS t
+WHERE g."group_value" > t."total_value" * 0.05
+ORDER BY g."group_value" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_1d9d55c5f7ad11f7/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_1d9d55c5f7ad11f7/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..bd6d451afb7a75a58401982d87d256df2899f2bb
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_1d9d55c5f7ad11f7/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_relative_total_threshold\nWITH \"grouped\" AS (\n  SELECT \"feature_11\", SUM(CAST(\"feature_15\" AS REAL)) AS \"group_value\"\n  FROM \"n9\"\n  GROUP BY \"feature_11\"\n), \"total\" AS (\n  SELECT SUM(\"group_value\") AS \"total_value\"\n  FROM \"grouped\"\n)\nSELECT g.\"feature_11\", g.\"group_value\"\nFROM \"grouped\" AS g\nCROSS JOIN \"total\" AS t\nWHERE g.\"group_value\" > t.\"total_value\" * 0.05\nORDER BY g.\"group_value\" DESC;", "result": "{\"query\": \"-- template_id: tpl_tpch_relative_total_threshold\\nWITH \\\"grouped\\\" AS (\\n  SELECT \\\"feature_11\\\", SUM(CAST(\\\"feature_15\\\" AS REAL)) AS \\\"group_value\\\"\\n  FROM \\\"n9\\\"\\n  GROUP BY \\\"feature_11\\\"\\n), \\\"total\\\" AS (\\n  SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n  FROM \\\"grouped\\\"\\n)\\nSELECT g.\\\"feature_11\\\", g.\\\"group_value\\\"\\nFROM \\\"grouped\\\" AS g\\nCROSS JOIN \\\"total\\\" AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.05\\nORDER BY g.\\\"group_value\\\" DESC;\", \"columns\": [\"feature_11\", \"group_value\"], \"rows\": [{\"feature_11\": \"0\", \"group_value\": 123045.0}, {\"feature_11\": \"100\", \"group_value\": 56070.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 11.09}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_1d9d55c5f7ad11f7/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_1d9d55c5f7ad11f7/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..5e7a5c87aa9e491a1ab8585e62e6c803cd634c28
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_1d9d55c5f7ad11f7/run_manifest.json
@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:49:04.991255+00:00",
+  "ended_at": "2026-05-19T15:49:20.818966+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_1d9d55c5f7ad11f7",
+    "problem_id": "v2p_n9_ce269b9d7d7d7ee3",
+    "dataset_id": "n9",
+    "template_id": "tpl_tpch_relative_total_threshold",
+    "template_name": "Relative-to-Total Extreme Threshold",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_mass_similarity",
+    "intended_facet_id": "tail_ranked_signal",
+    "variant_semantic_role": "filtered_stable_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=feature_11, measure_col=feature_15.",
+    "bindings": {
+      "group_col": "feature_11",
+      "measure_col": "feature_15",
+      "top_k": 18,
+      "top_n": 6,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.05,
+      "baseline_multiplier": 1.75,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 4,
+      "measure_threshold": 81.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "WITH grouped AS (\n    SELECT {group_col}, SUM({measure_col}) AS group_value\n    FROM {table}\n    GROUP BY {group_col}\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;",
+    "notes": [
+      "default_facets=tail_ranked_signal",
+      "template_selection_mode=rule",
+      "problem_index_within_template=7",
+      "sql_variant_index=2/2",
+      "binding_index=78"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 7,
+    "problem_index_within_template": 7,
+    "sql_variant_index": 2,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_1d9d55c5f7ad11f7.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_1d9d55c5f7ad11f7",
+    "api_calls": 0,
+    "input_tokens": 15078,
+    "cached_input_tokens": 13696,
+    "output_tokens": 645,
+    "total_tokens": 15723,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 15811.37,
+    "sql_execution_elapsed_ms_total": 11.09,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_1d9d55c5f7ad11f7/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_1d9d55c5f7ad11f7/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_1d9d55c5f7ad11f7/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..77d2b705dbfe0e725f911c97b62a1b57aef0ebb1
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_1d9d55c5f7ad11f7/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:49:20.805504+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 15811.37, "started_at": "2026-05-19T15:49:04.992839+00:00", "ended_at": "2026-05-19T15:49:20.804242+00:00", "prompt_metrics": {"chars": 9950, "bytes_utf8": 9950, "lines": 300, "estimated_tokens": null}, "response_metrics": {"chars": 667, "bytes_utf8": 667, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15078, "cached_input_tokens": 13696, "output_tokens": 645, "reasoning_output_tokens": 451}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH \\\"grouped\\\" AS (\\n  SELECT \\\"feature_11\\\", SUM(CAST(\\\"feature_15\\\" AS REAL)) AS \\\"group_value\\\"\\n  FROM \\\"n9\\\"\\n  GROUP BY \\\"feature_11\\\"\\n), \\\"total\\\" AS (\\n  SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n  FROM \\\"grouped\\\"\\n)\\nSELECT g.\\\"feature_11\\\", g.\\\"group_value\\\"\\nFROM \\\"grouped\\\" AS g\\nCROSS JOIN \\\"total\\\" AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.05\\nORDER BY g.\\\"group_value\\\" DESC;\",\"notes\":\"Uses the required Relative-to-Total Extreme Threshold template with group_col=\\\"feature_11\\\" and measure_col=\\\"feature_15\\\", casting the TEXT measure to REAL for SQLite aggregation.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_1d9d55c5f7ad11f7/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_1d9d55c5f7ad11f7/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..722c3cf9876ad3fb364c9efde4012f34095bcb68
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_1d9d55c5f7ad11f7/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_1d9d55c5f7ad11f7",
+  "api_calls": 0,
+  "input_tokens": 15078,
+  "cached_input_tokens": 13696,
+  "output_tokens": 645,
+  "total_tokens": 15723,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 15811.37,
+  "sql_execution_elapsed_ms_total": 11.09,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_1d9d55c5f7ad11f7/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_26d46d9a01d4e949/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_26d46d9a01d4e949/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..68d0d9fa5b92e402425b644f4952c3b560a8f56b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_26d46d9a01d4e949/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=feature_3, measure_col=feature_3.
+Result preview: [{"feature_3": "100", "total_measure": 30900.0}, {"feature_3": "62", "total_measure": 8618.0}, {"feature_3": "57", "total_measure": 8550.0}, {"feature_3": "60", "total_measure": 8460.0}, {"feature_3": "56", "total_measure": 8344.0}] Results were truncated.
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_26d46d9a01d4e949/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_26d46d9a01d4e949/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..14e61b862924141e6bf3dab55e879b3a54322fdf
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_26d46d9a01d4e949/generated_sql.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_n9_26d46d9a01d4e949
+-- problem_id: v2p_n9_58e5ab15cb8eb9ac
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_3", SUM(CAST("feature_3" AS REAL)) AS "total_measure"
+FROM "n9"
+GROUP BY "feature_3"
+ORDER BY "total_measure" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_26d46d9a01d4e949/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_26d46d9a01d4e949/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..1d21511855231edfb19960a0c943f65d44d41390
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_26d46d9a01d4e949/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_h2o_group_sum\nSELECT \"feature_3\", SUM(CAST(\"feature_3\" AS REAL)) AS \"total_measure\"\nFROM \"n9\"\nGROUP BY \"feature_3\"\nORDER BY \"total_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"feature_3\\\", SUM(CAST(\\\"feature_3\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_3\\\"\\nORDER BY \\\"total_measure\\\" DESC;\", \"columns\": [\"feature_3\", \"total_measure\"], \"rows\": [{\"feature_3\": \"100\", \"total_measure\": 30900.0}, {\"feature_3\": \"62\", \"total_measure\": 8618.0}, {\"feature_3\": \"57\", \"total_measure\": 8550.0}, {\"feature_3\": \"60\", \"total_measure\": 8460.0}, {\"feature_3\": \"56\", \"total_measure\": 8344.0}, {\"feature_3\": \"53\", \"total_measure\": 8321.0}, {\"feature_3\": \"58\", \"total_measure\": 8178.0}, {\"feature_3\": \"52\", \"total_measure\": 8164.0}, {\"feature_3\": \"46\", \"total_measure\": 8142.0}, {\"feature_3\": \"59\", \"total_measure\": 7906.0}, {\"feature_3\": \"54\", \"total_measure\": 7884.0}, {\"feature_3\": \"55\", \"total_measure\": 7755.0}, {\"feature_3\": \"51\", \"total_measure\": 7344.0}, {\"feature_3\": \"50\", \"total_measure\": 7250.0}, {\"feature_3\": \"44\", \"total_measure\": 7084.0}, {\"feature_3\": \"47\", \"total_measure\": 7050.0}, {\"feature_3\": \"49\", \"total_measure\": 7007.0}, {\"feature_3\": \"43\", \"total_measure\": 6837.0}, {\"feature_3\": \"40\", \"total_measure\": 6680.0}, {\"feature_3\": \"66\", \"total_measure\": 6666.0}, {\"feature_3\": \"61\", \"total_measure\": 6649.0}, {\"feature_3\": \"42\", \"total_measure\": 6594.0}, {\"feature_3\": \"39\", \"total_measure\": 6552.0}, {\"feature_3\": \"35\", \"total_measure\": 6475.0}, {\"feature_3\": \"64\", \"total_measure\": 6336.0}, {\"feature_3\": \"38\", \"total_measure\": 6308.0}, {\"feature_3\": \"63\", \"total_measure\": 6300.0}, {\"feature_3\": \"48\", \"total_measure\": 6288.0}, {\"feature_3\": \"68\", \"total_measure\": 6188.0}, {\"feature_3\": \"41\", \"total_measure\": 6068.0}, {\"feature_3\": \"67\", \"total_measure\": 5963.0}, {\"feature_3\": \"45\", \"total_measure\": 5940.0}, {\"feature_3\": \"77\", \"total_measure\": 5852.0}, {\"feature_3\": \"34\", \"total_measure\": 5678.0}, {\"feature_3\": \"73\", \"total_measure\": 5621.0}, {\"feature_3\": \"70\", \"total_measure\": 5460.0}, {\"feature_3\": \"74\", \"total_measure\": 5254.0}, {\"feature_3\": \"75\", \"total_measure\": 5250.0}, {\"feature_3\": \"69\", \"total_measure\": 5244.0}, {\"feature_3\": \"71\", \"total_measure\": 4970.0}, {\"feature_3\": \"72\", \"total_measure\": 4968.0}, {\"feature_3\": \"36\", \"total_measure\": 4968.0}, {\"feature_3\": \"37\", \"total_measure\": 4884.0}, {\"feature_3\": \"65\", \"total_measure\": 4745.0}, {\"feature_3\": \"76\", \"total_measure\": 4636.0}, {\"feature_3\": \"30\", \"total_measure\": 4560.0}, {\"feature_3\": \"33\", \"total_measure\": 4521.0}, {\"feature_3\": \"31\", \"total_measure\": 4402.0}, {\"feature_3\": \"80\", \"total_measure\": 4400.0}, {\"feature_3\": \"32\", \"total_measure\": 4384.0}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 5.07}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_26d46d9a01d4e949/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_26d46d9a01d4e949/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..070422d20db50e6c69e9df0b5d8c5915998e13b0
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_26d46d9a01d4e949/run_manifest.json
@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:29:11.183355+00:00",
+  "ended_at": "2026-05-19T15:29:21.117732+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_26d46d9a01d4e949",
+    "problem_id": "v2p_n9_58e5ab15cb8eb9ac",
+    "dataset_id": "n9",
+    "template_id": "tpl_h2o_group_sum",
+    "template_name": "Grouped Numeric Sum",
+    "family_id": "subgroup_structure",
+    "canonical_subitem_id": "internal_profile_stability",
+    "intended_facet_id": "subgroup_distribution_shift",
+    "variant_semantic_role": "collapsed_target_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=feature_3, measure_col=feature_3.",
+    "bindings": {
+      "group_col": "feature_3",
+      "measure_col": "feature_3",
+      "top_k": 17,
+      "top_n": 6,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.05,
+      "baseline_multiplier": 1.75,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 4,
+      "measure_threshold": 52.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;",
+    "notes": [
+      "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast",
+      "template_selection_mode=rule",
+      "problem_index_within_template=3",
+      "sql_variant_index=2/2",
+      "binding_index=2"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 1,
+    "problem_index_within_template": 3,
+    "sql_variant_index": 2,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_26d46d9a01d4e949.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_26d46d9a01d4e949",
+    "api_calls": 0,
+    "input_tokens": 14940,
+    "cached_input_tokens": 12032,
+    "output_tokens": 378,
+    "total_tokens": 15318,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 9924.5,
+    "sql_execution_elapsed_ms_total": 5.07,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_26d46d9a01d4e949/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_26d46d9a01d4e949/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_26d46d9a01d4e949/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..7fe009cee0a9a26458ac5b68d496738d60b32af2
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_26d46d9a01d4e949/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:29:21.111333+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 9924.5, "started_at": "2026-05-19T15:29:11.186055+00:00", "ended_at": "2026-05-19T15:29:21.110594+00:00", "prompt_metrics": {"chars": 9390, "bytes_utf8": 9390, "lines": 300, "estimated_tokens": null}, "response_metrics": {"chars": 398, "bytes_utf8": 398, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14940, "cached_input_tokens": 12032, "output_tokens": 378, "reasoning_output_tokens": 271}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"feature_3\\\", SUM(CAST(\\\"feature_3\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_3\\\"\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Applied the grouped numeric sum template with \\\"feature_3\\\" as both the grouping column and summed measure. CAST to REAL is used because the schema stores numeric-looking values as TEXT in SQLite.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_26d46d9a01d4e949/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_26d46d9a01d4e949/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..3a02527b0188e9b867428355fd35ea51244af561
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_26d46d9a01d4e949/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_26d46d9a01d4e949",
+  "api_calls": 0,
+  "input_tokens": 14940,
+  "cached_input_tokens": 12032,
+  "output_tokens": 378,
+  "total_tokens": 15318,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 9924.5,
+  "sql_execution_elapsed_ms_total": 5.07,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_26d46d9a01d4e949/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_292f1052ac11dc32/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_292f1052ac11dc32/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..47e032a4487d7db1e0f3fd66b182575186353183
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_292f1052ac11dc32/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=feature_5.
+Result preview: [{"feature_5": "100"}, {"feature_5": "100"}, {"feature_5": "100"}, {"feature_5": "100"}, {"feature_5": "100"}] Results were truncated.
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_292f1052ac11dc32/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_292f1052ac11dc32/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..95f116091899dbc60e247f7d8bffe18ad5c2a3bf
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_292f1052ac11dc32/generated_sql.sql
@@ -0,0 +1,22 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_set_consistency
+-- intended_facet_id: low_support_extremes
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_m4_quantile_tail_slice
+-- query_record_id: v2q_n9_292f1052ac11dc32
+-- problem_id: v2p_n9_ec4420756e1917a2
+-- realization_mode: agent
+-- source_kind: agent
+WITH buckets AS (
+    SELECT "feature_5",
+           NTILE(10) OVER (ORDER BY CAST("feature_5" AS REAL) DESC) AS tail_bucket
+    FROM "n9"
+)
+SELECT "feature_5"
+FROM buckets
+WHERE tail_bucket = 1
+ORDER BY CAST("feature_5" AS REAL) DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_292f1052ac11dc32/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_292f1052ac11dc32/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..62f9cdd01c25ae321a6bb55e9745be7d210ed3f7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_292f1052ac11dc32/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_quantile_tail_slice\nWITH buckets AS (\n    SELECT \"feature_5\",\n           NTILE(10) OVER (ORDER BY CAST(\"feature_5\" AS REAL) DESC) AS tail_bucket\n    FROM \"n9\"\n)\nSELECT \"feature_5\"\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY CAST(\"feature_5\" AS REAL) DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_quantile_tail_slice\\nWITH buckets AS (\\n    SELECT \\\"feature_5\\\",\\n           NTILE(10) OVER (ORDER BY CAST(\\\"feature_5\\\" AS REAL) DESC) AS tail_bucket\\n    FROM \\\"n9\\\"\\n)\\nSELECT \\\"feature_5\\\"\\nFROM buckets\\nWHERE tail_bucket = 1\\nORDER BY CAST(\\\"feature_5\\\" AS REAL) DESC;\", \"columns\": [\"feature_5\"], \"rows\": [{\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}, {\"feature_5\": \"100\"}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 14.65}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_292f1052ac11dc32/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_292f1052ac11dc32/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..8140cfe1bc8a6fe007a9965c4052c13dee320865
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_292f1052ac11dc32/run_manifest.json
@@ -0,0 +1,87 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:45:52.909239+00:00",
+  "ended_at": "2026-05-19T15:46:04.228972+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_292f1052ac11dc32",
+    "problem_id": "v2p_n9_ec4420756e1917a2",
+    "dataset_id": "n9",
+    "template_id": "tpl_m4_quantile_tail_slice",
+    "template_name": "Quantile Tail Slice",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_set_consistency",
+    "intended_facet_id": "low_support_extremes",
+    "variant_semantic_role": "rare_extreme_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=feature_5.",
+    "bindings": {
+      "measure_col": "feature_5",
+      "top_k": 13,
+      "top_n": 3,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 78.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "WITH buckets AS (\n    SELECT {measure_col},\n           NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n    FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;",
+    "notes": [
+      "default_facets=low_support_extremes",
+      "template_selection_mode=rule",
+      "problem_index_within_template=9",
+      "sql_variant_index=1/1",
+      "binding_index=68"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 6,
+    "problem_index_within_template": 9,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_292f1052ac11dc32.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_292f1052ac11dc32",
+    "api_calls": 0,
+    "input_tokens": 14991,
+    "cached_input_tokens": 13696,
+    "output_tokens": 527,
+    "total_tokens": 15518,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 11301.05,
+    "sql_execution_elapsed_ms_total": 14.65,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_292f1052ac11dc32/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_292f1052ac11dc32/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_292f1052ac11dc32/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..3ac8fae62d0ba257d8fa1eb505a0adcc3b84e6d6
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_292f1052ac11dc32/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:46:04.212949+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 11301.05, "started_at": "2026-05-19T15:45:52.911186+00:00", "ended_at": "2026-05-19T15:46:04.212265+00:00", "prompt_metrics": {"chars": 9558, "bytes_utf8": 9558, "lines": 298, "estimated_tokens": null}, "response_metrics": {"chars": 525, "bytes_utf8": 525, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14991, "cached_input_tokens": 13696, "output_tokens": 527, "reasoning_output_tokens": 379}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_quantile_tail_slice\\nWITH buckets AS (\\n    SELECT \\\"feature_5\\\",\\n           NTILE(10) OVER (ORDER BY CAST(\\\"feature_5\\\" AS REAL) DESC) AS tail_bucket\\n    FROM \\\"n9\\\"\\n)\\nSELECT \\\"feature_5\\\"\\nFROM buckets\\nWHERE tail_bucket = 1\\nORDER BY CAST(\\\"feature_5\\\" AS REAL) DESC;\",\"notes\":\"Applied the Quantile Tail Slice template with measure_col bound to \\\"feature_5\\\" and num_tiles=10. CAST(... AS REAL) is used because the schema stores features as TEXT, but the field is semantically numeric.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_292f1052ac11dc32/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_292f1052ac11dc32/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..dcd7149991c99c711ed84c5a124f281ffc1458bf
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_292f1052ac11dc32/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_292f1052ac11dc32",
+  "api_calls": 0,
+  "input_tokens": 14991,
+  "cached_input_tokens": 13696,
+  "output_tokens": 527,
+  "total_tokens": 15518,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 11301.05,
+  "sql_execution_elapsed_ms_total": 14.65,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_292f1052ac11dc32/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_2b75aa0b8aa3bfb7/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_2b75aa0b8aa3bfb7/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..5df3269fd9f216003c85c17d585d660cad9879a4
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_2b75aa0b8aa3bfb7/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=feature_4, measure_col=feature_9.
+Result preview: [{"feature_4": "0", "percentile_measure": 100.0}, {"feature_4": "10", "percentile_measure": 100.0}, {"feature_4": "100", "percentile_measure": 100.0}, {"feature_4": "14", "percentile_measure": 100.0}, {"feature_4": "16", "percentile_measure": 100.0}] Results were truncated.
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_2b75aa0b8aa3bfb7/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_2b75aa0b8aa3bfb7/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..012b4d13c8c143f898b6da99d9726016d936a078
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_2b75aa0b8aa3bfb7/generated_sql.sql
@@ -0,0 +1,67 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_n9_2b75aa0b8aa3bfb7
+-- problem_id: v2p_n9_ddd723ae4bfdc109
+-- realization_mode: agent
+-- source_kind: agent
+WITH "ordered" AS (
+  SELECT
+    "feature_4",
+    CAST("feature_9" AS REAL) AS "measure",
+    ROW_NUMBER() OVER (
+      PARTITION BY "feature_4"
+      ORDER BY CAST("feature_9" AS REAL)
+    ) AS "rn",
+    COUNT(*) OVER (PARTITION BY "feature_4") AS "cnt"
+  FROM "n9"
+  WHERE "feature_4" IS NOT NULL
+    AND "feature_9" IS NOT NULL
+),
+"positions" AS (
+  SELECT DISTINCT
+    "feature_4",
+    "cnt",
+    (0.95 * ("cnt" - 1)) + 1.0 AS "pos",
+    CAST((0.95 * ("cnt" - 1)) + 1.0 AS INT) AS "lower_rn",
+    CAST((0.95 * ("cnt" - 1)) + 1.0 AS INT) +
+      CASE
+        WHEN ((0.95 * ("cnt" - 1)) + 1.0) > CAST((0.95 * ("cnt" - 1)) + 1.0 AS INT) THEN 1
+        ELSE 0
+      END AS "upper_rn"
+  FROM "ordered"
+),
+"bounds" AS (
+  SELECT
+    "p"."feature_4",
+    "p"."cnt",
+    "p"."pos",
+    "p"."lower_rn",
+    "p"."upper_rn",
+    MAX(CASE WHEN "o"."rn" = "p"."lower_rn" THEN "o"."measure" END) AS "lower_val",
+    MAX(CASE WHEN "o"."rn" = "p"."upper_rn" THEN "o"."measure" END) AS "upper_val"
+  FROM "positions" AS "p"
+  JOIN "ordered" AS "o"
+    ON "o"."feature_4" = "p"."feature_4"
+  GROUP BY
+    "p"."feature_4",
+    "p"."cnt",
+    "p"."pos",
+    "p"."lower_rn",
+    "p"."upper_rn"
+)
+SELECT
+  "feature_4",
+  CASE
+    WHEN "lower_rn" = "upper_rn" THEN "lower_val"
+    ELSE "lower_val" + ("pos" - "lower_rn") * ("upper_val" - "lower_val")
+  END AS "percentile_measure"
+FROM "bounds"
+WHERE "cnt" >= 5
+ORDER BY "percentile_measure" DESC, "feature_4";
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_2b75aa0b8aa3bfb7/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_2b75aa0b8aa3bfb7/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..b3a7d59bd614e1df0fb323ac3f2769476e912a2e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_2b75aa0b8aa3bfb7/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH \"ordered\" AS (\n  SELECT\n    \"feature_4\",\n    CAST(\"feature_9\" AS REAL) AS \"measure\",\n    ROW_NUMBER() OVER (\n      PARTITION BY \"feature_4\"\n      ORDER BY CAST(\"feature_9\" AS REAL)\n    ) AS \"rn\",\n    COUNT(*) OVER (PARTITION BY \"feature_4\") AS \"cnt\"\n  FROM \"n9\"\n  WHERE \"feature_4\" IS NOT NULL\n    AND \"feature_9\" IS NOT NULL\n),\n\"positions\" AS (\n  SELECT DISTINCT\n    \"feature_4\",\n    \"cnt\",\n    (0.95 * (\"cnt\" - 1)) + 1.0 AS \"pos\",\n    CAST((0.95 * (\"cnt\" - 1)) + 1.0 AS INT) AS \"lower_rn\",\n    CAST((0.95 * (\"cnt\" - 1)) + 1.0 AS INT) +\n      CASE\n        WHEN ((0.95 * (\"cnt\" - 1)) + 1.0) > CAST((0.95 * (\"cnt\" - 1)) + 1.0 AS INT) THEN 1\n        ELSE 0\n      END AS \"upper_rn\"\n  FROM \"ordered\"\n),\n\"bounds\" AS (\n  SELECT\n    \"p\".\"feature_4\",\n    \"p\".\"cnt\",\n    \"p\".\"pos\",\n    \"p\".\"lower_rn\",\n    \"p\".\"upper_rn\",\n    MAX(CASE WHEN \"o\".\"rn\" = \"p\".\"lower_rn\" THEN \"o\".\"measure\" END) AS \"lower_val\",\n    MAX(CASE WHEN \"o\".\"rn\" = \"p\".\"upper_rn\" THEN \"o\".\"measure\" END) AS \"upper_val\"\n  FROM \"positions\" AS \"p\"\n  JOIN \"ordered\" AS \"o\"\n    ON \"o\".\"feature_4\" = \"p\".\"feature_4\"\n  GROUP BY\n    \"p\".\"feature_4\",\n    \"p\".\"cnt\",\n    \"p\".\"pos\",\n    \"p\".\"lower_rn\",\n    \"p\".\"upper_rn\"\n)\nSELECT\n  \"feature_4\",\n  CASE\n    WHEN \"lower_rn\" = \"upper_rn\" THEN \"lower_val\"\n    ELSE \"lower_val\" + (\"pos\" - \"lower_rn\") * (\"upper_val\" - \"lower_val\")\n  END AS \"percentile_measure\"\nFROM \"bounds\"\nWHERE \"cnt\" >= 5\nORDER BY \"percentile_measure\" DESC, \"feature_4\";", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ordered\\\" AS (\\n  SELECT\\n    \\\"feature_4\\\",\\n    CAST(\\\"feature_9\\\" AS REAL) AS \\\"measure\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"feature_4\\\"\\n      ORDER BY CAST(\\\"feature_9\\\" AS REAL)\\n    ) AS \\\"rn\\\",\\n    COUNT(*) OVER (PARTITION BY \\\"feature_4\\\") AS \\\"cnt\\\"\\n  FROM \\\"n9\\\"\\n  WHERE \\\"feature_4\\\" IS NOT NULL\\n    AND \\\"feature_9\\\" IS NOT NULL\\n),\\n\\\"positions\\\" AS (\\n  SELECT DISTINCT\\n    \\\"feature_4\\\",\\n    \\\"cnt\\\",\\n    (0.95 * (\\\"cnt\\\" - 1)) + 1.0 AS \\\"pos\\\",\\n    CAST((0.95 * (\\\"cnt\\\" - 1)) + 1.0 AS INT) AS \\\"lower_rn\\\",\\n    CAST((0.95 * (\\\"cnt\\\" - 1)) + 1.0 AS INT) +\\n      CASE\\n        WHEN ((0.95 * (\\\"cnt\\\" - 1)) + 1.0) > CAST((0.95 * (\\\"cnt\\\" - 1)) + 1.0 AS INT) THEN 1\\n        ELSE 0\\n      END AS \\\"upper_rn\\\"\\n  FROM \\\"ordered\\\"\\n),\\n\\\"bounds\\\" AS (\\n  SELECT\\n    \\\"p\\\".\\\"feature_4\\\",\\n    \\\"p\\\".\\\"cnt\\\",\\n    \\\"p\\\".\\\"pos\\\",\\n    \\\"p\\\".\\\"lower_rn\\\",\\n    \\\"p\\\".\\\"upper_rn\\\",\\n    MAX(CASE WHEN \\\"o\\\".\\\"rn\\\" = \\\"p\\\".\\\"lower_rn\\\" THEN \\\"o\\\".\\\"measure\\\" END) AS \\\"lower_val\\\",\\n    MAX(CASE WHEN \\\"o\\\".\\\"rn\\\" = \\\"p\\\".\\\"upper_rn\\\" THEN \\\"o\\\".\\\"measure\\\" END) AS \\\"upper_val\\\"\\n  FROM \\\"positions\\\" AS \\\"p\\\"\\n  JOIN \\\"ordered\\\" AS \\\"o\\\"\\n    ON \\\"o\\\".\\\"feature_4\\\" = \\\"p\\\".\\\"feature_4\\\"\\n  GROUP BY\\n    \\\"p\\\".\\\"feature_4\\\",\\n    \\\"p\\\".\\\"cnt\\\",\\n    \\\"p\\\".\\\"pos\\\",\\n    \\\"p\\\".\\\"lower_rn\\\",\\n    \\\"p\\\".\\\"upper_rn\\\"\\n)\\nSELECT\\n  \\\"feature_4\\\",\\n  CASE\\n    WHEN \\\"lower_rn\\\" = \\\"upper_rn\\\" THEN \\\"lower_val\\\"\\n    ELSE \\\"lower_val\\\" + (\\\"pos\\\" - \\\"lower_rn\\\") * (\\\"upper_val\\\" - \\\"lower_val\\\")\\n  END AS \\\"percentile_measure\\\"\\nFROM \\\"bounds\\\"\\nWHERE \\\"cnt\\\" >= 5\\nORDER BY \\\"percentile_measure\\\" DESC, \\\"feature_4\\\";\", \"columns\": [\"feature_4\", \"percentile_measure\"], \"rows\": [{\"feature_4\": \"0\", \"percentile_measure\": 100.0}, {\"feature_4\": \"10\", \"percentile_measure\": 100.0}, {\"feature_4\": \"100\", \"percentile_measure\": 100.0}, {\"feature_4\": \"14\", \"percentile_measure\": 100.0}, {\"feature_4\": \"16\", \"percentile_measure\": 100.0}, {\"feature_4\": \"18\", \"percentile_measure\": 100.0}, {\"feature_4\": \"20\", \"percentile_measure\": 100.0}, {\"feature_4\": \"21\", \"percentile_measure\": 100.0}, {\"feature_4\": \"24\", \"percentile_measure\": 100.0}, {\"feature_4\": \"25\", \"percentile_measure\": 100.0}, {\"feature_4\": \"26\", \"percentile_measure\": 100.0}, {\"feature_4\": \"27\", \"percentile_measure\": 100.0}, {\"feature_4\": \"28\", \"percentile_measure\": 100.0}, {\"feature_4\": \"29\", \"percentile_measure\": 100.0}, {\"feature_4\": \"30\", \"percentile_measure\": 100.0}, {\"feature_4\": \"31\", \"percentile_measure\": 100.0}, {\"feature_4\": \"32\", \"percentile_measure\": 100.0}, {\"feature_4\": \"33\", \"percentile_measure\": 100.0}, {\"feature_4\": \"34\", \"percentile_measure\": 100.0}, {\"feature_4\": \"35\", \"percentile_measure\": 100.0}, {\"feature_4\": \"36\", \"percentile_measure\": 100.0}, {\"feature_4\": \"37\", \"percentile_measure\": 100.0}, {\"feature_4\": \"38\", \"percentile_measure\": 100.0}, {\"feature_4\": \"39\", \"percentile_measure\": 100.0}, {\"feature_4\": \"40\", \"percentile_measure\": 100.0}, {\"feature_4\": \"41\", \"percentile_measure\": 100.0}, {\"feature_4\": \"42\", \"percentile_measure\": 100.0}, {\"feature_4\": \"43\", \"percentile_measure\": 100.0}, {\"feature_4\": \"44\", \"percentile_measure\": 100.0}, {\"feature_4\": \"45\", \"percentile_measure\": 100.0}, {\"feature_4\": \"46\", \"percentile_measure\": 100.0}, {\"feature_4\": \"47\", \"percentile_measure\": 100.0}, {\"feature_4\": \"48\", \"percentile_measure\": 100.0}, {\"feature_4\": \"49\", \"percentile_measure\": 100.0}, {\"feature_4\": \"50\", \"percentile_measure\": 100.0}, {\"feature_4\": \"51\", \"percentile_measure\": 100.0}, {\"feature_4\": \"52\", \"percentile_measure\": 100.0}, {\"feature_4\": \"53\", \"percentile_measure\": 100.0}, {\"feature_4\": \"54\", \"percentile_measure\": 100.0}, {\"feature_4\": \"55\", \"percentile_measure\": 100.0}, {\"feature_4\": \"56\", \"percentile_measure\": 100.0}, {\"feature_4\": \"57\", \"percentile_measure\": 100.0}, {\"feature_4\": \"58\", \"percentile_measure\": 100.0}, {\"feature_4\": \"59\", \"percentile_measure\": 100.0}, {\"feature_4\": \"60\", \"percentile_measure\": 100.0}, {\"feature_4\": \"61\", \"percentile_measure\": 100.0}, {\"feature_4\": \"62\", \"percentile_measure\": 100.0}, {\"feature_4\": \"63\", \"percentile_measure\": 100.0}, {\"feature_4\": \"64\", \"percentile_measure\": 100.0}, {\"feature_4\": \"65\", \"percentile_measure\": 100.0}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 42.11}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_2b75aa0b8aa3bfb7/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_2b75aa0b8aa3bfb7/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..f05fc5738a75224b2d6ae91258ec215ac620aff9
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_2b75aa0b8aa3bfb7/run_manifest.json
@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:53:48.266417+00:00",
+  "ended_at": "2026-05-19T15:54:49.848864+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_2b75aa0b8aa3bfb7",
+    "problem_id": "v2p_n9_ddd723ae4bfdc109",
+    "dataset_id": "n9",
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_concentration_consistency",
+    "intended_facet_id": "rare_target_concentration",
+    "variant_semantic_role": "focused_target_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=feature_4, measure_col=feature_9.",
+    "bindings": {
+      "group_col": "feature_4",
+      "measure_col": "feature_9",
+      "top_k": 13,
+      "top_n": 3,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 89.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;",
+    "notes": [
+      "default_facets=rare_target_concentration",
+      "template_selection_mode=rule",
+      "problem_index_within_template=5",
+      "sql_variant_index=1/2",
+      "binding_index=88"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 8,
+    "problem_index_within_template": 5,
+    "sql_variant_index": 1,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_2b75aa0b8aa3bfb7.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_2b75aa0b8aa3bfb7",
+    "api_calls": 0,
+    "input_tokens": 14978,
+    "cached_input_tokens": 12032,
+    "output_tokens": 4437,
+    "total_tokens": 19415,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 61536.49,
+    "sql_execution_elapsed_ms_total": 42.11,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_2b75aa0b8aa3bfb7/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_2b75aa0b8aa3bfb7/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_2b75aa0b8aa3bfb7/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..c39141af6b16b0af8bfc08808c5784e2428f57cf
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_2b75aa0b8aa3bfb7/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:54:49.804854+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 61536.49, "started_at": "2026-05-19T15:53:48.267516+00:00", "ended_at": "2026-05-19T15:54:49.804033+00:00", "prompt_metrics": {"chars": 9568, "bytes_utf8": 9568, "lines": 300, "estimated_tokens": null}, "response_metrics": {"chars": 1954, "bytes_utf8": 1954, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14978, "cached_input_tokens": 12032, "output_tokens": 4437, "reasoning_output_tokens": 3750}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ordered\\\" AS (\\n  SELECT\\n    \\\"feature_4\\\",\\n    CAST(\\\"feature_9\\\" AS REAL) AS \\\"measure\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"feature_4\\\"\\n      ORDER BY CAST(\\\"feature_9\\\" AS REAL)\\n    ) AS \\\"rn\\\",\\n    COUNT(*) OVER (PARTITION BY \\\"feature_4\\\") AS \\\"cnt\\\"\\n  FROM \\\"n9\\\"\\n  WHERE \\\"feature_4\\\" IS NOT NULL\\n    AND \\\"feature_9\\\" IS NOT NULL\\n),\\n\\\"positions\\\" AS (\\n  SELECT DISTINCT\\n    \\\"feature_4\\\",\\n    \\\"cnt\\\",\\n    (0.95 * (\\\"cnt\\\" - 1)) + 1.0 AS \\\"pos\\\",\\n    CAST((0.95 * (\\\"cnt\\\" - 1)) + 1.0 AS INT) AS \\\"lower_rn\\\",\\n    CAST((0.95 * (\\\"cnt\\\" - 1)) + 1.0 AS INT) +\\n      CASE\\n        WHEN ((0.95 * (\\\"cnt\\\" - 1)) + 1.0) > CAST((0.95 * (\\\"cnt\\\" - 1)) + 1.0 AS INT) THEN 1\\n        ELSE 0\\n      END AS \\\"upper_rn\\\"\\n  FROM \\\"ordered\\\"\\n),\\n\\\"bounds\\\" AS (\\n  SELECT\\n    \\\"p\\\".\\\"feature_4\\\",\\n    \\\"p\\\".\\\"cnt\\\",\\n    \\\"p\\\".\\\"pos\\\",\\n    \\\"p\\\".\\\"lower_rn\\\",\\n    \\\"p\\\".\\\"upper_rn\\\",\\n    MAX(CASE WHEN \\\"o\\\".\\"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_2b75aa0b8aa3bfb7/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_2b75aa0b8aa3bfb7/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..b3f6a7dd0d1398d75086a22cfc3cbdf3c18de89f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_2b75aa0b8aa3bfb7/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_2b75aa0b8aa3bfb7",
+  "api_calls": 0,
+  "input_tokens": 14978,
+  "cached_input_tokens": 12032,
+  "output_tokens": 4437,
+  "total_tokens": 19415,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 61536.49,
+  "sql_execution_elapsed_ms_total": 42.11,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_2b75aa0b8aa3bfb7/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_32a48e1986c6d0a7/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_32a48e1986c6d0a7/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..64b5c8fdfd465d84e2928fcc6aa7d64adff1a563
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_32a48e1986c6d0a7/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=feature_2.
+Result preview: [{"feature_2": "100", "row_count": 3115}, {"feature_2": "90", "row_count": 261}, {"feature_2": "91", "row_count": 259}, {"feature_2": "88", "row_count": 254}, {"feature_2": "96", "row_count": 247}] Results were truncated.
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_32a48e1986c6d0a7/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_32a48e1986c6d0a7/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..4205c8adc550fcf4b3830dcad5912a924672d646
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_32a48e1986c6d0a7/generated_sql.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: subgroup_size_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_clickbench_group_count
+-- query_record_id: v2q_n9_32a48e1986c6d0a7
+-- problem_id: v2p_n9_a23486fcb3be17ad
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_2", COUNT(*) AS "row_count"
+FROM "n9"
+GROUP BY "feature_2"
+ORDER BY "row_count" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_32a48e1986c6d0a7/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_32a48e1986c6d0a7/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..93b6a8e9f1cea53f7ec603c87fc7f3bef65d53ec
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_32a48e1986c6d0a7/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_clickbench_group_count\nSELECT \"feature_2\", COUNT(*) AS \"row_count\"\nFROM \"n9\"\nGROUP BY \"feature_2\"\nORDER BY \"row_count\" DESC;", "result": "{\"query\": \"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"feature_2\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_2\\\"\\nORDER BY \\\"row_count\\\" DESC;\", \"columns\": [\"feature_2\", \"row_count\"], \"rows\": [{\"feature_2\": \"100\", \"row_count\": 3115}, {\"feature_2\": \"90\", \"row_count\": 261}, {\"feature_2\": \"91\", \"row_count\": 259}, {\"feature_2\": \"88\", \"row_count\": 254}, {\"feature_2\": \"96\", \"row_count\": 247}, {\"feature_2\": \"93\", \"row_count\": 245}, {\"feature_2\": \"85\", \"row_count\": 245}, {\"feature_2\": \"89\", \"row_count\": 244}, {\"feature_2\": \"94\", \"row_count\": 242}, {\"feature_2\": \"82\", \"row_count\": 236}, {\"feature_2\": \"92\", \"row_count\": 235}, {\"feature_2\": \"95\", \"row_count\": 234}, {\"feature_2\": \"86\", \"row_count\": 232}, {\"feature_2\": \"87\", \"row_count\": 221}, {\"feature_2\": \"97\", \"row_count\": 217}, {\"feature_2\": \"81\", \"row_count\": 216}, {\"feature_2\": \"83\", \"row_count\": 213}, {\"feature_2\": \"84\", \"row_count\": 205}, {\"feature_2\": \"98\", \"row_count\": 203}, {\"feature_2\": \"80\", \"row_count\": 200}, {\"feature_2\": \"78\", \"row_count\": 200}, {\"feature_2\": \"77\", \"row_count\": 175}, {\"feature_2\": \"99\", \"row_count\": 172}, {\"feature_2\": \"76\", \"row_count\": 172}, {\"feature_2\": \"79\", \"row_count\": 167}, {\"feature_2\": \"73\", \"row_count\": 163}, {\"feature_2\": \"75\", \"row_count\": 161}, {\"feature_2\": \"74\", \"row_count\": 140}, {\"feature_2\": \"72\", \"row_count\": 134}, {\"feature_2\": \"71\", \"row_count\": 134}, {\"feature_2\": \"70\", \"row_count\": 118}, {\"feature_2\": \"67\", \"row_count\": 117}, {\"feature_2\": \"69\", \"row_count\": 115}, {\"feature_2\": \"66\", \"row_count\": 114}, {\"feature_2\": \"68\", \"row_count\": 108}, {\"feature_2\": \"65\", \"row_count\": 101}, {\"feature_2\": \"64\", \"row_count\": 97}, {\"feature_2\": \"63\", \"row_count\": 97}, {\"feature_2\": \"62\", \"row_count\": 69}, {\"feature_2\": \"61\", \"row_count\": 69}, {\"feature_2\": \"60\", \"row_count\": 61}, {\"feature_2\": \"55\", \"row_count\": 55}, {\"feature_2\": \"59\", \"row_count\": 52}, {\"feature_2\": \"58\", \"row_count\": 46}, {\"feature_2\": \"57\", \"row_count\": 44}, {\"feature_2\": \"54\", \"row_count\": 43}, {\"feature_2\": \"56\", \"row_count\": 42}, {\"feature_2\": \"53\", \"row_count\": 35}, {\"feature_2\": \"52\", \"row_count\": 34}, {\"feature_2\": \"51\", \"row_count\": 28}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 6.32}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_32a48e1986c6d0a7/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_32a48e1986c6d0a7/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..20c137047cd9082b9d5ff27f9998971a1f3157ac
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_32a48e1986c6d0a7/run_manifest.json
@@ -0,0 +1,87 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:33:17.018127+00:00",
+  "ended_at": "2026-05-19T15:33:43.276314+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_32a48e1986c6d0a7",
+    "problem_id": "v2p_n9_a23486fcb3be17ad",
+    "dataset_id": "n9",
+    "template_id": "tpl_clickbench_group_count",
+    "template_name": "Grouped Count by Category",
+    "family_id": "subgroup_structure",
+    "canonical_subitem_id": "subgroup_size_stability",
+    "intended_facet_id": "subgroup_distribution_shift",
+    "variant_semantic_role": "count_distribution",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=feature_2.",
+    "bindings": {
+      "group_col": "feature_2",
+      "top_k": 13,
+      "top_n": 5,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 58.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;",
+    "notes": [
+      "default_facets=subgroup_distribution_shift",
+      "template_selection_mode=rule",
+      "problem_index_within_template=7",
+      "sql_variant_index=1/1",
+      "binding_index=18"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 2,
+    "problem_index_within_template": 7,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_32a48e1986c6d0a7.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_32a48e1986c6d0a7",
+    "api_calls": 0,
+    "input_tokens": 14911,
+    "cached_input_tokens": 12032,
+    "output_tokens": 425,
+    "total_tokens": 15336,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 26246.26,
+    "sql_execution_elapsed_ms_total": 6.32,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_32a48e1986c6d0a7/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_32a48e1986c6d0a7/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_32a48e1986c6d0a7/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..f4c427eda97fb01e5d0b04cd991182e076eaae72
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_32a48e1986c6d0a7/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:33:43.268058+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 26246.26, "started_at": "2026-05-19T15:33:17.020555+00:00", "ended_at": "2026-05-19T15:33:43.266857+00:00", "prompt_metrics": {"chars": 9297, "bytes_utf8": 9297, "lines": 298, "estimated_tokens": null}, "response_metrics": {"chars": 268, "bytes_utf8": 268, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14911, "cached_input_tokens": 12032, "output_tokens": 425, "reasoning_output_tokens": 344}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"feature_2\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_2\\\"\\nORDER BY \\\"row_count\\\" DESC;\",\"notes\":\"Applied the grouped-count template on table \\\"n9\\\" with group_col bound to \\\"feature_2\\\".\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_32a48e1986c6d0a7/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_32a48e1986c6d0a7/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..7127a2d9a3f46d62df49afd961088cc391fbe6d7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_32a48e1986c6d0a7/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_32a48e1986c6d0a7",
+  "api_calls": 0,
+  "input_tokens": 14911,
+  "cached_input_tokens": 12032,
+  "output_tokens": 425,
+  "total_tokens": 15336,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 26246.26,
+  "sql_execution_elapsed_ms_total": 6.32,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_32a48e1986c6d0a7/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_39cf333bfd031134/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_39cf333bfd031134/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b2834d2053eae3ab84df6810ca41e73912505239
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_39cf333bfd031134/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=feature_10, measure_col=feature_14.
+Result preview: [{"feature_10": "0", "group_value": 99579.0}]
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_39cf333bfd031134/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_39cf333bfd031134/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..66675c3385cf2386babb04db4cfcbcbbfd4ae16c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_39cf333bfd031134/generated_sql.sql
@@ -0,0 +1,26 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_tpch_relative_total_threshold
+-- query_record_id: v2q_n9_39cf333bfd031134
+-- problem_id: v2p_n9_33c289b5e959e2e7
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+    SELECT "feature_10", SUM(CAST("feature_14" AS REAL)) AS group_value
+    FROM "n9"
+    GROUP BY "feature_10"
+), total AS (
+    SELECT SUM(group_value) AS total_value
+    FROM grouped
+)
+SELECT g."feature_10", g.group_value
+FROM grouped AS g
+CROSS JOIN total AS t
+WHERE g.group_value > t.total_value * 0.05
+ORDER BY g.group_value DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_39cf333bfd031134/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_39cf333bfd031134/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..63e64c68b808080138edbd859a591caedb95bcf4
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_39cf333bfd031134/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_relative_total_threshold\nWITH grouped AS (\n    SELECT \"feature_10\", SUM(CAST(\"feature_14\" AS REAL)) AS group_value\n    FROM \"n9\"\n    GROUP BY \"feature_10\"\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.\"feature_10\", g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * 0.05\nORDER BY g.group_value DESC;", "result": "{\"query\": \"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n    SELECT \\\"feature_10\\\", SUM(CAST(\\\"feature_14\\\" AS REAL)) AS group_value\\n    FROM \\\"n9\\\"\\n    GROUP BY \\\"feature_10\\\"\\n), total AS (\\n    SELECT SUM(group_value) AS total_value\\n    FROM grouped\\n)\\nSELECT g.\\\"feature_10\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.05\\nORDER BY g.group_value DESC;\", \"columns\": [\"feature_10\", \"group_value\"], \"rows\": [{\"feature_10\": \"0\", \"group_value\": 99579.0}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 9.66}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_39cf333bfd031134/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_39cf333bfd031134/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..72e14b7712f952e176a8bbdb320a9c844b8eef46
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_39cf333bfd031134/run_manifest.json
@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:48:34.360020+00:00",
+  "ended_at": "2026-05-19T15:48:46.642089+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_39cf333bfd031134",
+    "problem_id": "v2p_n9_33c289b5e959e2e7",
+    "dataset_id": "n9",
+    "template_id": "tpl_tpch_relative_total_threshold",
+    "template_name": "Relative-to-Total Extreme Threshold",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_mass_similarity",
+    "intended_facet_id": "tail_ranked_signal",
+    "variant_semantic_role": "count_distribution",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=feature_10, measure_col=feature_14.",
+    "bindings": {
+      "group_col": "feature_10",
+      "measure_col": "feature_14",
+      "top_k": 17,
+      "top_n": 5,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.05,
+      "baseline_multiplier": 1.75,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 4,
+      "measure_threshold": 36.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "WITH grouped AS (\n    SELECT {group_col}, SUM({measure_col}) AS group_value\n    FROM {table}\n    GROUP BY {group_col}\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;",
+    "notes": [
+      "default_facets=tail_ranked_signal",
+      "template_selection_mode=rule",
+      "problem_index_within_template=6",
+      "sql_variant_index=2/2",
+      "binding_index=77"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 7,
+    "problem_index_within_template": 6,
+    "sql_variant_index": 2,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_39cf333bfd031134.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_39cf333bfd031134",
+    "api_calls": 0,
+    "input_tokens": 15076,
+    "cached_input_tokens": 13696,
+    "output_tokens": 340,
+    "total_tokens": 15416,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 12267.41,
+    "sql_execution_elapsed_ms_total": 9.66,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_39cf333bfd031134/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_39cf333bfd031134/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_39cf333bfd031134/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..7ea673ed5f1a8136af2fe1db246048239a8890a6
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_39cf333bfd031134/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:48:46.630116+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 12267.41, "started_at": "2026-05-19T15:48:34.361311+00:00", "ended_at": "2026-05-19T15:48:46.628750+00:00", "prompt_metrics": {"chars": 9949, "bytes_utf8": 9949, "lines": 300, "estimated_tokens": null}, "response_metrics": {"chars": 658, "bytes_utf8": 658, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15076, "cached_input_tokens": 13696, "output_tokens": 340, "reasoning_output_tokens": 164}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n    SELECT \\\"feature_10\\\", SUM(CAST(\\\"feature_14\\\" AS REAL)) AS group_value\\n    FROM \\\"n9\\\"\\n    GROUP BY \\\"feature_10\\\"\\n), total AS (\\n    SELECT SUM(group_value) AS total_value\\n    FROM grouped\\n)\\nSELECT g.\\\"feature_10\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.05\\nORDER BY g.group_value DESC;\",\"notes\":\"Uses the required Relative-to-Total Extreme Threshold template with group_col=\\\"feature_10\\\", measure_col=\\\"feature_14\\\", and fraction_threshold=0.05. CAST is applied because the schema stores features as TEXT.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_39cf333bfd031134/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_39cf333bfd031134/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..f317cbeedce0105d601d1b7e4bd7c93b7f896838
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_39cf333bfd031134/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_39cf333bfd031134",
+  "api_calls": 0,
+  "input_tokens": 15076,
+  "cached_input_tokens": 13696,
+  "output_tokens": 340,
+  "total_tokens": 15416,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 12267.41,
+  "sql_execution_elapsed_ms_total": 9.66,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_39cf333bfd031134/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e5ea197b14f256d/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e5ea197b14f256d/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..06e4dd4ed158f9658f894bd286060149e190545a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e5ea197b14f256d/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=feature_6, measure_col=feature_6.
+Result preview: [{"feature_6": "100", "total_measure": 111500}, {"feature_6": "78", "total_measure": 16458}, {"feature_6": "79", "total_measure": 16195}, {"feature_6": "75", "total_measure": 15525}, {"feature_6": "76", "total_measure": 14668}] Results were truncated.
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e5ea197b14f256d/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e5ea197b14f256d/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..76dd15611683e27544aa5ad721dcb1b6901c74bc
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e5ea197b14f256d/generated_sql.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_conditional_contrast
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_n9_3e5ea197b14f256d
+-- problem_id: v2p_n9_6b3639abfed850a8
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_6", SUM(CAST("feature_6" AS NUMERIC)) AS total_measure
+FROM "n9"
+GROUP BY "feature_6"
+ORDER BY total_measure DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e5ea197b14f256d/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e5ea197b14f256d/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..8989eb82f17a0708cfd7a951ad3e8cff97828dcc
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e5ea197b14f256d/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_h2o_group_sum\nSELECT \"feature_6\", SUM(CAST(\"feature_6\" AS NUMERIC)) AS total_measure\nFROM \"n9\"\nGROUP BY \"feature_6\"\nORDER BY total_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"feature_6\\\", SUM(CAST(\\\"feature_6\\\" AS NUMERIC)) AS total_measure\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_6\\\"\\nORDER BY total_measure DESC;\", \"columns\": [\"feature_6\", \"total_measure\"], \"rows\": [{\"feature_6\": \"100\", \"total_measure\": 111500}, {\"feature_6\": \"78\", \"total_measure\": 16458}, {\"feature_6\": \"79\", \"total_measure\": 16195}, {\"feature_6\": \"75\", \"total_measure\": 15525}, {\"feature_6\": \"76\", \"total_measure\": 14668}, {\"feature_6\": \"72\", \"total_measure\": 14400}, {\"feature_6\": \"82\", \"total_measure\": 14268}, {\"feature_6\": \"77\", \"total_measure\": 14168}, {\"feature_6\": \"83\", \"total_measure\": 14110}, {\"feature_6\": \"80\", \"total_measure\": 14080}, {\"feature_6\": \"81\", \"total_measure\": 13689}, {\"feature_6\": \"99\", \"total_measure\": 13563}, {\"feature_6\": \"74\", \"total_measure\": 13542}, {\"feature_6\": \"88\", \"total_measure\": 13288}, {\"feature_6\": \"73\", \"total_measure\": 13140}, {\"feature_6\": \"98\", \"total_measure\": 12642}, {\"feature_6\": \"71\", \"total_measure\": 12496}, {\"feature_6\": \"70\", \"total_measure\": 12460}, {\"feature_6\": \"94\", \"total_measure\": 12408}, {\"feature_6\": \"97\", \"total_measure\": 12319}, {\"feature_6\": \"91\", \"total_measure\": 12194}, {\"feature_6\": \"85\", \"total_measure\": 11900}, {\"feature_6\": \"95\", \"total_measure\": 11875}, {\"feature_6\": \"68\", \"total_measure\": 11764}, {\"feature_6\": \"67\", \"total_measure\": 11390}, {\"feature_6\": \"87\", \"total_measure\": 11310}, {\"feature_6\": \"69\", \"total_measure\": 11247}, {\"feature_6\": \"84\", \"total_measure\": 11088}, {\"feature_6\": \"89\", \"total_measure\": 10947}, {\"feature_6\": \"86\", \"total_measure\": 10922}, {\"feature_6\": \"96\", \"total_measure\": 10560}, {\"feature_6\": \"90\", \"total_measure\": 9990}, {\"feature_6\": \"93\", \"total_measure\": 9951}, {\"feature_6\": \"92\", \"total_measure\": 9660}, {\"feature_6\": \"66\", \"total_measure\": 9438}, {\"feature_6\": \"65\", \"total_measure\": 9100}, {\"feature_6\": \"62\", \"total_measure\": 7440}, {\"feature_6\": \"63\", \"total_measure\": 7308}, {\"feature_6\": \"59\", \"total_measure\": 7257}, {\"feature_6\": \"60\", \"total_measure\": 7200}, {\"feature_6\": \"61\", \"total_measure\": 7076}, {\"feature_6\": \"64\", \"total_measure\": 6848}, {\"feature_6\": \"58\", \"total_measure\": 6670}, {\"feature_6\": \"52\", \"total_measure\": 6396}, {\"feature_6\": \"55\", \"total_measure\": 6325}, {\"feature_6\": \"56\", \"total_measure\": 6216}, {\"feature_6\": \"57\", \"total_measure\": 6156}, {\"feature_6\": \"53\", \"total_measure\": 5777}, {\"feature_6\": \"49\", \"total_measure\": 5733}, {\"feature_6\": \"50\", \"total_measure\": 5250}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 10.89}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e5ea197b14f256d/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e5ea197b14f256d/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..d41d6f5319d62f6f0a7bb82a98909681fd5cb1a1
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e5ea197b14f256d/run_manifest.json
@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:30:12.446077+00:00",
+  "ended_at": "2026-05-19T15:30:24.366914+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_3e5ea197b14f256d",
+    "problem_id": "v2p_n9_6b3639abfed850a8",
+    "dataset_id": "n9",
+    "template_id": "tpl_h2o_group_sum",
+    "template_name": "Grouped Numeric Sum",
+    "family_id": "subgroup_structure",
+    "canonical_subitem_id": "internal_profile_stability",
+    "intended_facet_id": "subgroup_conditional_contrast",
+    "variant_semantic_role": "collapsed_target_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=feature_6, measure_col=feature_6.",
+    "bindings": {
+      "group_col": "feature_6",
+      "measure_col": "feature_6",
+      "top_k": 10,
+      "top_n": 4,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 86.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;",
+    "notes": [
+      "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast",
+      "template_selection_mode=rule",
+      "problem_index_within_template=6",
+      "sql_variant_index=1/2",
+      "binding_index=5"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 1,
+    "problem_index_within_template": 6,
+    "sql_variant_index": 1,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_3e5ea197b14f256d.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_3e5ea197b14f256d",
+    "api_calls": 0,
+    "input_tokens": 14940,
+    "cached_input_tokens": 12032,
+    "output_tokens": 244,
+    "total_tokens": 15184,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 11904.66,
+    "sql_execution_elapsed_ms_total": 10.89,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e5ea197b14f256d/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e5ea197b14f256d/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e5ea197b14f256d/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..235d4492d690031e7f46b68060634c40cb00e668
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e5ea197b14f256d/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:30:24.353400+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 11904.66, "started_at": "2026-05-19T15:30:12.447278+00:00", "ended_at": "2026-05-19T15:30:24.351967+00:00", "prompt_metrics": {"chars": 9388, "bytes_utf8": 9388, "lines": 300, "estimated_tokens": null}, "response_metrics": {"chars": 370, "bytes_utf8": 370, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14940, "cached_input_tokens": 12032, "output_tokens": 244, "reasoning_output_tokens": 143}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"feature_6\\\", SUM(CAST(\\\"feature_6\\\" AS NUMERIC)) AS total_measure\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_6\\\"\\nORDER BY total_measure DESC;\",\"notes\":\"Applied the provided Grouped Numeric Sum template with group_col and measure_col both bound to \\\"feature_6\\\". CAST is used because the schema stores feature columns as TEXT.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e5ea197b14f256d/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e5ea197b14f256d/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..0db349f10efbe3c0d8dee5566a8adcdc8f578f11
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e5ea197b14f256d/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_3e5ea197b14f256d",
+  "api_calls": 0,
+  "input_tokens": 14940,
+  "cached_input_tokens": 12032,
+  "output_tokens": 244,
+  "total_tokens": 15184,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 11904.66,
+  "sql_execution_elapsed_ms_total": 10.89,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e5ea197b14f256d/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e7e9ca7687ee50b/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e7e9ca7687ee50b/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..963c3cd5d32823a8b83c7a9c2637bd4bd40845dd
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e7e9ca7687ee50b/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=feature_14, measure_col=feature_15.
+Result preview: [{"feature_14": "89", "feature_16": "100", "total_measure": 2166.0, "share_within_group": 85.47750591949487}, {"feature_14": "98", "feature_16": "100", "total_measure": 4194.0, "share_within_group": 84.45428916633105}, {"feature_14": "87", "feature_16": "100", "total_measure": 1706.0, "share_within_group": 84.37190900098912}, {"feature_14": "91", "feature_16": "100", "total_measure": 3260.0, "share_within_group": 83.07849133537206}, {"feature_14": "70", "feature_16": "100", "total_measure": 656.0, "share_within_group": 82.9329962073325}] Results were truncated.
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e7e9ca7687ee50b/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e7e9ca7687ee50b/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..9467da14ada137c6ba4de5f85e79a2ee1d718529
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e7e9ca7687ee50b/generated_sql.sql
@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: within_group_proportion
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_3e7e9ca7687ee50b
+-- problem_id: v2p_n9_8f10f270ae73308c
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+  "feature_14",
+  "feature_16",
+  SUM(CAST("feature_15" AS REAL)) AS total_measure,
+  SUM(CAST("feature_15" AS REAL)) * 100.0 / SUM(SUM(CAST("feature_15" AS REAL))) OVER (PARTITION BY "feature_14") AS share_within_group
+FROM "n9"
+GROUP BY "feature_14", "feature_16"
+ORDER BY share_within_group DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e7e9ca7687ee50b/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e7e9ca7687ee50b/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..91fb831520afe725fa17df0d1e2c72404378d8ae
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e7e9ca7687ee50b/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT\n  \"feature_14\",\n  \"feature_16\",\n  SUM(CAST(\"feature_15\" AS REAL)) AS total_measure,\n  SUM(CAST(\"feature_15\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"feature_15\" AS REAL))) OVER (PARTITION BY \"feature_14\") AS share_within_group\nFROM \"n9\"\nGROUP BY \"feature_14\", \"feature_16\"\nORDER BY share_within_group DESC;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n  \\\"feature_14\\\",\\n  \\\"feature_16\\\",\\n  SUM(CAST(\\\"feature_15\\\" AS REAL)) AS total_measure,\\n  SUM(CAST(\\\"feature_15\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"feature_15\\\" AS REAL))) OVER (PARTITION BY \\\"feature_14\\\") AS share_within_group\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_14\\\", \\\"feature_16\\\"\\nORDER BY share_within_group DESC;\", \"columns\": [\"feature_14\", \"feature_16\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"feature_14\": \"89\", \"feature_16\": \"100\", \"total_measure\": 2166.0, \"share_within_group\": 85.47750591949487}, {\"feature_14\": \"98\", \"feature_16\": \"100\", \"total_measure\": 4194.0, \"share_within_group\": 84.45428916633105}, {\"feature_14\": \"87\", \"feature_16\": \"100\", \"total_measure\": 1706.0, \"share_within_group\": 84.37190900098912}, {\"feature_14\": \"91\", \"feature_16\": \"100\", \"total_measure\": 3260.0, \"share_within_group\": 83.07849133537206}, {\"feature_14\": \"70\", \"feature_16\": \"100\", \"total_measure\": 656.0, \"share_within_group\": 82.9329962073325}, {\"feature_14\": \"25\", \"feature_16\": \"0\", \"total_measure\": 11168.0, \"share_within_group\": 80.45529860961025}, {\"feature_14\": \"86\", \"feature_16\": \"100\", \"total_measure\": 1565.0, \"share_within_group\": 80.1331285202253}, {\"feature_14\": \"88\", \"feature_16\": \"100\", \"total_measure\": 2189.0, \"share_within_group\": 79.65793304221252}, {\"feature_14\": \"93\", \"feature_16\": \"100\", \"total_measure\": 3463.0, \"share_within_group\": 79.3174530462666}, {\"feature_14\": \"92\", \"feature_16\": \"100\", \"total_measure\": 2777.0, \"share_within_group\": 77.700055959709}, {\"feature_14\": \"24\", \"feature_16\": \"0\", \"total_measure\": 9258.0, \"share_within_group\": 77.40155505392525}, {\"feature_14\": \"94\", \"feature_16\": \"100\", \"total_measure\": 4442.0, \"share_within_group\": 77.40024394493814}, {\"feature_14\": \"26\", \"feature_16\": \"0\", \"total_measure\": 7176.0, \"share_within_group\": 76.92142780576697}, {\"feature_14\": \"97\", \"feature_16\": \"100\", \"total_measure\": 3511.0, \"share_within_group\": 76.6593886462882}, {\"feature_14\": \"23\", \"feature_16\": \"0\", \"total_measure\": 6816.0, \"share_within_group\": 76.4382639901312}, {\"feature_14\": \"99\", \"feature_16\": \"100\", \"total_measure\": 3630.0, \"share_within_group\": 76.30859785579146}, {\"feature_14\": \"96\", \"feature_16\": \"100\", \"total_measure\": 3966.0, \"share_within_group\": 76.13745440583605}, {\"feature_14\": \"11\", \"feature_16\": \"0\", \"total_measure\": 2222.0, \"share_within_group\": 75.70698466780239}, {\"feature_14\": \"21\", \"feature_16\": \"0\", \"total_measure\": 4030.0, \"share_within_group\": 75.46816479400749}, {\"feature_14\": \"95\", \"feature_16\": \"100\", \"total_measure\": 4386.0, \"share_within_group\": 74.87196995561625}, {\"feature_14\": \"22\", \"feature_16\": \"0\", \"total_measure\": 5007.0, \"share_within_group\": 74.05709214613223}, {\"feature_14\": \"20\", \"feature_16\": \"0\", \"total_measure\": 3702.0, \"share_within_group\": 73.75971309025702}, {\"feature_14\": \"90\", \"feature_16\": \"100\", \"total_measure\": 2257.0, \"share_within_group\": 70.86342229199371}, {\"feature_14\": \"9\", \"feature_16\": \"0\", \"total_measure\": 3139.0, \"share_within_group\": 69.64721544264478}, {\"feature_14\": \"19\", \"feature_16\": \"0\", \"total_measure\": 3035.0, \"share_within_group\": 68.34046385949111}, {\"feature_14\": \"15\", \"feature_16\": \"0\", \"total_measure\": 1869.0, \"share_within_group\": 68.08743169398907}, {\"feature_14\": \"17\", \"feature_16\": \"0\", \"total_measure\": 2303.0, \"share_within_group\": 66.23526028185218}, {\"feature_14\": \"13\", \"feature_16\": \"0\", \"total_measure\": 2106.0, \"share_within_group\": 65.70982839313572}, {\"feature_14\": \"16\", \"feature_16\": \"0\", \"total_measure\": 1954.0, \"share_within_group\": 64.85230667109194}, {\"feature_14\": \"30\", \"feature_16\": \"0\", \"total_measure\": 6370.0, \"share_within_group\": 64.70946769605851}, {\"feature_14\": \"18\", \"feature_16\": \"0\", \"total_measure\": 2531.0, \"share_within_group\": 64.50050968399593}, {\"feature_14\": \"84\", \"feature_16\": \"100\", \"total_measure\": 965.0, \"share_within_group\": 64.07702523240371}, {\"feature_14\": \"12\", \"feature_16\": \"0\", \"total_measure\": 1599.0, \"share_within_group\": 62.755102040816325}, {\"feature_14\": \"29\", \"feature_16\": \"0\", \"total_measure\": 5944.0, \"share_within_group\": 62.733509234828496}, {\"feature_14\": \"32\", \"feature_16\": \"0\", \"total_measure\": 7925.0, \"share_within_group\": 62.09841717599122}, {\"feature_14\": \"28\", \"feature_16\": \"0\", \"total_measure\": 6454.0, \"share_within_group\": 62.00999231360492}, {\"feature_14\": \"1\", \"feature_16\": \"0\", \"total_measure\": 9375.0, \"share_within_group\": 61.48347324239244}, {\"feature_14\": \"31\", \"feature_16\": \"0\", \"total_measure\": 5766.0, \"share_within_group\": 59.856742447835565}, {\"feature_14\": \"6\", \"feature_16\": \"0\", \"total_measure\": 4046.0, \"share_within_group\": 59.21264451924484}, {\"feature_14\": \"14\", \"feature_16\": \"0\", \"total_measure\": 2322.0, \"share_within_group\": 59.038901601830666}, {\"feature_14\": \"27\", \"feature_16\": \"0\", \"total_measure\": 6350.0, \"share_within_group\": 57.14028615135427}, {\"feature_14\": \"83\", \"feature_16\": \"100\", \"total_measure\": 701.0, \"share_within_group\": 56.89935064935065}, {\"feature_14\": \"8\", \"feature_16\": \"0\", \"total_measure\": 3223.0, \"share_within_group\": 55.945148411734074}, {\"feature_14\": \"33\", \"feature_16\": \"0\", \"total_measure\": 4907.0, \"share_within_group\": 55.837505689576695}, {\"feature_14\": \"7\", \"feature_16\": \"0\", \"total_measure\": 3943.0, \"share_within_group\": 55.1006148686417}, {\"feature_14\": \"10\", \"feature_16\": \"0\", \"total_measure\": 2134.0, \"share_within_group\": 54.57800511508952}, {\"feature_14\": \"75\", \"feature_16\": \"100\", \"total_measure\": 396.0, \"share_within_group\": 54.24657534246575}, {\"feature_14\": \"79\", \"feature_16\": \"100\", \"total_measure\": 614.0, \"share_within_group\": 54.001759014951624}, {\"feature_14\": \"5\", \"feature_16\": \"0\", \"total_measure\": 4779.0, \"share_within_group\": 51.28232642987445}, {\"feature_14\": \"34\", \"feature_16\": \"0\", \"total_measure\": 6102.0, \"share_within_group\": 51.15265319808869}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 32.4}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e7e9ca7687ee50b/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e7e9ca7687ee50b/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..656e968cc0dfffecf491b4c98bc00c18bcaa175c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e7e9ca7687ee50b/run_manifest.json
@@ -0,0 +1,91 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:37:18.580732+00:00",
+  "ended_at": "2026-05-19T15:37:32.733849+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_3e7e9ca7687ee50b",
+    "problem_id": "v2p_n9_8f10f270ae73308c",
+    "dataset_id": "n9",
+    "template_id": "tpl_tpcds_within_group_share",
+    "template_name": "Within-Group Share of Total",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "dependency_strength_similarity",
+    "intended_facet_id": "pairwise_conditional_dependency",
+    "variant_semantic_role": "within_group_proportion",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=feature_14, measure_col=feature_15.",
+    "bindings": {
+      "group_col": "feature_14",
+      "measure_col": "feature_15",
+      "item_col": "feature_16",
+      "top_k": 10,
+      "top_n": 5,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 100.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "item_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;",
+    "notes": [
+      "default_facets=pairwise_conditional_dependency",
+      "template_selection_mode=rule",
+      "problem_index_within_template=7",
+      "sql_variant_index=1/2",
+      "binding_index=30"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 3,
+    "problem_index_within_template": 7,
+    "sql_variant_index": 1,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_3e7e9ca7687ee50b.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_3e7e9ca7687ee50b",
+    "api_calls": 0,
+    "input_tokens": 15060,
+    "cached_input_tokens": 12032,
+    "output_tokens": 696,
+    "total_tokens": 15756,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 14112.47,
+    "sql_execution_elapsed_ms_total": 32.4,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e7e9ca7687ee50b/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e7e9ca7687ee50b/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e7e9ca7687ee50b/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..d1e01b1824cdd3bc08032381fa3db1d9078b86b4
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e7e9ca7687ee50b/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:37:32.698122+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 14112.47, "started_at": "2026-05-19T15:37:18.583931+00:00", "ended_at": "2026-05-19T15:37:32.696445+00:00", "prompt_metrics": {"chars": 9806, "bytes_utf8": 9806, "lines": 302, "estimated_tokens": null}, "response_metrics": {"chars": 603, "bytes_utf8": 603, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15060, "cached_input_tokens": 12032, "output_tokens": 696, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n  \\\"feature_14\\\",\\n  \\\"feature_16\\\",\\n  SUM(CAST(\\\"feature_15\\\" AS REAL)) AS total_measure,\\n  SUM(CAST(\\\"feature_15\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"feature_15\\\" AS REAL))) OVER (PARTITION BY \\\"feature_14\\\") AS share_within_group\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_14\\\", \\\"feature_16\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Applied the Within-Group Share of Total template with group_col=\\\"feature_14\\\", item_col=\\\"feature_16\\\", and measure_col=\\\"feature_15\\\". CAST to REAL is used because the schema stores these fields as TEXT.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e7e9ca7687ee50b/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e7e9ca7687ee50b/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..ea8ed8e9524f8ec64db35327a3d6ea6a8673a696
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e7e9ca7687ee50b/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_3e7e9ca7687ee50b",
+  "api_calls": 0,
+  "input_tokens": 15060,
+  "cached_input_tokens": 12032,
+  "output_tokens": 696,
+  "total_tokens": 15756,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 14112.47,
+  "sql_execution_elapsed_ms_total": 32.4,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_3e7e9ca7687ee50b/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_412e5289d0794c43/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_412e5289d0794c43/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..d923a7a4cad66be8f7499623f3cbd9081e9f9116
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_412e5289d0794c43/final_answer.txt
@@ -0,0 +1 @@
+{"row_count": null, "preview_rows": [{"value_label": "0", "support": 1227, "support_share": 0.11162663755458516, "cumulative_support": 1227}, {"value_label": "50", "support": 224, "support_share": 0.020378457059679767, "cumulative_support": 1451}, {"value_label": "100", "support": 192, "support_share": 0.017467248908296942, "cumulative_support": 1643}, {"value_label": "16", "support": 191, "support_share": 0.01737627365356623, "cumulative_support": 1834}, {"value_label": "15", "support": 182, "support_share": 0.016557496360989812, "cumulative_support": 2016}]}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_412e5289d0794c43/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_412e5289d0794c43/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..5ec9e94accb0c44930f22265294286cca8b8f7fe
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_412e5289d0794c43/generated_sql.sql
@@ -0,0 +1,28 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: support_concentration
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_cardinality_distinct_share_profile
+-- query_record_id: v2q_n9_412e5289d0794c43
+-- problem_id: v2p_n9_855c65ff05382b46
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_12" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_12"
+), ranked AS (
+    SELECT
+        value_label,
+        support,
+        CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+        SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support
+    FROM grouped
+)
+SELECT *
+FROM ranked
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_412e5289d0794c43/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_412e5289d0794c43/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..1f3e617c72a2ed7626398a336dfb685ac37a56fd
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_412e5289d0794c43/query_results.jsonl
@@ -0,0 +1 @@
+{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: n9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: support_rank_profile_consistency\n-- intended_facet_id: support_concentration\n-- variant_semantic_role: ranked_signal_view\n-- template_id: tpl_cardinality_distinct_share_profile\n-- query_record_id: v2q_n9_412e5289d0794c43\n-- problem_id: v2p_n9_855c65ff05382b46\n-- realization_mode: deterministic\n-- source_kind: deterministic\nWITH grouped AS (\n    SELECT \"feature_12\" AS value_label, COUNT(*) AS support\n    FROM \"n9\"\n    GROUP BY \"feature_12\"\n), ranked AS (\n    SELECT\n        value_label,\n        support,\n        CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n        SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\n    FROM grouped\n)\nSELECT *\nFROM ranked\nORDER BY support DESC, value_label;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: n9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: support_rank_profile_consistency\\n-- intended_facet_id: support_concentration\\n-- variant_semantic_role: ranked_signal_view\\n-- template_id: tpl_cardinality_distinct_share_profile\\n-- query_record_id: v2q_n9_412e5289d0794c43\\n-- problem_id: v2p_n9_855c65ff05382b46\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nWITH grouped AS (\\n    SELECT \\\"feature_12\\\" AS value_label, COUNT(*) AS support\\n    FROM \\\"n9\\\"\\n    GROUP BY \\\"feature_12\\\"\\n), ranked AS (\\n    SELECT\\n        value_label,\\n        support,\\n        CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\\n        SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\\n    FROM grouped\\n)\\nSELECT *\\nFROM ranked\\nORDER BY support DESC, value_label;\", \"columns\": [\"value_label\", \"support\", \"support_share\", \"cumulative_support\"], \"rows\": [{\"value_label\": \"0\", \"support\": 1227, \"support_share\": 0.11162663755458516, \"cumulative_support\": 1227}, {\"value_label\": \"50\", \"support\": 224, \"support_share\": 0.020378457059679767, \"cumulative_support\": 1451}, {\"value_label\": \"100\", \"support\": 192, \"support_share\": 0.017467248908296942, \"cumulative_support\": 1643}, {\"value_label\": \"16\", \"support\": 191, \"support_share\": 0.01737627365356623, \"cumulative_support\": 1834}, {\"value_label\": \"15\", \"support\": 182, \"support_share\": 0.016557496360989812, \"cumulative_support\": 2016}, {\"value_label\": \"9\", \"support\": 168, \"support_share\": 0.015283842794759825, \"cumulative_support\": 2184}, {\"value_label\": \"18\", \"support\": 167, \"support_share\": 0.015192867540029112, \"cumulative_support\": 2351}, {\"value_label\": \"12\", \"support\": 161, \"support_share\": 0.014647016011644833, \"cumulative_support\": 2512}, {\"value_label\": \"17\", \"support\": 161, \"support_share\": 0.014647016011644833, \"cumulative_support\": 2673}, {\"value_label\": \"20\", \"support\": 156, \"support_share\": 0.014192139737991267, \"cumulative_support\": 2829}, {\"value_label\": \"19\", \"support\": 155, \"support_share\": 0.014101164483260552, \"cumulative_support\": 2984}, {\"value_label\": \"14\", \"support\": 154, \"support_share\": 0.01401018922852984, \"cumulative_support\": 3138}, {\"value_label\": \"8\", \"support\": 154, \"support_share\": 0.01401018922852984, \"cumulative_support\": 3292}, {\"value_label\": \"10\", \"support\": 153, \"support_share\": 0.013919213973799126, \"cumulative_support\": 3445}, {\"value_label\": \"51\", \"support\": 152, \"support_share\": 0.013828238719068414, \"cumulative_support\": 3597}, {\"value_label\": \"1\", \"support\": 149, \"support_share\": 0.013555312954876273, \"cumulative_support\": 3746}, {\"value_label\": \"13\", \"support\": 147, \"support_share\": 0.013373362445414847, \"cumulative_support\": 3893}, {\"value_label\": \"21\", \"support\": 147, \"support_share\": 0.013373362445414847, \"cumulative_support\": 4040}, {\"value_label\": \"11\", \"support\": 145, \"support_share\": 0.01319141193595342, \"cumulative_support\": 4185}, {\"value_label\": \"22\", \"support\": 138, \"support_share\": 0.012554585152838428, \"cumulative_support\": 4323}, {\"value_label\": \"24\", \"support\": 138, \"support_share\": 0.012554585152838428, \"cumulative_support\": 4461}, {\"value_label\": \"23\", \"support\": 137, \"support_share\": 0.012463609898107715, \"cumulative_support\": 4598}, {\"value_label\": \"30\", \"support\": 135, \"support_share\": 0.012281659388646287, \"cumulative_support\": 4733}, {\"value_label\": \"49\", \"support\": 135, \"support_share\": 0.012281659388646287, \"cumulative_support\": 4868}, {\"value_label\": \"29\", \"support\": 130, \"support_share\": 0.011826783114992722, \"cumulative_support\": 4998}, {\"value_label\": \"31\", \"support\": 130, \"support_share\": 0.011826783114992722, \"cumulative_support\": 5128}, {\"value_label\": \"6\", \"support\": 130, \"support_share\": 0.011826783114992722, \"cumulative_support\": 5258}, {\"value_label\": \"7\", \"support\": 128, \"support_share\": 0.011644832605531296, \"cumulative_support\": 5386}, {\"value_label\": \"3\", \"support\": 127, \"support_share\": 0.011553857350800582, \"cumulative_support\": 5513}, {\"value_label\": \"4\", \"support\": 126, \"support_share\": 0.01146288209606987, \"cumulative_support\": 5639}, {\"value_label\": \"5\", \"support\": 126, \"support_share\": 0.01146288209606987, \"cumulative_support\": 5765}, {\"value_label\": \"53\", \"support\": 125, \"support_share\": 0.011371906841339156, \"cumulative_support\": 5890}, {\"value_label\": \"2\", \"support\": 121, \"support_share\": 0.011008005822416303, \"cumulative_support\": 6011}, {\"value_label\": \"26\", \"support\": 121, \"support_share\": 0.011008005822416303, \"cumulative_support\": 6132}, {\"value_label\": \"25\", \"support\": 120, \"support_share\": 0.010917030567685589, \"cumulative_support\": 6252}, {\"value_label\": \"46\", \"support\": 120, \"support_share\": 0.010917030567685589, \"cumulative_support\": 6372}, {\"value_label\": \"32\", \"support\": 119, \"support_share\": 0.010826055312954877, \"cumulative_support\": 6491}, {\"value_label\": \"27\", \"support\": 117, \"support_share\": 0.01064410480349345, \"cumulative_support\": 6608}, {\"value_label\": \"28\", \"support\": 117, \"support_share\": 0.01064410480349345, \"cumulative_support\": 6725}, {\"value_label\": \"64\", \"support\": 115, \"support_share\": 0.010462154294032024, \"cumulative_support\": 6840}, {\"value_label\": \"66\", \"support\": 115, \"support_share\": 0.010462154294032024, \"cumulative_support\": 6955}, {\"value_label\": \"56\", \"support\": 113, \"support_share\": 0.010280203784570598, \"cumulative_support\": 7068}, {\"value_label\": \"33\", \"support\": 110, \"support_share\": 0.010007278020378457, \"cumulative_support\": 7178}, {\"value_label\": \"45\", \"support\": 108, \"support_share\": 0.009825327510917031, \"cumulative_support\": 7286}, {\"value_label\": \"68\", \"support\": 107, \"support_share\": 0.009734352256186317, \"cumulative_support\": 7393}, {\"value_label\": \"65\", \"support\": 104, \"support_share\": 0.009461426491994178, \"cumulative_support\": 7497}, {\"value_label\": \"43\", \"support\": 103, \"support_share\": 0.009370451237263464, \"cumulative_support\": 7600}, {\"value_label\": \"54\", \"support\": 103, \"support_share\": 0.009370451237263464, \"cumulative_support\": 7703}, {\"value_label\": \"60\", \"support\": 103, \"support_share\": 0.009370451237263464, \"cumulative_support\": 7806}, {\"value_label\": \"62\", \"support\": 103, \"support_share\": 0.009370451237263464, \"cumulative_support\": 7909}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 4.69}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_412e5289d0794c43/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_412e5289d0794c43/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..adbe0a0fad86de8bc028ccfd9790bb35678173b2
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_412e5289d0794c43/run_manifest.json
@@ -0,0 +1,57 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T16:10:15.759669+00:00",
+  "ended_at": "2026-05-19T16:10:15.765174+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_412e5289d0794c43",
+    "problem_id": "v2p_n9_855c65ff05382b46",
+    "dataset_id": "n9",
+    "template_id": "tpl_cardinality_distinct_share_profile",
+    "template_name": "Cardinality Distinct Share Profile",
+    "family_id": "cardinality_structure",
+    "canonical_subitem_id": "support_rank_profile_consistency",
+    "intended_facet_id": "support_concentration",
+    "variant_semantic_role": "ranked_signal_view",
+    "subitem_assignment_source": "template_fixed",
+    "source_kind": "deterministic",
+    "realization_mode": "deterministic",
+    "gate_priority": "deterministic",
+    "extended_family": true,
+    "question": "Use template Cardinality Distinct Share Profile to probe support_rank_profile_consistency with semantic role ranked_signal_view. Focus on group_col=feature_12.",
+    "bindings": {
+      "group_col": "feature_12"
+    },
+    "binding_roles": [
+      "group_col"
+    ],
+    "coverage_target_min": "enumerate_all_applicable",
+    "runtime_sql_skeleton": "WITH grouped AS (\n    SELECT {group_col} AS value_label, COUNT(*) AS support\n    FROM {table}\n    GROUP BY {group_col}\n), ranked AS (\n    SELECT\n        value_label,\n        support,\n        CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n        SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\n    FROM grouped\n)\nSELECT *\nFROM ranked\nORDER BY support DESC, value_label;",
+    "notes": [
+      "default_facets=support_concentration,value_imbalance_profile",
+      "template_selection_mode=deterministic",
+      "problem_index_within_template=9",
+      "sql_variant_index=1/1"
+    ],
+    "template_selection_mode": "deterministic",
+    "selected_template_rank": 0,
+    "problem_index_within_template": 9,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_412e5289d0794c43.sql",
+  "usage_summary": {
+    "engine": "template",
+    "input_tokens": 0,
+    "cached_input_tokens": 0,
+    "output_tokens": 0,
+    "total_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "none"
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_412e5289d0794c43/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_412e5289d0794c43/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_412e5289d0794c43/usage_summary.json
@@ -0,0 +1,9 @@
+{
+  "engine": "template",
+  "input_tokens": 0,
+  "cached_input_tokens": 0,
+  "output_tokens": 0,
+  "total_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "none"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_49e2f541fc7596a2/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_49e2f541fc7596a2/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..bdf9470dc1d24c93d0c38850157572fbe33a2182
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_49e2f541fc7596a2/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=feature_13.
+Result preview: [{"feature_13": "100", "row_count": 509}, {"feature_13": "50", "row_count": 443}, {"feature_13": "51", "row_count": 313}, {"feature_13": "49", "row_count": 298}, {"feature_13": "53", "row_count": 256}] Results were truncated.
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_49e2f541fc7596a2/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_49e2f541fc7596a2/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..dd7d9cca2728f41ef1afe3ff66abe0a142c2ec41
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_49e2f541fc7596a2/generated_sql.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: subgroup_size_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_clickbench_group_count
+-- query_record_id: v2q_n9_49e2f541fc7596a2
+-- problem_id: v2p_n9_636f98d40bd047c2
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_13", COUNT(*) AS row_count
+FROM "n9"
+GROUP BY "feature_13"
+ORDER BY row_count DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_49e2f541fc7596a2/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_49e2f541fc7596a2/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..3f5bffce3f21d75b1c06845b86759c2cd226ae9e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_49e2f541fc7596a2/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_clickbench_group_count\nSELECT \"feature_13\", COUNT(*) AS row_count\nFROM \"n9\"\nGROUP BY \"feature_13\"\nORDER BY row_count DESC;", "result": "{\"query\": \"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"feature_13\\\", COUNT(*) AS row_count\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_13\\\"\\nORDER BY row_count DESC;\", \"columns\": [\"feature_13\", \"row_count\"], \"rows\": [{\"feature_13\": \"100\", \"row_count\": 509}, {\"feature_13\": \"50\", \"row_count\": 443}, {\"feature_13\": \"51\", \"row_count\": 313}, {\"feature_13\": \"49\", \"row_count\": 298}, {\"feature_13\": \"53\", \"row_count\": 256}, {\"feature_13\": \"52\", \"row_count\": 255}, {\"feature_13\": \"48\", \"row_count\": 250}, {\"feature_13\": \"55\", \"row_count\": 225}, {\"feature_13\": \"46\", \"row_count\": 218}, {\"feature_13\": \"56\", \"row_count\": 217}, {\"feature_13\": \"54\", \"row_count\": 209}, {\"feature_13\": \"60\", \"row_count\": 208}, {\"feature_13\": \"58\", \"row_count\": 205}, {\"feature_13\": \"45\", \"row_count\": 205}, {\"feature_13\": \"62\", \"row_count\": 200}, {\"feature_13\": \"57\", \"row_count\": 199}, {\"feature_13\": \"47\", \"row_count\": 192}, {\"feature_13\": \"41\", \"row_count\": 192}, {\"feature_13\": \"0\", \"row_count\": 186}, {\"feature_13\": \"43\", \"row_count\": 184}, {\"feature_13\": \"42\", \"row_count\": 182}, {\"feature_13\": \"44\", \"row_count\": 181}, {\"feature_13\": \"61\", \"row_count\": 171}, {\"feature_13\": \"38\", \"row_count\": 161}, {\"feature_13\": \"40\", \"row_count\": 157}, {\"feature_13\": \"59\", \"row_count\": 155}, {\"feature_13\": \"37\", \"row_count\": 150}, {\"feature_13\": \"64\", \"row_count\": 141}, {\"feature_13\": \"63\", \"row_count\": 139}, {\"feature_13\": \"65\", \"row_count\": 138}, {\"feature_13\": \"39\", \"row_count\": 136}, {\"feature_13\": \"68\", \"row_count\": 133}, {\"feature_13\": \"66\", \"row_count\": 133}, {\"feature_13\": \"36\", \"row_count\": 129}, {\"feature_13\": \"67\", \"row_count\": 124}, {\"feature_13\": \"35\", \"row_count\": 122}, {\"feature_13\": \"70\", \"row_count\": 115}, {\"feature_13\": \"69\", \"row_count\": 105}, {\"feature_13\": \"76\", \"row_count\": 101}, {\"feature_13\": \"34\", \"row_count\": 101}, {\"feature_13\": \"32\", \"row_count\": 100}, {\"feature_13\": \"80\", \"row_count\": 97}, {\"feature_13\": \"33\", \"row_count\": 96}, {\"feature_13\": \"78\", \"row_count\": 93}, {\"feature_13\": \"75\", \"row_count\": 92}, {\"feature_13\": \"73\", \"row_count\": 90}, {\"feature_13\": \"74\", \"row_count\": 89}, {\"feature_13\": \"29\", \"row_count\": 87}, {\"feature_13\": \"84\", \"row_count\": 86}, {\"feature_13\": \"71\", \"row_count\": 82}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 4.81}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_49e2f541fc7596a2/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_49e2f541fc7596a2/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..de9fda2de19bdb1b8c83930ae219ea90fb6e9d69
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_49e2f541fc7596a2/run_manifest.json
@@ -0,0 +1,87 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:31:55.867057+00:00",
+  "ended_at": "2026-05-19T15:32:13.728648+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_49e2f541fc7596a2",
+    "problem_id": "v2p_n9_636f98d40bd047c2",
+    "dataset_id": "n9",
+    "template_id": "tpl_clickbench_group_count",
+    "template_name": "Grouped Count by Category",
+    "family_id": "subgroup_structure",
+    "canonical_subitem_id": "subgroup_size_stability",
+    "intended_facet_id": "subgroup_distribution_shift",
+    "variant_semantic_role": "count_distribution",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=feature_13.",
+    "bindings": {
+      "group_col": "feature_13",
+      "top_k": 12,
+      "top_n": 3,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 68.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;",
+    "notes": [
+      "default_facets=subgroup_distribution_shift",
+      "template_selection_mode=rule",
+      "problem_index_within_template=1",
+      "sql_variant_index=1/1",
+      "binding_index=12"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 2,
+    "problem_index_within_template": 1,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_49e2f541fc7596a2.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_49e2f541fc7596a2",
+    "api_calls": 0,
+    "input_tokens": 14911,
+    "cached_input_tokens": 13696,
+    "output_tokens": 202,
+    "total_tokens": 15113,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 17852.24,
+    "sql_execution_elapsed_ms_total": 4.81,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_49e2f541fc7596a2/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_49e2f541fc7596a2/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_49e2f541fc7596a2/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..a42e980f638f94d00c623b42b3d687fa6b027a2b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_49e2f541fc7596a2/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:32:13.722481+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 17852.24, "started_at": "2026-05-19T15:31:55.869458+00:00", "ended_at": "2026-05-19T15:32:13.721729+00:00", "prompt_metrics": {"chars": 9299, "bytes_utf8": 9299, "lines": 298, "estimated_tokens": null}, "response_metrics": {"chars": 279, "bytes_utf8": 279, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14911, "cached_input_tokens": 13696, "output_tokens": 202, "reasoning_output_tokens": 122}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"feature_13\\\", COUNT(*) AS row_count\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_13\\\"\\nORDER BY row_count DESC;\",\"notes\":\"Uses the planned grouped-count template with group_col bound to \\\"feature_13\\\" on the single table \\\"n9\\\".\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_49e2f541fc7596a2/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_49e2f541fc7596a2/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..cb5e36fcf4b674c424e590fdfc4e8c997e38d5a0
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_49e2f541fc7596a2/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_49e2f541fc7596a2",
+  "api_calls": 0,
+  "input_tokens": 14911,
+  "cached_input_tokens": 13696,
+  "output_tokens": 202,
+  "total_tokens": 15113,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 17852.24,
+  "sql_execution_elapsed_ms_total": 4.81,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_49e2f541fc7596a2/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_4ae578da22c929d1/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_4ae578da22c929d1/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..ca2564cbf10588e3b153c7c6d90d6eaa325012e6
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_4ae578da22c929d1/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=feature_7, condition_col=class.
+Result preview: [{"feature_7": "31", "condition_ratio": 7.0}, {"feature_7": "78", "condition_ratio": 5.5}, {"feature_7": "42", "condition_ratio": 4.666666666666667}, {"feature_7": "32", "condition_ratio": 3.875}, {"feature_7": "34", "condition_ratio": 3.2}] Results were truncated.
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_4ae578da22c929d1/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_4ae578da22c929d1/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..43a0f5af37329d6723abd0f799291902d8d82b59
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_4ae578da22c929d1/generated_sql.sql
@@ -0,0 +1,24 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: direction_consistency
+-- intended_facet_id: conditional_rate_shift
+-- variant_semantic_role: contrastive_conditional_view
+-- template_id: tpl_m4_group_ratio_two_conditions
+-- query_record_id: v2q_n9_4ae578da22c929d1
+-- problem_id: v2p_n9_6363107d279d93c4
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+    SELECT "feature_7",
+           SUM(CASE WHEN "class" = '2' THEN 1 ELSE 0 END) AS numerator_count,
+           SUM(CASE WHEN "class" = '4' THEN 1 ELSE 0 END) AS denominator_count
+    FROM "n9"
+    GROUP BY "feature_7"
+)
+SELECT "feature_7",
+       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio
+FROM grouped
+ORDER BY condition_ratio DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_4ae578da22c929d1/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_4ae578da22c929d1/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..eb836a70753d42b56fa1e2c57a8ee5c6035576e1
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_4ae578da22c929d1/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_ratio_two_conditions\nWITH grouped AS (\n    SELECT \"feature_7\",\n           SUM(CASE WHEN \"class\" = '2' THEN 1 ELSE 0 END) AS numerator_count,\n           SUM(CASE WHEN \"class\" = '4' THEN 1 ELSE 0 END) AS denominator_count\n    FROM \"n9\"\n    GROUP BY \"feature_7\"\n)\nSELECT \"feature_7\",\n       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n    SELECT \\\"feature_7\\\",\\n           SUM(CASE WHEN \\\"class\\\" = '2' THEN 1 ELSE 0 END) AS numerator_count,\\n           SUM(CASE WHEN \\\"class\\\" = '4' THEN 1 ELSE 0 END) AS denominator_count\\n    FROM \\\"n9\\\"\\n    GROUP BY \\\"feature_7\\\"\\n)\\nSELECT \\\"feature_7\\\",\\n       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\", \"columns\": [\"feature_7\", \"condition_ratio\"], \"rows\": [{\"feature_7\": \"31\", \"condition_ratio\": 7.0}, {\"feature_7\": \"78\", \"condition_ratio\": 5.5}, {\"feature_7\": \"42\", \"condition_ratio\": 4.666666666666667}, {\"feature_7\": \"32\", \"condition_ratio\": 3.875}, {\"feature_7\": \"34\", \"condition_ratio\": 3.2}, {\"feature_7\": \"35\", \"condition_ratio\": 3.1}, {\"feature_7\": \"88\", \"condition_ratio\": 3.0}, {\"feature_7\": \"33\", \"condition_ratio\": 2.875}, {\"feature_7\": \"76\", \"condition_ratio\": 2.8333333333333335}, {\"feature_7\": \"41\", \"condition_ratio\": 2.6666666666666665}, {\"feature_7\": \"30\", \"condition_ratio\": 2.5555555555555554}, {\"feature_7\": \"38\", \"condition_ratio\": 2.5}, {\"feature_7\": \"40\", \"condition_ratio\": 2.5}, {\"feature_7\": \"39\", \"condition_ratio\": 2.3846153846153846}, {\"feature_7\": \"37\", \"condition_ratio\": 2.2857142857142856}, {\"feature_7\": \"59\", \"condition_ratio\": 2.25}, {\"feature_7\": \"44\", \"condition_ratio\": 2.2222222222222223}, {\"feature_7\": \"69\", \"condition_ratio\": 2.1538461538461537}, {\"feature_7\": \"45\", \"condition_ratio\": 2.1}, {\"feature_7\": \"70\", \"condition_ratio\": 2.0}, {\"feature_7\": \"48\", \"condition_ratio\": 1.9}, {\"feature_7\": \"36\", \"condition_ratio\": 1.875}, {\"feature_7\": \"47\", \"condition_ratio\": 1.7777777777777777}, {\"feature_7\": \"53\", \"condition_ratio\": 1.75}, {\"feature_7\": \"71\", \"condition_ratio\": 1.7142857142857142}, {\"feature_7\": \"62\", \"condition_ratio\": 1.7}, {\"feature_7\": \"67\", \"condition_ratio\": 1.6666666666666667}, {\"feature_7\": \"94\", \"condition_ratio\": 1.6666666666666667}, {\"feature_7\": \"46\", \"condition_ratio\": 1.6153846153846154}, {\"feature_7\": \"26\", \"condition_ratio\": 1.5714285714285714}, {\"feature_7\": \"29\", \"condition_ratio\": 1.5714285714285714}, {\"feature_7\": \"77\", \"condition_ratio\": 1.5714285714285714}, {\"feature_7\": \"79\", \"condition_ratio\": 1.5714285714285714}, {\"feature_7\": \"43\", \"condition_ratio\": 1.5625}, {\"feature_7\": \"61\", \"condition_ratio\": 1.5}, {\"feature_7\": \"51\", \"condition_ratio\": 1.4615384615384615}, {\"feature_7\": \"72\", \"condition_ratio\": 1.4545454545454546}, {\"feature_7\": \"27\", \"condition_ratio\": 1.4}, {\"feature_7\": \"54\", \"condition_ratio\": 1.3846153846153846}, {\"feature_7\": \"56\", \"condition_ratio\": 1.3571428571428572}, {\"feature_7\": \"75\", \"condition_ratio\": 1.3333333333333333}, {\"feature_7\": \"73\", \"condition_ratio\": 1.2857142857142858}, {\"feature_7\": \"49\", \"condition_ratio\": 1.2666666666666666}, {\"feature_7\": \"55\", \"condition_ratio\": 1.25}, {\"feature_7\": \"80\", \"condition_ratio\": 1.25}, {\"feature_7\": \"83\", \"condition_ratio\": 1.25}, {\"feature_7\": \"87\", \"condition_ratio\": 1.25}, {\"feature_7\": \"93\", \"condition_ratio\": 1.25}, {\"feature_7\": \"74\", \"condition_ratio\": 1.1818181818181819}, {\"feature_7\": \"60\", \"condition_ratio\": 1.1666666666666667}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 14.84}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_4ae578da22c929d1/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_4ae578da22c929d1/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..8a1cd4078e0ac3e7988eb3f1bbef40d2cbf3eab0
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_4ae578da22c929d1/run_manifest.json
@@ -0,0 +1,92 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:40:33.059493+00:00",
+  "ended_at": "2026-05-19T15:40:47.754396+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_4ae578da22c929d1",
+    "problem_id": "v2p_n9_6363107d279d93c4",
+    "dataset_id": "n9",
+    "template_id": "tpl_m4_group_ratio_two_conditions",
+    "template_name": "Grouped Ratio of Two Conditions",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "direction_consistency",
+    "intended_facet_id": "conditional_rate_shift",
+    "variant_semantic_role": "contrastive_conditional_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=feature_7, condition_col=class.",
+    "bindings": {
+      "group_col": "feature_7",
+      "condition_col": "class",
+      "condition_value": "2",
+      "positive_value": "2",
+      "negative_value": "4",
+      "top_k": 10,
+      "top_n": 3,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 89.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "condition_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "WITH grouped AS (\n    SELECT {group_col},\n           SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n           SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n    FROM {table}\n    GROUP BY {group_col}\n)\nSELECT {group_col},\n       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;",
+    "notes": [
+      "default_facets=conditional_rate_shift",
+      "template_selection_mode=rule",
+      "problem_index_within_template=5",
+      "sql_variant_index=1/1",
+      "binding_index=40"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 4,
+    "problem_index_within_template": 5,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_4ae578da22c929d1.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_4ae578da22c929d1",
+    "api_calls": 0,
+    "input_tokens": 15145,
+    "cached_input_tokens": 13696,
+    "output_tokens": 467,
+    "total_tokens": 15612,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 14673.08,
+    "sql_execution_elapsed_ms_total": 14.84,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_4ae578da22c929d1/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_4ae578da22c929d1/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_4ae578da22c929d1/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..448d70e6e4f6b2546a0be6756310d19aaa4f427c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_4ae578da22c929d1/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:40:47.736368+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 14673.08, "started_at": "2026-05-19T15:40:33.061630+00:00", "ended_at": "2026-05-19T15:40:47.734747+00:00", "prompt_metrics": {"chars": 10187, "bytes_utf8": 10187, "lines": 303, "estimated_tokens": null}, "response_metrics": {"chars": 671, "bytes_utf8": 671, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15145, "cached_input_tokens": 13696, "output_tokens": 467, "reasoning_output_tokens": 280}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n    SELECT \\\"feature_7\\\",\\n           SUM(CASE WHEN \\\"class\\\" = '2' THEN 1 ELSE 0 END) AS numerator_count,\\n           SUM(CASE WHEN \\\"class\\\" = '4' THEN 1 ELSE 0 END) AS denominator_count\\n    FROM \\\"n9\\\"\\n    GROUP BY \\\"feature_7\\\"\\n)\\nSELECT \\\"feature_7\\\",\\n       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\",\"notes\":\"Applies the planned grouped ratio template with group_col=\\\"feature_7\\\" and condition_col=\\\"class\\\", computing the ratio of class '2' counts to class '4' counts for each feature_7 group.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_4ae578da22c929d1/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_4ae578da22c929d1/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..d200eb583191073df807e963f6abc05ff5e1c624
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_4ae578da22c929d1/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_4ae578da22c929d1",
+  "api_calls": 0,
+  "input_tokens": 15145,
+  "cached_input_tokens": 13696,
+  "output_tokens": 467,
+  "total_tokens": 15612,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 14673.08,
+  "sql_execution_elapsed_ms_total": 14.84,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_4ae578da22c929d1/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_52ce09dd6e4995e7/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_52ce09dd6e4995e7/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..8761d0d311b6e91a4933e893d6542fa0d49ac250
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_52ce09dd6e4995e7/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=feature_9, measure_col=feature_9.
+Result preview: [{"feature_9": "100", "total_measure": 176400.0}, {"feature_9": "88", "total_measure": 10912.0}, {"feature_9": "84", "total_measure": 10668.0}, {"feature_9": "94", "total_measure": 10622.0}, {"feature_9": "95", "total_measure": 10070.0}] Results were truncated.
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_52ce09dd6e4995e7/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_52ce09dd6e4995e7/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..c28a055b9951550161777d512894e7a05f7248a0
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_52ce09dd6e4995e7/generated_sql.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_conditional_contrast
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_n9_52ce09dd6e4995e7
+-- problem_id: v2p_n9_bf36a0c5193f9100
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_9", SUM(CAST("feature_9" AS REAL)) AS "total_measure"
+FROM "n9"
+GROUP BY "feature_9"
+ORDER BY "total_measure" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_52ce09dd6e4995e7/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_52ce09dd6e4995e7/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..a7d48fc02d2ac2a6cfcca9d26c6432283c19fdc9
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_52ce09dd6e4995e7/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_h2o_group_sum\nSELECT \"feature_9\", SUM(CAST(\"feature_9\" AS REAL)) AS \"total_measure\"\nFROM \"n9\"\nGROUP BY \"feature_9\"\nORDER BY \"total_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"feature_9\\\", SUM(CAST(\\\"feature_9\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_9\\\"\\nORDER BY \\\"total_measure\\\" DESC;\", \"columns\": [\"feature_9\", \"total_measure\"], \"rows\": [{\"feature_9\": \"100\", \"total_measure\": 176400.0}, {\"feature_9\": \"88\", \"total_measure\": 10912.0}, {\"feature_9\": \"84\", \"total_measure\": 10668.0}, {\"feature_9\": \"94\", \"total_measure\": 10622.0}, {\"feature_9\": \"95\", \"total_measure\": 10070.0}, {\"feature_9\": \"93\", \"total_measure\": 9393.0}, {\"feature_9\": \"92\", \"total_measure\": 9016.0}, {\"feature_9\": \"85\", \"total_measure\": 9010.0}, {\"feature_9\": \"79\", \"total_measure\": 8927.0}, {\"feature_9\": \"82\", \"total_measure\": 8856.0}, {\"feature_9\": \"91\", \"total_measure\": 8827.0}, {\"feature_9\": \"86\", \"total_measure\": 8686.0}, {\"feature_9\": \"96\", \"total_measure\": 8448.0}, {\"feature_9\": \"99\", \"total_measure\": 8316.0}, {\"feature_9\": \"81\", \"total_measure\": 8262.0}, {\"feature_9\": \"97\", \"total_measure\": 8245.0}, {\"feature_9\": \"90\", \"total_measure\": 8190.0}, {\"feature_9\": \"87\", \"total_measure\": 8178.0}, {\"feature_9\": \"89\", \"total_measure\": 8099.0}, {\"feature_9\": \"77\", \"total_measure\": 8085.0}, {\"feature_9\": \"78\", \"total_measure\": 8034.0}, {\"feature_9\": \"71\", \"total_measure\": 8023.0}, {\"feature_9\": \"83\", \"total_measure\": 7885.0}, {\"feature_9\": \"98\", \"total_measure\": 7644.0}, {\"feature_9\": \"80\", \"total_measure\": 7520.0}, {\"feature_9\": \"70\", \"total_measure\": 7140.0}, {\"feature_9\": \"72\", \"total_measure\": 6840.0}, {\"feature_9\": \"75\", \"total_measure\": 6750.0}, {\"feature_9\": \"73\", \"total_measure\": 6570.0}, {\"feature_9\": \"67\", \"total_measure\": 6566.0}, {\"feature_9\": \"60\", \"total_measure\": 6540.0}, {\"feature_9\": \"62\", \"total_measure\": 6324.0}, {\"feature_9\": \"76\", \"total_measure\": 6308.0}, {\"feature_9\": \"66\", \"total_measure\": 5808.0}, {\"feature_9\": \"59\", \"total_measure\": 5723.0}, {\"feature_9\": \"74\", \"total_measure\": 5698.0}, {\"feature_9\": \"58\", \"total_measure\": 5568.0}, {\"feature_9\": \"61\", \"total_measure\": 5246.0}, {\"feature_9\": \"68\", \"total_measure\": 5236.0}, {\"feature_9\": \"69\", \"total_measure\": 5175.0}, {\"feature_9\": \"55\", \"total_measure\": 5115.0}, {\"feature_9\": \"48\", \"total_measure\": 4752.0}, {\"feature_9\": \"51\", \"total_measure\": 4743.0}, {\"feature_9\": \"57\", \"total_measure\": 4731.0}, {\"feature_9\": \"63\", \"total_measure\": 4725.0}, {\"feature_9\": \"47\", \"total_measure\": 4606.0}, {\"feature_9\": \"46\", \"total_measure\": 4554.0}, {\"feature_9\": \"64\", \"total_measure\": 4480.0}, {\"feature_9\": \"41\", \"total_measure\": 4469.0}, {\"feature_9\": \"42\", \"total_measure\": 4326.0}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 7.58}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_52ce09dd6e4995e7/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_52ce09dd6e4995e7/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..7880e266b2ca67e84a326478ebd197695dff5a7f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_52ce09dd6e4995e7/run_manifest.json
@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:31:25.521142+00:00",
+  "ended_at": "2026-05-19T15:31:46.195296+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_52ce09dd6e4995e7",
+    "problem_id": "v2p_n9_bf36a0c5193f9100",
+    "dataset_id": "n9",
+    "template_id": "tpl_h2o_group_sum",
+    "template_name": "Grouped Numeric Sum",
+    "family_id": "subgroup_structure",
+    "canonical_subitem_id": "internal_profile_stability",
+    "intended_facet_id": "subgroup_conditional_contrast",
+    "variant_semantic_role": "collapsed_target_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=feature_9, measure_col=feature_9.",
+    "bindings": {
+      "group_col": "feature_9",
+      "measure_col": "feature_9",
+      "top_k": 13,
+      "top_n": 3,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 89.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;",
+    "notes": [
+      "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast",
+      "template_selection_mode=rule",
+      "problem_index_within_template=9",
+      "sql_variant_index=1/2",
+      "binding_index=8"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 1,
+    "problem_index_within_template": 9,
+    "sql_variant_index": 1,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_52ce09dd6e4995e7.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_52ce09dd6e4995e7",
+    "api_calls": 0,
+    "input_tokens": 14940,
+    "cached_input_tokens": 12032,
+    "output_tokens": 578,
+    "total_tokens": 15518,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 20661.5,
+    "sql_execution_elapsed_ms_total": 7.58,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_52ce09dd6e4995e7/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_52ce09dd6e4995e7/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_52ce09dd6e4995e7/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..a7e6a09a26b5687a4e3171850b185f31763d1ae3
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_52ce09dd6e4995e7/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:31:46.185742+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 20661.5, "started_at": "2026-05-19T15:31:25.523150+00:00", "ended_at": "2026-05-19T15:31:46.184682+00:00", "prompt_metrics": {"chars": 9389, "bytes_utf8": 9389, "lines": 300, "estimated_tokens": null}, "response_metrics": {"chars": 362, "bytes_utf8": 362, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14940, "cached_input_tokens": 12032, "output_tokens": 578, "reasoning_output_tokens": 475}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"feature_9\\\", SUM(CAST(\\\"feature_9\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_9\\\"\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Used the required template with group_col=\\\"feature_9\\\" and measure_col=\\\"feature_9\\\". CAST is applied because the schema stores numeric-looking values as TEXT.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_52ce09dd6e4995e7/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_52ce09dd6e4995e7/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..11aca51d38a4fa0fa72c37e4f26fbeec13b6a958
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_52ce09dd6e4995e7/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_52ce09dd6e4995e7",
+  "api_calls": 0,
+  "input_tokens": 14940,
+  "cached_input_tokens": 12032,
+  "output_tokens": 578,
+  "total_tokens": 15518,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 20661.5,
+  "sql_execution_elapsed_ms_total": 7.58,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_52ce09dd6e4995e7/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_53efae862dc8d800/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_53efae862dc8d800/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..eb156590080ffaa4476c48a8e93a60494c924dc8
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_53efae862dc8d800/final_answer.txt
@@ -0,0 +1 @@
+{"row_count": null, "preview_rows": [{"value_label": "100", "support": 2988, "support_share": 0.2718340611353712, "support_rank": 1}, {"value_label": "0", "support": 2917, "support_share": 0.26537481804949054, "support_rank": 2}, {"value_label": "7", "support": 96, "support_share": 0.008733624454148471, "support_rank": 3}, {"value_label": "8", "support": 89, "support_share": 0.008096797671033478, "support_rank": 4}, {"value_label": "5", "support": 86, "support_share": 0.00782387190684134, "support_rank": 5}]}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_53efae862dc8d800/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_53efae862dc8d800/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..4db6e64d69d9354bdb356861758b784a44be532d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_53efae862dc8d800/generated_sql.sql
@@ -0,0 +1,25 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: support_concentration
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_cardinality_support_rank_profile
+-- query_record_id: v2q_n9_53efae862dc8d800
+-- problem_id: v2p_n9_6833cb775d202bdf
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_15" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_15"
+)
+SELECT
+    value_label,
+    support,
+    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank
+FROM grouped
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_53efae862dc8d800/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_53efae862dc8d800/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..317a951ff609845654df8b77ae486735182fde34
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_53efae862dc8d800/query_results.jsonl
@@ -0,0 +1 @@
+{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: n9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: support_rank_profile_consistency\n-- intended_facet_id: support_concentration\n-- variant_semantic_role: count_distribution\n-- template_id: tpl_cardinality_support_rank_profile\n-- query_record_id: v2q_n9_53efae862dc8d800\n-- problem_id: v2p_n9_6833cb775d202bdf\n-- realization_mode: deterministic\n-- source_kind: deterministic\nWITH grouped AS (\n    SELECT \"feature_15\" AS value_label, COUNT(*) AS support\n    FROM \"n9\"\n    GROUP BY \"feature_15\"\n)\nSELECT\n    value_label,\n    support,\n    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\nFROM grouped\nORDER BY support DESC, value_label;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: n9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: support_rank_profile_consistency\\n-- intended_facet_id: support_concentration\\n-- variant_semantic_role: count_distribution\\n-- template_id: tpl_cardinality_support_rank_profile\\n-- query_record_id: v2q_n9_53efae862dc8d800\\n-- problem_id: v2p_n9_6833cb775d202bdf\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nWITH grouped AS (\\n    SELECT \\\"feature_15\\\" AS value_label, COUNT(*) AS support\\n    FROM \\\"n9\\\"\\n    GROUP BY \\\"feature_15\\\"\\n)\\nSELECT\\n    value_label,\\n    support,\\n    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\\n    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\\nFROM grouped\\nORDER BY support DESC, value_label;\", \"columns\": [\"value_label\", \"support\", \"support_share\", \"support_rank\"], \"rows\": [{\"value_label\": \"100\", \"support\": 2988, \"support_share\": 0.2718340611353712, \"support_rank\": 1}, {\"value_label\": \"0\", \"support\": 2917, \"support_share\": 0.26537481804949054, \"support_rank\": 2}, {\"value_label\": \"7\", \"support\": 96, \"support_share\": 0.008733624454148471, \"support_rank\": 3}, {\"value_label\": \"8\", \"support\": 89, \"support_share\": 0.008096797671033478, \"support_rank\": 4}, {\"value_label\": \"5\", \"support\": 86, \"support_share\": 0.00782387190684134, \"support_rank\": 5}, {\"value_label\": \"9\", \"support\": 86, \"support_share\": 0.00782387190684134, \"support_rank\": 6}, {\"value_label\": \"6\", \"support\": 83, \"support_share\": 0.007550946142649199, \"support_rank\": 7}, {\"value_label\": \"16\", \"support\": 82, \"support_share\": 0.007459970887918486, \"support_rank\": 8}, {\"value_label\": \"10\", \"support\": 81, \"support_share\": 0.007368995633187773, \"support_rank\": 9}, {\"value_label\": \"11\", \"support\": 77, \"support_share\": 0.00700509461426492, \"support_rank\": 10}, {\"value_label\": \"19\", \"support\": 77, \"support_share\": 0.00700509461426492, \"support_rank\": 11}, {\"value_label\": \"3\", \"support\": 74, \"support_share\": 0.006732168850072781, \"support_rank\": 12}, {\"value_label\": \"12\", \"support\": 73, \"support_share\": 0.0066411935953420665, \"support_rank\": 13}, {\"value_label\": \"15\", \"support\": 73, \"support_share\": 0.0066411935953420665, \"support_rank\": 14}, {\"value_label\": \"24\", \"support\": 71, \"support_share\": 0.00645924308588064, \"support_rank\": 15}, {\"value_label\": \"14\", \"support\": 70, \"support_share\": 0.006368267831149927, \"support_rank\": 16}, {\"value_label\": \"21\", \"support\": 70, \"support_share\": 0.006368267831149927, \"support_rank\": 17}, {\"value_label\": \"29\", \"support\": 70, \"support_share\": 0.006368267831149927, \"support_rank\": 18}, {\"value_label\": \"22\", \"support\": 69, \"support_share\": 0.006277292576419214, \"support_rank\": 19}, {\"value_label\": \"13\", \"support\": 68, \"support_share\": 0.006186317321688501, \"support_rank\": 20}, {\"value_label\": \"18\", \"support\": 68, \"support_share\": 0.006186317321688501, \"support_rank\": 21}, {\"value_label\": \"25\", \"support\": 66, \"support_share\": 0.006004366812227074, \"support_rank\": 22}, {\"value_label\": \"88\", \"support\": 66, \"support_share\": 0.006004366812227074, \"support_rank\": 23}, {\"value_label\": \"20\", \"support\": 64, \"support_share\": 0.005822416302765648, \"support_rank\": 24}, {\"value_label\": \"2\", \"support\": 63, \"support_share\": 0.005731441048034935, \"support_rank\": 25}, {\"value_label\": \"23\", \"support\": 61, \"support_share\": 0.005549490538573508, \"support_rank\": 26}, {\"value_label\": \"17\", \"support\": 60, \"support_share\": 0.0054585152838427945, \"support_rank\": 27}, {\"value_label\": \"39\", \"support\": 60, \"support_share\": 0.0054585152838427945, \"support_rank\": 28}, {\"value_label\": \"30\", \"support\": 57, \"support_share\": 0.005185589519650655, \"support_rank\": 29}, {\"value_label\": \"36\", \"support\": 57, \"support_share\": 0.005185589519650655, \"support_rank\": 30}, {\"value_label\": \"44\", \"support\": 57, \"support_share\": 0.005185589519650655, \"support_rank\": 31}, {\"value_label\": \"27\", \"support\": 56, \"support_share\": 0.005094614264919942, \"support_rank\": 32}, {\"value_label\": \"31\", \"support\": 56, \"support_share\": 0.005094614264919942, \"support_rank\": 33}, {\"value_label\": \"32\", \"support\": 56, \"support_share\": 0.005094614264919942, \"support_rank\": 34}, {\"value_label\": \"33\", \"support\": 56, \"support_share\": 0.005094614264919942, \"support_rank\": 35}, {\"value_label\": \"1\", \"support\": 55, \"support_share\": 0.005003639010189229, \"support_rank\": 36}, {\"value_label\": \"45\", \"support\": 55, \"support_share\": 0.005003639010189229, \"support_rank\": 37}, {\"value_label\": \"26\", \"support\": 54, \"support_share\": 0.0049126637554585155, \"support_rank\": 38}, {\"value_label\": \"28\", \"support\": 54, \"support_share\": 0.0049126637554585155, \"support_rank\": 39}, {\"value_label\": \"34\", \"support\": 53, \"support_share\": 0.004821688500727802, \"support_rank\": 40}, {\"value_label\": \"37\", \"support\": 53, \"support_share\": 0.004821688500727802, \"support_rank\": 41}, {\"value_label\": \"47\", \"support\": 53, \"support_share\": 0.004821688500727802, \"support_rank\": 42}, {\"value_label\": \"84\", \"support\": 53, \"support_share\": 0.004821688500727802, \"support_rank\": 43}, {\"value_label\": \"43\", \"support\": 51, \"support_share\": 0.004639737991266376, \"support_rank\": 44}, {\"value_label\": \"35\", \"support\": 49, \"support_share\": 0.004457787481804949, \"support_rank\": 45}, {\"value_label\": \"58\", \"support\": 49, \"support_share\": 0.004457787481804949, \"support_rank\": 46}, {\"value_label\": \"69\", \"support\": 49, \"support_share\": 0.004457787481804949, \"support_rank\": 47}, {\"value_label\": \"78\", \"support\": 49, \"support_share\": 0.004457787481804949, \"support_rank\": 48}, {\"value_label\": \"71\", \"support\": 48, \"support_share\": 0.004366812227074236, \"support_rank\": 49}, {\"value_label\": \"89\", \"support\": 47, \"support_share\": 0.004275836972343522, \"support_rank\": 50}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 4.39}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_53efae862dc8d800/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_53efae862dc8d800/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..566b18dacabd9cde2c8a0425a6f57334952c1332
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_53efae862dc8d800/run_manifest.json
@@ -0,0 +1,57 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T16:10:15.840657+00:00",
+  "ended_at": "2026-05-19T16:10:15.845814+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_53efae862dc8d800",
+    "problem_id": "v2p_n9_6833cb775d202bdf",
+    "dataset_id": "n9",
+    "template_id": "tpl_cardinality_support_rank_profile",
+    "template_name": "Cardinality Support Rank Profile",
+    "family_id": "cardinality_structure",
+    "canonical_subitem_id": "support_rank_profile_consistency",
+    "intended_facet_id": "support_concentration",
+    "variant_semantic_role": "count_distribution",
+    "subitem_assignment_source": "template_fixed",
+    "source_kind": "deterministic",
+    "realization_mode": "deterministic",
+    "gate_priority": "deterministic",
+    "extended_family": true,
+    "question": "Use template Cardinality Support Rank Profile to probe support_rank_profile_consistency with semantic role count_distribution. Focus on group_col=feature_15.",
+    "bindings": {
+      "group_col": "feature_15"
+    },
+    "binding_roles": [
+      "group_col"
+    ],
+    "coverage_target_min": "enumerate_all_applicable",
+    "runtime_sql_skeleton": "WITH grouped AS (\n    SELECT {group_col} AS value_label, COUNT(*) AS support\n    FROM {table}\n    GROUP BY {group_col}\n)\nSELECT\n    value_label,\n    support,\n    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\nFROM grouped\nORDER BY support DESC, value_label;",
+    "notes": [
+      "default_facets=support_concentration,value_imbalance_profile",
+      "template_selection_mode=deterministic",
+      "problem_index_within_template=11",
+      "sql_variant_index=1/1"
+    ],
+    "template_selection_mode": "deterministic",
+    "selected_template_rank": 0,
+    "problem_index_within_template": 11,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_53efae862dc8d800.sql",
+  "usage_summary": {
+    "engine": "template",
+    "input_tokens": 0,
+    "cached_input_tokens": 0,
+    "output_tokens": 0,
+    "total_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "none"
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_53efae862dc8d800/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_53efae862dc8d800/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_53efae862dc8d800/usage_summary.json
@@ -0,0 +1,9 @@
+{
+  "engine": "template",
+  "input_tokens": 0,
+  "cached_input_tokens": 0,
+  "output_tokens": 0,
+  "total_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "none"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_55adc71151b1e66e/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_55adc71151b1e66e/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..57dcc2ab28b4af8d3936ee082a1e4e80e08d0686
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_55adc71151b1e66e/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=feature_14, measure_col=feature_15.
+Result preview: [{"feature_14": "89", "feature_16": "100", "total_measure": 2166.0, "share_within_group": 85.47750591949487}, {"feature_14": "98", "feature_16": "100", "total_measure": 4194.0, "share_within_group": 84.45428916633105}, {"feature_14": "87", "feature_16": "100", "total_measure": 1706.0, "share_within_group": 84.37190900098912}, {"feature_14": "91", "feature_16": "100", "total_measure": 3260.0, "share_within_group": 83.07849133537206}, {"feature_14": "70", "feature_16": "100", "total_measure": 656.0, "share_within_group": 82.9329962073325}]
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_55adc71151b1e66e/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_55adc71151b1e66e/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..05339fbfcc5ebd39ea1cff066e00942ffc21f17a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_55adc71151b1e66e/generated_sql.sql
@@ -0,0 +1,23 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_55adc71151b1e66e
+-- problem_id: v2p_n9_c3e711b993738580
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+  "feature_14",
+  "feature_16",
+  SUM(CAST("feature_15" AS REAL)) AS "total_measure",
+  SUM(CAST("feature_15" AS REAL)) * 100.0
+    / SUM(SUM(CAST("feature_15" AS REAL))) OVER (PARTITION BY "feature_14") AS "share_within_group"
+FROM "n9"
+GROUP BY "feature_14", "feature_16"
+ORDER BY "share_within_group" DESC
+LIMIT 15;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_55adc71151b1e66e/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_55adc71151b1e66e/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..9b827e540e3098973361321c456bd26c16bba3fc
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_55adc71151b1e66e/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT\n  \"feature_14\",\n  \"feature_16\",\n  SUM(CAST(\"feature_15\" AS REAL)) AS \"total_measure\",\n  SUM(CAST(\"feature_15\" AS REAL)) * 100.0\n    / SUM(SUM(CAST(\"feature_15\" AS REAL))) OVER (PARTITION BY \"feature_14\") AS \"share_within_group\"\nFROM \"n9\"\nGROUP BY \"feature_14\", \"feature_16\"\nORDER BY \"share_within_group\" DESC\nLIMIT 15;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n  \\\"feature_14\\\",\\n  \\\"feature_16\\\",\\n  SUM(CAST(\\\"feature_15\\\" AS REAL)) AS \\\"total_measure\\\",\\n  SUM(CAST(\\\"feature_15\\\" AS REAL)) * 100.0\\n    / SUM(SUM(CAST(\\\"feature_15\\\" AS REAL))) OVER (PARTITION BY \\\"feature_14\\\") AS \\\"share_within_group\\\"\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_14\\\", \\\"feature_16\\\"\\nORDER BY \\\"share_within_group\\\" DESC\\nLIMIT 15;\", \"columns\": [\"feature_14\", \"feature_16\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"feature_14\": \"89\", \"feature_16\": \"100\", \"total_measure\": 2166.0, \"share_within_group\": 85.47750591949487}, {\"feature_14\": \"98\", \"feature_16\": \"100\", \"total_measure\": 4194.0, \"share_within_group\": 84.45428916633105}, {\"feature_14\": \"87\", \"feature_16\": \"100\", \"total_measure\": 1706.0, \"share_within_group\": 84.37190900098912}, {\"feature_14\": \"91\", \"feature_16\": \"100\", \"total_measure\": 3260.0, \"share_within_group\": 83.07849133537206}, {\"feature_14\": \"70\", \"feature_16\": \"100\", \"total_measure\": 656.0, \"share_within_group\": 82.9329962073325}, {\"feature_14\": \"25\", \"feature_16\": \"0\", \"total_measure\": 11168.0, \"share_within_group\": 80.45529860961025}, {\"feature_14\": \"86\", \"feature_16\": \"100\", \"total_measure\": 1565.0, \"share_within_group\": 80.1331285202253}, {\"feature_14\": \"88\", \"feature_16\": \"100\", \"total_measure\": 2189.0, \"share_within_group\": 79.65793304221252}, {\"feature_14\": \"93\", \"feature_16\": \"100\", \"total_measure\": 3463.0, \"share_within_group\": 79.3174530462666}, {\"feature_14\": \"92\", \"feature_16\": \"100\", \"total_measure\": 2777.0, \"share_within_group\": 77.700055959709}, {\"feature_14\": \"24\", \"feature_16\": \"0\", \"total_measure\": 9258.0, \"share_within_group\": 77.40155505392525}, {\"feature_14\": \"94\", \"feature_16\": \"100\", \"total_measure\": 4442.0, \"share_within_group\": 77.40024394493814}, {\"feature_14\": \"26\", \"feature_16\": \"0\", \"total_measure\": 7176.0, \"share_within_group\": 76.92142780576697}, {\"feature_14\": \"97\", \"feature_16\": \"100\", \"total_measure\": 3511.0, \"share_within_group\": 76.6593886462882}, {\"feature_14\": \"23\", \"feature_16\": \"0\", \"total_measure\": 6816.0, \"share_within_group\": 76.4382639901312}], \"row_count_returned\": 15, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 30.87}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_55adc71151b1e66e/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_55adc71151b1e66e/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..2c143dcf1b26cd278427864b9ee61a0c8530f028
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_55adc71151b1e66e/run_manifest.json
@@ -0,0 +1,91 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:37:32.734967+00:00",
+  "ended_at": "2026-05-19T15:37:48.605506+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_55adc71151b1e66e",
+    "problem_id": "v2p_n9_c3e711b993738580",
+    "dataset_id": "n9",
+    "template_id": "tpl_tpcds_within_group_share",
+    "template_name": "Within-Group Share of Total",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "dependency_strength_similarity",
+    "intended_facet_id": "pairwise_conditional_dependency",
+    "variant_semantic_role": "focused_target_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=feature_14, measure_col=feature_15.",
+    "bindings": {
+      "group_col": "feature_14",
+      "measure_col": "feature_15",
+      "item_col": "feature_16",
+      "top_k": 15,
+      "top_n": 6,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.05,
+      "baseline_multiplier": 1.75,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 4,
+      "measure_threshold": 81.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "item_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;",
+    "notes": [
+      "default_facets=pairwise_conditional_dependency",
+      "template_selection_mode=rule",
+      "problem_index_within_template=7",
+      "sql_variant_index=2/2",
+      "binding_index=30"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 3,
+    "problem_index_within_template": 7,
+    "sql_variant_index": 2,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_55adc71151b1e66e.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_55adc71151b1e66e",
+    "api_calls": 0,
+    "input_tokens": 15059,
+    "cached_input_tokens": 13696,
+    "output_tokens": 881,
+    "total_tokens": 15940,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 15832.63,
+    "sql_execution_elapsed_ms_total": 30.87,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_55adc71151b1e66e/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_55adc71151b1e66e/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_55adc71151b1e66e/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..81a17e8c4b837c10c3eba7676d484f1028416359
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_55adc71151b1e66e/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:37:48.571550+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 15832.63, "started_at": "2026-05-19T15:37:32.737180+00:00", "ended_at": "2026-05-19T15:37:48.569857+00:00", "prompt_metrics": {"chars": 9802, "bytes_utf8": 9802, "lines": 302, "estimated_tokens": null}, "response_metrics": {"chars": 681, "bytes_utf8": 681, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15059, "cached_input_tokens": 13696, "output_tokens": 881, "reasoning_output_tokens": 680}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n  \\\"feature_14\\\",\\n  \\\"feature_16\\\",\\n  SUM(CAST(\\\"feature_15\\\" AS REAL)) AS \\\"total_measure\\\",\\n  SUM(CAST(\\\"feature_15\\\" AS REAL)) * 100.0\\n    / SUM(SUM(CAST(\\\"feature_15\\\" AS REAL))) OVER (PARTITION BY \\\"feature_14\\\") AS \\\"share_within_group\\\"\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_14\\\", \\\"feature_16\\\"\\nORDER BY \\\"share_within_group\\\" DESC\\nLIMIT 15;\",\"notes\":\"Used the provided Within-Group Share of Total template with group_col=\\\"feature_14\\\", item_col=\\\"feature_16\\\", and measure_col=\\\"feature_15\\\". CAST to REAL is included because the schema stores features as TEXT. LIMIT 15 applies the provided top_k binding.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_55adc71151b1e66e/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_55adc71151b1e66e/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..8b1d7f43a8a1efc5044c8b983db847194cdbbe9e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_55adc71151b1e66e/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_55adc71151b1e66e",
+  "api_calls": 0,
+  "input_tokens": 15059,
+  "cached_input_tokens": 13696,
+  "output_tokens": 881,
+  "total_tokens": 15940,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 15832.63,
+  "sql_execution_elapsed_ms_total": 30.87,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_55adc71151b1e66e/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_56730f90dda0c039/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_56730f90dda0c039/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b2d0ad2d710002b4960a262e3561b1153a4e1b4a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_56730f90dda0c039/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=feature_7, measure_col=feature_12.
+Result preview: [{"feature_7": "83", "percentile_measure": 100.0}, {"feature_7": "86", "percentile_measure": 100.0}, {"feature_7": "87", "percentile_measure": 100.0}, {"feature_7": "89", "percentile_measure": 100.0}, {"feature_7": "90", "percentile_measure": 100.0}] Results were truncated.
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_56730f90dda0c039/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_56730f90dda0c039/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..7f038d60504859aa868f086a1218c160fb9dee08
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_56730f90dda0c039/generated_sql.sql
@@ -0,0 +1,38 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_n9_56730f90dda0c039
+-- problem_id: v2p_n9_22038214cd3c7bd8
+-- realization_mode: agent
+-- source_kind: agent
+WITH "ranked" AS (
+  SELECT
+    "feature_7" AS "group_col",
+    CAST("feature_12" AS REAL) AS "measure_value",
+    CUME_DIST() OVER (
+      PARTITION BY "feature_7"
+      ORDER BY CAST("feature_12" AS REAL)
+    ) AS "cum_dist"
+  FROM "n9"
+  WHERE "feature_7" IS NOT NULL
+    AND "feature_12" IS NOT NULL
+),
+"percentile_points" AS (
+  SELECT
+    "group_col",
+    MIN("measure_value") AS "percentile_measure"
+  FROM "ranked"
+  WHERE "cum_dist" >= 0.9
+  GROUP BY "group_col"
+)
+SELECT
+  "group_col" AS "feature_7",
+  "percentile_measure"
+FROM "percentile_points"
+ORDER BY "percentile_measure" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_56730f90dda0c039/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_56730f90dda0c039/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..4e78a69a0d749db4c49df60c1cd96d34de19bbcb
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_56730f90dda0c039/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH \"ranked\" AS (\n  SELECT\n    \"feature_7\" AS \"group_col\",\n    CAST(\"feature_12\" AS REAL) AS \"measure_value\",\n    CUME_DIST() OVER (\n      PARTITION BY \"feature_7\"\n      ORDER BY CAST(\"feature_12\" AS REAL)\n    ) AS \"cum_dist\"\n  FROM \"n9\"\n  WHERE \"feature_7\" IS NOT NULL\n    AND \"feature_12\" IS NOT NULL\n),\n\"percentile_points\" AS (\n  SELECT\n    \"group_col\",\n    MIN(\"measure_value\") AS \"percentile_measure\"\n  FROM \"ranked\"\n  WHERE \"cum_dist\" >= 0.9\n  GROUP BY \"group_col\"\n)\nSELECT\n  \"group_col\" AS \"feature_7\",\n  \"percentile_measure\"\nFROM \"percentile_points\"\nORDER BY \"percentile_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n  SELECT\\n    \\\"feature_7\\\" AS \\\"group_col\\\",\\n    CAST(\\\"feature_12\\\" AS REAL) AS \\\"measure_value\\\",\\n    CUME_DIST() OVER (\\n      PARTITION BY \\\"feature_7\\\"\\n      ORDER BY CAST(\\\"feature_12\\\" AS REAL)\\n    ) AS \\\"cum_dist\\\"\\n  FROM \\\"n9\\\"\\n  WHERE \\\"feature_7\\\" IS NOT NULL\\n    AND \\\"feature_12\\\" IS NOT NULL\\n),\\n\\\"percentile_points\\\" AS (\\n  SELECT\\n    \\\"group_col\\\",\\n    MIN(\\\"measure_value\\\") AS \\\"percentile_measure\\\"\\n  FROM \\\"ranked\\\"\\n  WHERE \\\"cum_dist\\\" >= 0.9\\n  GROUP BY \\\"group_col\\\"\\n)\\nSELECT\\n  \\\"group_col\\\" AS \\\"feature_7\\\",\\n  \\\"percentile_measure\\\"\\nFROM \\\"percentile_points\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\", \"columns\": [\"feature_7\", \"percentile_measure\"], \"rows\": [{\"feature_7\": \"83\", \"percentile_measure\": 100.0}, {\"feature_7\": \"86\", \"percentile_measure\": 100.0}, {\"feature_7\": \"87\", \"percentile_measure\": 100.0}, {\"feature_7\": \"89\", \"percentile_measure\": 100.0}, {\"feature_7\": \"90\", \"percentile_measure\": 100.0}, {\"feature_7\": \"92\", \"percentile_measure\": 100.0}, {\"feature_7\": \"95\", \"percentile_measure\": 100.0}, {\"feature_7\": \"84\", \"percentile_measure\": 98.0}, {\"feature_7\": \"77\", \"percentile_measure\": 95.0}, {\"feature_7\": \"85\", \"percentile_measure\": 94.0}, {\"feature_7\": \"93\", \"percentile_measure\": 93.0}, {\"feature_7\": \"78\", \"percentile_measure\": 92.0}, {\"feature_7\": \"82\", \"percentile_measure\": 92.0}, {\"feature_7\": \"74\", \"percentile_measure\": 90.0}, {\"feature_7\": \"80\", \"percentile_measure\": 90.0}, {\"feature_7\": \"73\", \"percentile_measure\": 89.0}, {\"feature_7\": \"76\", \"percentile_measure\": 89.0}, {\"feature_7\": \"71\", \"percentile_measure\": 88.0}, {\"feature_7\": \"91\", \"percentile_measure\": 88.0}, {\"feature_7\": \"99\", \"percentile_measure\": 88.0}, {\"feature_7\": \"81\", \"percentile_measure\": 87.0}, {\"feature_7\": \"69\", \"percentile_measure\": 86.0}, {\"feature_7\": \"79\", \"percentile_measure\": 86.0}, {\"feature_7\": \"70\", \"percentile_measure\": 84.0}, {\"feature_7\": \"66\", \"percentile_measure\": 83.0}, {\"feature_7\": \"7\", \"percentile_measure\": 83.0}, {\"feature_7\": \"75\", \"percentile_measure\": 83.0}, {\"feature_7\": \"4\", \"percentile_measure\": 81.0}, {\"feature_7\": \"17\", \"percentile_measure\": 80.0}, {\"feature_7\": \"63\", \"percentile_measure\": 79.0}, {\"feature_7\": \"8\", \"percentile_measure\": 79.0}, {\"feature_7\": \"1\", \"percentile_measure\": 78.0}, {\"feature_7\": \"67\", \"percentile_measure\": 78.0}, {\"feature_7\": \"9\", \"percentile_measure\": 78.0}, {\"feature_7\": \"97\", \"percentile_measure\": 78.0}, {\"feature_7\": \"13\", \"percentile_measure\": 77.0}, {\"feature_7\": \"20\", \"percentile_measure\": 77.0}, {\"feature_7\": \"61\", \"percentile_measure\": 77.0}, {\"feature_7\": \"64\", \"percentile_measure\": 77.0}, {\"feature_7\": \"23\", \"percentile_measure\": 76.0}, {\"feature_7\": \"24\", \"percentile_measure\": 76.0}, {\"feature_7\": \"62\", \"percentile_measure\": 76.0}, {\"feature_7\": \"72\", \"percentile_measure\": 76.0}, {\"feature_7\": \"65\", \"percentile_measure\": 75.0}, {\"feature_7\": \"18\", \"percentile_measure\": 74.0}, {\"feature_7\": \"21\", \"percentile_measure\": 74.0}, {\"feature_7\": \"16\", \"percentile_measure\": 73.0}, {\"feature_7\": \"25\", \"percentile_measure\": 73.0}, {\"feature_7\": \"60\", \"percentile_measure\": 73.0}, {\"feature_7\": \"68\", \"percentile_measure\": 73.0}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 16.68}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_56730f90dda0c039/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_56730f90dda0c039/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..9b2b5ee452fbd2b5c8e2ea8ab97b4464021da5ca
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_56730f90dda0c039/run_manifest.json
@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:57:09.736646+00:00",
+  "ended_at": "2026-05-19T15:57:25.113579+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_56730f90dda0c039",
+    "problem_id": "v2p_n9_22038214cd3c7bd8",
+    "dataset_id": "n9",
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_concentration_consistency",
+    "intended_facet_id": "rare_target_concentration",
+    "variant_semantic_role": "ranked_signal_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=feature_7, measure_col=feature_12.",
+    "bindings": {
+      "group_col": "feature_7",
+      "measure_col": "feature_12",
+      "top_k": 11,
+      "top_n": 6,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 55.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;",
+    "notes": [
+      "default_facets=rare_target_concentration",
+      "template_selection_mode=rule",
+      "problem_index_within_template=8",
+      "sql_variant_index=1/2",
+      "binding_index=91"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 8,
+    "problem_index_within_template": 8,
+    "sql_variant_index": 1,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_56730f90dda0c039.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_56730f90dda0c039",
+    "api_calls": 0,
+    "input_tokens": 14978,
+    "cached_input_tokens": 12032,
+    "output_tokens": 793,
+    "total_tokens": 15771,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 15356.34,
+    "sql_execution_elapsed_ms_total": 16.68,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_56730f90dda0c039/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_56730f90dda0c039/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_56730f90dda0c039/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..9c4962d332b369df699c3a134c0ffecbaf80e009
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_56730f90dda0c039/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:57:25.095367+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 15356.34, "started_at": "2026-05-19T15:57:09.738077+00:00", "ended_at": "2026-05-19T15:57:25.094439+00:00", "prompt_metrics": {"chars": 9568, "bytes_utf8": 9568, "lines": 300, "estimated_tokens": null}, "response_metrics": {"chars": 962, "bytes_utf8": 962, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14978, "cached_input_tokens": 12032, "output_tokens": 793, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n  SELECT\\n    \\\"feature_7\\\" AS \\\"group_col\\\",\\n    CAST(\\\"feature_12\\\" AS REAL) AS \\\"measure_value\\\",\\n    CUME_DIST() OVER (\\n      PARTITION BY \\\"feature_7\\\"\\n      ORDER BY CAST(\\\"feature_12\\\" AS REAL)\\n    ) AS \\\"cum_dist\\\"\\n  FROM \\\"n9\\\"\\n  WHERE \\\"feature_7\\\" IS NOT NULL\\n    AND \\\"feature_12\\\" IS NOT NULL\\n),\\n\\\"percentile_points\\\" AS (\\n  SELECT\\n    \\\"group_col\\\",\\n    MIN(\\\"measure_value\\\") AS \\\"percentile_measure\\\"\\n  FROM \\\"ranked\\\"\\n  WHERE \\\"cum_dist\\\" >= 0.9\\n  GROUP BY \\\"group_col\\\"\\n)\\nSELECT\\n  \\\"group_col\\\" AS \\\"feature_7\\\",\\n  \\\"percentile_measure\\\"\\nFROM \\\"percentile_points\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\",\"notes\":\"SQLite-compatible repair of the Grouped Percentile Point template using CUME_DIST() to approximate the 90th percentile as the smallest feature_12 value whose cumulative distribution within each feature_7 group reaches at least 0.9.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_56730f90dda0c039/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_56730f90dda0c039/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..fc4c1c7c444ff0d3c1fa06025b35f42365b4b8ee
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_56730f90dda0c039/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_56730f90dda0c039",
+  "api_calls": 0,
+  "input_tokens": 14978,
+  "cached_input_tokens": 12032,
+  "output_tokens": 793,
+  "total_tokens": 15771,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 15356.34,
+  "sql_execution_elapsed_ms_total": 16.68,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_56730f90dda0c039/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_5e4de333ec1e3b54/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_5e4de333ec1e3b54/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..ff141172bb315947e2062ff2f4244049586b1fc3
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_5e4de333ec1e3b54/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=feature_9, measure_col=feature_14.
+Result preview: [{"feature_9": "0", "percentile_measure": 100.0}, {"feature_9": "1", "percentile_measure": 100.0}, {"feature_9": "100", "percentile_measure": 100.0}, {"feature_9": "11", "percentile_measure": 100.0}, {"feature_9": "13", "percentile_measure": 100.0}] Results were truncated.
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_5e4de333ec1e3b54/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_5e4de333ec1e3b54/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..32b96984e8cbb60618d0162790e4f46970ba451f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_5e4de333ec1e3b54/generated_sql.sql
@@ -0,0 +1,76 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_n9_5e4de333ec1e3b54
+-- problem_id: v2p_n9_1419025a59f14835
+-- realization_mode: agent
+-- source_kind: agent
+WITH "base" AS (
+  SELECT
+    "feature_9",
+    CAST("feature_14" AS REAL) AS "measure"
+  FROM "n9"
+  WHERE "feature_9" IS NOT NULL
+    AND "feature_14" IS NOT NULL
+),
+"ranked" AS (
+  SELECT
+    "feature_9",
+    "measure",
+    ROW_NUMBER() OVER (
+      PARTITION BY "feature_9"
+      ORDER BY "measure"
+    ) AS "rn",
+    COUNT(*) OVER (
+      PARTITION BY "feature_9"
+    ) AS "cnt"
+  FROM "base"
+),
+"targets" AS (
+  SELECT DISTINCT
+    "feature_9",
+    "cnt",
+    1.0 + (0.95 * ("cnt" - 1)) AS "pos"
+  FROM "ranked"
+),
+"positions" AS (
+  SELECT
+    "feature_9",
+    "pos",
+    CAST("pos" AS INTEGER) AS "lower_rn",
+    CASE
+      WHEN ABS("pos" - CAST("pos" AS INTEGER)) < 1e-12 THEN CAST("pos" AS INTEGER)
+      ELSE CAST("pos" AS INTEGER) + 1
+    END AS "upper_rn"
+  FROM "targets"
+),
+"bounds" AS (
+  SELECT
+    p."feature_9",
+    p."pos",
+    p."lower_rn",
+    p."upper_rn",
+    lr."measure" AS "lower_measure",
+    ur."measure" AS "upper_measure"
+  FROM "positions" AS p
+  JOIN "ranked" AS lr
+    ON lr."feature_9" = p."feature_9"
+   AND lr."rn" = p."lower_rn"
+  JOIN "ranked" AS ur
+    ON ur."feature_9" = p."feature_9"
+   AND ur."rn" = p."upper_rn"
+)
+SELECT
+  "feature_9",
+  CASE
+    WHEN "lower_rn" = "upper_rn" THEN "lower_measure"
+    ELSE "lower_measure" + (("pos" - "lower_rn") * ("upper_measure" - "lower_measure"))
+  END AS "percentile_measure"
+FROM "bounds"
+ORDER BY "percentile_measure" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_5e4de333ec1e3b54/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_5e4de333ec1e3b54/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..97b483621ac957729731ab5a8be409e818400a04
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_5e4de333ec1e3b54/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH \"base\" AS (\n  SELECT\n    \"feature_9\",\n    CAST(\"feature_14\" AS REAL) AS \"measure\"\n  FROM \"n9\"\n  WHERE \"feature_9\" IS NOT NULL\n    AND \"feature_14\" IS NOT NULL\n),\n\"ranked\" AS (\n  SELECT\n    \"feature_9\",\n    \"measure\",\n    ROW_NUMBER() OVER (\n      PARTITION BY \"feature_9\"\n      ORDER BY \"measure\"\n    ) AS \"rn\",\n    COUNT(*) OVER (\n      PARTITION BY \"feature_9\"\n    ) AS \"cnt\"\n  FROM \"base\"\n),\n\"targets\" AS (\n  SELECT DISTINCT\n    \"feature_9\",\n    \"cnt\",\n    1.0 + (0.95 * (\"cnt\" - 1)) AS \"pos\"\n  FROM \"ranked\"\n),\n\"positions\" AS (\n  SELECT\n    \"feature_9\",\n    \"pos\",\n    CAST(\"pos\" AS INTEGER) AS \"lower_rn\",\n    CASE\n      WHEN ABS(\"pos\" - CAST(\"pos\" AS INTEGER)) < 1e-12 THEN CAST(\"pos\" AS INTEGER)\n      ELSE CAST(\"pos\" AS INTEGER) + 1\n    END AS \"upper_rn\"\n  FROM \"targets\"\n),\n\"bounds\" AS (\n  SELECT\n    p.\"feature_9\",\n    p.\"pos\",\n    p.\"lower_rn\",\n    p.\"upper_rn\",\n    lr.\"measure\" AS \"lower_measure\",\n    ur.\"measure\" AS \"upper_measure\"\n  FROM \"positions\" AS p\n  JOIN \"ranked\" AS lr\n    ON lr.\"feature_9\" = p.\"feature_9\"\n   AND lr.\"rn\" = p.\"lower_rn\"\n  JOIN \"ranked\" AS ur\n    ON ur.\"feature_9\" = p.\"feature_9\"\n   AND ur.\"rn\" = p.\"upper_rn\"\n)\nSELECT\n  \"feature_9\",\n  CASE\n    WHEN \"lower_rn\" = \"upper_rn\" THEN \"lower_measure\"\n    ELSE \"lower_measure\" + ((\"pos\" - \"lower_rn\") * (\"upper_measure\" - \"lower_measure\"))\n  END AS \"percentile_measure\"\nFROM \"bounds\"\nORDER BY \"percentile_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"base\\\" AS (\\n  SELECT\\n    \\\"feature_9\\\",\\n    CAST(\\\"feature_14\\\" AS REAL) AS \\\"measure\\\"\\n  FROM \\\"n9\\\"\\n  WHERE \\\"feature_9\\\" IS NOT NULL\\n    AND \\\"feature_14\\\" IS NOT NULL\\n),\\n\\\"ranked\\\" AS (\\n  SELECT\\n    \\\"feature_9\\\",\\n    \\\"measure\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"feature_9\\\"\\n      ORDER BY \\\"measure\\\"\\n    ) AS \\\"rn\\\",\\n    COUNT(*) OVER (\\n      PARTITION BY \\\"feature_9\\\"\\n    ) AS \\\"cnt\\\"\\n  FROM \\\"base\\\"\\n),\\n\\\"targets\\\" AS (\\n  SELECT DISTINCT\\n    \\\"feature_9\\\",\\n    \\\"cnt\\\",\\n    1.0 + (0.95 * (\\\"cnt\\\" - 1)) AS \\\"pos\\\"\\n  FROM \\\"ranked\\\"\\n),\\n\\\"positions\\\" AS (\\n  SELECT\\n    \\\"feature_9\\\",\\n    \\\"pos\\\",\\n    CAST(\\\"pos\\\" AS INTEGER) AS \\\"lower_rn\\\",\\n    CASE\\n      WHEN ABS(\\\"pos\\\" - CAST(\\\"pos\\\" AS INTEGER)) < 1e-12 THEN CAST(\\\"pos\\\" AS INTEGER)\\n      ELSE CAST(\\\"pos\\\" AS INTEGER) + 1\\n    END AS \\\"upper_rn\\\"\\n  FROM \\\"targets\\\"\\n),\\n\\\"bounds\\\" AS (\\n  SELECT\\n    p.\\\"feature_9\\\",\\n    p.\\\"pos\\\",\\n    p.\\\"lower_rn\\\",\\n    p.\\\"upper_rn\\\",\\n    lr.\\\"measure\\\" AS \\\"lower_measure\\\",\\n    ur.\\\"measure\\\" AS \\\"upper_measure\\\"\\n  FROM \\\"positions\\\" AS p\\n  JOIN \\\"ranked\\\" AS lr\\n    ON lr.\\\"feature_9\\\" = p.\\\"feature_9\\\"\\n   AND lr.\\\"rn\\\" = p.\\\"lower_rn\\\"\\n  JOIN \\\"ranked\\\" AS ur\\n    ON ur.\\\"feature_9\\\" = p.\\\"feature_9\\\"\\n   AND ur.\\\"rn\\\" = p.\\\"upper_rn\\\"\\n)\\nSELECT\\n  \\\"feature_9\\\",\\n  CASE\\n    WHEN \\\"lower_rn\\\" = \\\"upper_rn\\\" THEN \\\"lower_measure\\\"\\n    ELSE \\\"lower_measure\\\" + ((\\\"pos\\\" - \\\"lower_rn\\\") * (\\\"upper_measure\\\" - \\\"lower_measure\\\"))\\n  END AS \\\"percentile_measure\\\"\\nFROM \\\"bounds\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\", \"columns\": [\"feature_9\", \"percentile_measure\"], \"rows\": [{\"feature_9\": \"0\", \"percentile_measure\": 100.0}, {\"feature_9\": \"1\", \"percentile_measure\": 100.0}, {\"feature_9\": \"100\", \"percentile_measure\": 100.0}, {\"feature_9\": \"11\", \"percentile_measure\": 100.0}, {\"feature_9\": \"13\", \"percentile_measure\": 100.0}, {\"feature_9\": \"14\", \"percentile_measure\": 100.0}, {\"feature_9\": \"15\", \"percentile_measure\": 100.0}, {\"feature_9\": \"17\", \"percentile_measure\": 100.0}, {\"feature_9\": \"18\", \"percentile_measure\": 100.0}, {\"feature_9\": \"19\", \"percentile_measure\": 100.0}, {\"feature_9\": \"2\", \"percentile_measure\": 100.0}, {\"feature_9\": \"20\", \"percentile_measure\": 100.0}, {\"feature_9\": \"21\", \"percentile_measure\": 100.0}, {\"feature_9\": \"22\", \"percentile_measure\": 100.0}, {\"feature_9\": \"23\", \"percentile_measure\": 100.0}, {\"feature_9\": \"24\", \"percentile_measure\": 100.0}, {\"feature_9\": \"25\", \"percentile_measure\": 100.0}, {\"feature_9\": \"28\", \"percentile_measure\": 100.0}, {\"feature_9\": \"3\", \"percentile_measure\": 100.0}, {\"feature_9\": \"30\", \"percentile_measure\": 100.0}, {\"feature_9\": \"35\", \"percentile_measure\": 100.0}, {\"feature_9\": \"37\", \"percentile_measure\": 100.0}, {\"feature_9\": \"41\", \"percentile_measure\": 100.0}, {\"feature_9\": \"46\", \"percentile_measure\": 100.0}, {\"feature_9\": \"47\", \"percentile_measure\": 100.0}, {\"feature_9\": \"5\", \"percentile_measure\": 100.0}, {\"feature_9\": \"6\", \"percentile_measure\": 100.0}, {\"feature_9\": \"7\", \"percentile_measure\": 100.0}, {\"feature_9\": \"77\", \"percentile_measure\": 100.0}, {\"feature_9\": \"79\", \"percentile_measure\": 100.0}, {\"feature_9\": \"8\", \"percentile_measure\": 100.0}, {\"feature_9\": \"83\", \"percentile_measure\": 100.0}, {\"feature_9\": \"85\", \"percentile_measure\": 100.0}, {\"feature_9\": \"86\", \"percentile_measure\": 100.0}, {\"feature_9\": \"87\", \"percentile_measure\": 100.0}, {\"feature_9\": \"88\", \"percentile_measure\": 100.0}, {\"feature_9\": \"89\", \"percentile_measure\": 100.0}, {\"feature_9\": \"90\", \"percentile_measure\": 100.0}, {\"feature_9\": \"91\", \"percentile_measure\": 100.0}, {\"feature_9\": \"92\", \"percentile_measure\": 100.0}, {\"feature_9\": \"93\", \"percentile_measure\": 100.0}, {\"feature_9\": \"94\", \"percentile_measure\": 100.0}, {\"feature_9\": \"95\", \"percentile_measure\": 100.0}, {\"feature_9\": \"96\", \"percentile_measure\": 100.0}, {\"feature_9\": \"97\", \"percentile_measure\": 100.0}, {\"feature_9\": \"98\", \"percentile_measure\": 100.0}, {\"feature_9\": \"99\", \"percentile_measure\": 100.0}, {\"feature_9\": \"10\", \"percentile_measure\": 99.94999999999999}, {\"feature_9\": \"84\", \"percentile_measure\": 99.69999999999999}, {\"feature_9\": \"4\", \"percentile_measure\": 99.65}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 36.95}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_5e4de333ec1e3b54/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_5e4de333ec1e3b54/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..2e373149647951264d3e972bcc6e027b2995e64d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_5e4de333ec1e3b54/run_manifest.json
@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:59:55.164707+00:00",
+  "ended_at": "2026-05-19T16:00:58.412408+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_5e4de333ec1e3b54",
+    "problem_id": "v2p_n9_1419025a59f14835",
+    "dataset_id": "n9",
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_concentration_consistency",
+    "intended_facet_id": "rare_target_concentration",
+    "variant_semantic_role": "focused_target_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=feature_9, measure_col=feature_14.",
+    "bindings": {
+      "group_col": "feature_9",
+      "measure_col": "feature_14",
+      "top_k": 18,
+      "top_n": 5,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.05,
+      "baseline_multiplier": 1.75,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 4,
+      "measure_threshold": 36.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;",
+    "notes": [
+      "default_facets=rare_target_concentration",
+      "template_selection_mode=rule",
+      "problem_index_within_template=10",
+      "sql_variant_index=2/2",
+      "binding_index=93"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 8,
+    "problem_index_within_template": 10,
+    "sql_variant_index": 2,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_5e4de333ec1e3b54.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_5e4de333ec1e3b54",
+    "api_calls": 0,
+    "input_tokens": 14978,
+    "cached_input_tokens": 12032,
+    "output_tokens": 4217,
+    "total_tokens": 19195,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 63206.54,
+    "sql_execution_elapsed_ms_total": 36.95,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_5e4de333ec1e3b54/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_5e4de333ec1e3b54/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_5e4de333ec1e3b54/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..df46c5458a6681cd0186b7dc0cbb928417d8f015
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_5e4de333ec1e3b54/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T16:00:58.373525+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 63206.54, "started_at": "2026-05-19T15:59:55.166141+00:00", "ended_at": "2026-05-19T16:00:58.372707+00:00", "prompt_metrics": {"chars": 9572, "bytes_utf8": 9572, "lines": 300, "estimated_tokens": null}, "response_metrics": {"chars": 1929, "bytes_utf8": 1929, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14978, "cached_input_tokens": 12032, "output_tokens": 4217, "reasoning_output_tokens": 3599}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"base\\\" AS (\\n  SELECT\\n    \\\"feature_9\\\",\\n    CAST(\\\"feature_14\\\" AS REAL) AS \\\"measure\\\"\\n  FROM \\\"n9\\\"\\n  WHERE \\\"feature_9\\\" IS NOT NULL\\n    AND \\\"feature_14\\\" IS NOT NULL\\n),\\n\\\"ranked\\\" AS (\\n  SELECT\\n    \\\"feature_9\\\",\\n    \\\"measure\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"feature_9\\\"\\n      ORDER BY \\\"measure\\\"\\n    ) AS \\\"rn\\\",\\n    COUNT(*) OVER (\\n      PARTITION BY \\\"feature_9\\\"\\n    ) AS \\\"cnt\\\"\\n  FROM \\\"base\\\"\\n),\\n\\\"targets\\\" AS (\\n  SELECT DISTINCT\\n    \\\"feature_9\\\",\\n    \\\"cnt\\\",\\n    1.0 + (0.95 * (\\\"cnt\\\" - 1)) AS \\\"pos\\\"\\n  FROM \\\"ranked\\\"\\n),\\n\\\"positions\\\" AS (\\n  SELECT\\n    \\\"feature_9\\\",\\n    \\\"pos\\\",\\n    CAST(\\\"pos\\\" AS INTEGER) AS \\\"lower_rn\\\",\\n    CASE\\n      WHEN ABS(\\\"pos\\\" - CAST(\\\"pos\\\" AS INTEGER)) < 1e-12 THEN CAST(\\\"pos\\\" AS INTEGER)\\n      ELSE CAST(\\\"pos\\\" AS INTEGER) + 1\\n    END AS \\\"upper_rn\\\"\\n  FROM \\\"targets\\\"\\n),\\n\\\"bounds\\\" AS (\\n  SELECT\\n    p.\\\"feature_9\\\",\\n    "}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_5e4de333ec1e3b54/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_5e4de333ec1e3b54/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..fe75152dd503987db94774b14ac5ba216d5c3c48
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_5e4de333ec1e3b54/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_5e4de333ec1e3b54",
+  "api_calls": 0,
+  "input_tokens": 14978,
+  "cached_input_tokens": 12032,
+  "output_tokens": 4217,
+  "total_tokens": 19195,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 63206.54,
+  "sql_execution_elapsed_ms_total": 36.95,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_5e4de333ec1e3b54/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_5e876f335ec08f66/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_5e876f335ec08f66/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..27c0e34430d162dce9058b105c76193074cdbc52
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_5e876f335ec08f66/run_manifest.json
@@ -0,0 +1,72 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T16:01:28.207524+00:00",
+  "ended_at": "2026-05-19T16:01:35.820410+00:00",
+  "status": "failed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_5e876f335ec08f66",
+    "problem_id": "v2p_n9_3a83ba29a85d6f6e",
+    "dataset_id": "n9",
+    "template_id": "tpl_m4_group_condition_rate",
+    "template_name": "Grouped Condition Rate",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "direction_consistency",
+    "intended_facet_id": "conditional_rate_shift",
+    "variant_semantic_role": "within_group_proportion",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Condition Rate to probe direction_consistency with semantic role within_group_proportion. Focus on group_col=feature_13, condition_col=class.",
+    "bindings": {
+      "group_col": "feature_13",
+      "condition_col": "class",
+      "condition_value": "4",
+      "positive_value": "2",
+      "negative_value": "4",
+      "top_k": 17,
+      "top_n": 5,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.05,
+      "baseline_multiplier": 1.75,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 4,
+      "measure_threshold": 100.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "condition_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;",
+    "notes": [
+      "default_facets=conditional_rate_shift",
+      "template_selection_mode=rule",
+      "problem_index_within_template=2",
+      "sql_variant_index=2/2",
+      "binding_index=97"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 9,
+    "problem_index_within_template": 2,
+    "sql_variant_index": 2,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "error": "AI CLI command failed with exit code 1: "
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_5e876f335ec08f66/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_5e876f335ec08f66/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..bec8f049152b1299ecd825aca576e33ca8321a19
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_5e876f335ec08f66/trace.jsonl
@@ -0,0 +1,2 @@
+{"timestamp": "2026-05-19T16:01:31.620733+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3411.35, "started_at": "2026-05-19T16:01:28.208556+00:00", "ended_at": "2026-05-19T16:01:31.619938+00:00", "prompt_metrics": {"chars": 9627, "bytes_utf8": 9627, "lines": 303, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f8-818a-7b33-af6e-761e60de7557\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}
+{"timestamp": "2026-05-19T16:01:35.820317+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3197.18, "started_at": "2026-05-19T16:01:32.622365+00:00", "ended_at": "2026-05-19T16:01:35.819587+00:00", "prompt_metrics": {"chars": 9627, "bytes_utf8": 9627, "lines": 303, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f8-92cc-73d2-9623-a40a307c4ceb\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_600638f83ecb65a3/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_600638f83ecb65a3/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..db19fefb50bba3d0c75131c77769ff8254837258
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_600638f83ecb65a3/final_answer.txt
@@ -0,0 +1 @@
+{"row_count": null, "preview_rows": [{"value_label": "100", "support": 1115, "support_share": 0.10143740902474527, "support_rank": 1}, {"value_label": "0", "support": 397, "support_share": 0.03611717612809316, "support_rank": 2}, {"value_label": "78", "support": 211, "support_share": 0.019195778748180493, "support_rank": 3}, {"value_label": "75", "support": 207, "support_share": 0.01883187772925764, "support_rank": 4}, {"value_label": "79", "support": 205, "support_share": 0.018649927219796216, "support_rank": 5}]}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_600638f83ecb65a3/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_600638f83ecb65a3/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..4a42d4c17bfd91b70f09ef71fefeb3a6b15772db
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_600638f83ecb65a3/generated_sql.sql
@@ -0,0 +1,25 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: support_concentration
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_cardinality_support_rank_profile
+-- query_record_id: v2q_n9_600638f83ecb65a3
+-- problem_id: v2p_n9_23df0cf15e38f384
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_6" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_6"
+)
+SELECT
+    value_label,
+    support,
+    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank
+FROM grouped
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_600638f83ecb65a3/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_600638f83ecb65a3/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..dbdd06fe9597f5d0b92c827eaf38ffad41d1647a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_600638f83ecb65a3/query_results.jsonl
@@ -0,0 +1 @@
+{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: n9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: support_rank_profile_consistency\n-- intended_facet_id: support_concentration\n-- variant_semantic_role: count_distribution\n-- template_id: tpl_cardinality_support_rank_profile\n-- query_record_id: v2q_n9_600638f83ecb65a3\n-- problem_id: v2p_n9_23df0cf15e38f384\n-- realization_mode: deterministic\n-- source_kind: deterministic\nWITH grouped AS (\n    SELECT \"feature_6\" AS value_label, COUNT(*) AS support\n    FROM \"n9\"\n    GROUP BY \"feature_6\"\n)\nSELECT\n    value_label,\n    support,\n    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\nFROM grouped\nORDER BY support DESC, value_label;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: n9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: support_rank_profile_consistency\\n-- intended_facet_id: support_concentration\\n-- variant_semantic_role: count_distribution\\n-- template_id: tpl_cardinality_support_rank_profile\\n-- query_record_id: v2q_n9_600638f83ecb65a3\\n-- problem_id: v2p_n9_23df0cf15e38f384\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nWITH grouped AS (\\n    SELECT \\\"feature_6\\\" AS value_label, COUNT(*) AS support\\n    FROM \\\"n9\\\"\\n    GROUP BY \\\"feature_6\\\"\\n)\\nSELECT\\n    value_label,\\n    support,\\n    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\\n    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\\nFROM grouped\\nORDER BY support DESC, value_label;\", \"columns\": [\"value_label\", \"support\", \"support_share\", \"support_rank\"], \"rows\": [{\"value_label\": \"100\", \"support\": 1115, \"support_share\": 0.10143740902474527, \"support_rank\": 1}, {\"value_label\": \"0\", \"support\": 397, \"support_share\": 0.03611717612809316, \"support_rank\": 2}, {\"value_label\": \"78\", \"support\": 211, \"support_share\": 0.019195778748180493, \"support_rank\": 3}, {\"value_label\": \"75\", \"support\": 207, \"support_share\": 0.01883187772925764, \"support_rank\": 4}, {\"value_label\": \"79\", \"support\": 205, \"support_share\": 0.018649927219796216, \"support_rank\": 5}, {\"value_label\": \"72\", \"support\": 200, \"support_share\": 0.018195050946142648, \"support_rank\": 6}, {\"value_label\": \"76\", \"support\": 193, \"support_share\": 0.017558224163027658, \"support_rank\": 7}, {\"value_label\": \"77\", \"support\": 184, \"support_share\": 0.016739446870451237, \"support_rank\": 8}, {\"value_label\": \"74\", \"support\": 183, \"support_share\": 0.016648471615720525, \"support_rank\": 9}, {\"value_label\": \"73\", \"support\": 180, \"support_share\": 0.016375545851528384, \"support_rank\": 10}, {\"value_label\": \"70\", \"support\": 178, \"support_share\": 0.016193595342066956, \"support_rank\": 11}, {\"value_label\": \"71\", \"support\": 176, \"support_share\": 0.01601164483260553, \"support_rank\": 12}, {\"value_label\": \"80\", \"support\": 176, \"support_share\": 0.01601164483260553, \"support_rank\": 13}, {\"value_label\": \"82\", \"support\": 174, \"support_share\": 0.015829694323144104, \"support_rank\": 14}, {\"value_label\": \"68\", \"support\": 173, \"support_share\": 0.01573871906841339, \"support_rank\": 15}, {\"value_label\": \"67\", \"support\": 170, \"support_share\": 0.015465793304221253, \"support_rank\": 16}, {\"value_label\": \"83\", \"support\": 170, \"support_share\": 0.015465793304221253, \"support_rank\": 17}, {\"value_label\": \"81\", \"support\": 169, \"support_share\": 0.015374818049490539, \"support_rank\": 18}, {\"value_label\": \"69\", \"support\": 163, \"support_share\": 0.01482896652110626, \"support_rank\": 19}, {\"value_label\": \"88\", \"support\": 151, \"support_share\": 0.0137372634643377, \"support_rank\": 20}, {\"value_label\": \"66\", \"support\": 143, \"support_share\": 0.013009461426491994, \"support_rank\": 21}, {\"value_label\": \"65\", \"support\": 140, \"support_share\": 0.012736535662299854, \"support_rank\": 22}, {\"value_label\": \"85\", \"support\": 140, \"support_share\": 0.012736535662299854, \"support_rank\": 23}, {\"value_label\": \"99\", \"support\": 137, \"support_share\": 0.012463609898107715, \"support_rank\": 24}, {\"value_label\": \"91\", \"support\": 134, \"support_share\": 0.012190684133915575, \"support_rank\": 25}, {\"value_label\": \"84\", \"support\": 132, \"support_share\": 0.012008733624454149, \"support_rank\": 26}, {\"value_label\": \"94\", \"support\": 132, \"support_share\": 0.012008733624454149, \"support_rank\": 27}, {\"value_label\": \"87\", \"support\": 130, \"support_share\": 0.011826783114992722, \"support_rank\": 28}, {\"value_label\": \"98\", \"support\": 129, \"support_share\": 0.011735807860262008, \"support_rank\": 29}, {\"value_label\": \"86\", \"support\": 127, \"support_share\": 0.011553857350800582, \"support_rank\": 30}, {\"value_label\": \"97\", \"support\": 127, \"support_share\": 0.011553857350800582, \"support_rank\": 31}, {\"value_label\": \"95\", \"support\": 125, \"support_share\": 0.011371906841339156, \"support_rank\": 32}, {\"value_label\": \"52\", \"support\": 123, \"support_share\": 0.01118995633187773, \"support_rank\": 33}, {\"value_label\": \"59\", \"support\": 123, \"support_share\": 0.01118995633187773, \"support_rank\": 34}, {\"value_label\": \"89\", \"support\": 123, \"support_share\": 0.01118995633187773, \"support_rank\": 35}, {\"value_label\": \"60\", \"support\": 120, \"support_share\": 0.010917030567685589, \"support_rank\": 36}, {\"value_label\": \"62\", \"support\": 120, \"support_share\": 0.010917030567685589, \"support_rank\": 37}, {\"value_label\": \"49\", \"support\": 117, \"support_share\": 0.01064410480349345, \"support_rank\": 38}, {\"value_label\": \"61\", \"support\": 116, \"support_share\": 0.010553129548762736, \"support_rank\": 39}, {\"value_label\": \"63\", \"support\": 116, \"support_share\": 0.010553129548762736, \"support_rank\": 40}, {\"value_label\": \"55\", \"support\": 115, \"support_share\": 0.010462154294032024, \"support_rank\": 41}, {\"value_label\": \"58\", \"support\": 115, \"support_share\": 0.010462154294032024, \"support_rank\": 42}, {\"value_label\": \"56\", \"support\": 111, \"support_share\": 0.01009825327510917, \"support_rank\": 43}, {\"value_label\": \"90\", \"support\": 111, \"support_share\": 0.01009825327510917, \"support_rank\": 44}, {\"value_label\": \"96\", \"support\": 110, \"support_share\": 0.010007278020378457, \"support_rank\": 45}, {\"value_label\": \"53\", \"support\": 109, \"support_share\": 0.009916302765647743, \"support_rank\": 46}, {\"value_label\": \"57\", \"support\": 108, \"support_share\": 0.009825327510917031, \"support_rank\": 47}, {\"value_label\": \"64\", \"support\": 107, \"support_share\": 0.009734352256186317, \"support_rank\": 48}, {\"value_label\": \"93\", \"support\": 107, \"support_share\": 0.009734352256186317, \"support_rank\": 49}, {\"value_label\": \"50\", \"support\": 105, \"support_share\": 0.00955240174672489, \"support_rank\": 50}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 4.44}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_600638f83ecb65a3/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_600638f83ecb65a3/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..eb83480fb79c2ad949008d220d5e8eca3dd83d01
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_600638f83ecb65a3/run_manifest.json
@@ -0,0 +1,57 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T16:10:15.806018+00:00",
+  "ended_at": "2026-05-19T16:10:15.811259+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_600638f83ecb65a3",
+    "problem_id": "v2p_n9_23df0cf15e38f384",
+    "dataset_id": "n9",
+    "template_id": "tpl_cardinality_support_rank_profile",
+    "template_name": "Cardinality Support Rank Profile",
+    "family_id": "cardinality_structure",
+    "canonical_subitem_id": "support_rank_profile_consistency",
+    "intended_facet_id": "support_concentration",
+    "variant_semantic_role": "count_distribution",
+    "subitem_assignment_source": "template_fixed",
+    "source_kind": "deterministic",
+    "realization_mode": "deterministic",
+    "gate_priority": "deterministic",
+    "extended_family": true,
+    "question": "Use template Cardinality Support Rank Profile to probe support_rank_profile_consistency with semantic role count_distribution. Focus on group_col=feature_6.",
+    "bindings": {
+      "group_col": "feature_6"
+    },
+    "binding_roles": [
+      "group_col"
+    ],
+    "coverage_target_min": "enumerate_all_applicable",
+    "runtime_sql_skeleton": "WITH grouped AS (\n    SELECT {group_col} AS value_label, COUNT(*) AS support\n    FROM {table}\n    GROUP BY {group_col}\n)\nSELECT\n    value_label,\n    support,\n    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\nFROM grouped\nORDER BY support DESC, value_label;",
+    "notes": [
+      "default_facets=support_concentration,value_imbalance_profile",
+      "template_selection_mode=deterministic",
+      "problem_index_within_template=5",
+      "sql_variant_index=1/1"
+    ],
+    "template_selection_mode": "deterministic",
+    "selected_template_rank": 0,
+    "problem_index_within_template": 5,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_600638f83ecb65a3.sql",
+  "usage_summary": {
+    "engine": "template",
+    "input_tokens": 0,
+    "cached_input_tokens": 0,
+    "output_tokens": 0,
+    "total_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "none"
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_600638f83ecb65a3/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_600638f83ecb65a3/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_600638f83ecb65a3/usage_summary.json
@@ -0,0 +1,9 @@
+{
+  "engine": "template",
+  "input_tokens": 0,
+  "cached_input_tokens": 0,
+  "output_tokens": 0,
+  "total_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "none"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6143539db4c6b126/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6143539db4c6b126/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..ecb4893d164c5358f765160e94facb61cc959161
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6143539db4c6b126/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=feature_14.
+Result preview: [{"empirical_cdf_at_threshold": 0.7503639010189228}]
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6143539db4c6b126/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6143539db4c6b126/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..a9f98b2ea318a6f30a1f53dd578a20cde084f75b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6143539db4c6b126/generated_sql.sql
@@ -0,0 +1,15 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_set_consistency
+-- intended_facet_id: low_support_extremes
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_threshold_rarity_cdf
+-- query_record_id: v2q_n9_6143539db4c6b126
+-- problem_id: v2p_n9_e7e40418c024d312
+-- realization_mode: agent
+-- source_kind: agent
+SELECT AVG(CASE WHEN CAST("feature_14" AS REAL) <= 47.0 THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold
+FROM "n9";
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6143539db4c6b126/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6143539db4c6b126/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..851daed027de18544d9887c764b5236bdd2fcba5
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6143539db4c6b126/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 2, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_threshold_rarity_cdf\nSELECT AVG(CASE WHEN CAST(\"feature_14\" AS REAL) <= 47.0 THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM \"n9\";", "result": "{\"query\": \"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(\\\"feature_14\\\" AS REAL) <= 47.0 THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\\nFROM \\\"n9\\\";\", \"columns\": [\"empirical_cdf_at_threshold\"], \"rows\": [{\"empirical_cdf_at_threshold\": 0.7503639010189228}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 1.87}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6143539db4c6b126/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6143539db4c6b126/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..64d2d2f7762f87b6a98e4d8a0631ced3c7f010d7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6143539db4c6b126/run_manifest.json
@@ -0,0 +1,87 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T16:03:51.918648+00:00",
+  "ended_at": "2026-05-19T16:04:03.561465+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_6143539db4c6b126",
+    "problem_id": "v2p_n9_e7e40418c024d312",
+    "dataset_id": "n9",
+    "template_id": "tpl_threshold_rarity_cdf",
+    "template_name": "Threshold Rarity CDF",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_set_consistency",
+    "intended_facet_id": "low_support_extremes",
+    "variant_semantic_role": "rare_extreme_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=feature_14.",
+    "bindings": {
+      "measure_col": "feature_14",
+      "top_k": 14,
+      "top_n": 4,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 47.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};",
+    "notes": [
+      "default_facets=low_support_extremes",
+      "template_selection_mode=rule",
+      "problem_index_within_template=2",
+      "sql_variant_index=1/1",
+      "binding_index=109"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 10,
+    "problem_index_within_template": 2,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_6143539db4c6b126.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_6143539db4c6b126",
+    "api_calls": 0,
+    "input_tokens": 14927,
+    "cached_input_tokens": 13696,
+    "output_tokens": 232,
+    "total_tokens": 15159,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 2,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 10635.02,
+    "sql_execution_elapsed_ms_total": 1.87,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6143539db4c6b126/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6143539db4c6b126/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6143539db4c6b126/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..1800f7754068c90f3bd4326cd6ca200e197528f0
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6143539db4c6b126/trace.jsonl
@@ -0,0 +1,2 @@
+{"timestamp": "2026-05-19T16:03:55.040319+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3118.66, "started_at": "2026-05-19T16:03:51.920568+00:00", "ended_at": "2026-05-19T16:03:55.039260+00:00", "prompt_metrics": {"chars": 9325, "bytes_utf8": 9325, "lines": 298, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fa-b2f8-7c71-b875-d8f5b0547363\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}
+{"timestamp": "2026-05-19T16:04:03.558343+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 7516.36, "started_at": "2026-05-19T16:03:56.041213+00:00", "ended_at": "2026-05-19T16:04:03.557607+00:00", "prompt_metrics": {"chars": 9325, "bytes_utf8": 9325, "lines": 298, "estimated_tokens": null}, "response_metrics": {"chars": 377, "bytes_utf8": 377, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14927, "cached_input_tokens": 13696, "output_tokens": 232, "reasoning_output_tokens": 122}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(\\\"feature_14\\\" AS REAL) <= 47.0 THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\\nFROM \\\"n9\\\";\",\"notes\":\"Applied the Threshold Rarity CDF template with measure_col bound to \\\"feature_14\\\" and measure_threshold fixed at 47.0. Casted \\\"feature_14\\\" to REAL because the SQLite schema stores it as TEXT.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6143539db4c6b126/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6143539db4c6b126/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..e446f43ab0bf11b006974179404d6a6d7f4eb643
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6143539db4c6b126/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_6143539db4c6b126",
+  "api_calls": 0,
+  "input_tokens": 14927,
+  "cached_input_tokens": 13696,
+  "output_tokens": 232,
+  "total_tokens": 15159,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 2,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 10635.02,
+  "sql_execution_elapsed_ms_total": 1.87,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6143539db4c6b126/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_64a2d4d4dcbbab9b/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_64a2d4d4dcbbab9b/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..6a2fe9a0ffd6f8e888d0b94885d634f1b272192b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_64a2d4d4dcbbab9b/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=feature_1, measure_col=feature_6.
+Result preview: [{"feature_1": "0", "percentile_measure": 100.0}, {"feature_1": "1", "percentile_measure": 100.0}, {"feature_1": "10", "percentile_measure": 100.0}, {"feature_1": "12", "percentile_measure": 100.0}, {"feature_1": "2", "percentile_measure": 100.0}] Results were truncated.
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_64a2d4d4dcbbab9b/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_64a2d4d4dcbbab9b/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..4a7a4fb2c02f408967cfd0dcc726f83c961c443b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_64a2d4d4dcbbab9b/generated_sql.sql
@@ -0,0 +1,38 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_n9_64a2d4d4dcbbab9b
+-- problem_id: v2p_n9_6be6539cf6587990
+-- realization_mode: agent
+-- source_kind: agent
+WITH "ranked" AS (
+  SELECT
+    "feature_1",
+    CAST("feature_6" AS REAL) AS "measure_value",
+    CUME_DIST() OVER (
+      PARTITION BY "feature_1"
+      ORDER BY CAST("feature_6" AS REAL)
+    ) AS "cume_dist_value"
+  FROM "n9"
+  WHERE "feature_1" IS NOT NULL
+    AND "feature_6" IS NOT NULL
+),
+"percentiles" AS (
+  SELECT
+    "feature_1",
+    MIN("measure_value") AS "percentile_measure"
+  FROM "ranked"
+  WHERE "cume_dist_value" >= 0.9
+  GROUP BY "feature_1"
+)
+SELECT
+  "feature_1",
+  "percentile_measure"
+FROM "percentiles"
+ORDER BY "percentile_measure" DESC, "feature_1";
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_64a2d4d4dcbbab9b/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_64a2d4d4dcbbab9b/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..f69b7e166fac8dea406d957ef5c0673183bc0f65
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_64a2d4d4dcbbab9b/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH \"ranked\" AS (\n  SELECT\n    \"feature_1\",\n    CAST(\"feature_6\" AS REAL) AS \"measure_value\",\n    CUME_DIST() OVER (\n      PARTITION BY \"feature_1\"\n      ORDER BY CAST(\"feature_6\" AS REAL)\n    ) AS \"cume_dist_value\"\n  FROM \"n9\"\n  WHERE \"feature_1\" IS NOT NULL\n    AND \"feature_6\" IS NOT NULL\n),\n\"percentiles\" AS (\n  SELECT\n    \"feature_1\",\n    MIN(\"measure_value\") AS \"percentile_measure\"\n  FROM \"ranked\"\n  WHERE \"cume_dist_value\" >= 0.9\n  GROUP BY \"feature_1\"\n)\nSELECT\n  \"feature_1\",\n  \"percentile_measure\"\nFROM \"percentiles\"\nORDER BY \"percentile_measure\" DESC, \"feature_1\";", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n  SELECT\\n    \\\"feature_1\\\",\\n    CAST(\\\"feature_6\\\" AS REAL) AS \\\"measure_value\\\",\\n    CUME_DIST() OVER (\\n      PARTITION BY \\\"feature_1\\\"\\n      ORDER BY CAST(\\\"feature_6\\\" AS REAL)\\n    ) AS \\\"cume_dist_value\\\"\\n  FROM \\\"n9\\\"\\n  WHERE \\\"feature_1\\\" IS NOT NULL\\n    AND \\\"feature_6\\\" IS NOT NULL\\n),\\n\\\"percentiles\\\" AS (\\n  SELECT\\n    \\\"feature_1\\\",\\n    MIN(\\\"measure_value\\\") AS \\\"percentile_measure\\\"\\n  FROM \\\"ranked\\\"\\n  WHERE \\\"cume_dist_value\\\" >= 0.9\\n  GROUP BY \\\"feature_1\\\"\\n)\\nSELECT\\n  \\\"feature_1\\\",\\n  \\\"percentile_measure\\\"\\nFROM \\\"percentiles\\\"\\nORDER BY \\\"percentile_measure\\\" DESC, \\\"feature_1\\\";\", \"columns\": [\"feature_1\", \"percentile_measure\"], \"rows\": [{\"feature_1\": \"0\", \"percentile_measure\": 100.0}, {\"feature_1\": \"1\", \"percentile_measure\": 100.0}, {\"feature_1\": \"10\", \"percentile_measure\": 100.0}, {\"feature_1\": \"12\", \"percentile_measure\": 100.0}, {\"feature_1\": \"2\", \"percentile_measure\": 100.0}, {\"feature_1\": \"22\", \"percentile_measure\": 100.0}, {\"feature_1\": \"23\", \"percentile_measure\": 100.0}, {\"feature_1\": \"3\", \"percentile_measure\": 100.0}, {\"feature_1\": \"31\", \"percentile_measure\": 100.0}, {\"feature_1\": \"33\", \"percentile_measure\": 100.0}, {\"feature_1\": \"4\", \"percentile_measure\": 100.0}, {\"feature_1\": \"48\", \"percentile_measure\": 100.0}, {\"feature_1\": \"49\", \"percentile_measure\": 100.0}, {\"feature_1\": \"5\", \"percentile_measure\": 100.0}, {\"feature_1\": \"53\", \"percentile_measure\": 100.0}, {\"feature_1\": \"54\", \"percentile_measure\": 100.0}, {\"feature_1\": \"57\", \"percentile_measure\": 100.0}, {\"feature_1\": \"58\", \"percentile_measure\": 100.0}, {\"feature_1\": \"59\", \"percentile_measure\": 100.0}, {\"feature_1\": \"6\", \"percentile_measure\": 100.0}, {\"feature_1\": \"60\", \"percentile_measure\": 100.0}, {\"feature_1\": \"61\", \"percentile_measure\": 100.0}, {\"feature_1\": \"62\", \"percentile_measure\": 100.0}, {\"feature_1\": \"63\", \"percentile_measure\": 100.0}, {\"feature_1\": \"68\", \"percentile_measure\": 100.0}, {\"feature_1\": \"69\", \"percentile_measure\": 100.0}, {\"feature_1\": \"7\", \"percentile_measure\": 100.0}, {\"feature_1\": \"70\", \"percentile_measure\": 100.0}, {\"feature_1\": \"71\", \"percentile_measure\": 100.0}, {\"feature_1\": \"79\", \"percentile_measure\": 100.0}, {\"feature_1\": \"8\", \"percentile_measure\": 100.0}, {\"feature_1\": \"9\", \"percentile_measure\": 100.0}, {\"feature_1\": \"13\", \"percentile_measure\": 99.0}, {\"feature_1\": \"19\", \"percentile_measure\": 99.0}, {\"feature_1\": \"21\", \"percentile_measure\": 99.0}, {\"feature_1\": \"24\", \"percentile_measure\": 99.0}, {\"feature_1\": \"28\", \"percentile_measure\": 99.0}, {\"feature_1\": \"39\", \"percentile_measure\": 99.0}, {\"feature_1\": \"45\", \"percentile_measure\": 99.0}, {\"feature_1\": \"11\", \"percentile_measure\": 98.0}, {\"feature_1\": \"15\", \"percentile_measure\": 98.0}, {\"feature_1\": \"18\", \"percentile_measure\": 98.0}, {\"feature_1\": \"30\", \"percentile_measure\": 98.0}, {\"feature_1\": \"46\", \"percentile_measure\": 98.0}, {\"feature_1\": \"64\", \"percentile_measure\": 98.0}, {\"feature_1\": \"92\", \"percentile_measure\": 98.0}, {\"feature_1\": \"95\", \"percentile_measure\": 98.0}, {\"feature_1\": \"14\", \"percentile_measure\": 97.0}, {\"feature_1\": \"29\", \"percentile_measure\": 97.0}, {\"feature_1\": \"36\", \"percentile_measure\": 97.0}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 27.91}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_64a2d4d4dcbbab9b/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_64a2d4d4dcbbab9b/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..7679e3987614ae221be4b865a9bbcad601026300
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_64a2d4d4dcbbab9b/run_manifest.json
@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:51:28.745272+00:00",
+  "ended_at": "2026-05-19T15:51:52.273112+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_64a2d4d4dcbbab9b",
+    "problem_id": "v2p_n9_6be6539cf6587990",
+    "dataset_id": "n9",
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_concentration_consistency",
+    "intended_facet_id": "rare_target_concentration",
+    "variant_semantic_role": "ranked_signal_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=feature_1, measure_col=feature_6.",
+    "bindings": {
+      "group_col": "feature_1",
+      "measure_col": "feature_6",
+      "top_k": 10,
+      "top_n": 4,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 86.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;",
+    "notes": [
+      "default_facets=rare_target_concentration",
+      "template_selection_mode=rule",
+      "problem_index_within_template=2",
+      "sql_variant_index=1/2",
+      "binding_index=85"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 8,
+    "problem_index_within_template": 2,
+    "sql_variant_index": 1,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_64a2d4d4dcbbab9b.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_64a2d4d4dcbbab9b",
+    "api_calls": 0,
+    "input_tokens": 14978,
+    "cached_input_tokens": 13696,
+    "output_tokens": 1370,
+    "total_tokens": 16348,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 23495.25,
+    "sql_execution_elapsed_ms_total": 27.91,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_64a2d4d4dcbbab9b/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_64a2d4d4dcbbab9b/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_64a2d4d4dcbbab9b/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..acab8f948c388d81b149ca783791f06d321386a1
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_64a2d4d4dcbbab9b/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:51:52.243006+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 23495.25, "started_at": "2026-05-19T15:51:28.746574+00:00", "ended_at": "2026-05-19T15:51:52.241851+00:00", "prompt_metrics": {"chars": 9566, "bytes_utf8": 9566, "lines": 300, "estimated_tokens": null}, "response_metrics": {"chars": 929, "bytes_utf8": 929, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14978, "cached_input_tokens": 13696, "output_tokens": 1370, "reasoning_output_tokens": 1090}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n  SELECT\\n    \\\"feature_1\\\",\\n    CAST(\\\"feature_6\\\" AS REAL) AS \\\"measure_value\\\",\\n    CUME_DIST() OVER (\\n      PARTITION BY \\\"feature_1\\\"\\n      ORDER BY CAST(\\\"feature_6\\\" AS REAL)\\n    ) AS \\\"cume_dist_value\\\"\\n  FROM \\\"n9\\\"\\n  WHERE \\\"feature_1\\\" IS NOT NULL\\n    AND \\\"feature_6\\\" IS NOT NULL\\n),\\n\\\"percentiles\\\" AS (\\n  SELECT\\n    \\\"feature_1\\\",\\n    MIN(\\\"measure_value\\\") AS \\\"percentile_measure\\\"\\n  FROM \\\"ranked\\\"\\n  WHERE \\\"cume_dist_value\\\" >= 0.9\\n  GROUP BY \\\"feature_1\\\"\\n)\\nSELECT\\n  \\\"feature_1\\\",\\n  \\\"percentile_measure\\\"\\nFROM \\\"percentiles\\\"\\nORDER BY \\\"percentile_measure\\\" DESC, \\\"feature_1\\\";\",\"notes\":\"SQLite does not support PERCENTILE_CONT, so this query uses CUME_DIST() to approximate the grouped 90th percentile point for \\\"feature_6\\\" within each \\\"feature_1\\\" group, casting the TEXT measure column to REAL first.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_64a2d4d4dcbbab9b/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_64a2d4d4dcbbab9b/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..8b5b17e122c6b6e5520d9eef146070f4d4eb6c03
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_64a2d4d4dcbbab9b/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_64a2d4d4dcbbab9b",
+  "api_calls": 0,
+  "input_tokens": 14978,
+  "cached_input_tokens": 13696,
+  "output_tokens": 1370,
+  "total_tokens": 16348,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 23495.25,
+  "sql_execution_elapsed_ms_total": 27.91,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_64a2d4d4dcbbab9b/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_66d15541665feda3/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_66d15541665feda3/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..9689413b8ca495074706b7a94ae16d31bc934d87
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_66d15541665feda3/final_answer.txt
@@ -0,0 +1 @@
+{"row_count": null, "preview_rows": [{"value_label": "100", "support": 509, "support_share": 0.046306404657933044, "support_rank": 1}, {"value_label": "50", "support": 443, "support_share": 0.04030203784570597, "support_rank": 2}, {"value_label": "51", "support": 313, "support_share": 0.028475254730713245, "support_rank": 3}, {"value_label": "49", "support": 298, "support_share": 0.027110625909752547, "support_rank": 4}, {"value_label": "53", "support": 256, "support_share": 0.023289665211062592, "support_rank": 5}]}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_66d15541665feda3/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_66d15541665feda3/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..5101998d1f8a89e4a4863f92ad8a9ef5c962ff3e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_66d15541665feda3/generated_sql.sql
@@ -0,0 +1,25 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: value_imbalance_profile
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_cardinality_support_rank_profile
+-- query_record_id: v2q_n9_66d15541665feda3
+-- problem_id: v2p_n9_3b8473c4cad49fb3
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_13" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_13"
+)
+SELECT
+    value_label,
+    support,
+    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank
+FROM grouped
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_66d15541665feda3/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_66d15541665feda3/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..e2cc03780e4e1b911a673c37bf4a650beaf88dcc
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_66d15541665feda3/query_results.jsonl
@@ -0,0 +1 @@
+{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: n9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: support_rank_profile_consistency\n-- intended_facet_id: value_imbalance_profile\n-- variant_semantic_role: count_distribution\n-- template_id: tpl_cardinality_support_rank_profile\n-- query_record_id: v2q_n9_66d15541665feda3\n-- problem_id: v2p_n9_3b8473c4cad49fb3\n-- realization_mode: deterministic\n-- source_kind: deterministic\nWITH grouped AS (\n    SELECT \"feature_13\" AS value_label, COUNT(*) AS support\n    FROM \"n9\"\n    GROUP BY \"feature_13\"\n)\nSELECT\n    value_label,\n    support,\n    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\nFROM grouped\nORDER BY support DESC, value_label;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: n9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: support_rank_profile_consistency\\n-- intended_facet_id: value_imbalance_profile\\n-- variant_semantic_role: count_distribution\\n-- template_id: tpl_cardinality_support_rank_profile\\n-- query_record_id: v2q_n9_66d15541665feda3\\n-- problem_id: v2p_n9_3b8473c4cad49fb3\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nWITH grouped AS (\\n    SELECT \\\"feature_13\\\" AS value_label, COUNT(*) AS support\\n    FROM \\\"n9\\\"\\n    GROUP BY \\\"feature_13\\\"\\n)\\nSELECT\\n    value_label,\\n    support,\\n    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\\n    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\\nFROM grouped\\nORDER BY support DESC, value_label;\", \"columns\": [\"value_label\", \"support\", \"support_share\", \"support_rank\"], \"rows\": [{\"value_label\": \"100\", \"support\": 509, \"support_share\": 0.046306404657933044, \"support_rank\": 1}, {\"value_label\": \"50\", \"support\": 443, \"support_share\": 0.04030203784570597, \"support_rank\": 2}, {\"value_label\": \"51\", \"support\": 313, \"support_share\": 0.028475254730713245, \"support_rank\": 3}, {\"value_label\": \"49\", \"support\": 298, \"support_share\": 0.027110625909752547, \"support_rank\": 4}, {\"value_label\": \"53\", \"support\": 256, \"support_share\": 0.023289665211062592, \"support_rank\": 5}, {\"value_label\": \"52\", \"support\": 255, \"support_share\": 0.023198689956331876, \"support_rank\": 6}, {\"value_label\": \"48\", \"support\": 250, \"support_share\": 0.02274381368267831, \"support_rank\": 7}, {\"value_label\": \"55\", \"support\": 225, \"support_share\": 0.02046943231441048, \"support_rank\": 8}, {\"value_label\": \"46\", \"support\": 218, \"support_share\": 0.019832605531295486, \"support_rank\": 9}, {\"value_label\": \"56\", \"support\": 217, \"support_share\": 0.019741630276564774, \"support_rank\": 10}, {\"value_label\": \"54\", \"support\": 209, \"support_share\": 0.01901382823871907, \"support_rank\": 11}, {\"value_label\": \"60\", \"support\": 208, \"support_share\": 0.018922852983988356, \"support_rank\": 12}, {\"value_label\": \"45\", \"support\": 205, \"support_share\": 0.018649927219796216, \"support_rank\": 13}, {\"value_label\": \"58\", \"support\": 205, \"support_share\": 0.018649927219796216, \"support_rank\": 14}, {\"value_label\": \"62\", \"support\": 200, \"support_share\": 0.018195050946142648, \"support_rank\": 15}, {\"value_label\": \"57\", \"support\": 199, \"support_share\": 0.018104075691411935, \"support_rank\": 16}, {\"value_label\": \"41\", \"support\": 192, \"support_share\": 0.017467248908296942, \"support_rank\": 17}, {\"value_label\": \"47\", \"support\": 192, \"support_share\": 0.017467248908296942, \"support_rank\": 18}, {\"value_label\": \"0\", \"support\": 186, \"support_share\": 0.016921397379912665, \"support_rank\": 19}, {\"value_label\": \"43\", \"support\": 184, \"support_share\": 0.016739446870451237, \"support_rank\": 20}, {\"value_label\": \"42\", \"support\": 182, \"support_share\": 0.016557496360989812, \"support_rank\": 21}, {\"value_label\": \"44\", \"support\": 181, \"support_share\": 0.016466521106259097, \"support_rank\": 22}, {\"value_label\": \"61\", \"support\": 171, \"support_share\": 0.015556768558951965, \"support_rank\": 23}, {\"value_label\": \"38\", \"support\": 161, \"support_share\": 0.014647016011644833, \"support_rank\": 24}, {\"value_label\": \"40\", \"support\": 157, \"support_share\": 0.014283114992721979, \"support_rank\": 25}, {\"value_label\": \"59\", \"support\": 155, \"support_share\": 0.014101164483260552, \"support_rank\": 26}, {\"value_label\": \"37\", \"support\": 150, \"support_share\": 0.013646288209606987, \"support_rank\": 27}, {\"value_label\": \"64\", \"support\": 141, \"support_share\": 0.012827510917030568, \"support_rank\": 28}, {\"value_label\": \"63\", \"support\": 139, \"support_share\": 0.012645560407569142, \"support_rank\": 29}, {\"value_label\": \"65\", \"support\": 138, \"support_share\": 0.012554585152838428, \"support_rank\": 30}, {\"value_label\": \"39\", \"support\": 136, \"support_share\": 0.012372634643377001, \"support_rank\": 31}, {\"value_label\": \"66\", \"support\": 133, \"support_share\": 0.012099708879184861, \"support_rank\": 32}, {\"value_label\": \"68\", \"support\": 133, \"support_share\": 0.012099708879184861, \"support_rank\": 33}, {\"value_label\": \"36\", \"support\": 129, \"support_share\": 0.011735807860262008, \"support_rank\": 34}, {\"value_label\": \"67\", \"support\": 124, \"support_share\": 0.011280931586608443, \"support_rank\": 35}, {\"value_label\": \"35\", \"support\": 122, \"support_share\": 0.011098981077147015, \"support_rank\": 36}, {\"value_label\": \"70\", \"support\": 115, \"support_share\": 0.010462154294032024, \"support_rank\": 37}, {\"value_label\": \"69\", \"support\": 105, \"support_share\": 0.00955240174672489, \"support_rank\": 38}, {\"value_label\": \"34\", \"support\": 101, \"support_share\": 0.009188500727802038, \"support_rank\": 39}, {\"value_label\": \"76\", \"support\": 101, \"support_share\": 0.009188500727802038, \"support_rank\": 40}, {\"value_label\": \"32\", \"support\": 100, \"support_share\": 0.009097525473071324, \"support_rank\": 41}, {\"value_label\": \"80\", \"support\": 97, \"support_share\": 0.008824599708879185, \"support_rank\": 42}, {\"value_label\": \"33\", \"support\": 96, \"support_share\": 0.008733624454148471, \"support_rank\": 43}, {\"value_label\": \"78\", \"support\": 93, \"support_share\": 0.008460698689956333, \"support_rank\": 44}, {\"value_label\": \"75\", \"support\": 92, \"support_share\": 0.008369723435225618, \"support_rank\": 45}, {\"value_label\": \"73\", \"support\": 90, \"support_share\": 0.008187772925764192, \"support_rank\": 46}, {\"value_label\": \"74\", \"support\": 89, \"support_share\": 0.008096797671033478, \"support_rank\": 47}, {\"value_label\": \"29\", \"support\": 87, \"support_share\": 0.007914847161572052, \"support_rank\": 48}, {\"value_label\": \"84\", \"support\": 86, \"support_share\": 0.00782387190684134, \"support_rank\": 49}, {\"value_label\": \"71\", \"support\": 82, \"support_share\": 0.007459970887918486, \"support_rank\": 50}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 4.57}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_66d15541665feda3/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_66d15541665feda3/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..8adc2b685f27fca20269da641aa1be497ce3770d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_66d15541665feda3/run_manifest.json
@@ -0,0 +1,57 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T16:10:15.834775+00:00",
+  "ended_at": "2026-05-19T16:10:15.840195+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_66d15541665feda3",
+    "problem_id": "v2p_n9_3b8473c4cad49fb3",
+    "dataset_id": "n9",
+    "template_id": "tpl_cardinality_support_rank_profile",
+    "template_name": "Cardinality Support Rank Profile",
+    "family_id": "cardinality_structure",
+    "canonical_subitem_id": "support_rank_profile_consistency",
+    "intended_facet_id": "value_imbalance_profile",
+    "variant_semantic_role": "count_distribution",
+    "subitem_assignment_source": "template_fixed",
+    "source_kind": "deterministic",
+    "realization_mode": "deterministic",
+    "gate_priority": "deterministic",
+    "extended_family": true,
+    "question": "Use template Cardinality Support Rank Profile to probe support_rank_profile_consistency with semantic role count_distribution. Focus on group_col=feature_13.",
+    "bindings": {
+      "group_col": "feature_13"
+    },
+    "binding_roles": [
+      "group_col"
+    ],
+    "coverage_target_min": "enumerate_all_applicable",
+    "runtime_sql_skeleton": "WITH grouped AS (\n    SELECT {group_col} AS value_label, COUNT(*) AS support\n    FROM {table}\n    GROUP BY {group_col}\n)\nSELECT\n    value_label,\n    support,\n    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\nFROM grouped\nORDER BY support DESC, value_label;",
+    "notes": [
+      "default_facets=support_concentration,value_imbalance_profile",
+      "template_selection_mode=deterministic",
+      "problem_index_within_template=10",
+      "sql_variant_index=1/1"
+    ],
+    "template_selection_mode": "deterministic",
+    "selected_template_rank": 0,
+    "problem_index_within_template": 10,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_66d15541665feda3.sql",
+  "usage_summary": {
+    "engine": "template",
+    "input_tokens": 0,
+    "cached_input_tokens": 0,
+    "output_tokens": 0,
+    "total_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "none"
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_66d15541665feda3/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_66d15541665feda3/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_66d15541665feda3/usage_summary.json
@@ -0,0 +1,9 @@
+{
+  "engine": "template",
+  "input_tokens": 0,
+  "cached_input_tokens": 0,
+  "output_tokens": 0,
+  "total_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "none"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6c6df2e940326b15/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6c6df2e940326b15/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..b62ca339e49b02988b07a46013cc924d97dde65b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6c6df2e940326b15/generated_sql.sql
@@ -0,0 +1,22 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_set_consistency
+-- intended_facet_id: low_support_extremes
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_m4_quantile_tail_slice
+-- query_record_id: v2q_n9_6c6df2e940326b15
+-- problem_id: v2p_n9_4fdf003f96d9b191
+-- realization_mode: agent
+-- source_kind: agent
+WITH buckets AS (
+    SELECT CAST("feature_4" AS REAL) AS "feature_4",
+           NTILE(10) OVER (ORDER BY CAST("feature_4" AS REAL) DESC) AS "tail_bucket"
+    FROM "n9"
+)
+SELECT "feature_4"
+FROM buckets
+WHERE "tail_bucket" = 1
+ORDER BY "feature_4" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6c6df2e940326b15/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6c6df2e940326b15/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..ba629524ec7a57ea3ce22e915f34f681a0d936bb
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6c6df2e940326b15/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_quantile_tail_slice\nWITH buckets AS (\n    SELECT CAST(\"feature_4\" AS REAL) AS \"feature_4\",\n           NTILE(10) OVER (ORDER BY CAST(\"feature_4\" AS REAL) DESC) AS \"tail_bucket\"\n    FROM \"n9\"\n)\nSELECT \"feature_4\"\nFROM buckets\nWHERE \"tail_bucket\" = 1\nORDER BY \"feature_4\" DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_quantile_tail_slice\\nWITH buckets AS (\\n    SELECT CAST(\\\"feature_4\\\" AS REAL) AS \\\"feature_4\\\",\\n           NTILE(10) OVER (ORDER BY CAST(\\\"feature_4\\\" AS REAL) DESC) AS \\\"tail_bucket\\\"\\n    FROM \\\"n9\\\"\\n)\\nSELECT \\\"feature_4\\\"\\nFROM buckets\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY \\\"feature_4\\\" DESC;\", \"columns\": [\"feature_4\"], \"rows\": [{\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}, {\"feature_4\": 100.0}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 24.63}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6c6df2e940326b15/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6c6df2e940326b15/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..f78d2f781ab8024d5565cf9211b4bbcc7a0e158c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6c6df2e940326b15/run_manifest.json
@@ -0,0 +1,87 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:45:34.000315+00:00",
+  "ended_at": "2026-05-19T15:45:52.908410+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_6c6df2e940326b15",
+    "problem_id": "v2p_n9_4fdf003f96d9b191",
+    "dataset_id": "n9",
+    "template_id": "tpl_m4_quantile_tail_slice",
+    "template_name": "Quantile Tail Slice",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_set_consistency",
+    "intended_facet_id": "low_support_extremes",
+    "variant_semantic_role": "rare_extreme_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=feature_4.",
+    "bindings": {
+      "measure_col": "feature_4",
+      "top_k": 12,
+      "top_n": 6,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 100.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "WITH buckets AS (\n    SELECT {measure_col},\n           NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n    FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;",
+    "notes": [
+      "default_facets=low_support_extremes",
+      "template_selection_mode=rule",
+      "problem_index_within_template=8",
+      "sql_variant_index=1/1",
+      "binding_index=67"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 6,
+    "problem_index_within_template": 8,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_6c6df2e940326b15.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_6c6df2e940326b15",
+    "api_calls": 0,
+    "input_tokens": 14991,
+    "cached_input_tokens": 13696,
+    "output_tokens": 409,
+    "total_tokens": 15400,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 18878.88,
+    "sql_execution_elapsed_ms_total": 24.63,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6c6df2e940326b15/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6c6df2e940326b15/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6c6df2e940326b15/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..e4bd2f9019eb449ae171a282c6af3dc9be2037a6
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6c6df2e940326b15/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_6c6df2e940326b15",
+  "api_calls": 0,
+  "input_tokens": 14991,
+  "cached_input_tokens": 13696,
+  "output_tokens": 409,
+  "total_tokens": 15400,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 18878.88,
+  "sql_execution_elapsed_ms_total": 24.63,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_6c6df2e940326b15/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_79f6d2c0a420d0c0/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_79f6d2c0a420d0c0/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..eacb5b7b4fd15c08396326d5803b381e8c8d9f9f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_79f6d2c0a420d0c0/final_answer.txt
@@ -0,0 +1 @@
+{"row_count": null, "preview_rows": [{"feature_12": "0", "support": 1227, "avg_response": 36.66259168704156}, {"feature_12": "50", "support": 224, "avg_response": 16.232142857142858}, {"feature_12": "100", "support": 192, "avg_response": 19.463541666666668}, {"feature_12": "16", "support": 191, "avg_response": 45.204188481675395}, {"feature_12": "15", "support": 182, "avg_response": 41.714285714285715}]}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_79f6d2c0a420d0c0/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_79f6d2c0a420d0c0/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..515279007b733581d11a72f2955610b642320329
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_79f6d2c0a420d0c0/generated_sql.sql
@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: high_cardinality_response_stability
+-- intended_facet_id: target_cardinality_cross_section
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_cardinality_high_card_response_stability
+-- query_record_id: v2q_n9_79f6d2c0a420d0c0
+-- problem_id: v2p_n9_948b2bedbf1ffdea
+-- realization_mode: deterministic
+-- source_kind: deterministic
+SELECT
+    "feature_12",
+    COUNT(*) AS support,
+    AVG("feature_1") AS avg_response
+FROM "n9"
+GROUP BY "feature_12"
+HAVING COUNT(*) >= 5.0
+ORDER BY support DESC, avg_response DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_79f6d2c0a420d0c0/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_79f6d2c0a420d0c0/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..b3e339adac2d5114cf77c5a0b15ce36f5ccb9471
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_79f6d2c0a420d0c0/query_results.jsonl
@@ -0,0 +1 @@
+{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: n9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: high_cardinality_response_stability\n-- intended_facet_id: target_cardinality_cross_section\n-- variant_semantic_role: focused_target_view\n-- template_id: tpl_cardinality_high_card_response_stability\n-- query_record_id: v2q_n9_79f6d2c0a420d0c0\n-- problem_id: v2p_n9_948b2bedbf1ffdea\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n    \"feature_12\",\n    COUNT(*) AS support,\n    AVG(\"feature_1\") AS avg_response\nFROM \"n9\"\nGROUP BY \"feature_12\"\nHAVING COUNT(*) >= 5.0\nORDER BY support DESC, avg_response DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: n9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: high_cardinality_response_stability\\n-- intended_facet_id: target_cardinality_cross_section\\n-- variant_semantic_role: focused_target_view\\n-- template_id: tpl_cardinality_high_card_response_stability\\n-- query_record_id: v2q_n9_79f6d2c0a420d0c0\\n-- problem_id: v2p_n9_948b2bedbf1ffdea\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n    \\\"feature_12\\\",\\n    COUNT(*) AS support,\\n    AVG(\\\"feature_1\\\") AS avg_response\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_12\\\"\\nHAVING COUNT(*) >= 5.0\\nORDER BY support DESC, avg_response DESC;\", \"columns\": [\"feature_12\", \"support\", \"avg_response\"], \"rows\": [{\"feature_12\": \"0\", \"support\": 1227, \"avg_response\": 36.66259168704156}, {\"feature_12\": \"50\", \"support\": 224, \"avg_response\": 16.232142857142858}, {\"feature_12\": \"100\", \"support\": 192, \"avg_response\": 19.463541666666668}, {\"feature_12\": \"16\", \"support\": 191, \"avg_response\": 45.204188481675395}, {\"feature_12\": \"15\", \"support\": 182, \"avg_response\": 41.714285714285715}, {\"feature_12\": \"9\", \"support\": 168, \"avg_response\": 39.69642857142857}, {\"feature_12\": \"18\", \"support\": 167, \"avg_response\": 45.30538922155689}, {\"feature_12\": \"12\", \"support\": 161, \"avg_response\": 47.01242236024845}, {\"feature_12\": \"17\", \"support\": 161, \"avg_response\": 43.03105590062112}, {\"feature_12\": \"20\", \"support\": 156, \"avg_response\": 43.28846153846154}, {\"feature_12\": \"19\", \"support\": 155, \"avg_response\": 43.56774193548387}, {\"feature_12\": \"8\", \"support\": 154, \"avg_response\": 48.75974025974026}, {\"feature_12\": \"14\", \"support\": 154, \"avg_response\": 43.94155844155844}, {\"feature_12\": \"10\", \"support\": 153, \"avg_response\": 41.947712418300654}, {\"feature_12\": \"51\", \"support\": 152, \"avg_response\": 29.723684210526315}, {\"feature_12\": \"1\", \"support\": 149, \"avg_response\": 30.516778523489933}, {\"feature_12\": \"21\", \"support\": 147, \"avg_response\": 44.095238095238095}, {\"feature_12\": \"13\", \"support\": 147, \"avg_response\": 43.6530612244898}, {\"feature_12\": \"11\", \"support\": 145, \"avg_response\": 46.15172413793103}, {\"feature_12\": \"24\", \"support\": 138, \"avg_response\": 48.30434782608695}, {\"feature_12\": \"22\", \"support\": 138, \"avg_response\": 42.630434782608695}, {\"feature_12\": \"23\", \"support\": 137, \"avg_response\": 48.53284671532847}, {\"feature_12\": \"30\", \"support\": 135, \"avg_response\": 49.60740740740741}, {\"feature_12\": \"49\", \"support\": 135, \"avg_response\": 24.814814814814813}, {\"feature_12\": \"29\", \"support\": 130, \"avg_response\": 53.65384615384615}, {\"feature_12\": \"31\", \"support\": 130, \"avg_response\": 51.56923076923077}, {\"feature_12\": \"6\", \"support\": 130, \"avg_response\": 41.753846153846155}, {\"feature_12\": \"7\", \"support\": 128, \"avg_response\": 38.453125}, {\"feature_12\": \"3\", \"support\": 127, \"avg_response\": 31.299212598425196}, {\"feature_12\": \"4\", \"support\": 126, \"avg_response\": 44.817460317460316}, {\"feature_12\": \"5\", \"support\": 126, \"avg_response\": 34.80952380952381}, {\"feature_12\": \"53\", \"support\": 125, \"avg_response\": 33.672}, {\"feature_12\": \"26\", \"support\": 121, \"avg_response\": 44.1900826446281}, {\"feature_12\": \"2\", \"support\": 121, \"avg_response\": 34.3801652892562}, {\"feature_12\": \"25\", \"support\": 120, \"avg_response\": 44.766666666666666}, {\"feature_12\": \"46\", \"support\": 120, \"avg_response\": 40.125}, {\"feature_12\": \"32\", \"support\": 119, \"avg_response\": 43.94957983193277}, {\"feature_12\": \"28\", \"support\": 117, \"avg_response\": 51.1965811965812}, {\"feature_12\": \"27\", \"support\": 117, \"avg_response\": 49.675213675213676}, {\"feature_12\": \"66\", \"support\": 115, \"avg_response\": 36.99130434782609}, {\"feature_12\": \"64\", \"support\": 115, \"avg_response\": 36.47826086956522}, {\"feature_12\": \"56\", \"support\": 113, \"avg_response\": 42.23893805309734}, {\"feature_12\": \"33\", \"support\": 110, \"avg_response\": 52.13636363636363}, {\"feature_12\": \"45\", \"support\": 108, \"avg_response\": 41.425925925925924}, {\"feature_12\": \"68\", \"support\": 107, \"avg_response\": 32.05607476635514}, {\"feature_12\": \"65\", \"support\": 104, \"avg_response\": 44.86538461538461}, {\"feature_12\": \"43\", \"support\": 103, \"avg_response\": 41.95145631067961}, {\"feature_12\": \"60\", \"support\": 103, \"avg_response\": 38.80582524271845}, {\"feature_12\": \"62\", \"support\": 103, \"avg_response\": 37.19417475728155}, {\"feature_12\": \"54\", \"support\": 103, \"avg_response\": 36.48543689320388}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 5.38}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_79f6d2c0a420d0c0/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_79f6d2c0a420d0c0/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..cf3c903f90c935c279f8a4c177df231c767a6487
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_79f6d2c0a420d0c0/run_manifest.json
@@ -0,0 +1,60 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T16:10:15.902890+00:00",
+  "ended_at": "2026-05-19T16:10:15.908974+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_79f6d2c0a420d0c0",
+    "problem_id": "v2p_n9_948b2bedbf1ffdea",
+    "dataset_id": "n9",
+    "template_id": "tpl_cardinality_high_card_response_stability",
+    "template_name": "High-Cardinality Response Stability",
+    "family_id": "cardinality_structure",
+    "canonical_subitem_id": "high_cardinality_response_stability",
+    "intended_facet_id": "target_cardinality_cross_section",
+    "variant_semantic_role": "focused_target_view",
+    "subitem_assignment_source": "template_fixed",
+    "source_kind": "deterministic",
+    "realization_mode": "deterministic",
+    "gate_priority": "deterministic",
+    "extended_family": true,
+    "question": "Use template High-Cardinality Response Stability to probe high_cardinality_response_stability with semantic role focused_target_view. Focus on measure_col=feature_1, key_col=feature_12.",
+    "bindings": {
+      "key_col": "feature_12",
+      "measure_col": "feature_1",
+      "min_support": 5
+    },
+    "binding_roles": [
+      "key_col",
+      "target_col"
+    ],
+    "coverage_target_min": "enumerate_all_applicable",
+    "runtime_sql_skeleton": "SELECT\n    {key_col},\n    COUNT(*) AS support,\n    AVG({measure_col}) AS avg_response\nFROM {table}\nGROUP BY {key_col}\nHAVING COUNT(*) >= {min_support}\nORDER BY support DESC, avg_response DESC;",
+    "notes": [
+      "default_facets=target_cardinality_cross_section",
+      "template_selection_mode=deterministic",
+      "problem_index_within_template=9",
+      "sql_variant_index=1/1"
+    ],
+    "template_selection_mode": "deterministic",
+    "selected_template_rank": 0,
+    "problem_index_within_template": 9,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_79f6d2c0a420d0c0.sql",
+  "usage_summary": {
+    "engine": "template",
+    "input_tokens": 0,
+    "cached_input_tokens": 0,
+    "output_tokens": 0,
+    "total_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "none"
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_79f6d2c0a420d0c0/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_79f6d2c0a420d0c0/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_79f6d2c0a420d0c0/usage_summary.json
@@ -0,0 +1,9 @@
+{
+  "engine": "template",
+  "input_tokens": 0,
+  "cached_input_tokens": 0,
+  "output_tokens": 0,
+  "total_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "none"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_79f8ee093333c387/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_79f8ee093333c387/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..d4020ce778086a4b675bd1a247fb0c234bc26175
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_79f8ee093333c387/run_manifest.json
@@ -0,0 +1,67 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T16:04:47.297037+00:00",
+  "ended_at": "2026-05-19T16:04:55.434360+00:00",
+  "status": "failed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_79f8ee093333c387",
+    "problem_id": "v2p_n9_5e5a07407901c3f0",
+    "dataset_id": "n9",
+    "template_id": "tpl_threshold_rarity_cdf",
+    "template_name": "Threshold Rarity CDF",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_set_consistency",
+    "intended_facet_id": "low_support_extremes",
+    "variant_semantic_role": "rare_extreme_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=feature_4.",
+    "bindings": {
+      "measure_col": "feature_4",
+      "top_k": 10,
+      "top_n": 6,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 100.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};",
+    "notes": [
+      "default_facets=low_support_extremes",
+      "template_selection_mode=rule",
+      "problem_index_within_template=8",
+      "sql_variant_index=1/1",
+      "binding_index=115"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 10,
+    "problem_index_within_template": 8,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "error": "AI CLI command failed with exit code 1: "
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_79f8ee093333c387/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_79f8ee093333c387/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..6c8b24b1159bdf4b750b8fe820260ffbc9a57416
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_79f8ee093333c387/trace.jsonl
@@ -0,0 +1,2 @@
+{"timestamp": "2026-05-19T16:04:51.114932+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3816.07, "started_at": "2026-05-19T16:04:47.298133+00:00", "ended_at": "2026-05-19T16:04:51.114221+00:00", "prompt_metrics": {"chars": 9324, "bytes_utf8": 9324, "lines": 298, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fb-8b42-7843-8e86-fc73bf3a5983\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}
+{"timestamp": "2026-05-19T16:04:55.434270+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3316.58, "started_at": "2026-05-19T16:04:52.116874+00:00", "ended_at": "2026-05-19T16:04:55.433502+00:00", "prompt_metrics": {"chars": 9324, "bytes_utf8": 9324, "lines": 298, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fb-9e34-7ef1-8d09-dd06132e8fde\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7b094f86425ab76d/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7b094f86425ab76d/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..9627e30a58cc3c60fa521315e31cfde5e1554c61
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7b094f86425ab76d/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Low-Support Group Count to probe tail_mass_similarity with semantic role rare_extreme_view. Focus on group_col=feature_9.
+Result preview: [{"feature_9": "9", "support": 39}, {"feature_9": "18", "support": 41}, {"feature_9": "2", "support": 45}, {"feature_9": "4", "support": 48}, {"feature_9": "21", "support": 51}]
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7b094f86425ab76d/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7b094f86425ab76d/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..12b48b6919b5f6f31066a2e65854d4b4399e3b9a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7b094f86425ab76d/generated_sql.sql
@@ -0,0 +1,20 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_tail_low_support_group_count_v2
+-- query_record_id: v2q_n9_7b094f86425ab76d
+-- problem_id: v2p_n9_52a613b3efe49ecf
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+    "feature_9",
+    COUNT(*) AS support
+FROM "n9"
+GROUP BY "feature_9"
+ORDER BY support ASC, "feature_9"
+LIMIT 17;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7b094f86425ab76d/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7b094f86425ab76d/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..96faed3db61feaebadc551fcfc0bb25f1c9d65bf
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7b094f86425ab76d/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 2, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tail_low_support_group_count_v2.\nSELECT\n    \"feature_9\",\n    COUNT(*) AS support\nFROM \"n9\"\nGROUP BY \"feature_9\"\nORDER BY support ASC, \"feature_9\"\nLIMIT 17;", "result": "{\"query\": \"-- template_id: tpl_tail_low_support_group_count_v2.\\nSELECT\\n    \\\"feature_9\\\",\\n    COUNT(*) AS support\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_9\\\"\\nORDER BY support ASC, \\\"feature_9\\\"\\nLIMIT 17;\", \"columns\": [\"feature_9\", \"support\"], \"rows\": [{\"feature_9\": \"9\", \"support\": 39}, {\"feature_9\": \"18\", \"support\": 41}, {\"feature_9\": \"2\", \"support\": 45}, {\"feature_9\": \"4\", \"support\": 48}, {\"feature_9\": \"21\", \"support\": 51}, {\"feature_9\": \"7\", \"support\": 51}, {\"feature_9\": \"13\", \"support\": 53}, {\"feature_9\": \"1\", \"support\": 55}, {\"feature_9\": \"16\", \"support\": 55}, {\"feature_9\": \"23\", \"support\": 55}, {\"feature_9\": \"6\", \"support\": 56}, {\"feature_9\": \"3\", \"support\": 57}, {\"feature_9\": \"17\", \"support\": 59}, {\"feature_9\": \"14\", \"support\": 60}, {\"feature_9\": \"5\", \"support\": 60}, {\"feature_9\": \"15\", \"support\": 61}, {\"feature_9\": \"10\", \"support\": 62}], \"row_count_returned\": 17, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 4.68}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7b094f86425ab76d/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7b094f86425ab76d/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..a2c6a8e1d4be425f0296750707d816689116a957
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7b094f86425ab76d/run_manifest.json
@@ -0,0 +1,87 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T16:07:41.411041+00:00",
+  "ended_at": "2026-05-19T16:07:53.606008+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_7b094f86425ab76d",
+    "problem_id": "v2p_n9_52a613b3efe49ecf",
+    "dataset_id": "n9",
+    "template_id": "tpl_tail_low_support_group_count_v2",
+    "template_name": "Low-Support Group Count",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_mass_similarity",
+    "intended_facet_id": "tail_ranked_signal",
+    "variant_semantic_role": "rare_extreme_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Low-Support Group Count to probe tail_mass_similarity with semantic role rare_extreme_view. Focus on group_col=feature_9.",
+    "bindings": {
+      "group_col": "feature_9",
+      "top_k": 17,
+      "top_n": 7,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.05,
+      "baseline_multiplier": 1.75,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 4,
+      "measure_threshold": 51.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT\n    {group_col},\n    COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};",
+    "notes": [
+      "default_facets=tail_ranked_signal",
+      "template_selection_mode=rule",
+      "problem_index_within_template=8",
+      "sql_variant_index=2/2",
+      "binding_index=127"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 11,
+    "problem_index_within_template": 8,
+    "sql_variant_index": 2,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_7b094f86425ab76d.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_7b094f86425ab76d",
+    "api_calls": 0,
+    "input_tokens": 14948,
+    "cached_input_tokens": 13696,
+    "output_tokens": 271,
+    "total_tokens": 15219,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 2,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 11184.62,
+    "sql_execution_elapsed_ms_total": 4.68,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7b094f86425ab76d/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7b094f86425ab76d/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7b094f86425ab76d/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..6a2076dc9124f5c827542a980a1d189f7259bddd
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7b094f86425ab76d/trace.jsonl
@@ -0,0 +1,2 @@
+{"timestamp": "2026-05-19T16:07:44.990452+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3576.73, "started_at": "2026-05-19T16:07:41.412608+00:00", "ended_at": "2026-05-19T16:07:44.989367+00:00", "prompt_metrics": {"chars": 9378, "bytes_utf8": 9378, "lines": 298, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fe-3375-77b2-ae2c-eb2cb0492b5f\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}
+{"timestamp": "2026-05-19T16:07:53.599959+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 7607.89, "started_at": "2026-05-19T16:07:45.991344+00:00", "ended_at": "2026-05-19T16:07:53.599258+00:00", "prompt_metrics": {"chars": 9378, "bytes_utf8": 9378, "lines": 298, "estimated_tokens": null}, "response_metrics": {"chars": 373, "bytes_utf8": 373, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14948, "cached_input_tokens": 13696, "output_tokens": 271, "reasoning_output_tokens": 163}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tail_low_support_group_count_v2.\\nSELECT\\n    \\\"feature_9\\\",\\n    COUNT(*) AS support\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_9\\\"\\nORDER BY support ASC, \\\"feature_9\\\"\\nLIMIT 17;\",\"notes\":\"Applied the planned Low-Support Group Count template with group_col bound to \\\"feature_9\\\" and top_k=17. Grouping and ordering use the column as stored in SQLite.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7b094f86425ab76d/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7b094f86425ab76d/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..e8d915da589cbc8402f96aee5e0cd46d574feb35
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7b094f86425ab76d/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_7b094f86425ab76d",
+  "api_calls": 0,
+  "input_tokens": 14948,
+  "cached_input_tokens": 13696,
+  "output_tokens": 271,
+  "total_tokens": 15219,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 2,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 11184.62,
+  "sql_execution_elapsed_ms_total": 4.68,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7b094f86425ab76d/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7e97a63641733b89/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7e97a63641733b89/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..7785128012e87710e97f54e2c58b00d9ab876f7b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7e97a63641733b89/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=feature_5, measure_col=feature_10.
+Result preview: [{"feature_5": "6", "percentile_measure": 82.0}, {"feature_5": "27", "percentile_measure": 80.0}, {"feature_5": "37", "percentile_measure": 79.0}, {"feature_5": "32", "percentile_measure": 79.0}, {"feature_5": "9", "percentile_measure": 78.0}] Results were truncated.
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7e97a63641733b89/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7e97a63641733b89/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..62d952c7fdfb709c7335eb5da89a60d934b755e3
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7e97a63641733b89/generated_sql.sql
@@ -0,0 +1,30 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_n9_7e97a63641733b89
+-- problem_id: v2p_n9_e343c6b824d3fa8c
+-- realization_mode: agent
+-- source_kind: agent
+WITH "ranked" AS (
+  SELECT
+    "feature_5",
+    CAST("feature_10" AS REAL) AS "measure_value",
+    CUME_DIST() OVER (
+      PARTITION BY "feature_5"
+      ORDER BY CAST("feature_10" AS REAL)
+    ) AS "cum_dist"
+  FROM "n9"
+)
+SELECT
+  "feature_5",
+  MIN("measure_value") AS "percentile_measure"
+FROM "ranked"
+WHERE "cum_dist" >= 0.9
+GROUP BY "feature_5"
+ORDER BY "percentile_measure" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7e97a63641733b89/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7e97a63641733b89/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..667013875b9a5d1603de8c240a96e130abe11ea2
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7e97a63641733b89/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH \"ranked\" AS (\n  SELECT\n    \"feature_5\",\n    CAST(\"feature_10\" AS REAL) AS \"measure_value\",\n    CUME_DIST() OVER (\n      PARTITION BY \"feature_5\"\n      ORDER BY CAST(\"feature_10\" AS REAL)\n    ) AS \"cum_dist\"\n  FROM \"n9\"\n)\nSELECT\n  \"feature_5\",\n  MIN(\"measure_value\") AS \"percentile_measure\"\nFROM \"ranked\"\nWHERE \"cum_dist\" >= 0.9\nGROUP BY \"feature_5\"\nORDER BY \"percentile_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n  SELECT\\n    \\\"feature_5\\\",\\n    CAST(\\\"feature_10\\\" AS REAL) AS \\\"measure_value\\\",\\n    CUME_DIST() OVER (\\n      PARTITION BY \\\"feature_5\\\"\\n      ORDER BY CAST(\\\"feature_10\\\" AS REAL)\\n    ) AS \\\"cum_dist\\\"\\n  FROM \\\"n9\\\"\\n)\\nSELECT\\n  \\\"feature_5\\\",\\n  MIN(\\\"measure_value\\\") AS \\\"percentile_measure\\\"\\nFROM \\\"ranked\\\"\\nWHERE \\\"cum_dist\\\" >= 0.9\\nGROUP BY \\\"feature_5\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\", \"columns\": [\"feature_5\", \"percentile_measure\"], \"rows\": [{\"feature_5\": \"6\", \"percentile_measure\": 82.0}, {\"feature_5\": \"27\", \"percentile_measure\": 80.0}, {\"feature_5\": \"37\", \"percentile_measure\": 79.0}, {\"feature_5\": \"32\", \"percentile_measure\": 79.0}, {\"feature_5\": \"9\", \"percentile_measure\": 78.0}, {\"feature_5\": \"69\", \"percentile_measure\": 78.0}, {\"feature_5\": \"67\", \"percentile_measure\": 78.0}, {\"feature_5\": \"66\", \"percentile_measure\": 78.0}, {\"feature_5\": \"63\", \"percentile_measure\": 78.0}, {\"feature_5\": \"61\", \"percentile_measure\": 78.0}, {\"feature_5\": \"52\", \"percentile_measure\": 78.0}, {\"feature_5\": \"50\", \"percentile_measure\": 78.0}, {\"feature_5\": \"41\", \"percentile_measure\": 78.0}, {\"feature_5\": \"15\", \"percentile_measure\": 78.0}, {\"feature_5\": \"59\", \"percentile_measure\": 77.0}, {\"feature_5\": \"49\", \"percentile_measure\": 77.0}, {\"feature_5\": \"0\", \"percentile_measure\": 77.0}, {\"feature_5\": \"71\", \"percentile_measure\": 76.0}, {\"feature_5\": \"7\", \"percentile_measure\": 76.0}, {\"feature_5\": \"68\", \"percentile_measure\": 76.0}, {\"feature_5\": \"65\", \"percentile_measure\": 76.0}, {\"feature_5\": \"48\", \"percentile_measure\": 76.0}, {\"feature_5\": \"42\", \"percentile_measure\": 76.0}, {\"feature_5\": \"39\", \"percentile_measure\": 76.0}, {\"feature_5\": \"31\", \"percentile_measure\": 76.0}, {\"feature_5\": \"87\", \"percentile_measure\": 75.0}, {\"feature_5\": \"80\", \"percentile_measure\": 75.0}, {\"feature_5\": \"77\", \"percentile_measure\": 75.0}, {\"feature_5\": \"76\", \"percentile_measure\": 75.0}, {\"feature_5\": \"74\", \"percentile_measure\": 75.0}, {\"feature_5\": \"73\", \"percentile_measure\": 75.0}, {\"feature_5\": \"72\", \"percentile_measure\": 75.0}, {\"feature_5\": \"70\", \"percentile_measure\": 75.0}, {\"feature_5\": \"64\", \"percentile_measure\": 75.0}, {\"feature_5\": \"62\", \"percentile_measure\": 75.0}, {\"feature_5\": \"57\", \"percentile_measure\": 75.0}, {\"feature_5\": \"54\", \"percentile_measure\": 75.0}, {\"feature_5\": \"53\", \"percentile_measure\": 75.0}, {\"feature_5\": \"51\", \"percentile_measure\": 75.0}, {\"feature_5\": \"45\", \"percentile_measure\": 75.0}, {\"feature_5\": \"38\", \"percentile_measure\": 75.0}, {\"feature_5\": \"79\", \"percentile_measure\": 74.0}, {\"feature_5\": \"78\", \"percentile_measure\": 74.0}, {\"feature_5\": \"60\", \"percentile_measure\": 74.0}, {\"feature_5\": \"29\", \"percentile_measure\": 74.0}, {\"feature_5\": \"28\", \"percentile_measure\": 74.0}, {\"feature_5\": \"25\", \"percentile_measure\": 74.0}, {\"feature_5\": \"17\", \"percentile_measure\": 74.0}, {\"feature_5\": \"16\", \"percentile_measure\": 74.0}, {\"feature_5\": \"95\", \"percentile_measure\": 73.0}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 16.61}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7e97a63641733b89/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7e97a63641733b89/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..513d042271b43784eec6301a756547b8bac2b82e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7e97a63641733b89/run_manifest.json
@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:54:56.686543+00:00",
+  "ended_at": "2026-05-19T15:55:13.358262+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_7e97a63641733b89",
+    "problem_id": "v2p_n9_e343c6b824d3fa8c",
+    "dataset_id": "n9",
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_concentration_consistency",
+    "intended_facet_id": "rare_target_concentration",
+    "variant_semantic_role": "ranked_signal_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=feature_5, measure_col=feature_10.",
+    "bindings": {
+      "group_col": "feature_5",
+      "measure_col": "feature_10",
+      "top_k": 14,
+      "top_n": 4,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 54.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;",
+    "notes": [
+      "default_facets=rare_target_concentration",
+      "template_selection_mode=rule",
+      "problem_index_within_template=6",
+      "sql_variant_index=1/2",
+      "binding_index=89"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 8,
+    "problem_index_within_template": 6,
+    "sql_variant_index": 1,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_7e97a63641733b89.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_7e97a63641733b89",
+    "api_calls": 0,
+    "input_tokens": 14978,
+    "cached_input_tokens": 12032,
+    "output_tokens": 737,
+    "total_tokens": 15715,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 16650.97,
+    "sql_execution_elapsed_ms_total": 16.61,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7e97a63641733b89/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7e97a63641733b89/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7e97a63641733b89/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..2f9d7302045462b9fe9b4e12c292cdea1fc08c0c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7e97a63641733b89/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:55:13.340089+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 16650.97, "started_at": "2026-05-19T15:54:56.688217+00:00", "ended_at": "2026-05-19T15:55:13.339222+00:00", "prompt_metrics": {"chars": 9568, "bytes_utf8": 9568, "lines": 300, "estimated_tokens": null}, "response_metrics": {"chars": 762, "bytes_utf8": 762, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14978, "cached_input_tokens": 12032, "output_tokens": 737, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n  SELECT\\n    \\\"feature_5\\\",\\n    CAST(\\\"feature_10\\\" AS REAL) AS \\\"measure_value\\\",\\n    CUME_DIST() OVER (\\n      PARTITION BY \\\"feature_5\\\"\\n      ORDER BY CAST(\\\"feature_10\\\" AS REAL)\\n    ) AS \\\"cum_dist\\\"\\n  FROM \\\"n9\\\"\\n)\\nSELECT\\n  \\\"feature_5\\\",\\n  MIN(\\\"measure_value\\\") AS \\\"percentile_measure\\\"\\nFROM \\\"ranked\\\"\\nWHERE \\\"cum_dist\\\" >= 0.9\\nGROUP BY \\\"feature_5\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\",\"notes\":\"SQLite does not support PERCENTILE_CONT, so this uses CUME_DIST() to emulate the 90th percentile per feature_5 group as the smallest feature_10 value whose cumulative distribution reaches at least 0.9. feature_10 is cast from TEXT to REAL for numeric ordering.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7e97a63641733b89/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7e97a63641733b89/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..0a645b57724b4feecaa0bff65ae5e229a4dbc0e1
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7e97a63641733b89/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_7e97a63641733b89",
+  "api_calls": 0,
+  "input_tokens": 14978,
+  "cached_input_tokens": 12032,
+  "output_tokens": 737,
+  "total_tokens": 15715,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 16650.97,
+  "sql_execution_elapsed_ms_total": 16.61,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7e97a63641733b89/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7f8a0603780a1a99/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7f8a0603780a1a99/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..587d4c19cbe26f110d462d1e3f233e3bccef1306
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7f8a0603780a1a99/final_answer.txt
@@ -0,0 +1 @@
+{"row_count": null, "preview_rows": [{"value_label": "100", "support": 1115, "support_share": 0.10143740902474527, "cumulative_support": 1115}, {"value_label": "0", "support": 397, "support_share": 0.03611717612809316, "cumulative_support": 1512}, {"value_label": "78", "support": 211, "support_share": 0.019195778748180493, "cumulative_support": 1723}, {"value_label": "75", "support": 207, "support_share": 0.01883187772925764, "cumulative_support": 1930}, {"value_label": "79", "support": 205, "support_share": 0.018649927219796216, "cumulative_support": 2135}]}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7f8a0603780a1a99/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7f8a0603780a1a99/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..707de573ae43febe7ab3b2400ac03406392e1656
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7f8a0603780a1a99/generated_sql.sql
@@ -0,0 +1,28 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: support_concentration
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_cardinality_distinct_share_profile
+-- query_record_id: v2q_n9_7f8a0603780a1a99
+-- problem_id: v2p_n9_85d22479c1fc7083
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_6" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_6"
+), ranked AS (
+    SELECT
+        value_label,
+        support,
+        CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+        SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support
+    FROM grouped
+)
+SELECT *
+FROM ranked
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7f8a0603780a1a99/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7f8a0603780a1a99/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..9e90fb7a1d546f18c9aeb82caf6bb14cfa69d7d5
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7f8a0603780a1a99/query_results.jsonl
@@ -0,0 +1 @@
+{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: n9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: support_rank_profile_consistency\n-- intended_facet_id: support_concentration\n-- variant_semantic_role: ranked_signal_view\n-- template_id: tpl_cardinality_distinct_share_profile\n-- query_record_id: v2q_n9_7f8a0603780a1a99\n-- problem_id: v2p_n9_85d22479c1fc7083\n-- realization_mode: deterministic\n-- source_kind: deterministic\nWITH grouped AS (\n    SELECT \"feature_6\" AS value_label, COUNT(*) AS support\n    FROM \"n9\"\n    GROUP BY \"feature_6\"\n), ranked AS (\n    SELECT\n        value_label,\n        support,\n        CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n        SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\n    FROM grouped\n)\nSELECT *\nFROM ranked\nORDER BY support DESC, value_label;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: n9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: support_rank_profile_consistency\\n-- intended_facet_id: support_concentration\\n-- variant_semantic_role: ranked_signal_view\\n-- template_id: tpl_cardinality_distinct_share_profile\\n-- query_record_id: v2q_n9_7f8a0603780a1a99\\n-- problem_id: v2p_n9_85d22479c1fc7083\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nWITH grouped AS (\\n    SELECT \\\"feature_6\\\" AS value_label, COUNT(*) AS support\\n    FROM \\\"n9\\\"\\n    GROUP BY \\\"feature_6\\\"\\n), ranked AS (\\n    SELECT\\n        value_label,\\n        support,\\n        CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\\n        SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\\n    FROM grouped\\n)\\nSELECT *\\nFROM ranked\\nORDER BY support DESC, value_label;\", \"columns\": [\"value_label\", \"support\", \"support_share\", \"cumulative_support\"], \"rows\": [{\"value_label\": \"100\", \"support\": 1115, \"support_share\": 0.10143740902474527, \"cumulative_support\": 1115}, {\"value_label\": \"0\", \"support\": 397, \"support_share\": 0.03611717612809316, \"cumulative_support\": 1512}, {\"value_label\": \"78\", \"support\": 211, \"support_share\": 0.019195778748180493, \"cumulative_support\": 1723}, {\"value_label\": \"75\", \"support\": 207, \"support_share\": 0.01883187772925764, \"cumulative_support\": 1930}, {\"value_label\": \"79\", \"support\": 205, \"support_share\": 0.018649927219796216, \"cumulative_support\": 2135}, {\"value_label\": \"72\", \"support\": 200, \"support_share\": 0.018195050946142648, \"cumulative_support\": 2335}, {\"value_label\": \"76\", \"support\": 193, \"support_share\": 0.017558224163027658, \"cumulative_support\": 2528}, {\"value_label\": \"77\", \"support\": 184, \"support_share\": 0.016739446870451237, \"cumulative_support\": 2712}, {\"value_label\": \"74\", \"support\": 183, \"support_share\": 0.016648471615720525, \"cumulative_support\": 2895}, {\"value_label\": \"73\", \"support\": 180, \"support_share\": 0.016375545851528384, \"cumulative_support\": 3075}, {\"value_label\": \"70\", \"support\": 178, \"support_share\": 0.016193595342066956, \"cumulative_support\": 3253}, {\"value_label\": \"71\", \"support\": 176, \"support_share\": 0.01601164483260553, \"cumulative_support\": 3429}, {\"value_label\": \"80\", \"support\": 176, \"support_share\": 0.01601164483260553, \"cumulative_support\": 3605}, {\"value_label\": \"82\", \"support\": 174, \"support_share\": 0.015829694323144104, \"cumulative_support\": 3779}, {\"value_label\": \"68\", \"support\": 173, \"support_share\": 0.01573871906841339, \"cumulative_support\": 3952}, {\"value_label\": \"67\", \"support\": 170, \"support_share\": 0.015465793304221253, \"cumulative_support\": 4122}, {\"value_label\": \"83\", \"support\": 170, \"support_share\": 0.015465793304221253, \"cumulative_support\": 4292}, {\"value_label\": \"81\", \"support\": 169, \"support_share\": 0.015374818049490539, \"cumulative_support\": 4461}, {\"value_label\": \"69\", \"support\": 163, \"support_share\": 0.01482896652110626, \"cumulative_support\": 4624}, {\"value_label\": \"88\", \"support\": 151, \"support_share\": 0.0137372634643377, \"cumulative_support\": 4775}, {\"value_label\": \"66\", \"support\": 143, \"support_share\": 0.013009461426491994, \"cumulative_support\": 4918}, {\"value_label\": \"65\", \"support\": 140, \"support_share\": 0.012736535662299854, \"cumulative_support\": 5058}, {\"value_label\": \"85\", \"support\": 140, \"support_share\": 0.012736535662299854, \"cumulative_support\": 5198}, {\"value_label\": \"99\", \"support\": 137, \"support_share\": 0.012463609898107715, \"cumulative_support\": 5335}, {\"value_label\": \"91\", \"support\": 134, \"support_share\": 0.012190684133915575, \"cumulative_support\": 5469}, {\"value_label\": \"84\", \"support\": 132, \"support_share\": 0.012008733624454149, \"cumulative_support\": 5601}, {\"value_label\": \"94\", \"support\": 132, \"support_share\": 0.012008733624454149, \"cumulative_support\": 5733}, {\"value_label\": \"87\", \"support\": 130, \"support_share\": 0.011826783114992722, \"cumulative_support\": 5863}, {\"value_label\": \"98\", \"support\": 129, \"support_share\": 0.011735807860262008, \"cumulative_support\": 5992}, {\"value_label\": \"86\", \"support\": 127, \"support_share\": 0.011553857350800582, \"cumulative_support\": 6119}, {\"value_label\": \"97\", \"support\": 127, \"support_share\": 0.011553857350800582, \"cumulative_support\": 6246}, {\"value_label\": \"95\", \"support\": 125, \"support_share\": 0.011371906841339156, \"cumulative_support\": 6371}, {\"value_label\": \"52\", \"support\": 123, \"support_share\": 0.01118995633187773, \"cumulative_support\": 6494}, {\"value_label\": \"59\", \"support\": 123, \"support_share\": 0.01118995633187773, \"cumulative_support\": 6617}, {\"value_label\": \"89\", \"support\": 123, \"support_share\": 0.01118995633187773, \"cumulative_support\": 6740}, {\"value_label\": \"60\", \"support\": 120, \"support_share\": 0.010917030567685589, \"cumulative_support\": 6860}, {\"value_label\": \"62\", \"support\": 120, \"support_share\": 0.010917030567685589, \"cumulative_support\": 6980}, {\"value_label\": \"49\", \"support\": 117, \"support_share\": 0.01064410480349345, \"cumulative_support\": 7097}, {\"value_label\": \"61\", \"support\": 116, \"support_share\": 0.010553129548762736, \"cumulative_support\": 7213}, {\"value_label\": \"63\", \"support\": 116, \"support_share\": 0.010553129548762736, \"cumulative_support\": 7329}, {\"value_label\": \"55\", \"support\": 115, \"support_share\": 0.010462154294032024, \"cumulative_support\": 7444}, {\"value_label\": \"58\", \"support\": 115, \"support_share\": 0.010462154294032024, \"cumulative_support\": 7559}, {\"value_label\": \"56\", \"support\": 111, \"support_share\": 0.01009825327510917, \"cumulative_support\": 7670}, {\"value_label\": \"90\", \"support\": 111, \"support_share\": 0.01009825327510917, \"cumulative_support\": 7781}, {\"value_label\": \"96\", \"support\": 110, \"support_share\": 0.010007278020378457, \"cumulative_support\": 7891}, {\"value_label\": \"53\", \"support\": 109, \"support_share\": 0.009916302765647743, \"cumulative_support\": 8000}, {\"value_label\": \"57\", \"support\": 108, \"support_share\": 0.009825327510917031, \"cumulative_support\": 8108}, {\"value_label\": \"64\", \"support\": 107, \"support_share\": 0.009734352256186317, \"cumulative_support\": 8215}, {\"value_label\": \"93\", \"support\": 107, \"support_share\": 0.009734352256186317, \"cumulative_support\": 8322}, {\"value_label\": \"50\", \"support\": 105, \"support_share\": 0.00955240174672489, \"cumulative_support\": 8427}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 4.54}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7f8a0603780a1a99/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7f8a0603780a1a99/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..51bb8bb5a76b352af0b90466aa3e529fee258fb6
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7f8a0603780a1a99/run_manifest.json
@@ -0,0 +1,57 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T16:10:15.736274+00:00",
+  "ended_at": "2026-05-19T16:10:15.741700+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_7f8a0603780a1a99",
+    "problem_id": "v2p_n9_85d22479c1fc7083",
+    "dataset_id": "n9",
+    "template_id": "tpl_cardinality_distinct_share_profile",
+    "template_name": "Cardinality Distinct Share Profile",
+    "family_id": "cardinality_structure",
+    "canonical_subitem_id": "support_rank_profile_consistency",
+    "intended_facet_id": "support_concentration",
+    "variant_semantic_role": "ranked_signal_view",
+    "subitem_assignment_source": "template_fixed",
+    "source_kind": "deterministic",
+    "realization_mode": "deterministic",
+    "gate_priority": "deterministic",
+    "extended_family": true,
+    "question": "Use template Cardinality Distinct Share Profile to probe support_rank_profile_consistency with semantic role ranked_signal_view. Focus on group_col=feature_6.",
+    "bindings": {
+      "group_col": "feature_6"
+    },
+    "binding_roles": [
+      "group_col"
+    ],
+    "coverage_target_min": "enumerate_all_applicable",
+    "runtime_sql_skeleton": "WITH grouped AS (\n    SELECT {group_col} AS value_label, COUNT(*) AS support\n    FROM {table}\n    GROUP BY {group_col}\n), ranked AS (\n    SELECT\n        value_label,\n        support,\n        CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n        SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\n    FROM grouped\n)\nSELECT *\nFROM ranked\nORDER BY support DESC, value_label;",
+    "notes": [
+      "default_facets=support_concentration,value_imbalance_profile",
+      "template_selection_mode=deterministic",
+      "problem_index_within_template=5",
+      "sql_variant_index=1/1"
+    ],
+    "template_selection_mode": "deterministic",
+    "selected_template_rank": 0,
+    "problem_index_within_template": 5,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_7f8a0603780a1a99.sql",
+  "usage_summary": {
+    "engine": "template",
+    "input_tokens": 0,
+    "cached_input_tokens": 0,
+    "output_tokens": 0,
+    "total_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "none"
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7f8a0603780a1a99/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7f8a0603780a1a99/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_7f8a0603780a1a99/usage_summary.json
@@ -0,0 +1,9 @@
+{
+  "engine": "template",
+  "input_tokens": 0,
+  "cached_input_tokens": 0,
+  "output_tokens": 0,
+  "total_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "none"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_8018cd36f1aa3207/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_8018cd36f1aa3207/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..bbca13c4a96f9278e7944c5fcb861f7341ab68df
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_8018cd36f1aa3207/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=feature_16.
+Result preview: [{"empirical_cdf_at_threshold": 0.7510917030567685}]
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_8018cd36f1aa3207/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_8018cd36f1aa3207/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..a962fbdc5a45b9de31097e95b3ea8d5d788bcc96
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_8018cd36f1aa3207/generated_sql.sql
@@ -0,0 +1,15 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_set_consistency
+-- intended_facet_id: low_support_extremes
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_threshold_rarity_cdf
+-- query_record_id: v2q_n9_8018cd36f1aa3207
+-- problem_id: v2p_n9_68ff71d8ab8b1789
+-- realization_mode: agent
+-- source_kind: agent
+SELECT AVG(CASE WHEN CAST("feature_16" AS REAL) <= 51.0 THEN 1 ELSE 0 END) AS "empirical_cdf_at_threshold"
+FROM "n9";
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_8018cd36f1aa3207/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_8018cd36f1aa3207/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..38390db449716b68a093e101a482dd63efff565a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_8018cd36f1aa3207/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_threshold_rarity_cdf\nSELECT AVG(CASE WHEN CAST(\"feature_16\" AS REAL) <= 51.0 THEN 1 ELSE 0 END) AS \"empirical_cdf_at_threshold\"\nFROM \"n9\";", "result": "{\"query\": \"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(\\\"feature_16\\\" AS REAL) <= 51.0 THEN 1 ELSE 0 END) AS \\\"empirical_cdf_at_threshold\\\"\\nFROM \\\"n9\\\";\", \"columns\": [\"empirical_cdf_at_threshold\"], \"rows\": [{\"empirical_cdf_at_threshold\": 0.7510917030567685}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 1.89}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_8018cd36f1aa3207/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_8018cd36f1aa3207/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..3e72fcd569c02fee94f51b481c9bd3e15e502a57
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_8018cd36f1aa3207/run_manifest.json
@@ -0,0 +1,87 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T16:04:12.494216+00:00",
+  "ended_at": "2026-05-19T16:04:21.022530+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_8018cd36f1aa3207",
+    "problem_id": "v2p_n9_68ff71d8ab8b1789",
+    "dataset_id": "n9",
+    "template_id": "tpl_threshold_rarity_cdf",
+    "template_name": "Threshold Rarity CDF",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_set_consistency",
+    "intended_facet_id": "low_support_extremes",
+    "variant_semantic_role": "rare_extreme_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=feature_16.",
+    "bindings": {
+      "measure_col": "feature_16",
+      "top_k": 11,
+      "top_n": 6,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 51.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};",
+    "notes": [
+      "default_facets=low_support_extremes",
+      "template_selection_mode=rule",
+      "problem_index_within_template=4",
+      "sql_variant_index=1/1",
+      "binding_index=111"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 10,
+    "problem_index_within_template": 4,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8018cd36f1aa3207.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_8018cd36f1aa3207",
+    "api_calls": 0,
+    "input_tokens": 14927,
+    "cached_input_tokens": 12032,
+    "output_tokens": 306,
+    "total_tokens": 15233,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 8523.04,
+    "sql_execution_elapsed_ms_total": 1.89,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_8018cd36f1aa3207/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_8018cd36f1aa3207/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_8018cd36f1aa3207/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..d0cbc4e6d033ac19abc4856c561fab8707b7edbe
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_8018cd36f1aa3207/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T16:04:21.019218+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 8523.04, "started_at": "2026-05-19T16:04:12.495418+00:00", "ended_at": "2026-05-19T16:04:21.018480+00:00", "prompt_metrics": {"chars": 9325, "bytes_utf8": 9325, "lines": 298, "estimated_tokens": null}, "response_metrics": {"chars": 377, "bytes_utf8": 377, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14927, "cached_input_tokens": 12032, "output_tokens": 306, "reasoning_output_tokens": 197}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(\\\"feature_16\\\" AS REAL) <= 51.0 THEN 1 ELSE 0 END) AS \\\"empirical_cdf_at_threshold\\\"\\nFROM \\\"n9\\\";\",\"notes\":\"Used the planned Threshold Rarity CDF template with measure_col bound to \\\"feature_16\\\" and threshold 51.0. CAST to REAL is included because the feature columns are stored as TEXT in SQLite.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_8018cd36f1aa3207/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_8018cd36f1aa3207/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..f1097057d625cd881feb0e8a425b7c29640e6c8c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_8018cd36f1aa3207/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_8018cd36f1aa3207",
+  "api_calls": 0,
+  "input_tokens": 14927,
+  "cached_input_tokens": 12032,
+  "output_tokens": 306,
+  "total_tokens": 15233,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 8523.04,
+  "sql_execution_elapsed_ms_total": 1.89,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_8018cd36f1aa3207/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_834804424cb72fa9/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_834804424cb72fa9/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..0a0b2651e50cfc8314423922bbae717b7b20e09d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_834804424cb72fa9/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=feature_15.
+Result preview: [{"feature_15": "100", "row_count": 2988}, {"feature_15": "0", "row_count": 2917}, {"feature_15": "7", "row_count": 96}, {"feature_15": "8", "row_count": 89}, {"feature_15": "9", "row_count": 86}] Results were truncated.
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_834804424cb72fa9/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_834804424cb72fa9/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..7acfaf636252f07e5497dff6a30905431f776c3d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_834804424cb72fa9/generated_sql.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: subgroup_size_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_clickbench_group_count
+-- query_record_id: v2q_n9_834804424cb72fa9
+-- problem_id: v2p_n9_dcfd6e19e94f3a38
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_15", COUNT(*) AS "row_count"
+FROM "n9"
+GROUP BY "feature_15"
+ORDER BY "row_count" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_834804424cb72fa9/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_834804424cb72fa9/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..7cdeeb745615797c3209d435961e95b0028d34f6
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_834804424cb72fa9/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_clickbench_group_count\nSELECT \"feature_15\", COUNT(*) AS \"row_count\"\nFROM \"n9\"\nGROUP BY \"feature_15\"\nORDER BY \"row_count\" DESC;", "result": "{\"query\": \"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"feature_15\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_15\\\"\\nORDER BY \\\"row_count\\\" DESC;\", \"columns\": [\"feature_15\", \"row_count\"], \"rows\": [{\"feature_15\": \"100\", \"row_count\": 2988}, {\"feature_15\": \"0\", \"row_count\": 2917}, {\"feature_15\": \"7\", \"row_count\": 96}, {\"feature_15\": \"8\", \"row_count\": 89}, {\"feature_15\": \"9\", \"row_count\": 86}, {\"feature_15\": \"5\", \"row_count\": 86}, {\"feature_15\": \"6\", \"row_count\": 83}, {\"feature_15\": \"16\", \"row_count\": 82}, {\"feature_15\": \"10\", \"row_count\": 81}, {\"feature_15\": \"19\", \"row_count\": 77}, {\"feature_15\": \"11\", \"row_count\": 77}, {\"feature_15\": \"3\", \"row_count\": 74}, {\"feature_15\": \"15\", \"row_count\": 73}, {\"feature_15\": \"12\", \"row_count\": 73}, {\"feature_15\": \"24\", \"row_count\": 71}, {\"feature_15\": \"29\", \"row_count\": 70}, {\"feature_15\": \"21\", \"row_count\": 70}, {\"feature_15\": \"14\", \"row_count\": 70}, {\"feature_15\": \"22\", \"row_count\": 69}, {\"feature_15\": \"18\", \"row_count\": 68}, {\"feature_15\": \"13\", \"row_count\": 68}, {\"feature_15\": \"88\", \"row_count\": 66}, {\"feature_15\": \"25\", \"row_count\": 66}, {\"feature_15\": \"20\", \"row_count\": 64}, {\"feature_15\": \"2\", \"row_count\": 63}, {\"feature_15\": \"23\", \"row_count\": 61}, {\"feature_15\": \"39\", \"row_count\": 60}, {\"feature_15\": \"17\", \"row_count\": 60}, {\"feature_15\": \"44\", \"row_count\": 57}, {\"feature_15\": \"36\", \"row_count\": 57}, {\"feature_15\": \"30\", \"row_count\": 57}, {\"feature_15\": \"33\", \"row_count\": 56}, {\"feature_15\": \"32\", \"row_count\": 56}, {\"feature_15\": \"31\", \"row_count\": 56}, {\"feature_15\": \"27\", \"row_count\": 56}, {\"feature_15\": \"45\", \"row_count\": 55}, {\"feature_15\": \"1\", \"row_count\": 55}, {\"feature_15\": \"28\", \"row_count\": 54}, {\"feature_15\": \"26\", \"row_count\": 54}, {\"feature_15\": \"84\", \"row_count\": 53}, {\"feature_15\": \"47\", \"row_count\": 53}, {\"feature_15\": \"37\", \"row_count\": 53}, {\"feature_15\": \"34\", \"row_count\": 53}, {\"feature_15\": \"43\", \"row_count\": 51}, {\"feature_15\": \"78\", \"row_count\": 49}, {\"feature_15\": \"69\", \"row_count\": 49}, {\"feature_15\": \"58\", \"row_count\": 49}, {\"feature_15\": \"35\", \"row_count\": 49}, {\"feature_15\": \"71\", \"row_count\": 48}, {\"feature_15\": \"89\", \"row_count\": 47}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 10.54}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_834804424cb72fa9/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_834804424cb72fa9/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..457dd17adf6006fac869c237f7276255eeae93d1
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_834804424cb72fa9/run_manifest.json
@@ -0,0 +1,87 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:32:30.760632+00:00",
+  "ended_at": "2026-05-19T15:32:45.246524+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_834804424cb72fa9",
+    "problem_id": "v2p_n9_dcfd6e19e94f3a38",
+    "dataset_id": "n9",
+    "template_id": "tpl_clickbench_group_count",
+    "template_name": "Grouped Count by Category",
+    "family_id": "subgroup_structure",
+    "canonical_subitem_id": "subgroup_size_stability",
+    "intended_facet_id": "subgroup_distribution_shift",
+    "variant_semantic_role": "count_distribution",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=feature_15.",
+    "bindings": {
+      "group_col": "feature_15",
+      "top_k": 14,
+      "top_n": 5,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 100.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;",
+    "notes": [
+      "default_facets=subgroup_distribution_shift",
+      "template_selection_mode=rule",
+      "problem_index_within_template=3",
+      "sql_variant_index=1/1",
+      "binding_index=14"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 2,
+    "problem_index_within_template": 3,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_834804424cb72fa9.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_834804424cb72fa9",
+    "api_calls": 0,
+    "input_tokens": 14911,
+    "cached_input_tokens": 13696,
+    "output_tokens": 242,
+    "total_tokens": 15153,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 14468.63,
+    "sql_execution_elapsed_ms_total": 10.54,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_834804424cb72fa9/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_834804424cb72fa9/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_834804424cb72fa9/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..7146a0ed1a358e4f464541f0d7d35ca09915f4dd
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_834804424cb72fa9/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:32:45.232930+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 14468.63, "started_at": "2026-05-19T15:32:30.762589+00:00", "ended_at": "2026-05-19T15:32:45.231251+00:00", "prompt_metrics": {"chars": 9300, "bytes_utf8": 9300, "lines": 298, "estimated_tokens": null}, "response_metrics": {"chars": 283, "bytes_utf8": 283, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14911, "cached_input_tokens": 13696, "output_tokens": 242, "reasoning_output_tokens": 159}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"feature_15\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_15\\\"\\nORDER BY \\\"row_count\\\" DESC;\",\"notes\":\"Uses the planned grouped-count template with group_col bound to \\\"feature_15\\\" on single table \\\"n9\\\".\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_834804424cb72fa9/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_834804424cb72fa9/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..efb8462499ba5e7e48d525ab76442c769856da6b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_834804424cb72fa9/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_834804424cb72fa9",
+  "api_calls": 0,
+  "input_tokens": 14911,
+  "cached_input_tokens": 13696,
+  "output_tokens": 242,
+  "total_tokens": 15153,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 14468.63,
+  "sql_execution_elapsed_ms_total": 10.54,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_834804424cb72fa9/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9a62b46e99f2dc1e/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9a62b46e99f2dc1e/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..94992f5275c530f39951e4389e9901e68fc43f89
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9a62b46e99f2dc1e/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=feature_9, measure_col=feature_10.
+Result preview: [{"feature_9": "91", "feature_11": "100", "total_measure": 2760.0, "share_within_group": 55.11182108626198}, {"feature_9": "9", "feature_11": "0", "total_measure": 212.0, "share_within_group": 51.707317073170735}, {"feature_9": "97", "feature_11": "100", "total_measure": 2470.0, "share_within_group": 50.91733663162235}, {"feature_9": "99", "feature_11": "100", "total_measure": 2164.0, "share_within_group": 50.47818987637042}, {"feature_9": "5", "feature_11": "0", "total_measure": 610.0, "share_within_group": 50.37159372419488}]
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9a62b46e99f2dc1e/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9a62b46e99f2dc1e/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..903ef8746fad78fe42cb43fa42466fcfdf7bd6eb
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9a62b46e99f2dc1e/generated_sql.sql
@@ -0,0 +1,23 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_9a62b46e99f2dc1e
+-- problem_id: v2p_n9_8f75b5420170d1c4
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+  "feature_9",
+  "feature_11",
+  SUM(CAST("feature_10" AS REAL)) AS total_measure,
+  SUM(CAST("feature_10" AS REAL)) * 100.0
+    / SUM(SUM(CAST("feature_10" AS REAL))) OVER (PARTITION BY "feature_9") AS share_within_group
+FROM "n9"
+GROUP BY "feature_9", "feature_11"
+ORDER BY share_within_group DESC
+LIMIT 10;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9a62b46e99f2dc1e/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9a62b46e99f2dc1e/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..6b85c3736b174849a81ac0d6a1f1ba8ae439a31b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9a62b46e99f2dc1e/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT\n  \"feature_9\",\n  \"feature_11\",\n  SUM(CAST(\"feature_10\" AS REAL)) AS total_measure,\n  SUM(CAST(\"feature_10\" AS REAL)) * 100.0\n    / SUM(SUM(CAST(\"feature_10\" AS REAL))) OVER (PARTITION BY \"feature_9\") AS share_within_group\nFROM \"n9\"\nGROUP BY \"feature_9\", \"feature_11\"\nORDER BY share_within_group DESC\nLIMIT 10;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n  \\\"feature_9\\\",\\n  \\\"feature_11\\\",\\n  SUM(CAST(\\\"feature_10\\\" AS REAL)) AS total_measure,\\n  SUM(CAST(\\\"feature_10\\\" AS REAL)) * 100.0\\n    / SUM(SUM(CAST(\\\"feature_10\\\" AS REAL))) OVER (PARTITION BY \\\"feature_9\\\") AS share_within_group\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_9\\\", \\\"feature_11\\\"\\nORDER BY share_within_group DESC\\nLIMIT 10;\", \"columns\": [\"feature_9\", \"feature_11\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"feature_9\": \"91\", \"feature_11\": \"100\", \"total_measure\": 2760.0, \"share_within_group\": 55.11182108626198}, {\"feature_9\": \"9\", \"feature_11\": \"0\", \"total_measure\": 212.0, \"share_within_group\": 51.707317073170735}, {\"feature_9\": \"97\", \"feature_11\": \"100\", \"total_measure\": 2470.0, \"share_within_group\": 50.91733663162235}, {\"feature_9\": \"99\", \"feature_11\": \"100\", \"total_measure\": 2164.0, \"share_within_group\": 50.47818987637042}, {\"feature_9\": \"5\", \"feature_11\": \"0\", \"total_measure\": 610.0, \"share_within_group\": 50.37159372419488}, {\"feature_9\": \"10\", \"feature_11\": \"0\", \"total_measure\": 439.0, \"share_within_group\": 46.21052631578947}, {\"feature_9\": \"93\", \"feature_11\": \"100\", \"total_measure\": 2466.0, \"share_within_group\": 45.339216767788194}, {\"feature_9\": \"62\", \"feature_11\": \"100\", \"total_measure\": 1266.0, \"share_within_group\": 44.40547176429323}, {\"feature_9\": \"1\", \"feature_11\": \"0\", \"total_measure\": 490.0, \"share_within_group\": 43.51687388987567}, {\"feature_9\": \"56\", \"feature_11\": \"100\", \"total_measure\": 651.0, \"share_within_group\": 43.371085942704866}], \"row_count_returned\": 10, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 35.19}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9a62b46e99f2dc1e/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9a62b46e99f2dc1e/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..5bc313af0219bc3f2456cee1c0513578ae9299d5
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9a62b46e99f2dc1e/run_manifest.json
@@ -0,0 +1,91 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:34:50.229295+00:00",
+  "ended_at": "2026-05-19T15:35:03.483625+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_9a62b46e99f2dc1e",
+    "problem_id": "v2p_n9_8f75b5420170d1c4",
+    "dataset_id": "n9",
+    "template_id": "tpl_tpcds_within_group_share",
+    "template_name": "Within-Group Share of Total",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "dependency_strength_similarity",
+    "intended_facet_id": "pairwise_conditional_dependency",
+    "variant_semantic_role": "focused_target_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=feature_9, measure_col=feature_10.",
+    "bindings": {
+      "group_col": "feature_9",
+      "measure_col": "feature_10",
+      "item_col": "feature_11",
+      "top_k": 10,
+      "top_n": 4,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 54.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "item_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;",
+    "notes": [
+      "default_facets=pairwise_conditional_dependency",
+      "template_selection_mode=rule",
+      "problem_index_within_template=2",
+      "sql_variant_index=1/2",
+      "binding_index=25"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 3,
+    "problem_index_within_template": 2,
+    "sql_variant_index": 1,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_9a62b46e99f2dc1e.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_9a62b46e99f2dc1e",
+    "api_calls": 0,
+    "input_tokens": 15059,
+    "cached_input_tokens": 12032,
+    "output_tokens": 698,
+    "total_tokens": 15757,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 13212.32,
+    "sql_execution_elapsed_ms_total": 35.19,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9a62b46e99f2dc1e/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9a62b46e99f2dc1e/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9a62b46e99f2dc1e/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..466ad30b31b9ff39088b5a220ac82cac32c10feb
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9a62b46e99f2dc1e/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:35:03.445508+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 13212.32, "started_at": "2026-05-19T15:34:50.231345+00:00", "ended_at": "2026-05-19T15:35:03.443703+00:00", "prompt_metrics": {"chars": 9798, "bytes_utf8": 9798, "lines": 302, "estimated_tokens": null}, "response_metrics": {"chars": 605, "bytes_utf8": 605, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15059, "cached_input_tokens": 12032, "output_tokens": 698, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n  \\\"feature_9\\\",\\n  \\\"feature_11\\\",\\n  SUM(CAST(\\\"feature_10\\\" AS REAL)) AS total_measure,\\n  SUM(CAST(\\\"feature_10\\\" AS REAL)) * 100.0\\n    / SUM(SUM(CAST(\\\"feature_10\\\" AS REAL))) OVER (PARTITION BY \\\"feature_9\\\") AS share_within_group\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_9\\\", \\\"feature_11\\\"\\nORDER BY share_within_group DESC\\nLIMIT 10;\",\"notes\":\"Uses the provided template with group_col=\\\"feature_9\\\", item_col=\\\"feature_11\\\", and measure_col=\\\"feature_10\\\". CAST is applied because the schema stores these numeric fields as TEXT in SQLite.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9a62b46e99f2dc1e/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9a62b46e99f2dc1e/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..43f5ed421052995451afd5ba297c8d67c4481a82
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9a62b46e99f2dc1e/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_9a62b46e99f2dc1e",
+  "api_calls": 0,
+  "input_tokens": 15059,
+  "cached_input_tokens": 12032,
+  "output_tokens": 698,
+  "total_tokens": 15757,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 13212.32,
+  "sql_execution_elapsed_ms_total": 35.19,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9a62b46e99f2dc1e/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9e6f038061c97750/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9e6f038061c97750/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..5e7e7a1fd395d97da1927a2ae8953d47c4e5f24c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9e6f038061c97750/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=feature_2, measure_col=feature_7.
+Result preview: [{"feature_2": "98", "percentile_measure": 100.0}, {"feature_2": "97", "percentile_measure": 100.0}, {"feature_2": "95", "percentile_measure": 100.0}, {"feature_2": "94", "percentile_measure": 100.0}, {"feature_2": "93", "percentile_measure": 100.0}] Results were truncated.
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9e6f038061c97750/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9e6f038061c97750/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..8bf4b92d802a16f2dadf4d75bbd4c136da25fe3f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9e6f038061c97750/generated_sql.sql
@@ -0,0 +1,41 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_n9_9e6f038061c97750
+-- problem_id: v2p_n9_bc8cb896c6617d43
+-- realization_mode: agent
+-- source_kind: agent
+WITH "ranked" AS (
+  SELECT
+    "feature_2",
+    CAST("feature_7" AS REAL) AS "measure_value",
+    ROW_NUMBER() OVER (
+      PARTITION BY "feature_2"
+      ORDER BY CAST("feature_7" AS REAL)
+    ) AS "rn",
+    COUNT(*) OVER (PARTITION BY "feature_2") AS "cnt"
+  FROM "n9"
+  WHERE "feature_2" IS NOT NULL
+    AND "feature_7" IS NOT NULL
+),
+"thresholded" AS (
+  SELECT
+    "feature_2",
+    "measure_value",
+    "rn",
+    CAST(((95 * "cnt") + 99) / 100 AS INTEGER) AS "target_rn"
+  FROM "ranked"
+)
+SELECT
+  "feature_2",
+  MIN("measure_value") AS "percentile_measure"
+FROM "thresholded"
+WHERE "rn" >= "target_rn"
+GROUP BY "feature_2"
+ORDER BY "percentile_measure" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9e6f038061c97750/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9e6f038061c97750/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..82545fd6a6ee04bc4587c5820a1b0b8217000fa9
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9e6f038061c97750/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH \"ranked\" AS (\n  SELECT\n    \"feature_2\",\n    CAST(\"feature_7\" AS REAL) AS \"measure_value\",\n    ROW_NUMBER() OVER (\n      PARTITION BY \"feature_2\"\n      ORDER BY CAST(\"feature_7\" AS REAL)\n    ) AS \"rn\",\n    COUNT(*) OVER (PARTITION BY \"feature_2\") AS \"cnt\"\n  FROM \"n9\"\n  WHERE \"feature_2\" IS NOT NULL\n    AND \"feature_7\" IS NOT NULL\n),\n\"thresholded\" AS (\n  SELECT\n    \"feature_2\",\n    \"measure_value\",\n    \"rn\",\n    CAST(((95 * \"cnt\") + 99) / 100 AS INTEGER) AS \"target_rn\"\n  FROM \"ranked\"\n)\nSELECT\n  \"feature_2\",\n  MIN(\"measure_value\") AS \"percentile_measure\"\nFROM \"thresholded\"\nWHERE \"rn\" >= \"target_rn\"\nGROUP BY \"feature_2\"\nORDER BY \"percentile_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n  SELECT\\n    \\\"feature_2\\\",\\n    CAST(\\\"feature_7\\\" AS REAL) AS \\\"measure_value\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"feature_2\\\"\\n      ORDER BY CAST(\\\"feature_7\\\" AS REAL)\\n    ) AS \\\"rn\\\",\\n    COUNT(*) OVER (PARTITION BY \\\"feature_2\\\") AS \\\"cnt\\\"\\n  FROM \\\"n9\\\"\\n  WHERE \\\"feature_2\\\" IS NOT NULL\\n    AND \\\"feature_7\\\" IS NOT NULL\\n),\\n\\\"thresholded\\\" AS (\\n  SELECT\\n    \\\"feature_2\\\",\\n    \\\"measure_value\\\",\\n    \\\"rn\\\",\\n    CAST(((95 * \\\"cnt\\\") + 99) / 100 AS INTEGER) AS \\\"target_rn\\\"\\n  FROM \\\"ranked\\\"\\n)\\nSELECT\\n  \\\"feature_2\\\",\\n  MIN(\\\"measure_value\\\") AS \\\"percentile_measure\\\"\\nFROM \\\"thresholded\\\"\\nWHERE \\\"rn\\\" >= \\\"target_rn\\\"\\nGROUP BY \\\"feature_2\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\", \"columns\": [\"feature_2\", \"percentile_measure\"], \"rows\": [{\"feature_2\": \"98\", \"percentile_measure\": 100.0}, {\"feature_2\": \"97\", \"percentile_measure\": 100.0}, {\"feature_2\": \"95\", \"percentile_measure\": 100.0}, {\"feature_2\": \"94\", \"percentile_measure\": 100.0}, {\"feature_2\": \"93\", \"percentile_measure\": 100.0}, {\"feature_2\": \"9\", \"percentile_measure\": 100.0}, {\"feature_2\": \"87\", \"percentile_measure\": 100.0}, {\"feature_2\": \"81\", \"percentile_measure\": 100.0}, {\"feature_2\": \"75\", \"percentile_measure\": 100.0}, {\"feature_2\": \"74\", \"percentile_measure\": 100.0}, {\"feature_2\": \"73\", \"percentile_measure\": 100.0}, {\"feature_2\": \"72\", \"percentile_measure\": 100.0}, {\"feature_2\": \"71\", \"percentile_measure\": 100.0}, {\"feature_2\": \"70\", \"percentile_measure\": 100.0}, {\"feature_2\": \"69\", \"percentile_measure\": 100.0}, {\"feature_2\": \"68\", \"percentile_measure\": 100.0}, {\"feature_2\": \"67\", \"percentile_measure\": 100.0}, {\"feature_2\": \"66\", \"percentile_measure\": 100.0}, {\"feature_2\": \"65\", \"percentile_measure\": 100.0}, {\"feature_2\": \"64\", \"percentile_measure\": 100.0}, {\"feature_2\": \"63\", \"percentile_measure\": 100.0}, {\"feature_2\": \"62\", \"percentile_measure\": 100.0}, {\"feature_2\": \"61\", \"percentile_measure\": 100.0}, {\"feature_2\": \"60\", \"percentile_measure\": 100.0}, {\"feature_2\": \"59\", \"percentile_measure\": 100.0}, {\"feature_2\": \"58\", \"percentile_measure\": 100.0}, {\"feature_2\": \"57\", \"percentile_measure\": 100.0}, {\"feature_2\": \"56\", \"percentile_measure\": 100.0}, {\"feature_2\": \"55\", \"percentile_measure\": 100.0}, {\"feature_2\": \"54\", \"percentile_measure\": 100.0}, {\"feature_2\": \"53\", \"percentile_measure\": 100.0}, {\"feature_2\": \"52\", \"percentile_measure\": 100.0}, {\"feature_2\": \"51\", \"percentile_measure\": 100.0}, {\"feature_2\": \"50\", \"percentile_measure\": 100.0}, {\"feature_2\": \"5\", \"percentile_measure\": 100.0}, {\"feature_2\": \"49\", \"percentile_measure\": 100.0}, {\"feature_2\": \"48\", \"percentile_measure\": 100.0}, {\"feature_2\": \"47\", \"percentile_measure\": 100.0}, {\"feature_2\": \"46\", \"percentile_measure\": 100.0}, {\"feature_2\": \"45\", \"percentile_measure\": 100.0}, {\"feature_2\": \"44\", \"percentile_measure\": 100.0}, {\"feature_2\": \"43\", \"percentile_measure\": 100.0}, {\"feature_2\": \"42\", \"percentile_measure\": 100.0}, {\"feature_2\": \"41\", \"percentile_measure\": 100.0}, {\"feature_2\": \"40\", \"percentile_measure\": 100.0}, {\"feature_2\": \"39\", \"percentile_measure\": 100.0}, {\"feature_2\": \"38\", \"percentile_measure\": 100.0}, {\"feature_2\": \"37\", \"percentile_measure\": 100.0}, {\"feature_2\": \"36\", \"percentile_measure\": 100.0}, {\"feature_2\": \"35\", \"percentile_measure\": 100.0}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 33.94}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9e6f038061c97750/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9e6f038061c97750/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..a72d822c443dacba3817cb0d2c76540ed9c7b1cb
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9e6f038061c97750/run_manifest.json
@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:52:07.014264+00:00",
+  "ended_at": "2026-05-19T15:52:28.332378+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_9e6f038061c97750",
+    "problem_id": "v2p_n9_bc8cb896c6617d43",
+    "dataset_id": "n9",
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_concentration_consistency",
+    "intended_facet_id": "rare_target_concentration",
+    "variant_semantic_role": "focused_target_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=feature_2, measure_col=feature_7.",
+    "bindings": {
+      "group_col": "feature_2",
+      "measure_col": "feature_7",
+      "top_k": 11,
+      "top_n": 5,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 74.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;",
+    "notes": [
+      "default_facets=rare_target_concentration",
+      "template_selection_mode=rule",
+      "problem_index_within_template=3",
+      "sql_variant_index=1/2",
+      "binding_index=86"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 8,
+    "problem_index_within_template": 3,
+    "sql_variant_index": 1,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_9e6f038061c97750.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_9e6f038061c97750",
+    "api_calls": 0,
+    "input_tokens": 14978,
+    "cached_input_tokens": 13696,
+    "output_tokens": 831,
+    "total_tokens": 15809,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 21279.85,
+    "sql_execution_elapsed_ms_total": 33.94,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9e6f038061c97750/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9e6f038061c97750/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9e6f038061c97750/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..a1d48530d11b344daaa4fd82b622643de1d01873
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9e6f038061c97750/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:52:28.296461+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 21279.85, "started_at": "2026-05-19T15:52:07.015752+00:00", "ended_at": "2026-05-19T15:52:28.295624+00:00", "prompt_metrics": {"chars": 9568, "bytes_utf8": 9568, "lines": 300, "estimated_tokens": null}, "response_metrics": {"chars": 1027, "bytes_utf8": 1027, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14978, "cached_input_tokens": 13696, "output_tokens": 831, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n  SELECT\\n    \\\"feature_2\\\",\\n    CAST(\\\"feature_7\\\" AS REAL) AS \\\"measure_value\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"feature_2\\\"\\n      ORDER BY CAST(\\\"feature_7\\\" AS REAL)\\n    ) AS \\\"rn\\\",\\n    COUNT(*) OVER (PARTITION BY \\\"feature_2\\\") AS \\\"cnt\\\"\\n  FROM \\\"n9\\\"\\n  WHERE \\\"feature_2\\\" IS NOT NULL\\n    AND \\\"feature_7\\\" IS NOT NULL\\n),\\n\\\"thresholded\\\" AS (\\n  SELECT\\n    \\\"feature_2\\\",\\n    \\\"measure_value\\\",\\n    \\\"rn\\\",\\n    CAST(((95 * \\\"cnt\\\") + 99) / 100 AS INTEGER) AS \\\"target_rn\\\"\\n  FROM \\\"ranked\\\"\\n)\\nSELECT\\n  \\\"feature_2\\\",\\n  MIN(\\\"measure_value\\\") AS \\\"percentile_measure\\\"\\nFROM \\\"thresholded\\\"\\nWHERE \\\"rn\\\" >= \\\"target_rn\\\"\\nGROUP BY \\\"feature_2\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\",\"notes\":\"SQLite does not support PERCENTILE_CONT, so this emulates the 0.95 percentile per feature_2 group by ranking CAST(feature_7 AS REAL) values and selecting the smallest value at or above rank"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9e6f038061c97750/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9e6f038061c97750/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..844d9479580079526aa50f780d0433f7dfccc652
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9e6f038061c97750/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_9e6f038061c97750",
+  "api_calls": 0,
+  "input_tokens": 14978,
+  "cached_input_tokens": 13696,
+  "output_tokens": 831,
+  "total_tokens": 15809,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 21279.85,
+  "sql_execution_elapsed_ms_total": 33.94,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_9e6f038061c97750/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_a0d0df6c31921147/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_a0d0df6c31921147/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..2fb434e8315975a66133814b25f686c7643b1b1d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_a0d0df6c31921147/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=feature_1.
+Result preview: [{"empirical_cdf_at_threshold": 0.7537299854439592}]
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_a0d0df6c31921147/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_a0d0df6c31921147/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..e6c5d6e0e851d773192bf6dc9185defec589e07e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_a0d0df6c31921147/generated_sql.sql
@@ -0,0 +1,15 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_set_consistency
+-- intended_facet_id: low_support_extremes
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_threshold_rarity_cdf
+-- query_record_id: v2q_n9_a0d0df6c31921147
+-- problem_id: v2p_n9_12181171f623022a
+-- realization_mode: agent
+-- source_kind: agent
+SELECT AVG(CASE WHEN CAST("feature_1" AS REAL) <= 65.0 THEN 1 ELSE 0 END) AS "empirical_cdf_at_threshold"
+FROM "n9";
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_a0d0df6c31921147/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_a0d0df6c31921147/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..98aab85315448558827f17762f59711ceac32a55
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_a0d0df6c31921147/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_threshold_rarity_cdf\nSELECT AVG(CASE WHEN CAST(\"feature_1\" AS REAL) <= 65.0 THEN 1 ELSE 0 END) AS \"empirical_cdf_at_threshold\"\nFROM \"n9\";", "result": "{\"query\": \"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(\\\"feature_1\\\" AS REAL) <= 65.0 THEN 1 ELSE 0 END) AS \\\"empirical_cdf_at_threshold\\\"\\nFROM \\\"n9\\\";\", \"columns\": [\"empirical_cdf_at_threshold\"], \"rows\": [{\"empirical_cdf_at_threshold\": 0.7537299854439592}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 1.92}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_a0d0df6c31921147/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_a0d0df6c31921147/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..8cff11cd52e05c5ab59639a61e89acc97f4df5b7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_a0d0df6c31921147/run_manifest.json
@@ -0,0 +1,87 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T16:04:21.023056+00:00",
+  "ended_at": "2026-05-19T16:04:31.443410+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_a0d0df6c31921147",
+    "problem_id": "v2p_n9_12181171f623022a",
+    "dataset_id": "n9",
+    "template_id": "tpl_threshold_rarity_cdf",
+    "template_name": "Threshold Rarity CDF",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_set_consistency",
+    "intended_facet_id": "low_support_extremes",
+    "variant_semantic_role": "rare_extreme_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=feature_1.",
+    "bindings": {
+      "measure_col": "feature_1",
+      "top_k": 12,
+      "top_n": 3,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 65.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};",
+    "notes": [
+      "default_facets=low_support_extremes",
+      "template_selection_mode=rule",
+      "problem_index_within_template=5",
+      "sql_variant_index=1/1",
+      "binding_index=112"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 10,
+    "problem_index_within_template": 5,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_a0d0df6c31921147.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_a0d0df6c31921147",
+    "api_calls": 0,
+    "input_tokens": 14927,
+    "cached_input_tokens": 12032,
+    "output_tokens": 266,
+    "total_tokens": 15193,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 10415.19,
+    "sql_execution_elapsed_ms_total": 1.92,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_a0d0df6c31921147/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_a0d0df6c31921147/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_a0d0df6c31921147/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..8a474df78543b3173fb359ac472dc3b5fed43b1c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_a0d0df6c31921147/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T16:04:31.440108+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 10415.19, "started_at": "2026-05-19T16:04:21.024103+00:00", "ended_at": "2026-05-19T16:04:31.439316+00:00", "prompt_metrics": {"chars": 9324, "bytes_utf8": 9324, "lines": 298, "estimated_tokens": null}, "response_metrics": {"chars": 395, "bytes_utf8": 395, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14927, "cached_input_tokens": 12032, "output_tokens": 266, "reasoning_output_tokens": 155}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(\\\"feature_1\\\" AS REAL) <= 65.0 THEN 1 ELSE 0 END) AS \\\"empirical_cdf_at_threshold\\\"\\nFROM \\\"n9\\\";\",\"notes\":\"Used the provided Threshold Rarity CDF template with measure_col bound to \\\"feature_1\\\" and measure_threshold fixed at 65.0. CAST to REAL is included because the schema stores numeric-looking features as TEXT.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_a0d0df6c31921147/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_a0d0df6c31921147/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..8043cf707486f8a1f68d0f7f6edaf609c0e0c9d7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_a0d0df6c31921147/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_a0d0df6c31921147",
+  "api_calls": 0,
+  "input_tokens": 14927,
+  "cached_input_tokens": 12032,
+  "output_tokens": 266,
+  "total_tokens": 15193,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 10415.19,
+  "sql_execution_elapsed_ms_total": 1.92,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_a0d0df6c31921147/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_a26c3695d5882b4b/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_a26c3695d5882b4b/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..ac33238a13d1ef9ae6a9d60a16f6f04249d13f47
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_a26c3695d5882b4b/run_manifest.json
@@ -0,0 +1,69 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T16:08:31.225342+00:00",
+  "ended_at": "2026-05-19T16:08:38.538892+00:00",
+  "status": "failed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_a26c3695d5882b4b",
+    "problem_id": "v2p_n9_e38dd0427974682f",
+    "dataset_id": "n9",
+    "template_id": "tpl_m4_window_partition_avg",
+    "template_name": "Window Partition Average",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "slice_level_consistency",
+    "intended_facet_id": "conditional_interaction_hotspots",
+    "variant_semantic_role": "ranked_signal_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Window Partition Average to probe slice_level_consistency with semantic role ranked_signal_view. Focus on group_col=feature_16, measure_col=feature_7.",
+    "bindings": {
+      "group_col": "feature_16",
+      "measure_col": "feature_7",
+      "top_k": 19,
+      "top_n": 6,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.05,
+      "baseline_multiplier": 1.75,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 4,
+      "measure_threshold": 67.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;",
+    "notes": [
+      "default_facets=conditional_interaction_hotspots",
+      "template_selection_mode=rule",
+      "problem_index_within_template=3",
+      "sql_variant_index=2/2",
+      "binding_index=134"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 12,
+    "problem_index_within_template": 3,
+    "sql_variant_index": 2,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "error": "AI CLI command failed with exit code 1: "
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_a26c3695d5882b4b/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_a26c3695d5882b4b/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..cf93d8821f108a61ab5cea1f6284239865bb2d13
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_a26c3695d5882b4b/trace.jsonl
@@ -0,0 +1,2 @@
+{"timestamp": "2026-05-19T16:08:34.637058+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3409.44, "started_at": "2026-05-19T16:08:31.226778+00:00", "ended_at": "2026-05-19T16:08:34.636244+00:00", "prompt_metrics": {"chars": 9476, "bytes_utf8": 9476, "lines": 300, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fe-f5f4-7e92-890d-4b692a86e1b2\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}
+{"timestamp": "2026-05-19T16:08:38.538797+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 2899.12, "started_at": "2026-05-19T16:08:35.638876+00:00", "ended_at": "2026-05-19T16:08:38.538040+00:00", "prompt_metrics": {"chars": 9476, "bytes_utf8": 9476, "lines": 300, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40ff-0751-7991-ac4a-099d565bb146\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_afe7268b45844569/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_afe7268b45844569/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..edfdb356e42ef986e123fdb53460574c4956f805
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_afe7268b45844569/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=feature_10, condition_col=class.
+Result preview: [{"feature_10": "13", "condition_ratio": 35.0}, {"feature_10": "15", "condition_ratio": 35.0}, {"feature_10": "12", "condition_ratio": 23.0}, {"feature_10": "11", "condition_ratio": 15.5}, {"feature_10": "16", "condition_ratio": 14.0}] Results were truncated.
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_afe7268b45844569/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_afe7268b45844569/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..192ac50ebeade6954e3ad52d993d07c3caccffaa
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_afe7268b45844569/generated_sql.sql
@@ -0,0 +1,24 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: direction_consistency
+-- intended_facet_id: conditional_rate_shift
+-- variant_semantic_role: contrastive_conditional_view
+-- template_id: tpl_m4_group_ratio_two_conditions
+-- query_record_id: v2q_n9_afe7268b45844569
+-- problem_id: v2p_n9_d413f72fa4117bbc
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+    SELECT "feature_10",
+           SUM(CASE WHEN "class" = '2' THEN 1 ELSE 0 END) AS numerator_count,
+           SUM(CASE WHEN "class" = '4' THEN 1 ELSE 0 END) AS denominator_count
+    FROM "n9"
+    GROUP BY "feature_10"
+)
+SELECT "feature_10",
+       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio
+FROM grouped
+ORDER BY condition_ratio DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_afe7268b45844569/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_afe7268b45844569/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..b796f8c0b49914fa54d8322e91938336c141d9fa
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_afe7268b45844569/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_ratio_two_conditions\nWITH grouped AS (\n    SELECT \"feature_10\",\n           SUM(CASE WHEN \"class\" = '2' THEN 1 ELSE 0 END) AS numerator_count,\n           SUM(CASE WHEN \"class\" = '4' THEN 1 ELSE 0 END) AS denominator_count\n    FROM \"n9\"\n    GROUP BY \"feature_10\"\n)\nSELECT \"feature_10\",\n       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n    SELECT \\\"feature_10\\\",\\n           SUM(CASE WHEN \\\"class\\\" = '2' THEN 1 ELSE 0 END) AS numerator_count,\\n           SUM(CASE WHEN \\\"class\\\" = '4' THEN 1 ELSE 0 END) AS denominator_count\\n    FROM \\\"n9\\\"\\n    GROUP BY \\\"feature_10\\\"\\n)\\nSELECT \\\"feature_10\\\",\\n       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\", \"columns\": [\"feature_10\", \"condition_ratio\"], \"rows\": [{\"feature_10\": \"13\", \"condition_ratio\": 35.0}, {\"feature_10\": \"15\", \"condition_ratio\": 35.0}, {\"feature_10\": \"12\", \"condition_ratio\": 23.0}, {\"feature_10\": \"11\", \"condition_ratio\": 15.5}, {\"feature_10\": \"16\", \"condition_ratio\": 14.0}, {\"feature_10\": \"8\", \"condition_ratio\": 13.5}, {\"feature_10\": \"14\", \"condition_ratio\": 8.5}, {\"feature_10\": \"19\", \"condition_ratio\": 8.5}, {\"feature_10\": \"18\", \"condition_ratio\": 6.5}, {\"feature_10\": \"21\", \"condition_ratio\": 5.8}, {\"feature_10\": \"17\", \"condition_ratio\": 5.6}, {\"feature_10\": \"20\", \"condition_ratio\": 4.0}, {\"feature_10\": \"23\", \"condition_ratio\": 3.857142857142857}, {\"feature_10\": \"22\", \"condition_ratio\": 3.2}, {\"feature_10\": \"26\", \"condition_ratio\": 2.5}, {\"feature_10\": \"24\", \"condition_ratio\": 2.3636363636363638}, {\"feature_10\": \"25\", \"condition_ratio\": 2.3333333333333335}, {\"feature_10\": \"28\", \"condition_ratio\": 1.7857142857142858}, {\"feature_10\": \"31\", \"condition_ratio\": 1.6875}, {\"feature_10\": \"27\", \"condition_ratio\": 1.3846153846153846}, {\"feature_10\": \"29\", \"condition_ratio\": 1.1818181818181819}, {\"feature_10\": \"32\", \"condition_ratio\": 1.0}, {\"feature_10\": \"30\", \"condition_ratio\": 0.8518518518518519}, {\"feature_10\": \"33\", \"condition_ratio\": 0.5909090909090909}, {\"feature_10\": \"43\", \"condition_ratio\": 0.5789473684210527}, {\"feature_10\": \"42\", \"condition_ratio\": 0.5714285714285714}, {\"feature_10\": \"35\", \"condition_ratio\": 0.5428571428571428}, {\"feature_10\": \"36\", \"condition_ratio\": 0.5357142857142857}, {\"feature_10\": \"38\", \"condition_ratio\": 0.4642857142857143}, {\"feature_10\": \"41\", \"condition_ratio\": 0.44}, {\"feature_10\": \"37\", \"condition_ratio\": 0.43478260869565216}, {\"feature_10\": \"44\", \"condition_ratio\": 0.42857142857142855}, {\"feature_10\": \"34\", \"condition_ratio\": 0.42424242424242425}, {\"feature_10\": \"39\", \"condition_ratio\": 0.4230769230769231}, {\"feature_10\": \"46\", \"condition_ratio\": 0.4230769230769231}, {\"feature_10\": \"51\", \"condition_ratio\": 0.3125}, {\"feature_10\": \"47\", \"condition_ratio\": 0.25}, {\"feature_10\": \"40\", \"condition_ratio\": 0.2}, {\"feature_10\": \"48\", \"condition_ratio\": 0.2}, {\"feature_10\": \"50\", \"condition_ratio\": 0.2}, {\"feature_10\": \"61\", \"condition_ratio\": 0.18181818181818182}, {\"feature_10\": \"52\", \"condition_ratio\": 0.17647058823529413}, {\"feature_10\": \"54\", \"condition_ratio\": 0.125}, {\"feature_10\": \"45\", \"condition_ratio\": 0.12}, {\"feature_10\": \"49\", \"condition_ratio\": 0.1111111111111111}, {\"feature_10\": \"55\", \"condition_ratio\": 0.1}, {\"feature_10\": \"53\", \"condition_ratio\": 0.07142857142857142}, {\"feature_10\": \"62\", \"condition_ratio\": 0.045454545454545456}, {\"feature_10\": \"100\", \"condition_ratio\": 0.0}, {\"feature_10\": \"56\", \"condition_ratio\": 0.0}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 6.23}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_afe7268b45844569/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_afe7268b45844569/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..ce7f327a37e73347a130280fcbaa5364b4949d72
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_afe7268b45844569/run_manifest.json
@@ -0,0 +1,92 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:41:14.558063+00:00",
+  "ended_at": "2026-05-19T15:41:24.161568+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_afe7268b45844569",
+    "problem_id": "v2p_n9_d413f72fa4117bbc",
+    "dataset_id": "n9",
+    "template_id": "tpl_m4_group_ratio_two_conditions",
+    "template_name": "Grouped Ratio of Two Conditions",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "direction_consistency",
+    "intended_facet_id": "conditional_rate_shift",
+    "variant_semantic_role": "contrastive_conditional_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=feature_10, condition_col=class.",
+    "bindings": {
+      "group_col": "feature_10",
+      "condition_col": "class",
+      "condition_value": "2",
+      "positive_value": "2",
+      "negative_value": "4",
+      "top_k": 13,
+      "top_n": 6,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 55.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "condition_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "WITH grouped AS (\n    SELECT {group_col},\n           SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n           SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n    FROM {table}\n    GROUP BY {group_col}\n)\nSELECT {group_col},\n       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;",
+    "notes": [
+      "default_facets=conditional_rate_shift",
+      "template_selection_mode=rule",
+      "problem_index_within_template=8",
+      "sql_variant_index=1/1",
+      "binding_index=43"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 4,
+    "problem_index_within_template": 8,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_afe7268b45844569.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_afe7268b45844569",
+    "api_calls": 0,
+    "input_tokens": 15145,
+    "cached_input_tokens": 14720,
+    "output_tokens": 348,
+    "total_tokens": 15493,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 9592.87,
+    "sql_execution_elapsed_ms_total": 6.23,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_afe7268b45844569/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_afe7268b45844569/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_afe7268b45844569/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..f110ee82e8611e5d2db9ba5a90f41a6f33a08356
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_afe7268b45844569/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:41:24.153336+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 9592.87, "started_at": "2026-05-19T15:41:14.559626+00:00", "ended_at": "2026-05-19T15:41:24.152528+00:00", "prompt_metrics": {"chars": 10188, "bytes_utf8": 10188, "lines": 303, "estimated_tokens": null}, "response_metrics": {"chars": 664, "bytes_utf8": 664, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15145, "cached_input_tokens": 14720, "output_tokens": 348, "reasoning_output_tokens": 165}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n    SELECT \\\"feature_10\\\",\\n           SUM(CASE WHEN \\\"class\\\" = '2' THEN 1 ELSE 0 END) AS numerator_count,\\n           SUM(CASE WHEN \\\"class\\\" = '4' THEN 1 ELSE 0 END) AS denominator_count\\n    FROM \\\"n9\\\"\\n    GROUP BY \\\"feature_10\\\"\\n)\\nSELECT \\\"feature_10\\\",\\n       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\",\"notes\":\"Used the required grouped ratio template with group_col bound to \\\"feature_10\\\" and condition_col bound to \\\"class\\\", comparing class '2' to class '4' in SQLite-compatible SQL.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_afe7268b45844569/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_afe7268b45844569/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..db1dc9958de63500d5d599fb6cc42743f5696440
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_afe7268b45844569/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_afe7268b45844569",
+  "api_calls": 0,
+  "input_tokens": 15145,
+  "cached_input_tokens": 14720,
+  "output_tokens": 348,
+  "total_tokens": 15493,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 9592.87,
+  "sql_execution_elapsed_ms_total": 6.23,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_afe7268b45844569/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_b890b34e16713778/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_b890b34e16713778/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..155654ac472630050a45863c5b9b865cd4a4a48f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_b890b34e16713778/run_manifest.json
@@ -0,0 +1,69 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:54:49.849403+00:00",
+  "ended_at": "2026-05-19T15:54:56.685737+00:00",
+  "status": "failed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_b890b34e16713778",
+    "problem_id": "v2p_n9_b8d7e0be8cebdd9b",
+    "dataset_id": "n9",
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_concentration_consistency",
+    "intended_facet_id": "rare_target_concentration",
+    "variant_semantic_role": "ranked_signal_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=feature_4, measure_col=feature_9.",
+    "bindings": {
+      "group_col": "feature_4",
+      "measure_col": "feature_9",
+      "top_k": 18,
+      "top_n": 4,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.05,
+      "baseline_multiplier": 1.75,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 4,
+      "measure_threshold": 80.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;",
+    "notes": [
+      "default_facets=rare_target_concentration",
+      "template_selection_mode=rule",
+      "problem_index_within_template=5",
+      "sql_variant_index=2/2",
+      "binding_index=88"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 8,
+    "problem_index_within_template": 5,
+    "sql_variant_index": 2,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "error": "AI CLI command failed with exit code 1: "
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_b890b34e16713778/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_b890b34e16713778/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..9c3b27183dbed0a7ccd554a19a306a858845423e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_b890b34e16713778/trace.jsonl
@@ -0,0 +1,2 @@
+{"timestamp": "2026-05-19T15:54:52.664593+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 2813.25, "started_at": "2026-05-19T15:54:49.850559+00:00", "ended_at": "2026-05-19T15:54:52.663835+00:00", "prompt_metrics": {"chars": 9568, "bytes_utf8": 9568, "lines": 300, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f2-6d9b-7ff2-bd56-1436d9ccad32\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}
+{"timestamp": "2026-05-19T15:54:56.685539+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3018.72, "started_at": "2026-05-19T15:54:53.665454+00:00", "ended_at": "2026-05-19T15:54:56.684205+00:00", "prompt_metrics": {"chars": 9568, "bytes_utf8": 9568, "lines": 300, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f2-7c5b-7d73-97e8-c86394d0023f\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_bb8de1438d36f116/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_bb8de1438d36f116/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..8ed2526a9a49cf934e76f5c5e0dbd894e688772f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_bb8de1438d36f116/final_answer.txt
@@ -0,0 +1 @@
+{"row_count": null, "preview_rows": [{"feature_13": "100", "support": 509, "avg_response": 90.54616895874263}, {"feature_13": "50", "support": 443, "avg_response": 78.76523702031602}, {"feature_13": "51", "support": 313, "avg_response": 84.07987220447285}, {"feature_13": "49", "support": 298, "avg_response": 83.09395973154362}, {"feature_13": "53", "support": 256, "avg_response": 84.49609375}]}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_bb8de1438d36f116/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_bb8de1438d36f116/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..530574830ca77fa6717c55333cb93bf607fb4637
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_bb8de1438d36f116/generated_sql.sql
@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: high_cardinality_response_stability
+-- intended_facet_id: target_cardinality_cross_section
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_cardinality_high_card_response_stability
+-- query_record_id: v2q_n9_bb8de1438d36f116
+-- problem_id: v2p_n9_f8bbcc636b2d27e6
+-- realization_mode: deterministic
+-- source_kind: deterministic
+SELECT
+    "feature_13",
+    COUNT(*) AS support,
+    AVG("feature_2") AS avg_response
+FROM "n9"
+GROUP BY "feature_13"
+HAVING COUNT(*) >= 5.0
+ORDER BY support DESC, avg_response DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_bb8de1438d36f116/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_bb8de1438d36f116/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..88ba28b2020fc08ca79359f02ec927dcff9a4a63
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_bb8de1438d36f116/query_results.jsonl
@@ -0,0 +1 @@
+{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: n9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: high_cardinality_response_stability\n-- intended_facet_id: target_cardinality_cross_section\n-- variant_semantic_role: focused_target_view\n-- template_id: tpl_cardinality_high_card_response_stability\n-- query_record_id: v2q_n9_bb8de1438d36f116\n-- problem_id: v2p_n9_f8bbcc636b2d27e6\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n    \"feature_13\",\n    COUNT(*) AS support,\n    AVG(\"feature_2\") AS avg_response\nFROM \"n9\"\nGROUP BY \"feature_13\"\nHAVING COUNT(*) >= 5.0\nORDER BY support DESC, avg_response DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: n9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: high_cardinality_response_stability\\n-- intended_facet_id: target_cardinality_cross_section\\n-- variant_semantic_role: focused_target_view\\n-- template_id: tpl_cardinality_high_card_response_stability\\n-- query_record_id: v2q_n9_bb8de1438d36f116\\n-- problem_id: v2p_n9_f8bbcc636b2d27e6\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n    \\\"feature_13\\\",\\n    COUNT(*) AS support,\\n    AVG(\\\"feature_2\\\") AS avg_response\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_13\\\"\\nHAVING COUNT(*) >= 5.0\\nORDER BY support DESC, avg_response DESC;\", \"columns\": [\"feature_13\", \"support\", \"avg_response\"], \"rows\": [{\"feature_13\": \"100\", \"support\": 509, \"avg_response\": 90.54616895874263}, {\"feature_13\": \"50\", \"support\": 443, \"avg_response\": 78.76523702031602}, {\"feature_13\": \"51\", \"support\": 313, \"avg_response\": 84.07987220447285}, {\"feature_13\": \"49\", \"support\": 298, \"avg_response\": 83.09395973154362}, {\"feature_13\": \"53\", \"support\": 256, \"avg_response\": 84.49609375}, {\"feature_13\": \"52\", \"support\": 255, \"avg_response\": 84.6156862745098}, {\"feature_13\": \"48\", \"support\": 250, \"avg_response\": 84.88}, {\"feature_13\": \"55\", \"support\": 225, \"avg_response\": 84.7911111111111}, {\"feature_13\": \"46\", \"support\": 218, \"avg_response\": 86.53211009174312}, {\"feature_13\": \"56\", \"support\": 217, \"avg_response\": 83.39170506912443}, {\"feature_13\": \"54\", \"support\": 209, \"avg_response\": 83.7846889952153}, {\"feature_13\": \"60\", \"support\": 208, \"avg_response\": 85.96634615384616}, {\"feature_13\": \"45\", \"support\": 205, \"avg_response\": 85.8048780487805}, {\"feature_13\": \"58\", \"support\": 205, \"avg_response\": 83.76585365853659}, {\"feature_13\": \"62\", \"support\": 200, \"avg_response\": 86.32}, {\"feature_13\": \"57\", \"support\": 199, \"avg_response\": 82.84422110552764}, {\"feature_13\": \"41\", \"support\": 192, \"avg_response\": 86.18229166666667}, {\"feature_13\": \"47\", \"support\": 192, \"avg_response\": 85.484375}, {\"feature_13\": \"0\", \"support\": 186, \"avg_response\": 80.51612903225806}, {\"feature_13\": \"43\", \"support\": 184, \"avg_response\": 85.28260869565217}, {\"feature_13\": \"42\", \"support\": 182, \"avg_response\": 85.23626373626374}, {\"feature_13\": \"44\", \"support\": 181, \"avg_response\": 87.23756906077348}, {\"feature_13\": \"61\", \"support\": 171, \"avg_response\": 84.28654970760233}, {\"feature_13\": \"38\", \"support\": 161, \"avg_response\": 86.36024844720497}, {\"feature_13\": \"40\", \"support\": 157, \"avg_response\": 84.54777070063695}, {\"feature_13\": \"59\", \"support\": 155, \"avg_response\": 84.31612903225806}, {\"feature_13\": \"37\", \"support\": 150, \"avg_response\": 84.42}, {\"feature_13\": \"64\", \"support\": 141, \"avg_response\": 86.08510638297872}, {\"feature_13\": \"63\", \"support\": 139, \"avg_response\": 85.9136690647482}, {\"feature_13\": \"65\", \"support\": 138, \"avg_response\": 82.64492753623189}, {\"feature_13\": \"39\", \"support\": 136, \"avg_response\": 88.05882352941177}, {\"feature_13\": \"68\", \"support\": 133, \"avg_response\": 86.35338345864662}, {\"feature_13\": \"66\", \"support\": 133, \"avg_response\": 85.26315789473684}, {\"feature_13\": \"36\", \"support\": 129, \"avg_response\": 82.93023255813954}, {\"feature_13\": \"67\", \"support\": 124, \"avg_response\": 84.5725806451613}, {\"feature_13\": \"35\", \"support\": 122, \"avg_response\": 85.80327868852459}, {\"feature_13\": \"70\", \"support\": 115, \"avg_response\": 87.99130434782609}, {\"feature_13\": \"69\", \"support\": 105, \"avg_response\": 85.87619047619047}, {\"feature_13\": \"76\", \"support\": 101, \"avg_response\": 85.16831683168317}, {\"feature_13\": \"34\", \"support\": 101, \"avg_response\": 85.0990099009901}, {\"feature_13\": \"32\", \"support\": 100, \"avg_response\": 81.8}, {\"feature_13\": \"80\", \"support\": 97, \"avg_response\": 88.03092783505154}, {\"feature_13\": \"33\", \"support\": 96, \"avg_response\": 82.28125}, {\"feature_13\": \"78\", \"support\": 93, \"avg_response\": 86.76344086021506}, {\"feature_13\": \"75\", \"support\": 92, \"avg_response\": 87.47826086956522}, {\"feature_13\": \"73\", \"support\": 90, \"avg_response\": 84.06666666666666}, {\"feature_13\": \"74\", \"support\": 89, \"avg_response\": 86.48314606741573}, {\"feature_13\": \"29\", \"support\": 87, \"avg_response\": 83.67816091954023}, {\"feature_13\": \"84\", \"support\": 86, \"avg_response\": 88.29069767441861}, {\"feature_13\": \"71\", \"support\": 82, \"avg_response\": 86.13414634146342}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 5.24}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_bb8de1438d36f116/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_bb8de1438d36f116/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..376834949921bcbca59ae5b0f8775fab00c992ca
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_bb8de1438d36f116/run_manifest.json
@@ -0,0 +1,60 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T16:10:15.909420+00:00",
+  "ended_at": "2026-05-19T16:10:15.915419+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_bb8de1438d36f116",
+    "problem_id": "v2p_n9_f8bbcc636b2d27e6",
+    "dataset_id": "n9",
+    "template_id": "tpl_cardinality_high_card_response_stability",
+    "template_name": "High-Cardinality Response Stability",
+    "family_id": "cardinality_structure",
+    "canonical_subitem_id": "high_cardinality_response_stability",
+    "intended_facet_id": "target_cardinality_cross_section",
+    "variant_semantic_role": "focused_target_view",
+    "subitem_assignment_source": "template_fixed",
+    "source_kind": "deterministic",
+    "realization_mode": "deterministic",
+    "gate_priority": "deterministic",
+    "extended_family": true,
+    "question": "Use template High-Cardinality Response Stability to probe high_cardinality_response_stability with semantic role focused_target_view. Focus on measure_col=feature_2, key_col=feature_13.",
+    "bindings": {
+      "key_col": "feature_13",
+      "measure_col": "feature_2",
+      "min_support": 5
+    },
+    "binding_roles": [
+      "key_col",
+      "target_col"
+    ],
+    "coverage_target_min": "enumerate_all_applicable",
+    "runtime_sql_skeleton": "SELECT\n    {key_col},\n    COUNT(*) AS support,\n    AVG({measure_col}) AS avg_response\nFROM {table}\nGROUP BY {key_col}\nHAVING COUNT(*) >= {min_support}\nORDER BY support DESC, avg_response DESC;",
+    "notes": [
+      "default_facets=target_cardinality_cross_section",
+      "template_selection_mode=deterministic",
+      "problem_index_within_template=10",
+      "sql_variant_index=1/1"
+    ],
+    "template_selection_mode": "deterministic",
+    "selected_template_rank": 0,
+    "problem_index_within_template": 10,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_bb8de1438d36f116.sql",
+  "usage_summary": {
+    "engine": "template",
+    "input_tokens": 0,
+    "cached_input_tokens": 0,
+    "output_tokens": 0,
+    "total_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "none"
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_bb8de1438d36f116/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_bb8de1438d36f116/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_bb8de1438d36f116/usage_summary.json
@@ -0,0 +1,9 @@
+{
+  "engine": "template",
+  "input_tokens": 0,
+  "cached_input_tokens": 0,
+  "output_tokens": 0,
+  "total_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "none"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c3e0fbce48684752/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c3e0fbce48684752/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..a4b6523a1298b071192773e7db9100e66ef03a48
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c3e0fbce48684752/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=feature_6, measure_col=feature_10.
+Result preview: [{"feature_6": "100", "group_value": 57057.0}]
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c3e0fbce48684752/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c3e0fbce48684752/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..7d987c25fc183635dba0aec886897a6940471c34
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c3e0fbce48684752/generated_sql.sql
@@ -0,0 +1,26 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: filtered_stable_view
+-- template_id: tpl_tpch_relative_total_threshold
+-- query_record_id: v2q_n9_c3e0fbce48684752
+-- problem_id: v2p_n9_38055fcac0a748d7
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+    SELECT "feature_6", SUM(CAST("feature_10" AS REAL)) AS group_value
+    FROM "n9"
+    GROUP BY "feature_6"
+), total AS (
+    SELECT SUM(group_value) AS total_value
+    FROM grouped
+)
+SELECT g."feature_6", g.group_value
+FROM grouped AS g
+CROSS JOIN total AS t
+WHERE g.group_value > t.total_value * 0.1
+ORDER BY g.group_value DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c3e0fbce48684752/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c3e0fbce48684752/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..b0e880f6edf87845b05ee6d210d6caa946cb9022
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c3e0fbce48684752/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_relative_total_threshold\nWITH grouped AS (\n    SELECT \"feature_6\", SUM(CAST(\"feature_10\" AS REAL)) AS group_value\n    FROM \"n9\"\n    GROUP BY \"feature_6\"\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.\"feature_6\", g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * 0.1\nORDER BY g.group_value DESC;", "result": "{\"query\": \"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n    SELECT \\\"feature_6\\\", SUM(CAST(\\\"feature_10\\\" AS REAL)) AS group_value\\n    FROM \\\"n9\\\"\\n    GROUP BY \\\"feature_6\\\"\\n), total AS (\\n    SELECT SUM(group_value) AS total_value\\n    FROM grouped\\n)\\nSELECT g.\\\"feature_6\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.1\\nORDER BY g.group_value DESC;\", \"columns\": [\"feature_6\", \"group_value\"], \"rows\": [{\"feature_6\": \"100\", \"group_value\": 57057.0}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 7.01}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c3e0fbce48684752/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c3e0fbce48684752/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..3bb8528b11193669399328280a8729305b7aa783
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c3e0fbce48684752/run_manifest.json
@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:46:38.971236+00:00",
+  "ended_at": "2026-05-19T15:46:50.577598+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_c3e0fbce48684752",
+    "problem_id": "v2p_n9_38055fcac0a748d7",
+    "dataset_id": "n9",
+    "template_id": "tpl_tpch_relative_total_threshold",
+    "template_name": "Relative-to-Total Extreme Threshold",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_mass_similarity",
+    "intended_facet_id": "tail_ranked_signal",
+    "variant_semantic_role": "filtered_stable_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=feature_6, measure_col=feature_10.",
+    "bindings": {
+      "group_col": "feature_6",
+      "measure_col": "feature_10",
+      "top_k": 13,
+      "top_n": 4,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 54.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "WITH grouped AS (\n    SELECT {group_col}, SUM({measure_col}) AS group_value\n    FROM {table}\n    GROUP BY {group_col}\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;",
+    "notes": [
+      "default_facets=tail_ranked_signal",
+      "template_selection_mode=rule",
+      "problem_index_within_template=2",
+      "sql_variant_index=1/2",
+      "binding_index=73"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 7,
+    "problem_index_within_template": 2,
+    "sql_variant_index": 1,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_c3e0fbce48684752.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_c3e0fbce48684752",
+    "api_calls": 0,
+    "input_tokens": 15078,
+    "cached_input_tokens": 13696,
+    "output_tokens": 490,
+    "total_tokens": 15568,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 11593.26,
+    "sql_execution_elapsed_ms_total": 7.01,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c3e0fbce48684752/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c3e0fbce48684752/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c3e0fbce48684752/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..4c1a8d826922e9c5d75790318ae1816610bf8d71
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c3e0fbce48684752/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:46:50.568294+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 11593.26, "started_at": "2026-05-19T15:46:38.973514+00:00", "ended_at": "2026-05-19T15:46:50.566835+00:00", "prompt_metrics": {"chars": 9946, "bytes_utf8": 9946, "lines": 300, "estimated_tokens": null}, "response_metrics": {"chars": 633, "bytes_utf8": 633, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15078, "cached_input_tokens": 13696, "output_tokens": 490, "reasoning_output_tokens": 319}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n    SELECT \\\"feature_6\\\", SUM(CAST(\\\"feature_10\\\" AS REAL)) AS group_value\\n    FROM \\\"n9\\\"\\n    GROUP BY \\\"feature_6\\\"\\n), total AS (\\n    SELECT SUM(group_value) AS total_value\\n    FROM grouped\\n)\\nSELECT g.\\\"feature_6\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.1\\nORDER BY g.group_value DESC;\",\"notes\":\"Applied the planned Relative-to-Total Extreme Threshold template with group_col=\\\"feature_6\\\" and measure_col=\\\"feature_10\\\". CAST is used because the schema stores feature columns as TEXT.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c3e0fbce48684752/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c3e0fbce48684752/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..30b4305d72b090de33432fe3e4eed3b9cf5308ff
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c3e0fbce48684752/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_c3e0fbce48684752",
+  "api_calls": 0,
+  "input_tokens": 15078,
+  "cached_input_tokens": 13696,
+  "output_tokens": 490,
+  "total_tokens": 15568,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 11593.26,
+  "sql_execution_elapsed_ms_total": 7.01,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c3e0fbce48684752/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c421da0d9c0dc129/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c421da0d9c0dc129/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..bc680f2991a338decf208b3fccb7785a65b02631
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c421da0d9c0dc129/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=feature_14.
+Result preview: [{"feature_14": "0", "row_count": 1756}, {"feature_14": "100", "row_count": 894}, {"feature_14": "25", "row_count": 294}, {"feature_14": "1", "row_count": 246}, {"feature_14": "32", "row_count": 233}] Results were truncated.
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c421da0d9c0dc129/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c421da0d9c0dc129/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..1ee3100c06bd5bd317110c453e50efcb162942f9
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c421da0d9c0dc129/generated_sql.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: subgroup_size_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_clickbench_group_count
+-- query_record_id: v2q_n9_c421da0d9c0dc129
+-- problem_id: v2p_n9_f2492a490073b82a
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_14", COUNT(*) AS row_count
+FROM "n9"
+GROUP BY "feature_14"
+ORDER BY row_count DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c421da0d9c0dc129/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c421da0d9c0dc129/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..102c4413bd8b10deb1f5dc57679b473e1c14fe3c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c421da0d9c0dc129/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_clickbench_group_count\nSELECT \"feature_14\", COUNT(*) AS row_count\nFROM \"n9\"\nGROUP BY \"feature_14\"\nORDER BY row_count DESC;", "result": "{\"query\": \"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"feature_14\\\", COUNT(*) AS row_count\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_14\\\"\\nORDER BY row_count DESC;\", \"columns\": [\"feature_14\", \"row_count\"], \"rows\": [{\"feature_14\": \"0\", \"row_count\": 1756}, {\"feature_14\": \"100\", \"row_count\": 894}, {\"feature_14\": \"25\", \"row_count\": 294}, {\"feature_14\": \"1\", \"row_count\": 246}, {\"feature_14\": \"32\", \"row_count\": 233}, {\"feature_14\": \"2\", \"row_count\": 233}, {\"feature_14\": \"24\", \"row_count\": 231}, {\"feature_14\": \"34\", \"row_count\": 204}, {\"feature_14\": \"27\", \"row_count\": 202}, {\"feature_14\": \"4\", \"row_count\": 201}, {\"feature_14\": \"28\", \"row_count\": 199}, {\"feature_14\": \"26\", \"row_count\": 199}, {\"feature_14\": \"23\", \"row_count\": 189}, {\"feature_14\": \"29\", \"row_count\": 186}, {\"feature_14\": \"31\", \"row_count\": 184}, {\"feature_14\": \"30\", \"row_count\": 183}, {\"feature_14\": \"3\", \"row_count\": 162}, {\"feature_14\": \"5\", \"row_count\": 159}, {\"feature_14\": \"33\", \"row_count\": 159}, {\"feature_14\": \"35\", \"row_count\": 155}, {\"feature_14\": \"22\", \"row_count\": 155}, {\"feature_14\": \"6\", \"row_count\": 144}, {\"feature_14\": \"36\", \"row_count\": 143}, {\"feature_14\": \"7\", \"row_count\": 137}, {\"feature_14\": \"20\", \"row_count\": 137}, {\"feature_14\": \"39\", \"row_count\": 134}, {\"feature_14\": \"38\", \"row_count\": 123}, {\"feature_14\": \"21\", \"row_count\": 121}, {\"feature_14\": \"37\", \"row_count\": 119}, {\"feature_14\": \"8\", \"row_count\": 114}, {\"feature_14\": \"40\", \"row_count\": 111}, {\"feature_14\": \"9\", \"row_count\": 101}, {\"feature_14\": \"14\", \"row_count\": 100}, {\"feature_14\": \"95\", \"row_count\": 96}, {\"feature_14\": \"18\", \"row_count\": 95}, {\"feature_14\": \"19\", \"row_count\": 90}, {\"feature_14\": \"16\", \"row_count\": 89}, {\"feature_14\": \"15\", \"row_count\": 89}, {\"feature_14\": \"17\", \"row_count\": 87}, {\"feature_14\": \"42\", \"row_count\": 83}, {\"feature_14\": \"41\", \"row_count\": 83}, {\"feature_14\": \"99\", \"row_count\": 82}, {\"feature_14\": \"10\", \"row_count\": 82}, {\"feature_14\": \"94\", \"row_count\": 81}, {\"feature_14\": \"97\", \"row_count\": 79}, {\"feature_14\": \"13\", \"row_count\": 78}, {\"feature_14\": \"98\", \"row_count\": 77}, {\"feature_14\": \"43\", \"row_count\": 77}, {\"feature_14\": \"45\", \"row_count\": 74}, {\"feature_14\": \"96\", \"row_count\": 73}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 6.59}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c421da0d9c0dc129/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c421da0d9c0dc129/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..9f2fb6b08f2a42a23d6e5f2ef74919050ef83cb5
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c421da0d9c0dc129/run_manifest.json
@@ -0,0 +1,87 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:32:13.729151+00:00",
+  "ended_at": "2026-05-19T15:32:30.759905+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_c421da0d9c0dc129",
+    "problem_id": "v2p_n9_f2492a490073b82a",
+    "dataset_id": "n9",
+    "template_id": "tpl_clickbench_group_count",
+    "template_name": "Grouped Count by Category",
+    "family_id": "subgroup_structure",
+    "canonical_subitem_id": "subgroup_size_stability",
+    "intended_facet_id": "subgroup_distribution_shift",
+    "variant_semantic_role": "count_distribution",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=feature_14.",
+    "bindings": {
+      "group_col": "feature_14",
+      "top_k": 13,
+      "top_n": 4,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 47.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;",
+    "notes": [
+      "default_facets=subgroup_distribution_shift",
+      "template_selection_mode=rule",
+      "problem_index_within_template=2",
+      "sql_variant_index=1/1",
+      "binding_index=13"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 2,
+    "problem_index_within_template": 2,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_c421da0d9c0dc129.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_c421da0d9c0dc129",
+    "api_calls": 0,
+    "input_tokens": 14911,
+    "cached_input_tokens": 12032,
+    "output_tokens": 204,
+    "total_tokens": 15115,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 17020.05,
+    "sql_execution_elapsed_ms_total": 6.59,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c421da0d9c0dc129/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c421da0d9c0dc129/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c421da0d9c0dc129/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..5b1c9229cd69ff3ac7e4c14422fadb03ffd554cd
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c421da0d9c0dc129/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:32:30.751482+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 17020.05, "started_at": "2026-05-19T15:32:13.730292+00:00", "ended_at": "2026-05-19T15:32:30.750376+00:00", "prompt_metrics": {"chars": 9298, "bytes_utf8": 9298, "lines": 298, "estimated_tokens": null}, "response_metrics": {"chars": 295, "bytes_utf8": 295, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14911, "cached_input_tokens": 12032, "output_tokens": 204, "reasoning_output_tokens": 121}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"feature_14\\\", COUNT(*) AS row_count\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_14\\\"\\nORDER BY row_count DESC;\",\"notes\":\"Applied the provided Grouped Count by Category template with group_col bound to \\\"feature_14\\\" on the single table \\\"n9\\\".\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c421da0d9c0dc129/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c421da0d9c0dc129/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..4f5ead353a3b5f8f1dc2bcbc74559ef1dec8cf9d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c421da0d9c0dc129/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_c421da0d9c0dc129",
+  "api_calls": 0,
+  "input_tokens": 14911,
+  "cached_input_tokens": 12032,
+  "output_tokens": 204,
+  "total_tokens": 15115,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 17020.05,
+  "sql_execution_elapsed_ms_total": 6.59,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c421da0d9c0dc129/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c518757c15e9b81c/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c518757c15e9b81c/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..7bfa52b3b529ea7368bf22d26032a2058ac82021
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c518757c15e9b81c/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Filtered Two-Dimensional Group Count to probe slice_level_consistency with semantic role count_distribution. Focus on group_col=feature_4, group_col_2=feature_8.
+Result preview: [{"feature_4": "100", "feature_8": "35", "row_count": 84}, {"feature_4": "100", "feature_8": "36", "row_count": 84}, {"feature_4": "100", "feature_8": "39", "row_count": 83}, {"feature_4": "100", "feature_8": "40", "row_count": 83}, {"feature_4": "100", "feature_8": "34", "row_count": 78}] Results were truncated.
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c518757c15e9b81c/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c518757c15e9b81c/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..8b7aceeb2bd30548394e261fb0a327519f3c15df
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c518757c15e9b81c/generated_sql.sql
@@ -0,0 +1,18 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: slice_level_consistency
+-- intended_facet_id: conditional_interaction_hotspots
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_c2_filtered_group_count_2d
+-- query_record_id: v2q_n9_c518757c15e9b81c
+-- problem_id: v2p_n9_beb718169fa657f3
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_4", "feature_8", COUNT(*) AS row_count
+FROM "n9"
+WHERE CAST("feature_15" AS REAL) >= 100.0
+GROUP BY "feature_4", "feature_8"
+ORDER BY row_count DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c518757c15e9b81c/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c518757c15e9b81c/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..b66eb97a1dc990de2fcc3c92fe31e27edabce2fb
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c518757c15e9b81c/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_c2_filtered_group_count_2d\nSELECT \"feature_4\", \"feature_8\", COUNT(*) AS row_count\nFROM \"n9\"\nWHERE CAST(\"feature_15\" AS REAL) >= 100.0\nGROUP BY \"feature_4\", \"feature_8\"\nORDER BY row_count DESC;", "result": "{\"query\": \"-- template_id: tpl_c2_filtered_group_count_2d\\nSELECT \\\"feature_4\\\", \\\"feature_8\\\", COUNT(*) AS row_count\\nFROM \\\"n9\\\"\\nWHERE CAST(\\\"feature_15\\\" AS REAL) >= 100.0\\nGROUP BY \\\"feature_4\\\", \\\"feature_8\\\"\\nORDER BY row_count DESC;\", \"columns\": [\"feature_4\", \"feature_8\", \"row_count\"], \"rows\": [{\"feature_4\": \"100\", \"feature_8\": \"35\", \"row_count\": 84}, {\"feature_4\": \"100\", \"feature_8\": \"36\", \"row_count\": 84}, {\"feature_4\": \"100\", \"feature_8\": \"39\", \"row_count\": 83}, {\"feature_4\": \"100\", \"feature_8\": \"40\", \"row_count\": 83}, {\"feature_4\": \"100\", \"feature_8\": \"34\", \"row_count\": 78}, {\"feature_4\": \"100\", \"feature_8\": \"43\", \"row_count\": 72}, {\"feature_4\": \"100\", \"feature_8\": \"33\", \"row_count\": 70}, {\"feature_4\": \"100\", \"feature_8\": \"37\", \"row_count\": 66}, {\"feature_4\": \"100\", \"feature_8\": \"38\", \"row_count\": 64}, {\"feature_4\": \"100\", \"feature_8\": \"42\", \"row_count\": 63}, {\"feature_4\": \"100\", \"feature_8\": \"41\", \"row_count\": 57}, {\"feature_4\": \"100\", \"feature_8\": \"45\", \"row_count\": 52}, {\"feature_4\": \"100\", \"feature_8\": \"46\", \"row_count\": 52}, {\"feature_4\": \"100\", \"feature_8\": \"31\", \"row_count\": 51}, {\"feature_4\": \"100\", \"feature_8\": \"32\", \"row_count\": 50}, {\"feature_4\": \"100\", \"feature_8\": \"50\", \"row_count\": 48}, {\"feature_4\": \"100\", \"feature_8\": \"44\", \"row_count\": 46}, {\"feature_4\": \"100\", \"feature_8\": \"48\", \"row_count\": 43}, {\"feature_4\": \"100\", \"feature_8\": \"52\", \"row_count\": 40}, {\"feature_4\": \"100\", \"feature_8\": \"53\", \"row_count\": 39}, {\"feature_4\": \"100\", \"feature_8\": \"30\", \"row_count\": 35}, {\"feature_4\": \"100\", \"feature_8\": \"47\", \"row_count\": 34}, {\"feature_4\": \"100\", \"feature_8\": \"55\", \"row_count\": 31}, {\"feature_4\": \"100\", \"feature_8\": \"27\", \"row_count\": 30}, {\"feature_4\": \"100\", \"feature_8\": \"58\", \"row_count\": 30}, {\"feature_4\": \"100\", \"feature_8\": \"51\", \"row_count\": 29}, {\"feature_4\": \"62\", \"feature_8\": \"0\", \"row_count\": 29}, {\"feature_4\": \"100\", \"feature_8\": \"49\", \"row_count\": 27}, {\"feature_4\": \"63\", \"feature_8\": \"0\", \"row_count\": 26}, {\"feature_4\": \"100\", \"feature_8\": \"54\", \"row_count\": 25}, {\"feature_4\": \"64\", \"feature_8\": \"0\", \"row_count\": 25}, {\"feature_4\": \"54\", \"feature_8\": \"0\", \"row_count\": 24}, {\"feature_4\": \"100\", \"feature_8\": \"57\", \"row_count\": 23}, {\"feature_4\": \"57\", \"feature_8\": \"0\", \"row_count\": 22}, {\"feature_4\": \"61\", \"feature_8\": \"0\", \"row_count\": 22}, {\"feature_4\": \"55\", \"feature_8\": \"0\", \"row_count\": 21}, {\"feature_4\": \"58\", \"feature_8\": \"0\", \"row_count\": 21}, {\"feature_4\": \"100\", \"feature_8\": \"26\", \"row_count\": 20}, {\"feature_4\": \"59\", \"feature_8\": \"0\", \"row_count\": 20}, {\"feature_4\": \"66\", \"feature_8\": \"0\", \"row_count\": 20}, {\"feature_4\": \"100\", \"feature_8\": \"29\", \"row_count\": 19}, {\"feature_4\": \"100\", \"feature_8\": \"56\", \"row_count\": 19}, {\"feature_4\": \"100\", \"feature_8\": \"23\", \"row_count\": 18}, {\"feature_4\": \"100\", \"feature_8\": \"25\", \"row_count\": 18}, {\"feature_4\": \"100\", \"feature_8\": \"28\", \"row_count\": 18}, {\"feature_4\": \"100\", \"feature_8\": \"62\", \"row_count\": 17}, {\"feature_4\": \"100\", \"feature_8\": \"63\", \"row_count\": 17}, {\"feature_4\": \"53\", \"feature_8\": \"0\", \"row_count\": 17}, {\"feature_4\": \"60\", \"feature_8\": \"0\", \"row_count\": 17}, {\"feature_4\": \"100\", \"feature_8\": \"21\", \"row_count\": 16}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 3.57}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c518757c15e9b81c/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c518757c15e9b81c/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..d332e4fe936916c7d69dc12e13d04d8491424dce
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c518757c15e9b81c/run_manifest.json
@@ -0,0 +1,93 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:41:24.162218+00:00",
+  "ended_at": "2026-05-19T15:41:36.134879+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_c518757c15e9b81c",
+    "problem_id": "v2p_n9_beb718169fa657f3",
+    "dataset_id": "n9",
+    "template_id": "tpl_c2_filtered_group_count_2d",
+    "template_name": "Filtered Two-Dimensional Group Count",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "slice_level_consistency",
+    "intended_facet_id": "conditional_interaction_hotspots",
+    "variant_semantic_role": "count_distribution",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Filtered Two-Dimensional Group Count to probe slice_level_consistency with semantic role count_distribution. Focus on group_col=feature_4, group_col_2=feature_8.",
+    "bindings": {
+      "group_col": "feature_4",
+      "group_col_2": "feature_8",
+      "predicate_col": "feature_15",
+      "predicate_op": ">=",
+      "predicate_value": 100.0,
+      "top_k": 13,
+      "top_n": 3,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 65.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "group_col_2",
+      "predicate_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;",
+    "notes": [
+      "default_facets=conditional_interaction_hotspots",
+      "template_selection_mode=rule",
+      "problem_index_within_template=1",
+      "sql_variant_index=1/1",
+      "binding_index=48"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 5,
+    "problem_index_within_template": 1,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_c518757c15e9b81c.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_c518757c15e9b81c",
+    "api_calls": 0,
+    "input_tokens": 15036,
+    "cached_input_tokens": 13696,
+    "output_tokens": 357,
+    "total_tokens": 15393,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 11964.47,
+    "sql_execution_elapsed_ms_total": 3.57,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c518757c15e9b81c/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c518757c15e9b81c/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c518757c15e9b81c/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..4ba33abc69f1b650531962faec8d93ad152fb321
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c518757c15e9b81c/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:41:36.129947+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 11964.47, "started_at": "2026-05-19T15:41:24.164730+00:00", "ended_at": "2026-05-19T15:41:36.129235+00:00", "prompt_metrics": {"chars": 9703, "bytes_utf8": 9703, "lines": 304, "estimated_tokens": null}, "response_metrics": {"chars": 479, "bytes_utf8": 479, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15036, "cached_input_tokens": 13696, "output_tokens": 357, "reasoning_output_tokens": 223}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_c2_filtered_group_count_2d\\nSELECT \\\"feature_4\\\", \\\"feature_8\\\", COUNT(*) AS row_count\\nFROM \\\"n9\\\"\\nWHERE CAST(\\\"feature_15\\\" AS REAL) >= 100.0\\nGROUP BY \\\"feature_4\\\", \\\"feature_8\\\"\\nORDER BY row_count DESC;\",\"notes\":\"Used the provided filtered two-dimensional group count template with group_col=\\\"feature_4\\\", group_col_2=\\\"feature_8\\\", and predicate_col=\\\"feature_15\\\". CAST to REAL is applied because the schema stores feature columns as TEXT.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c518757c15e9b81c/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c518757c15e9b81c/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..63f200f7edcbc9002b485e689b7b2db109a0cdc6
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c518757c15e9b81c/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_c518757c15e9b81c",
+  "api_calls": 0,
+  "input_tokens": 15036,
+  "cached_input_tokens": 13696,
+  "output_tokens": 357,
+  "total_tokens": 15393,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 11964.47,
+  "sql_execution_elapsed_ms_total": 3.57,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c518757c15e9b81c/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c6ca8dcc4bd2d03c/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c6ca8dcc4bd2d03c/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..db1bce125f71677c2dce8b08f31af2a7e04631ce
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c6ca8dcc4bd2d03c/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=feature_13, measure_col=feature_1.
+Result preview: [{"feature_13": "100", "group_value": 25905.0}]
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c6ca8dcc4bd2d03c/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c6ca8dcc4bd2d03c/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..0ad29280234c4d11effd8c81ab87a53faf15d791
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c6ca8dcc4bd2d03c/generated_sql.sql
@@ -0,0 +1,26 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: filtered_stable_view
+-- template_id: tpl_tpch_relative_total_threshold
+-- query_record_id: v2q_n9_c6ca8dcc4bd2d03c
+-- problem_id: v2p_n9_93c326343243397b
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+    SELECT "feature_13", SUM(CAST("feature_1" AS REAL)) AS group_value
+    FROM "n9"
+    GROUP BY "feature_13"
+), total AS (
+    SELECT SUM(group_value) AS total_value
+    FROM grouped
+)
+SELECT g."feature_13", g.group_value
+FROM grouped AS g
+CROSS JOIN total AS t
+WHERE g.group_value > t.total_value * 0.05
+ORDER BY g.group_value DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c6ca8dcc4bd2d03c/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c6ca8dcc4bd2d03c/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..e4acae4ac32a1aa5ff1351a3ef691bfaaf57a7af
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c6ca8dcc4bd2d03c/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_relative_total_threshold\nWITH grouped AS (\n    SELECT \"feature_13\", SUM(CAST(\"feature_1\" AS REAL)) AS group_value\n    FROM \"n9\"\n    GROUP BY \"feature_13\"\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.\"feature_13\", g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * 0.05\nORDER BY g.group_value DESC;", "result": "{\"query\": \"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n    SELECT \\\"feature_13\\\", SUM(CAST(\\\"feature_1\\\" AS REAL)) AS group_value\\n    FROM \\\"n9\\\"\\n    GROUP BY \\\"feature_13\\\"\\n), total AS (\\n    SELECT SUM(group_value) AS total_value\\n    FROM grouped\\n)\\nSELECT g.\\\"feature_13\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.05\\nORDER BY g.group_value DESC;\", \"columns\": [\"feature_13\", \"group_value\"], \"rows\": [{\"feature_13\": \"100\", \"group_value\": 25905.0}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 10.19}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c6ca8dcc4bd2d03c/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c6ca8dcc4bd2d03c/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..7a922f0cca22b45696ab3c83ef288126ebb14a99
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c6ca8dcc4bd2d03c/run_manifest.json
@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:50:06.626369+00:00",
+  "ended_at": "2026-05-19T15:50:14.954407+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_c6ca8dcc4bd2d03c",
+    "problem_id": "v2p_n9_93c326343243397b",
+    "dataset_id": "n9",
+    "template_id": "tpl_tpch_relative_total_threshold",
+    "template_name": "Relative-to-Total Extreme Threshold",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_mass_similarity",
+    "intended_facet_id": "tail_ranked_signal",
+    "variant_semantic_role": "filtered_stable_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=feature_13, measure_col=feature_1.",
+    "bindings": {
+      "group_col": "feature_13",
+      "measure_col": "feature_1",
+      "top_k": 15,
+      "top_n": 4,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.05,
+      "baseline_multiplier": 1.75,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 4,
+      "measure_threshold": 50.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "WITH grouped AS (\n    SELECT {group_col}, SUM({measure_col}) AS group_value\n    FROM {table}\n    GROUP BY {group_col}\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;",
+    "notes": [
+      "default_facets=tail_ranked_signal",
+      "template_selection_mode=rule",
+      "problem_index_within_template=9",
+      "sql_variant_index=2/2",
+      "binding_index=80"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 7,
+    "problem_index_within_template": 9,
+    "sql_variant_index": 2,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_c6ca8dcc4bd2d03c.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_c6ca8dcc4bd2d03c",
+    "api_calls": 0,
+    "input_tokens": 15078,
+    "cached_input_tokens": 13696,
+    "output_tokens": 290,
+    "total_tokens": 15368,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 8311.63,
+    "sql_execution_elapsed_ms_total": 10.19,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c6ca8dcc4bd2d03c/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c6ca8dcc4bd2d03c/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c6ca8dcc4bd2d03c/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..0d690ec60c8e50ad3631682156730ce3462eadde
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c6ca8dcc4bd2d03c/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:50:14.942073+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 8311.63, "started_at": "2026-05-19T15:50:06.628983+00:00", "ended_at": "2026-05-19T15:50:14.940670+00:00", "prompt_metrics": {"chars": 9948, "bytes_utf8": 9948, "lines": 300, "estimated_tokens": null}, "response_metrics": {"chars": 645, "bytes_utf8": 645, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15078, "cached_input_tokens": 13696, "output_tokens": 290, "reasoning_output_tokens": 115}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n    SELECT \\\"feature_13\\\", SUM(CAST(\\\"feature_1\\\" AS REAL)) AS group_value\\n    FROM \\\"n9\\\"\\n    GROUP BY \\\"feature_13\\\"\\n), total AS (\\n    SELECT SUM(group_value) AS total_value\\n    FROM grouped\\n)\\nSELECT g.\\\"feature_13\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.05\\nORDER BY g.group_value DESC;\",\"notes\":\"Applied the provided Relative-to-Total Extreme Threshold template with group_col=\\\"feature_13\\\" and measure_col=\\\"feature_1\\\". Cast \\\"feature_1\\\" from TEXT to REAL for numeric aggregation in SQLite.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c6ca8dcc4bd2d03c/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c6ca8dcc4bd2d03c/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..07d7575ddf8e13424331a5385f204a5517215f0e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c6ca8dcc4bd2d03c/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_c6ca8dcc4bd2d03c",
+  "api_calls": 0,
+  "input_tokens": 15078,
+  "cached_input_tokens": 13696,
+  "output_tokens": 290,
+  "total_tokens": 15368,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 8311.63,
+  "sql_execution_elapsed_ms_total": 10.19,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c6ca8dcc4bd2d03c/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c9c0bd481266cabb/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c9c0bd481266cabb/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..cdeb70ddc7cbe6c7dbb7e54215f0c9547391cbea
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c9c0bd481266cabb/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=feature_8, measure_col=feature_13.
+Result preview: [{"feature_8": "0", "percentile_measure": 100.0}, {"feature_8": "1", "percentile_measure": 100.0}, {"feature_8": "6", "percentile_measure": 100.0}, {"feature_8": "2", "percentile_measure": 98.0}, {"feature_8": "13", "percentile_measure": 97.5}] Results were truncated.
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c9c0bd481266cabb/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c9c0bd481266cabb/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..4f765141bae1400d69d6db66411fda33e377b7ca
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c9c0bd481266cabb/generated_sql.sql
@@ -0,0 +1,64 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_n9_c9c0bd481266cabb
+-- problem_id: v2p_n9_4d20ee7acaa09e02
+-- realization_mode: agent
+-- source_kind: agent
+WITH "ranked" AS (
+  SELECT
+    "feature_8" AS "group_value",
+    CAST("feature_13" AS REAL) AS "measure_value",
+    ROW_NUMBER() OVER (
+      PARTITION BY "feature_8"
+      ORDER BY CAST("feature_13" AS REAL)
+    ) AS "rn",
+    COUNT(*) OVER (
+      PARTITION BY "feature_8"
+    ) AS "n"
+  FROM "n9"
+  WHERE "feature_8" IS NOT NULL
+    AND "feature_13" IS NOT NULL
+),
+"prep" AS (
+  SELECT
+    "group_value",
+    "measure_value",
+    "rn",
+    "n",
+    (1.0 + 0.9 * ("n" - 1)) AS "r",
+    CAST((1.0 + 0.9 * ("n" - 1)) AS INTEGER) AS "lo",
+    CASE
+      WHEN (1.0 + 0.9 * ("n" - 1)) = CAST((1.0 + 0.9 * ("n" - 1)) AS INTEGER)
+        THEN CAST((1.0 + 0.9 * ("n" - 1)) AS INTEGER)
+      ELSE CAST((1.0 + 0.9 * ("n" - 1)) AS INTEGER) + 1
+    END AS "hi"
+  FROM "ranked"
+),
+"percentiles" AS (
+  SELECT
+    "group_value",
+    CASE
+      WHEN MAX("lo") = MAX("hi") THEN MAX(CASE WHEN "rn" = "lo" THEN "measure_value" END)
+      ELSE
+        MAX(CASE WHEN "rn" = "lo" THEN "measure_value" END) +
+        (MAX("r") - MAX("lo")) * (
+          MAX(CASE WHEN "rn" = "hi" THEN "measure_value" END) -
+          MAX(CASE WHEN "rn" = "lo" THEN "measure_value" END)
+        )
+    END AS "percentile_measure"
+  FROM "prep"
+  GROUP BY "group_value"
+  HAVING MAX("n") >= 5
+)
+SELECT
+  "group_value" AS "feature_8",
+  "percentile_measure"
+FROM "percentiles"
+ORDER BY "percentile_measure" DESC, "feature_8";
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c9c0bd481266cabb/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c9c0bd481266cabb/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..1d6aa708e6c4ffc3af1171aa78a27062d52e87d1
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c9c0bd481266cabb/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH \"ranked\" AS (\n  SELECT\n    \"feature_8\" AS \"group_value\",\n    CAST(\"feature_13\" AS REAL) AS \"measure_value\",\n    ROW_NUMBER() OVER (\n      PARTITION BY \"feature_8\"\n      ORDER BY CAST(\"feature_13\" AS REAL)\n    ) AS \"rn\",\n    COUNT(*) OVER (\n      PARTITION BY \"feature_8\"\n    ) AS \"n\"\n  FROM \"n9\"\n  WHERE \"feature_8\" IS NOT NULL\n    AND \"feature_13\" IS NOT NULL\n),\n\"prep\" AS (\n  SELECT\n    \"group_value\",\n    \"measure_value\",\n    \"rn\",\n    \"n\",\n    (1.0 + 0.9 * (\"n\" - 1)) AS \"r\",\n    CAST((1.0 + 0.9 * (\"n\" - 1)) AS INTEGER) AS \"lo\",\n    CASE\n      WHEN (1.0 + 0.9 * (\"n\" - 1)) = CAST((1.0 + 0.9 * (\"n\" - 1)) AS INTEGER)\n        THEN CAST((1.0 + 0.9 * (\"n\" - 1)) AS INTEGER)\n      ELSE CAST((1.0 + 0.9 * (\"n\" - 1)) AS INTEGER) + 1\n    END AS \"hi\"\n  FROM \"ranked\"\n),\n\"percentiles\" AS (\n  SELECT\n    \"group_value\",\n    CASE\n      WHEN MAX(\"lo\") = MAX(\"hi\") THEN MAX(CASE WHEN \"rn\" = \"lo\" THEN \"measure_value\" END)\n      ELSE\n        MAX(CASE WHEN \"rn\" = \"lo\" THEN \"measure_value\" END) +\n        (MAX(\"r\") - MAX(\"lo\")) * (\n          MAX(CASE WHEN \"rn\" = \"hi\" THEN \"measure_value\" END) -\n          MAX(CASE WHEN \"rn\" = \"lo\" THEN \"measure_value\" END)\n        )\n    END AS \"percentile_measure\"\n  FROM \"prep\"\n  GROUP BY \"group_value\"\n  HAVING MAX(\"n\") >= 5\n)\nSELECT\n  \"group_value\" AS \"feature_8\",\n  \"percentile_measure\"\nFROM \"percentiles\"\nORDER BY \"percentile_measure\" DESC, \"feature_8\";", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n  SELECT\\n    \\\"feature_8\\\" AS \\\"group_value\\\",\\n    CAST(\\\"feature_13\\\" AS REAL) AS \\\"measure_value\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"feature_8\\\"\\n      ORDER BY CAST(\\\"feature_13\\\" AS REAL)\\n    ) AS \\\"rn\\\",\\n    COUNT(*) OVER (\\n      PARTITION BY \\\"feature_8\\\"\\n    ) AS \\\"n\\\"\\n  FROM \\\"n9\\\"\\n  WHERE \\\"feature_8\\\" IS NOT NULL\\n    AND \\\"feature_13\\\" IS NOT NULL\\n),\\n\\\"prep\\\" AS (\\n  SELECT\\n    \\\"group_value\\\",\\n    \\\"measure_value\\\",\\n    \\\"rn\\\",\\n    \\\"n\\\",\\n    (1.0 + 0.9 * (\\\"n\\\" - 1)) AS \\\"r\\\",\\n    CAST((1.0 + 0.9 * (\\\"n\\\" - 1)) AS INTEGER) AS \\\"lo\\\",\\n    CASE\\n      WHEN (1.0 + 0.9 * (\\\"n\\\" - 1)) = CAST((1.0 + 0.9 * (\\\"n\\\" - 1)) AS INTEGER)\\n        THEN CAST((1.0 + 0.9 * (\\\"n\\\" - 1)) AS INTEGER)\\n      ELSE CAST((1.0 + 0.9 * (\\\"n\\\" - 1)) AS INTEGER) + 1\\n    END AS \\\"hi\\\"\\n  FROM \\\"ranked\\\"\\n),\\n\\\"percentiles\\\" AS (\\n  SELECT\\n    \\\"group_value\\\",\\n    CASE\\n      WHEN MAX(\\\"lo\\\") = MAX(\\\"hi\\\") THEN MAX(CASE WHEN \\\"rn\\\" = \\\"lo\\\" THEN \\\"measure_value\\\" END)\\n      ELSE\\n        MAX(CASE WHEN \\\"rn\\\" = \\\"lo\\\" THEN \\\"measure_value\\\" END) +\\n        (MAX(\\\"r\\\") - MAX(\\\"lo\\\")) * (\\n          MAX(CASE WHEN \\\"rn\\\" = \\\"hi\\\" THEN \\\"measure_value\\\" END) -\\n          MAX(CASE WHEN \\\"rn\\\" = \\\"lo\\\" THEN \\\"measure_value\\\" END)\\n        )\\n    END AS \\\"percentile_measure\\\"\\n  FROM \\\"prep\\\"\\n  GROUP BY \\\"group_value\\\"\\n  HAVING MAX(\\\"n\\\") >= 5\\n)\\nSELECT\\n  \\\"group_value\\\" AS \\\"feature_8\\\",\\n  \\\"percentile_measure\\\"\\nFROM \\\"percentiles\\\"\\nORDER BY \\\"percentile_measure\\\" DESC, \\\"feature_8\\\";\", \"columns\": [\"feature_8\", \"percentile_measure\"], \"rows\": [{\"feature_8\": \"0\", \"percentile_measure\": 100.0}, {\"feature_8\": \"1\", \"percentile_measure\": 100.0}, {\"feature_8\": \"6\", \"percentile_measure\": 100.0}, {\"feature_8\": \"2\", \"percentile_measure\": 98.0}, {\"feature_8\": \"13\", \"percentile_measure\": 97.5}, {\"feature_8\": \"25\", \"percentile_measure\": 95.60000000000001}, {\"feature_8\": \"30\", \"percentile_measure\": 95.0}, {\"feature_8\": \"7\", \"percentile_measure\": 94.2}, {\"feature_8\": \"5\", \"percentile_measure\": 93.6}, {\"feature_8\": \"22\", \"percentile_measure\": 93.0}, {\"feature_8\": \"3\", \"percentile_measure\": 92.80000000000003}, {\"feature_8\": \"27\", \"percentile_measure\": 92.5}, {\"feature_8\": \"10\", \"percentile_measure\": 92.40000000000002}, {\"feature_8\": \"4\", \"percentile_measure\": 92.00000000000001}, {\"feature_8\": \"24\", \"percentile_measure\": 92.0}, {\"feature_8\": \"84\", \"percentile_measure\": 91.80000000000003}, {\"feature_8\": \"28\", \"percentile_measure\": 91.80000000000001}, {\"feature_8\": \"40\", \"percentile_measure\": 91.5}, {\"feature_8\": \"93\", \"percentile_measure\": 90.5}, {\"feature_8\": \"41\", \"percentile_measure\": 90.0}, {\"feature_8\": \"29\", \"percentile_measure\": 89.0}, {\"feature_8\": \"36\", \"percentile_measure\": 89.0}, {\"feature_8\": \"35\", \"percentile_measure\": 88.80000000000001}, {\"feature_8\": \"23\", \"percentile_measure\": 88.6}, {\"feature_8\": \"17\", \"percentile_measure\": 88.0}, {\"feature_8\": \"21\", \"percentile_measure\": 88.0}, {\"feature_8\": \"26\", \"percentile_measure\": 88.0}, {\"feature_8\": \"33\", \"percentile_measure\": 87.20000000000002}, {\"feature_8\": \"34\", \"percentile_measure\": 86.4}, {\"feature_8\": \"83\", \"percentile_measure\": 86.39999999999999}, {\"feature_8\": \"32\", \"percentile_measure\": 86.10000000000001}, {\"feature_8\": \"95\", \"percentile_measure\": 86.0}, {\"feature_8\": \"96\", \"percentile_measure\": 86.0}, {\"feature_8\": \"44\", \"percentile_measure\": 85.9}, {\"feature_8\": \"39\", \"percentile_measure\": 85.6}, {\"feature_8\": \"100\", \"percentile_measure\": 85.0}, {\"feature_8\": \"31\", \"percentile_measure\": 85.0}, {\"feature_8\": \"42\", \"percentile_measure\": 85.0}, {\"feature_8\": \"43\", \"percentile_measure\": 85.0}, {\"feature_8\": \"47\", \"percentile_measure\": 85.0}, {\"feature_8\": \"20\", \"percentile_measure\": 84.0}, {\"feature_8\": \"78\", \"percentile_measure\": 83.5}, {\"feature_8\": \"38\", \"percentile_measure\": 83.4}, {\"feature_8\": \"99\", \"percentile_measure\": 83.2}, {\"feature_8\": \"37\", \"percentile_measure\": 83.0}, {\"feature_8\": \"89\", \"percentile_measure\": 83.0}, {\"feature_8\": \"16\", \"percentile_measure\": 82.80000000000003}, {\"feature_8\": \"91\", \"percentile_measure\": 82.7}, {\"feature_8\": \"81\", \"percentile_measure\": 82.6}, {\"feature_8\": \"94\", \"percentile_measure\": 82.4}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 33.1}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c9c0bd481266cabb/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c9c0bd481266cabb/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..d958f0282b50051ebb45ef01221872463a0e5248
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c9c0bd481266cabb/run_manifest.json
@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:58:36.739075+00:00",
+  "ended_at": "2026-05-19T15:59:17.420613+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_c9c0bd481266cabb",
+    "problem_id": "v2p_n9_4d20ee7acaa09e02",
+    "dataset_id": "n9",
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_concentration_consistency",
+    "intended_facet_id": "rare_target_concentration",
+    "variant_semantic_role": "ranked_signal_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=feature_8, measure_col=feature_13.",
+    "bindings": {
+      "group_col": "feature_8",
+      "measure_col": "feature_13",
+      "top_k": 17,
+      "top_n": 4,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.05,
+      "baseline_multiplier": 1.75,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 4,
+      "measure_threshold": 61.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;",
+    "notes": [
+      "default_facets=rare_target_concentration",
+      "template_selection_mode=rule",
+      "problem_index_within_template=9",
+      "sql_variant_index=2/2",
+      "binding_index=92"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 8,
+    "problem_index_within_template": 9,
+    "sql_variant_index": 2,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_c9c0bd481266cabb.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_c9c0bd481266cabb",
+    "api_calls": 0,
+    "input_tokens": 14978,
+    "cached_input_tokens": 13696,
+    "output_tokens": 2562,
+    "total_tokens": 17540,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 40644.14,
+    "sql_execution_elapsed_ms_total": 33.1,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c9c0bd481266cabb/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c9c0bd481266cabb/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c9c0bd481266cabb/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..ec9b952cc0c3ae0956e380d33fdafdbf44243b52
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c9c0bd481266cabb/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:59:17.385721+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 40644.14, "started_at": "2026-05-19T15:58:36.740635+00:00", "ended_at": "2026-05-19T15:59:17.384804+00:00", "prompt_metrics": {"chars": 9570, "bytes_utf8": 9570, "lines": 300, "estimated_tokens": null}, "response_metrics": {"chars": 1883, "bytes_utf8": 1883, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14978, "cached_input_tokens": 13696, "output_tokens": 2562, "reasoning_output_tokens": 1933}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n  SELECT\\n    \\\"feature_8\\\" AS \\\"group_value\\\",\\n    CAST(\\\"feature_13\\\" AS REAL) AS \\\"measure_value\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"feature_8\\\"\\n      ORDER BY CAST(\\\"feature_13\\\" AS REAL)\\n    ) AS \\\"rn\\\",\\n    COUNT(*) OVER (\\n      PARTITION BY \\\"feature_8\\\"\\n    ) AS \\\"n\\\"\\n  FROM \\\"n9\\\"\\n  WHERE \\\"feature_8\\\" IS NOT NULL\\n    AND \\\"feature_13\\\" IS NOT NULL\\n),\\n\\\"prep\\\" AS (\\n  SELECT\\n    \\\"group_value\\\",\\n    \\\"measure_value\\\",\\n    \\\"rn\\\",\\n    \\\"n\\\",\\n    (1.0 + 0.9 * (\\\"n\\\" - 1)) AS \\\"r\\\",\\n    CAST((1.0 + 0.9 * (\\\"n\\\" - 1)) AS INTEGER) AS \\\"lo\\\",\\n    CASE\\n      WHEN (1.0 + 0.9 * (\\\"n\\\" - 1)) = CAST((1.0 + 0.9 * (\\\"n\\\" - 1)) AS INTEGER)\\n        THEN CAST((1.0 + 0.9 * (\\\"n\\\" - 1)) AS INTEGER)\\n      ELSE CAST((1.0 + 0.9 * (\\\"n\\\" - 1)) AS INTEGER) + 1\\n    END AS \\\"hi\\\"\\n  FROM \\\"ranked\\\"\\n),\\n\\\"percentiles\\\" AS (\\n  SELECT\\n    \\\"group_value\\\",\\n    CASE\\n      WHEN MAX(\\\"lo\\\") = "}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c9c0bd481266cabb/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c9c0bd481266cabb/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..1917396c846bf66801609b3c1abf98599feb3502
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c9c0bd481266cabb/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_c9c0bd481266cabb",
+  "api_calls": 0,
+  "input_tokens": 14978,
+  "cached_input_tokens": 13696,
+  "output_tokens": 2562,
+  "total_tokens": 17540,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 40644.14,
+  "sql_execution_elapsed_ms_total": 33.1,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_c9c0bd481266cabb/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_cb93d30f6e25f3a4/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_cb93d30f6e25f3a4/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..c9fcb34831975b2a42973cdb53529247da8d69e5
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_cb93d30f6e25f3a4/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=class, measure_col=feature_2.
+Result preview: [{"class": "0", "feature_3": "0", "total_measure": 32419.0, "share_within_group": 32.95585080968985}, {"class": "4", "feature_3": "0", "total_measure": 19162.0, "share_within_group": 16.827370602595852}, {"class": "8", "feature_3": "0", "total_measure": 11112.0, "share_within_group": 12.832149662220683}, {"class": "5", "feature_3": "0", "total_measure": 10649.0, "share_within_group": 11.099067173901714}, {"class": "5", "feature_3": "100", "total_measure": 10570.0, "share_within_group": 11.016728333941321}] Results were truncated.
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_cb93d30f6e25f3a4/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_cb93d30f6e25f3a4/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..3ba6b8f64e0c4a8e7c681606faf2189de1588b28
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_cb93d30f6e25f3a4/generated_sql.sql
@@ -0,0 +1,19 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_cb93d30f6e25f3a4
+-- problem_id: v2p_n9_f7b916dc2286e142
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "class", "feature_3",
+       SUM(CAST("feature_2" AS REAL)) AS total_measure,
+       SUM(CAST("feature_2" AS REAL)) * 100.0 / SUM(SUM(CAST("feature_2" AS REAL))) OVER (PARTITION BY "class") AS share_within_group
+FROM "n9"
+GROUP BY "class", "feature_3"
+ORDER BY share_within_group DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_cb93d30f6e25f3a4/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_cb93d30f6e25f3a4/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..526dff88205439236804d8cd3cac7bd9a43736bb
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_cb93d30f6e25f3a4/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT \"class\", \"feature_3\",\n       SUM(CAST(\"feature_2\" AS REAL)) AS total_measure,\n       SUM(CAST(\"feature_2\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"feature_2\" AS REAL))) OVER (PARTITION BY \"class\") AS share_within_group\nFROM \"n9\"\nGROUP BY \"class\", \"feature_3\"\nORDER BY share_within_group DESC;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"class\\\", \\\"feature_3\\\",\\n       SUM(CAST(\\\"feature_2\\\" AS REAL)) AS total_measure,\\n       SUM(CAST(\\\"feature_2\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"feature_2\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\") AS share_within_group\\nFROM \\\"n9\\\"\\nGROUP BY \\\"class\\\", \\\"feature_3\\\"\\nORDER BY share_within_group DESC;\", \"columns\": [\"class\", \"feature_3\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"class\": \"0\", \"feature_3\": \"0\", \"total_measure\": 32419.0, \"share_within_group\": 32.95585080968985}, {\"class\": \"4\", \"feature_3\": \"0\", \"total_measure\": 19162.0, \"share_within_group\": 16.827370602595852}, {\"class\": \"8\", \"feature_3\": \"0\", \"total_measure\": 11112.0, \"share_within_group\": 12.832149662220683}, {\"class\": \"5\", \"feature_3\": \"0\", \"total_measure\": 10649.0, \"share_within_group\": 11.099067173901714}, {\"class\": \"5\", \"feature_3\": \"100\", \"total_measure\": 10570.0, \"share_within_group\": 11.016728333941321}, {\"class\": \"9\", \"feature_3\": \"100\", \"total_measure\": 5470.0, \"share_within_group\": 6.375960182303505}, {\"class\": \"7\", \"feature_3\": \"0\", \"total_measure\": 5362.0, \"share_within_group\": 5.159142516260632}, {\"class\": \"1\", \"feature_3\": \"100\", \"total_measure\": 3371.0, \"share_within_group\": 4.803910391609189}, {\"class\": \"9\", \"feature_3\": \"0\", \"total_measure\": 3629.0, \"share_within_group\": 4.230047440873752}, {\"class\": \"0\", \"feature_3\": \"8\", \"total_measure\": 3535.0, \"share_within_group\": 3.5935387461751938}, {\"class\": \"6\", \"feature_3\": \"56\", \"total_measure\": 3591.0, \"share_within_group\": 3.4446704013506255}, {\"class\": \"0\", \"feature_3\": \"1\", \"total_measure\": 3300.0, \"share_within_group\": 3.3546472029358245}, {\"class\": \"6\", \"feature_3\": \"55\", \"total_measure\": 3489.0, \"share_within_group\": 3.3468267976364054}, {\"class\": \"6\", \"feature_3\": \"58\", \"total_measure\": 3455.0, \"share_within_group\": 3.314212263064999}, {\"class\": \"7\", \"feature_3\": \"41\", \"total_measure\": 3273.0, \"share_within_group\": 3.1491744602239926}, {\"class\": \"0\", \"feature_3\": \"2\", \"total_measure\": 3053.0, \"share_within_group\": 3.1035569425948704}, {\"class\": \"7\", \"feature_3\": \"51\", \"total_measure\": 3147.0, \"share_within_group\": 3.0279413462648654}, {\"class\": \"0\", \"feature_3\": \"12\", \"total_measure\": 2953.0, \"share_within_group\": 3.0019009667483303}, {\"class\": \"1\", \"feature_3\": \"35\", \"total_measure\": 2075.0, \"share_within_group\": 2.9570198939748047}, {\"class\": \"6\", \"feature_3\": \"52\", \"total_measure\": 3080.0, \"share_within_group\": 2.9544931317627197}, {\"class\": \"0\", \"feature_3\": \"15\", \"total_measure\": 2862.0, \"share_within_group\": 2.909394028727979}, {\"class\": \"0\", \"feature_3\": \"5\", \"total_measure\": 2852.0, \"share_within_group\": 2.899228431143325}, {\"class\": \"1\", \"feature_3\": \"0\", \"total_measure\": 2018.0, \"share_within_group\": 2.875790913754774}, {\"class\": \"6\", \"feature_3\": \"54\", \"total_measure\": 2995.0, \"share_within_group\": 2.8729567953342032}, {\"class\": \"6\", \"feature_3\": \"46\", \"total_measure\": 2986.0, \"share_within_group\": 2.8643235361829484}, {\"class\": \"6\", \"feature_3\": \"57\", \"total_measure\": 2982.0, \"share_within_group\": 2.8604865321157242}, {\"class\": \"7\", \"feature_3\": \"45\", \"total_measure\": 2917.0, \"share_within_group\": 2.8066428049109033}, {\"class\": \"7\", \"feature_3\": \"53\", \"total_measure\": 2911.0, \"share_within_group\": 2.8008697994842784}, {\"class\": \"7\", \"feature_3\": \"40\", \"total_measure\": 2905.0, \"share_within_group\": 2.795096794057653}, {\"class\": \"1\", \"feature_3\": \"42\", \"total_measure\": 1960.0, \"share_within_group\": 2.7931368637063216}, {\"class\": \"6\", \"feature_3\": \"62\", \"total_measure\": 2850.0, \"share_within_group\": 2.733865397897322}, {\"class\": \"3\", \"feature_3\": \"68\", \"total_measure\": 2424.0, \"share_within_group\": 2.7333002570925986}, {\"class\": \"7\", \"feature_3\": \"44\", \"total_measure\": 2829.0, \"share_within_group\": 2.7219720586537353}, {\"class\": \"2\", \"feature_3\": \"34\", \"total_measure\": 2393.0, \"share_within_group\": 2.718391457457685}, {\"class\": \"6\", \"feature_3\": \"59\", \"total_measure\": 2833.0, \"share_within_group\": 2.7175581306116183}, {\"class\": \"1\", \"feature_3\": \"39\", \"total_measure\": 1888.0, \"share_within_group\": 2.690531836059967}, {\"class\": \"6\", \"feature_3\": \"53\", \"total_measure\": 2798.0, \"share_within_group\": 2.6839843450234055}, {\"class\": \"2\", \"feature_3\": \"28\", \"total_measure\": 2344.0, \"share_within_group\": 2.662728615244803}, {\"class\": \"7\", \"feature_3\": \"43\", \"total_measure\": 2760.0, \"share_within_group\": 2.6555824962475465}, {\"class\": \"3\", \"feature_3\": \"50\", \"total_measure\": 2355.0, \"share_within_group\": 2.6554959180912}, {\"class\": \"2\", \"feature_3\": \"26\", \"total_measure\": 2323.0, \"share_within_group\": 2.638873111439282}, {\"class\": \"7\", \"feature_3\": \"50\", \"total_measure\": 2703.0, \"share_within_group\": 2.600738944694608}, {\"class\": \"0\", \"feature_3\": \"6\", \"total_measure\": 2539.0, \"share_within_group\": 2.581045226743654}, {\"class\": \"6\", \"feature_3\": \"48\", \"total_measure\": 2678.0, \"share_within_group\": 2.5688742230066763}, {\"class\": \"0\", \"feature_3\": \"14\", \"total_measure\": 2512.0, \"share_within_group\": 2.5535981132650885}, {\"class\": \"1\", \"feature_3\": \"38\", \"total_measure\": 1791.0, \"share_within_group\": 2.5523000627030723}, {\"class\": \"0\", \"feature_3\": \"9\", \"total_measure\": 2490.0, \"share_within_group\": 2.5312337985788496}, {\"class\": \"2\", \"feature_3\": \"35\", \"total_measure\": 2191.0, \"share_within_group\": 2.488924230376008}, {\"class\": \"6\", \"feature_3\": \"49\", \"total_measure\": 2583.0, \"share_within_group\": 2.477745376410099}, {\"class\": \"6\", \"feature_3\": \"60\", \"total_measure\": 2581.0, \"share_within_group\": 2.475826874376487}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 14.95}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_cb93d30f6e25f3a4/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_cb93d30f6e25f3a4/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..57b84c9e3a903325f5bcd46dabbe87701ec80948
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_cb93d30f6e25f3a4/run_manifest.json
@@ -0,0 +1,91 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:38:43.027438+00:00",
+  "ended_at": "2026-05-19T15:38:56.141327+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_cb93d30f6e25f3a4",
+    "problem_id": "v2p_n9_f7b916dc2286e142",
+    "dataset_id": "n9",
+    "template_id": "tpl_tpcds_within_group_share",
+    "template_name": "Within-Group Share of Total",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "dependency_strength_similarity",
+    "intended_facet_id": "pairwise_conditional_dependency",
+    "variant_semantic_role": "focused_target_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=class, measure_col=feature_2.",
+    "bindings": {
+      "group_col": "class",
+      "measure_col": "feature_2",
+      "item_col": "feature_3",
+      "top_k": 13,
+      "top_n": 4,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 100.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "item_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;",
+    "notes": [
+      "default_facets=pairwise_conditional_dependency",
+      "template_selection_mode=rule",
+      "problem_index_within_template=10",
+      "sql_variant_index=1/2",
+      "binding_index=33"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 3,
+    "problem_index_within_template": 10,
+    "sql_variant_index": 1,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_cb93d30f6e25f3a4.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_cb93d30f6e25f3a4",
+    "api_calls": 0,
+    "input_tokens": 15055,
+    "cached_input_tokens": 12032,
+    "output_tokens": 686,
+    "total_tokens": 15741,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 13094.74,
+    "sql_execution_elapsed_ms_total": 14.95,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_cb93d30f6e25f3a4/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_cb93d30f6e25f3a4/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_cb93d30f6e25f3a4/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..9c6f379bd2fd33ab87054105a73958bfd0e0161d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_cb93d30f6e25f3a4/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:38:56.124412+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 13094.74, "started_at": "2026-05-19T15:38:43.028680+00:00", "ended_at": "2026-05-19T15:38:56.123443+00:00", "prompt_metrics": {"chars": 9788, "bytes_utf8": 9788, "lines": 302, "estimated_tokens": null}, "response_metrics": {"chars": 595, "bytes_utf8": 595, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15055, "cached_input_tokens": 12032, "output_tokens": 686, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"class\\\", \\\"feature_3\\\",\\n       SUM(CAST(\\\"feature_2\\\" AS REAL)) AS total_measure,\\n       SUM(CAST(\\\"feature_2\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"feature_2\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\") AS share_within_group\\nFROM \\\"n9\\\"\\nGROUP BY \\\"class\\\", \\\"feature_3\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Instantiated the Within-Group Share of Total template with group_col=\\\"class\\\", item_col=\\\"feature_3\\\", and measure_col=\\\"feature_2\\\". CAST to REAL is used because the SQLite schema stores feature columns as TEXT.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_cb93d30f6e25f3a4/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_cb93d30f6e25f3a4/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..4af18c2dd685efaa4e23e8e71e8787c9c3692d92
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_cb93d30f6e25f3a4/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_cb93d30f6e25f3a4",
+  "api_calls": 0,
+  "input_tokens": 15055,
+  "cached_input_tokens": 12032,
+  "output_tokens": 686,
+  "total_tokens": 15741,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 13094.74,
+  "sql_execution_elapsed_ms_total": 14.95,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_cb93d30f6e25f3a4/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_d66b137ae99dd77e/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_d66b137ae99dd77e/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b9d6828875e767ebc955daee406e603314cfe6e4
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_d66b137ae99dd77e/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=feature_9, measure_col=feature_10.
+Result preview: [{"feature_9": "91", "feature_11": "100", "total_measure": 2760.0, "share_within_group": 55.11182108626198}, {"feature_9": "9", "feature_11": "0", "total_measure": 212.0, "share_within_group": 51.707317073170735}, {"feature_9": "97", "feature_11": "100", "total_measure": 2470.0, "share_within_group": 50.91733663162235}, {"feature_9": "99", "feature_11": "100", "total_measure": 2164.0, "share_within_group": 50.47818987637042}, {"feature_9": "5", "feature_11": "0", "total_measure": 610.0, "share_within_group": 50.37159372419488}] Results were truncated.
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_d66b137ae99dd77e/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_d66b137ae99dd77e/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..8f77bdfab06fdfcdc42adbf9ccc371ca3443ae7a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_d66b137ae99dd77e/generated_sql.sql
@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: within_group_proportion
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_d66b137ae99dd77e
+-- problem_id: v2p_n9_70e0a2b7690171fa
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+  "feature_9",
+  "feature_11",
+  SUM(CAST("feature_10" AS REAL)) AS "total_measure",
+  SUM(CAST("feature_10" AS REAL)) * 100.0 / SUM(SUM(CAST("feature_10" AS REAL))) OVER (PARTITION BY "feature_9") AS "share_within_group"
+FROM "n9"
+GROUP BY "feature_9", "feature_11"
+ORDER BY "share_within_group" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_d66b137ae99dd77e/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_d66b137ae99dd77e/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..5f4e284522e773abf6a1785283a90313fc2b2f4b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_d66b137ae99dd77e/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT\n  \"feature_9\",\n  \"feature_11\",\n  SUM(CAST(\"feature_10\" AS REAL)) AS \"total_measure\",\n  SUM(CAST(\"feature_10\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"feature_10\" AS REAL))) OVER (PARTITION BY \"feature_9\") AS \"share_within_group\"\nFROM \"n9\"\nGROUP BY \"feature_9\", \"feature_11\"\nORDER BY \"share_within_group\" DESC;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n  \\\"feature_9\\\",\\n  \\\"feature_11\\\",\\n  SUM(CAST(\\\"feature_10\\\" AS REAL)) AS \\\"total_measure\\\",\\n  SUM(CAST(\\\"feature_10\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"feature_10\\\" AS REAL))) OVER (PARTITION BY \\\"feature_9\\\") AS \\\"share_within_group\\\"\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_9\\\", \\\"feature_11\\\"\\nORDER BY \\\"share_within_group\\\" DESC;\", \"columns\": [\"feature_9\", \"feature_11\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"feature_9\": \"91\", \"feature_11\": \"100\", \"total_measure\": 2760.0, \"share_within_group\": 55.11182108626198}, {\"feature_9\": \"9\", \"feature_11\": \"0\", \"total_measure\": 212.0, \"share_within_group\": 51.707317073170735}, {\"feature_9\": \"97\", \"feature_11\": \"100\", \"total_measure\": 2470.0, \"share_within_group\": 50.91733663162235}, {\"feature_9\": \"99\", \"feature_11\": \"100\", \"total_measure\": 2164.0, \"share_within_group\": 50.47818987637042}, {\"feature_9\": \"5\", \"feature_11\": \"0\", \"total_measure\": 610.0, \"share_within_group\": 50.37159372419488}, {\"feature_9\": \"10\", \"feature_11\": \"0\", \"total_measure\": 439.0, \"share_within_group\": 46.21052631578947}, {\"feature_9\": \"93\", \"feature_11\": \"100\", \"total_measure\": 2466.0, \"share_within_group\": 45.339216767788194}, {\"feature_9\": \"62\", \"feature_11\": \"100\", \"total_measure\": 1266.0, \"share_within_group\": 44.40547176429323}, {\"feature_9\": \"1\", \"feature_11\": \"0\", \"total_measure\": 490.0, \"share_within_group\": 43.51687388987567}, {\"feature_9\": \"56\", \"feature_11\": \"100\", \"total_measure\": 651.0, \"share_within_group\": 43.371085942704866}, {\"feature_9\": \"72\", \"feature_11\": \"100\", \"total_measure\": 1593.0, \"share_within_group\": 43.030794165316046}, {\"feature_9\": \"69\", \"feature_11\": \"100\", \"total_measure\": 1048.0, \"share_within_group\": 42.60162601626016}, {\"feature_9\": \"95\", \"feature_11\": \"100\", \"total_measure\": 2400.0, \"share_within_group\": 42.17185028993147}, {\"feature_9\": \"68\", \"feature_11\": \"100\", \"total_measure\": 1121.0, \"share_within_group\": 42.06378986866792}, {\"feature_9\": \"70\", \"feature_11\": \"100\", \"total_measure\": 1526.0, \"share_within_group\": 41.98074277854195}, {\"feature_9\": \"4\", \"feature_11\": \"0\", \"total_measure\": 371.0, \"share_within_group\": 41.68539325842696}, {\"feature_9\": \"84\", \"feature_11\": \"100\", \"total_measure\": 2545.0, \"share_within_group\": 41.12134432056875}, {\"feature_9\": \"6\", \"feature_11\": \"0\", \"total_measure\": 453.0, \"share_within_group\": 40.958408679927665}, {\"feature_9\": \"60\", \"feature_11\": \"100\", \"total_measure\": 1501.0, \"share_within_group\": 40.921483097055614}, {\"feature_9\": \"54\", \"feature_11\": \"100\", \"total_measure\": 680.0, \"share_within_group\": 40.572792362768496}, {\"feature_9\": \"96\", \"feature_11\": \"100\", \"total_measure\": 1870.0, \"share_within_group\": 40.484953453128384}, {\"feature_9\": \"89\", \"feature_11\": \"100\", \"total_measure\": 1970.0, \"share_within_group\": 40.31102926130551}, {\"feature_9\": \"90\", \"feature_11\": \"100\", \"total_measure\": 2000.0, \"share_within_group\": 39.856516540454365}, {\"feature_9\": \"13\", \"feature_11\": \"0\", \"total_measure\": 404.0, \"share_within_group\": 39.80295566502463}, {\"feature_9\": \"98\", \"feature_11\": \"100\", \"total_measure\": 1573.0, \"share_within_group\": 39.21715282971827}, {\"feature_9\": \"82\", \"feature_11\": \"100\", \"total_measure\": 1865.0, \"share_within_group\": 39.21362489486964}, {\"feature_9\": \"17\", \"feature_11\": \"0\", \"total_measure\": 328.0, \"share_within_group\": 39.04761904761905}, {\"feature_9\": \"75\", \"feature_11\": \"100\", \"total_measure\": 1373.0, \"share_within_group\": 39.00568181818182}, {\"feature_9\": \"81\", \"feature_11\": \"100\", \"total_measure\": 1899.0, \"share_within_group\": 38.63682604272635}, {\"feature_9\": \"51\", \"feature_11\": \"100\", \"total_measure\": 748.0, \"share_within_group\": 38.378655720882506}, {\"feature_9\": \"88\", \"feature_11\": \"100\", \"total_measure\": 2611.0, \"share_within_group\": 37.676767676767675}, {\"feature_9\": \"49\", \"feature_11\": \"100\", \"total_measure\": 581.0, \"share_within_group\": 36.77215189873418}, {\"feature_9\": \"74\", \"feature_11\": \"100\", \"total_measure\": 1256.0, \"share_within_group\": 36.522244838615876}, {\"feature_9\": \"85\", \"feature_11\": \"100\", \"total_measure\": 1955.0, \"share_within_group\": 36.33828996282528}, {\"feature_9\": \"55\", \"feature_11\": \"100\", \"total_measure\": 820.0, \"share_within_group\": 36.203090507726266}, {\"feature_9\": \"80\", \"feature_11\": \"100\", \"total_measure\": 1622.0, \"share_within_group\": 36.140819964349376}, {\"feature_9\": \"58\", \"feature_11\": \"100\", \"total_measure\": 957.0, \"share_within_group\": 35.963923337091316}, {\"feature_9\": \"29\", \"feature_11\": \"0\", \"total_measure\": 508.0, \"share_within_group\": 35.549335199440165}, {\"feature_9\": \"3\", \"feature_11\": \"0\", \"total_measure\": 381.0, \"share_within_group\": 35.4089219330855}, {\"feature_9\": \"86\", \"feature_11\": \"100\", \"total_measure\": 1878.0, \"share_within_group\": 34.81646273637375}, {\"feature_9\": \"78\", \"feature_11\": \"100\", \"total_measure\": 1465.0, \"share_within_group\": 34.617202268431}, {\"feature_9\": \"92\", \"feature_11\": \"100\", \"total_measure\": 1809.0, \"share_within_group\": 34.19013419013419}, {\"feature_9\": \"67\", \"feature_11\": \"100\", \"total_measure\": 1071.0, \"share_within_group\": 34.075723830734965}, {\"feature_9\": \"44\", \"feature_11\": \"100\", \"total_measure\": 646.0, \"share_within_group\": 33.69848721961398}, {\"feature_9\": \"77\", \"feature_11\": \"100\", \"total_measure\": 1481.0, \"share_within_group\": 33.43869948069542}, {\"feature_9\": \"14\", \"feature_11\": \"0\", \"total_measure\": 299.0, \"share_within_group\": 33.11184939091916}, {\"feature_9\": \"73\", \"feature_11\": \"100\", \"total_measure\": 1139.0, \"share_within_group\": 32.37635019897669}, {\"feature_9\": \"11\", \"feature_11\": \"0\", \"total_measure\": 337.0, \"share_within_group\": 32.248803827751196}, {\"feature_9\": \"45\", \"feature_11\": \"100\", \"total_measure\": 673.0, \"share_within_group\": 32.15480172001911}, {\"feature_9\": \"79\", \"feature_11\": \"100\", \"total_measure\": 1540.0, \"share_within_group\": 31.791907514450866}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 17.54}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_d66b137ae99dd77e/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_d66b137ae99dd77e/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..c480e3f4aa9e110ddccb51f85a1c15028ee66c22
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_d66b137ae99dd77e/run_manifest.json
@@ -0,0 +1,91 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:35:03.484725+00:00",
+  "ended_at": "2026-05-19T15:35:27.008071+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_d66b137ae99dd77e",
+    "problem_id": "v2p_n9_70e0a2b7690171fa",
+    "dataset_id": "n9",
+    "template_id": "tpl_tpcds_within_group_share",
+    "template_name": "Within-Group Share of Total",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "dependency_strength_similarity",
+    "intended_facet_id": "pairwise_conditional_dependency",
+    "variant_semantic_role": "within_group_proportion",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=feature_9, measure_col=feature_10.",
+    "bindings": {
+      "group_col": "feature_9",
+      "measure_col": "feature_10",
+      "item_col": "feature_11",
+      "top_k": 15,
+      "top_n": 5,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.05,
+      "baseline_multiplier": 1.75,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 4,
+      "measure_threshold": 45.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "item_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;",
+    "notes": [
+      "default_facets=pairwise_conditional_dependency",
+      "template_selection_mode=rule",
+      "problem_index_within_template=2",
+      "sql_variant_index=2/2",
+      "binding_index=25"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 3,
+    "problem_index_within_template": 2,
+    "sql_variant_index": 2,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d66b137ae99dd77e.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_d66b137ae99dd77e",
+    "api_calls": 0,
+    "input_tokens": 15060,
+    "cached_input_tokens": 13696,
+    "output_tokens": 1316,
+    "total_tokens": 16376,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 23500.98,
+    "sql_execution_elapsed_ms_total": 17.54,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_d66b137ae99dd77e/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_d66b137ae99dd77e/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_d66b137ae99dd77e/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..2469689564e72671262887d90fd76000d005347f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_d66b137ae99dd77e/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:35:26.988895+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 23500.98, "started_at": "2026-05-19T15:35:03.487096+00:00", "ended_at": "2026-05-19T15:35:26.988108+00:00", "prompt_metrics": {"chars": 9805, "bytes_utf8": 9805, "lines": 302, "estimated_tokens": null}, "response_metrics": {"chars": 621, "bytes_utf8": 621, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15060, "cached_input_tokens": 13696, "output_tokens": 1316, "reasoning_output_tokens": 1129}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n  \\\"feature_9\\\",\\n  \\\"feature_11\\\",\\n  SUM(CAST(\\\"feature_10\\\" AS REAL)) AS \\\"total_measure\\\",\\n  SUM(CAST(\\\"feature_10\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"feature_10\\\" AS REAL))) OVER (PARTITION BY \\\"feature_9\\\") AS \\\"share_within_group\\\"\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_9\\\", \\\"feature_11\\\"\\nORDER BY \\\"share_within_group\\\" DESC;\",\"notes\":\"Uses the Within-Group Share of Total template with group_col=\\\"feature_9\\\", item_col=\\\"feature_11\\\", and measure_col=\\\"feature_10\\\". The measure column is cast from TEXT to REAL so SQLite aggregates it numerically.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_d66b137ae99dd77e/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_d66b137ae99dd77e/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..5d893dcffa28a0d09091de40e822f0777e02098f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_d66b137ae99dd77e/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_d66b137ae99dd77e",
+  "api_calls": 0,
+  "input_tokens": 15060,
+  "cached_input_tokens": 13696,
+  "output_tokens": 1316,
+  "total_tokens": 16376,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 23500.98,
+  "sql_execution_elapsed_ms_total": 17.54,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_d66b137ae99dd77e/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e729a248d43a4026/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e729a248d43a4026/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..cb5ff930f8464c96116d4eb268535089e7d1f583
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e729a248d43a4026/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Filtered Two-Dimensional Group Count to probe slice_level_consistency with semantic role count_distribution. Focus on group_col=feature_4, group_col_2=feature_9.
+Result preview: [{"feature_4": "100", "feature_9": "100", "row_count": 28}, {"feature_4": "61", "feature_9": "0", "row_count": 21}, {"feature_4": "63", "feature_9": "0", "row_count": 21}, {"feature_4": "64", "feature_9": "0", "row_count": 21}, {"feature_4": "66", "feature_9": "0", "row_count": 21}] Results were truncated.
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e729a248d43a4026/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e729a248d43a4026/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..b72ea71ab89f7be9f6e20c02d42762ad4ae33109
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e729a248d43a4026/generated_sql.sql
@@ -0,0 +1,18 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: slice_level_consistency
+-- intended_facet_id: conditional_interaction_hotspots
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_c2_filtered_group_count_2d
+-- query_record_id: v2q_n9_e729a248d43a4026
+-- problem_id: v2p_n9_8f6d69eb0851971d
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_4", "feature_9", COUNT(*) AS row_count
+FROM "n9"
+WHERE CAST("feature_16" AS REAL) >= 51.0
+GROUP BY "feature_4", "feature_9"
+ORDER BY row_count DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e729a248d43a4026/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e729a248d43a4026/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..2a30e807f5a3399ccea020016750c01d1fca4689
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e729a248d43a4026/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_c2_filtered_group_count_2d\nSELECT \"feature_4\", \"feature_9\", COUNT(*) AS row_count\nFROM \"n9\"\nWHERE CAST(\"feature_16\" AS REAL) >= 51.0\nGROUP BY \"feature_4\", \"feature_9\"\nORDER BY row_count DESC;", "result": "{\"query\": \"-- template_id: tpl_c2_filtered_group_count_2d\\nSELECT \\\"feature_4\\\", \\\"feature_9\\\", COUNT(*) AS row_count\\nFROM \\\"n9\\\"\\nWHERE CAST(\\\"feature_16\\\" AS REAL) >= 51.0\\nGROUP BY \\\"feature_4\\\", \\\"feature_9\\\"\\nORDER BY row_count DESC;\", \"columns\": [\"feature_4\", \"feature_9\", \"row_count\"], \"rows\": [{\"feature_4\": \"100\", \"feature_9\": \"100\", \"row_count\": 28}, {\"feature_4\": \"61\", \"feature_9\": \"0\", \"row_count\": 21}, {\"feature_4\": \"63\", \"feature_9\": \"0\", \"row_count\": 21}, {\"feature_4\": \"64\", \"feature_9\": \"0\", \"row_count\": 21}, {\"feature_4\": \"66\", \"feature_9\": \"0\", \"row_count\": 21}, {\"feature_4\": \"68\", \"feature_9\": \"0\", \"row_count\": 18}, {\"feature_4\": \"57\", \"feature_9\": \"0\", \"row_count\": 17}, {\"feature_4\": \"71\", \"feature_9\": \"0\", \"row_count\": 17}, {\"feature_4\": \"100\", \"feature_9\": \"0\", \"row_count\": 15}, {\"feature_4\": \"60\", \"feature_9\": \"0\", \"row_count\": 15}, {\"feature_4\": \"62\", \"feature_9\": \"0\", \"row_count\": 15}, {\"feature_4\": \"72\", \"feature_9\": \"0\", \"row_count\": 14}, {\"feature_4\": \"54\", \"feature_9\": \"0\", \"row_count\": 13}, {\"feature_4\": \"65\", \"feature_9\": \"0\", \"row_count\": 13}, {\"feature_4\": \"73\", \"feature_9\": \"0\", \"row_count\": 13}, {\"feature_4\": \"78\", \"feature_9\": \"0\", \"row_count\": 13}, {\"feature_4\": \"100\", \"feature_9\": \"47\", \"row_count\": 12}, {\"feature_4\": \"25\", \"feature_9\": \"100\", \"row_count\": 12}, {\"feature_4\": \"42\", \"feature_9\": \"100\", \"row_count\": 12}, {\"feature_4\": \"43\", \"feature_9\": \"100\", \"row_count\": 12}, {\"feature_4\": \"69\", \"feature_9\": \"0\", \"row_count\": 12}, {\"feature_4\": \"100\", \"feature_9\": \"42\", \"row_count\": 11}, {\"feature_4\": \"100\", \"feature_9\": \"46\", \"row_count\": 11}, {\"feature_4\": \"45\", \"feature_9\": \"100\", \"row_count\": 11}, {\"feature_4\": \"47\", \"feature_9\": \"100\", \"row_count\": 11}, {\"feature_4\": \"52\", \"feature_9\": \"0\", \"row_count\": 11}, {\"feature_4\": \"70\", \"feature_9\": \"0\", \"row_count\": 11}, {\"feature_4\": \"76\", \"feature_9\": \"0\", \"row_count\": 11}, {\"feature_4\": \"100\", \"feature_9\": \"40\", \"row_count\": 10}, {\"feature_4\": \"100\", \"feature_9\": \"67\", \"row_count\": 10}, {\"feature_4\": \"100\", \"feature_9\": \"68\", \"row_count\": 10}, {\"feature_4\": \"50\", \"feature_9\": \"0\", \"row_count\": 10}, {\"feature_4\": \"50\", \"feature_9\": \"100\", \"row_count\": 10}, {\"feature_4\": \"53\", \"feature_9\": \"0\", \"row_count\": 10}, {\"feature_4\": \"55\", \"feature_9\": \"0\", \"row_count\": 10}, {\"feature_4\": \"56\", \"feature_9\": \"0\", \"row_count\": 10}, {\"feature_4\": \"58\", \"feature_9\": \"0\", \"row_count\": 10}, {\"feature_4\": \"59\", \"feature_9\": \"0\", \"row_count\": 10}, {\"feature_4\": \"60\", \"feature_9\": \"100\", \"row_count\": 10}, {\"feature_4\": \"61\", \"feature_9\": \"100\", \"row_count\": 10}, {\"feature_4\": \"67\", \"feature_9\": \"0\", \"row_count\": 10}, {\"feature_4\": \"75\", \"feature_9\": \"0\", \"row_count\": 10}, {\"feature_4\": \"100\", \"feature_9\": \"27\", \"row_count\": 9}, {\"feature_4\": \"100\", \"feature_9\": \"52\", \"row_count\": 9}, {\"feature_4\": \"100\", \"feature_9\": \"62\", \"row_count\": 9}, {\"feature_4\": \"100\", \"feature_9\": \"66\", \"row_count\": 9}, {\"feature_4\": \"27\", \"feature_9\": \"100\", \"row_count\": 9}, {\"feature_4\": \"35\", \"feature_9\": \"100\", \"row_count\": 9}, {\"feature_4\": \"36\", \"feature_9\": \"100\", \"row_count\": 9}, {\"feature_4\": \"41\", \"feature_9\": \"100\", \"row_count\": 9}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 3.79}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e729a248d43a4026/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e729a248d43a4026/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..f2b408fb42f0c76e2a5eb68741a8567c639f986b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e729a248d43a4026/run_manifest.json
@@ -0,0 +1,93 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:41:36.135413+00:00",
+  "ended_at": "2026-05-19T15:41:44.511945+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_e729a248d43a4026",
+    "problem_id": "v2p_n9_8f6d69eb0851971d",
+    "dataset_id": "n9",
+    "template_id": "tpl_c2_filtered_group_count_2d",
+    "template_name": "Filtered Two-Dimensional Group Count",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "slice_level_consistency",
+    "intended_facet_id": "conditional_interaction_hotspots",
+    "variant_semantic_role": "count_distribution",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Filtered Two-Dimensional Group Count to probe slice_level_consistency with semantic role count_distribution. Focus on group_col=feature_4, group_col_2=feature_9.",
+    "bindings": {
+      "group_col": "feature_4",
+      "group_col_2": "feature_9",
+      "predicate_col": "feature_16",
+      "predicate_op": ">=",
+      "predicate_value": 51.0,
+      "top_k": 14,
+      "top_n": 4,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 100.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "group_col_2",
+      "predicate_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;",
+    "notes": [
+      "default_facets=conditional_interaction_hotspots",
+      "template_selection_mode=rule",
+      "problem_index_within_template=2",
+      "sql_variant_index=1/1",
+      "binding_index=49"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 5,
+    "problem_index_within_template": 2,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_e729a248d43a4026.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_e729a248d43a4026",
+    "api_calls": 0,
+    "input_tokens": 15036,
+    "cached_input_tokens": 13696,
+    "output_tokens": 340,
+    "total_tokens": 15376,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 8369.59,
+    "sql_execution_elapsed_ms_total": 3.79,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e729a248d43a4026/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e729a248d43a4026/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e729a248d43a4026/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..fa01453d862d2c1960b5daac92080f67d88cb3bf
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e729a248d43a4026/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:41:44.506786+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 8369.59, "started_at": "2026-05-19T15:41:36.136489+00:00", "ended_at": "2026-05-19T15:41:44.506103+00:00", "prompt_metrics": {"chars": 9702, "bytes_utf8": 9702, "lines": 304, "estimated_tokens": null}, "response_metrics": {"chars": 475, "bytes_utf8": 475, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15036, "cached_input_tokens": 13696, "output_tokens": 340, "reasoning_output_tokens": 205}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_c2_filtered_group_count_2d\\nSELECT \\\"feature_4\\\", \\\"feature_9\\\", COUNT(*) AS row_count\\nFROM \\\"n9\\\"\\nWHERE CAST(\\\"feature_16\\\" AS REAL) >= 51.0\\nGROUP BY \\\"feature_4\\\", \\\"feature_9\\\"\\nORDER BY row_count DESC;\",\"notes\":\"Applied the provided filtered two-dimensional group count template with group_col=feature_4, group_col_2=feature_9, and predicate_col=feature_16. Used CAST(... AS REAL) because the schema stores numeric-looking fields as TEXT.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e729a248d43a4026/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e729a248d43a4026/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..504e646b63d8c535170cddcc155fccd99f6c60ac
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e729a248d43a4026/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_e729a248d43a4026",
+  "api_calls": 0,
+  "input_tokens": 15036,
+  "cached_input_tokens": 13696,
+  "output_tokens": 340,
+  "total_tokens": 15376,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 8369.59,
+  "sql_execution_elapsed_ms_total": 3.79,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e729a248d43a4026/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e772ce8ed4c8ee71/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e772ce8ed4c8ee71/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b0744e1dd5ac6c5702a7d75b7b27a68f3bc62844
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e772ce8ed4c8ee71/final_answer.txt
@@ -0,0 +1 @@
+{"row_count": null, "preview_rows": [{"value_label": "0", "support": 2364, "support_share": 0.21506550218340612, "cumulative_support": 2364}, {"value_label": "100", "support": 1143, "support_share": 0.10398471615720524, "cumulative_support": 3507}, {"value_label": "32", "support": 137, "support_share": 0.012463609898107715, "cumulative_support": 3644}, {"value_label": "26", "support": 129, "support_share": 0.011735807860262008, "cumulative_support": 3773}, {"value_label": "38", "support": 123, "support_share": 0.01118995633187773, "cumulative_support": 3896}]}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e772ce8ed4c8ee71/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e772ce8ed4c8ee71/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..b149535a7027a7ffd335849c829e2d217c2a41c7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e772ce8ed4c8ee71/generated_sql.sql
@@ -0,0 +1,28 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: support_concentration
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_cardinality_distinct_share_profile
+-- query_record_id: v2q_n9_e772ce8ed4c8ee71
+-- problem_id: v2p_n9_be52a332eaa20855
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_1" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_1"
+), ranked AS (
+    SELECT
+        value_label,
+        support,
+        CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+        SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support
+    FROM grouped
+)
+SELECT *
+FROM ranked
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e772ce8ed4c8ee71/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e772ce8ed4c8ee71/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..ab41e21d04b1d4a2896d154e3d9caabd66675d7a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e772ce8ed4c8ee71/query_results.jsonl
@@ -0,0 +1 @@
+{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: n9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: support_rank_profile_consistency\n-- intended_facet_id: support_concentration\n-- variant_semantic_role: ranked_signal_view\n-- template_id: tpl_cardinality_distinct_share_profile\n-- query_record_id: v2q_n9_e772ce8ed4c8ee71\n-- problem_id: v2p_n9_be52a332eaa20855\n-- realization_mode: deterministic\n-- source_kind: deterministic\nWITH grouped AS (\n    SELECT \"feature_1\" AS value_label, COUNT(*) AS support\n    FROM \"n9\"\n    GROUP BY \"feature_1\"\n), ranked AS (\n    SELECT\n        value_label,\n        support,\n        CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n        SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\n    FROM grouped\n)\nSELECT *\nFROM ranked\nORDER BY support DESC, value_label;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: n9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: support_rank_profile_consistency\\n-- intended_facet_id: support_concentration\\n-- variant_semantic_role: ranked_signal_view\\n-- template_id: tpl_cardinality_distinct_share_profile\\n-- query_record_id: v2q_n9_e772ce8ed4c8ee71\\n-- problem_id: v2p_n9_be52a332eaa20855\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nWITH grouped AS (\\n    SELECT \\\"feature_1\\\" AS value_label, COUNT(*) AS support\\n    FROM \\\"n9\\\"\\n    GROUP BY \\\"feature_1\\\"\\n), ranked AS (\\n    SELECT\\n        value_label,\\n        support,\\n        CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\\n        SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\\n    FROM grouped\\n)\\nSELECT *\\nFROM ranked\\nORDER BY support DESC, value_label;\", \"columns\": [\"value_label\", \"support\", \"support_share\", \"cumulative_support\"], \"rows\": [{\"value_label\": \"0\", \"support\": 2364, \"support_share\": 0.21506550218340612, \"cumulative_support\": 2364}, {\"value_label\": \"100\", \"support\": 1143, \"support_share\": 0.10398471615720524, \"cumulative_support\": 3507}, {\"value_label\": \"32\", \"support\": 137, \"support_share\": 0.012463609898107715, \"cumulative_support\": 3644}, {\"value_label\": \"26\", \"support\": 129, \"support_share\": 0.011735807860262008, \"cumulative_support\": 3773}, {\"value_label\": \"38\", \"support\": 123, \"support_share\": 0.01118995633187773, \"cumulative_support\": 3896}, {\"value_label\": \"16\", \"support\": 120, \"support_share\": 0.010917030567685589, \"cumulative_support\": 4016}, {\"value_label\": \"19\", \"support\": 120, \"support_share\": 0.010917030567685589, \"cumulative_support\": 4136}, {\"value_label\": \"15\", \"support\": 117, \"support_share\": 0.01064410480349345, \"cumulative_support\": 4253}, {\"value_label\": \"23\", \"support\": 117, \"support_share\": 0.01064410480349345, \"cumulative_support\": 4370}, {\"value_label\": \"25\", \"support\": 117, \"support_share\": 0.01064410480349345, \"cumulative_support\": 4487}, {\"value_label\": \"20\", \"support\": 115, \"support_share\": 0.010462154294032024, \"cumulative_support\": 4602}, {\"value_label\": \"30\", \"support\": 115, \"support_share\": 0.010462154294032024, \"cumulative_support\": 4717}, {\"value_label\": \"31\", \"support\": 114, \"support_share\": 0.01037117903930131, \"cumulative_support\": 4831}, {\"value_label\": \"13\", \"support\": 113, \"support_share\": 0.010280203784570598, \"cumulative_support\": 4944}, {\"value_label\": \"27\", \"support\": 112, \"support_share\": 0.010189228529839884, \"cumulative_support\": 5056}, {\"value_label\": \"29\", \"support\": 112, \"support_share\": 0.010189228529839884, \"cumulative_support\": 5168}, {\"value_label\": \"42\", \"support\": 111, \"support_share\": 0.01009825327510917, \"cumulative_support\": 5279}, {\"value_label\": \"24\", \"support\": 110, \"support_share\": 0.010007278020378457, \"cumulative_support\": 5389}, {\"value_label\": \"14\", \"support\": 109, \"support_share\": 0.009916302765647743, \"cumulative_support\": 5498}, {\"value_label\": \"35\", \"support\": 109, \"support_share\": 0.009916302765647743, \"cumulative_support\": 5607}, {\"value_label\": \"21\", \"support\": 108, \"support_share\": 0.009825327510917031, \"cumulative_support\": 5715}, {\"value_label\": \"33\", \"support\": 108, \"support_share\": 0.009825327510917031, \"cumulative_support\": 5823}, {\"value_label\": \"12\", \"support\": 105, \"support_share\": 0.00955240174672489, \"cumulative_support\": 5928}, {\"value_label\": \"36\", \"support\": 103, \"support_share\": 0.009370451237263464, \"cumulative_support\": 6031}, {\"value_label\": \"22\", \"support\": 102, \"support_share\": 0.009279475982532752, \"cumulative_support\": 6133}, {\"value_label\": \"40\", \"support\": 102, \"support_share\": 0.009279475982532752, \"cumulative_support\": 6235}, {\"value_label\": \"17\", \"support\": 101, \"support_share\": 0.009188500727802038, \"cumulative_support\": 6336}, {\"value_label\": \"34\", \"support\": 101, \"support_share\": 0.009188500727802038, \"cumulative_support\": 6437}, {\"value_label\": \"11\", \"support\": 99, \"support_share\": 0.009006550218340612, \"cumulative_support\": 6536}, {\"value_label\": \"44\", \"support\": 95, \"support_share\": 0.008642649199417759, \"cumulative_support\": 6631}, {\"value_label\": \"46\", \"support\": 94, \"support_share\": 0.008551673944687045, \"cumulative_support\": 6725}, {\"value_label\": \"39\", \"support\": 93, \"support_share\": 0.008460698689956333, \"cumulative_support\": 6818}, {\"value_label\": \"7\", \"support\": 91, \"support_share\": 0.008278748180494906, \"cumulative_support\": 6909}, {\"value_label\": \"41\", \"support\": 89, \"support_share\": 0.008096797671033478, \"cumulative_support\": 6998}, {\"value_label\": \"28\", \"support\": 88, \"support_share\": 0.008005822416302766, \"cumulative_support\": 7086}, {\"value_label\": \"45\", \"support\": 88, \"support_share\": 0.008005822416302766, \"cumulative_support\": 7174}, {\"value_label\": \"9\", \"support\": 87, \"support_share\": 0.007914847161572052, \"cumulative_support\": 7261}, {\"value_label\": \"49\", \"support\": 86, \"support_share\": 0.00782387190684134, \"cumulative_support\": 7347}, {\"value_label\": \"55\", \"support\": 86, \"support_share\": 0.00782387190684134, \"cumulative_support\": 7433}, {\"value_label\": \"8\", \"support\": 86, \"support_share\": 0.00782387190684134, \"cumulative_support\": 7519}, {\"value_label\": \"2\", \"support\": 85, \"support_share\": 0.007732896652110626, \"cumulative_support\": 7604}, {\"value_label\": \"37\", \"support\": 85, \"support_share\": 0.007732896652110626, \"cumulative_support\": 7689}, {\"value_label\": \"18\", \"support\": 84, \"support_share\": 0.007641921397379912, \"cumulative_support\": 7773}, {\"value_label\": \"43\", \"support\": 84, \"support_share\": 0.007641921397379912, \"cumulative_support\": 7857}, {\"value_label\": \"48\", \"support\": 82, \"support_share\": 0.007459970887918486, \"cumulative_support\": 7939}, {\"value_label\": \"53\", \"support\": 81, \"support_share\": 0.007368995633187773, \"cumulative_support\": 8020}, {\"value_label\": \"56\", \"support\": 81, \"support_share\": 0.007368995633187773, \"cumulative_support\": 8101}, {\"value_label\": \"4\", \"support\": 79, \"support_share\": 0.007187045123726346, \"cumulative_support\": 8180}, {\"value_label\": \"10\", \"support\": 78, \"support_share\": 0.007096069868995633, \"cumulative_support\": 8258}, {\"value_label\": \"47\", \"support\": 78, \"support_share\": 0.007096069868995633, \"cumulative_support\": 8336}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 4.8}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e772ce8ed4c8ee71/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e772ce8ed4c8ee71/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..25c7bd503e21bd4fb0958f0c24d0b223ff5c5c12
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e772ce8ed4c8ee71/run_manifest.json
@@ -0,0 +1,57 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T16:10:15.711769+00:00",
+  "ended_at": "2026-05-19T16:10:15.717676+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_e772ce8ed4c8ee71",
+    "problem_id": "v2p_n9_be52a332eaa20855",
+    "dataset_id": "n9",
+    "template_id": "tpl_cardinality_distinct_share_profile",
+    "template_name": "Cardinality Distinct Share Profile",
+    "family_id": "cardinality_structure",
+    "canonical_subitem_id": "support_rank_profile_consistency",
+    "intended_facet_id": "support_concentration",
+    "variant_semantic_role": "ranked_signal_view",
+    "subitem_assignment_source": "template_fixed",
+    "source_kind": "deterministic",
+    "realization_mode": "deterministic",
+    "gate_priority": "deterministic",
+    "extended_family": true,
+    "question": "Use template Cardinality Distinct Share Profile to probe support_rank_profile_consistency with semantic role ranked_signal_view. Focus on group_col=feature_1.",
+    "bindings": {
+      "group_col": "feature_1"
+    },
+    "binding_roles": [
+      "group_col"
+    ],
+    "coverage_target_min": "enumerate_all_applicable",
+    "runtime_sql_skeleton": "WITH grouped AS (\n    SELECT {group_col} AS value_label, COUNT(*) AS support\n    FROM {table}\n    GROUP BY {group_col}\n), ranked AS (\n    SELECT\n        value_label,\n        support,\n        CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n        SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\n    FROM grouped\n)\nSELECT *\nFROM ranked\nORDER BY support DESC, value_label;",
+    "notes": [
+      "default_facets=support_concentration,value_imbalance_profile",
+      "template_selection_mode=deterministic",
+      "problem_index_within_template=1",
+      "sql_variant_index=1/1"
+    ],
+    "template_selection_mode": "deterministic",
+    "selected_template_rank": 0,
+    "problem_index_within_template": 1,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_e772ce8ed4c8ee71.sql",
+  "usage_summary": {
+    "engine": "template",
+    "input_tokens": 0,
+    "cached_input_tokens": 0,
+    "output_tokens": 0,
+    "total_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "none"
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e772ce8ed4c8ee71/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e772ce8ed4c8ee71/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e772ce8ed4c8ee71/usage_summary.json
@@ -0,0 +1,9 @@
+{
+  "engine": "template",
+  "input_tokens": 0,
+  "cached_input_tokens": 0,
+  "output_tokens": 0,
+  "total_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "none"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e94aa6e012d8d33c/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e94aa6e012d8d33c/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..3b252b4cc78f1b6d4c39a7162a91152b8e022ece
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e94aa6e012d8d33c/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Window Partition Average to probe slice_level_consistency with semantic role filtered_stable_view. Focus on group_col=feature_14, measure_col=feature_5.
+Result preview: [{"feature_14": "9", "avg_measure": 71.46534653465346}, {"feature_14": "13", "avg_measure": 70.3974358974359}, {"feature_14": "7", "avg_measure": 69.55474452554745}, {"feature_14": "10", "avg_measure": 69.54878048780488}, {"feature_14": "0", "avg_measure": 68.04328018223235}] Results were truncated.
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e94aa6e012d8d33c/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e94aa6e012d8d33c/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..5538814f19b6788fa523c2326d676dbf9aa9cfa4
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e94aa6e012d8d33c/generated_sql.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: slice_level_consistency
+-- intended_facet_id: conditional_interaction_hotspots
+-- variant_semantic_role: filtered_stable_view
+-- template_id: tpl_m4_window_partition_avg
+-- query_record_id: v2q_n9_e94aa6e012d8d33c
+-- problem_id: v2p_n9_f64c6ea983d7118c
+-- realization_mode: agent
+-- source_kind: agent
+SELECT DISTINCT "feature_14",
+       AVG(CAST("feature_5" AS REAL)) OVER (PARTITION BY "feature_14") AS avg_measure
+FROM "n9"
+ORDER BY avg_measure DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e94aa6e012d8d33c/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e94aa6e012d8d33c/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..e897ba171891b089c1398eb1adcb6ac39d5d7410
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e94aa6e012d8d33c/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_window_partition_avg\nSELECT DISTINCT \"feature_14\",\n       AVG(CAST(\"feature_5\" AS REAL)) OVER (PARTITION BY \"feature_14\") AS avg_measure\nFROM \"n9\"\nORDER BY avg_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"feature_14\\\",\\n       AVG(CAST(\\\"feature_5\\\" AS REAL)) OVER (PARTITION BY \\\"feature_14\\\") AS avg_measure\\nFROM \\\"n9\\\"\\nORDER BY avg_measure DESC;\", \"columns\": [\"feature_14\", \"avg_measure\"], \"rows\": [{\"feature_14\": \"9\", \"avg_measure\": 71.46534653465346}, {\"feature_14\": \"13\", \"avg_measure\": 70.3974358974359}, {\"feature_14\": \"7\", \"avg_measure\": 69.55474452554745}, {\"feature_14\": \"10\", \"avg_measure\": 69.54878048780488}, {\"feature_14\": \"0\", \"avg_measure\": 68.04328018223235}, {\"feature_14\": \"3\", \"avg_measure\": 67.73456790123457}, {\"feature_14\": \"6\", \"avg_measure\": 67.625}, {\"feature_14\": \"12\", \"avg_measure\": 66.65625}, {\"feature_14\": \"5\", \"avg_measure\": 65.9245283018868}, {\"feature_14\": \"2\", \"avg_measure\": 65.2274678111588}, {\"feature_14\": \"11\", \"avg_measure\": 63.983050847457626}, {\"feature_14\": \"1\", \"avg_measure\": 63.666666666666664}, {\"feature_14\": \"15\", \"avg_measure\": 63.651685393258425}, {\"feature_14\": \"4\", \"avg_measure\": 62.527363184079604}, {\"feature_14\": \"14\", \"avg_measure\": 62.32}, {\"feature_14\": \"20\", \"avg_measure\": 62.160583941605836}, {\"feature_14\": \"16\", \"avg_measure\": 61.449438202247194}, {\"feature_14\": \"8\", \"avg_measure\": 60.92982456140351}, {\"feature_14\": \"17\", \"avg_measure\": 59.333333333333336}, {\"feature_14\": \"19\", \"avg_measure\": 56.28888888888889}, {\"feature_14\": \"94\", \"avg_measure\": 53.370370370370374}, {\"feature_14\": \"25\", \"avg_measure\": 53.09183673469388}, {\"feature_14\": \"21\", \"avg_measure\": 52.16528925619835}, {\"feature_14\": \"76\", \"avg_measure\": 50.714285714285715}, {\"feature_14\": \"40\", \"avg_measure\": 48.78378378378378}, {\"feature_14\": \"23\", \"avg_measure\": 48.455026455026456}, {\"feature_14\": \"22\", \"avg_measure\": 48.21935483870968}, {\"feature_14\": \"96\", \"avg_measure\": 47.42465753424658}, {\"feature_14\": \"41\", \"avg_measure\": 47.25301204819277}, {\"feature_14\": \"18\", \"avg_measure\": 46.410526315789475}, {\"feature_14\": \"91\", \"avg_measure\": 45.27272727272727}, {\"feature_14\": \"88\", \"avg_measure\": 45.142857142857146}, {\"feature_14\": \"92\", \"avg_measure\": 44.738461538461536}, {\"feature_14\": \"48\", \"avg_measure\": 44.388888888888886}, {\"feature_14\": \"24\", \"avg_measure\": 44.15151515151515}, {\"feature_14\": \"90\", \"avg_measure\": 44.13793103448276}, {\"feature_14\": \"97\", \"avg_measure\": 43.9746835443038}, {\"feature_14\": \"93\", \"avg_measure\": 43.6764705882353}, {\"feature_14\": \"37\", \"avg_measure\": 43.57142857142857}, {\"feature_14\": \"95\", \"avg_measure\": 43.541666666666664}, {\"feature_14\": \"98\", \"avg_measure\": 43.51948051948052}, {\"feature_14\": \"39\", \"avg_measure\": 43.24626865671642}, {\"feature_14\": \"38\", \"avg_measure\": 42.7479674796748}, {\"feature_14\": \"44\", \"avg_measure\": 42.57142857142857}, {\"feature_14\": \"84\", \"avg_measure\": 42.10344827586207}, {\"feature_14\": \"49\", \"avg_measure\": 41.94736842105263}, {\"feature_14\": \"26\", \"avg_measure\": 41.39698492462311}, {\"feature_14\": \"45\", \"avg_measure\": 41.28378378378378}, {\"feature_14\": \"50\", \"avg_measure\": 41.166666666666664}, {\"feature_14\": \"46\", \"avg_measure\": 40.851851851851855}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 30.33}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e94aa6e012d8d33c/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e94aa6e012d8d33c/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..4259712690d1127026b105ff409583cf54de6870
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e94aa6e012d8d33c/run_manifest.json
@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T16:07:53.606541+00:00",
+  "ended_at": "2026-05-19T16:08:03.176372+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_e94aa6e012d8d33c",
+    "problem_id": "v2p_n9_f64c6ea983d7118c",
+    "dataset_id": "n9",
+    "template_id": "tpl_m4_window_partition_avg",
+    "template_name": "Window Partition Average",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "slice_level_consistency",
+    "intended_facet_id": "conditional_interaction_hotspots",
+    "variant_semantic_role": "filtered_stable_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Window Partition Average to probe slice_level_consistency with semantic role filtered_stable_view. Focus on group_col=feature_14, measure_col=feature_5.",
+    "bindings": {
+      "group_col": "feature_14",
+      "measure_col": "feature_5",
+      "top_k": 12,
+      "top_n": 3,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 78.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;",
+    "notes": [
+      "default_facets=conditional_interaction_hotspots",
+      "template_selection_mode=rule",
+      "problem_index_within_template=1",
+      "sql_variant_index=1/2",
+      "binding_index=132"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 12,
+    "problem_index_within_template": 1,
+    "sql_variant_index": 1,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_e94aa6e012d8d33c.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_e94aa6e012d8d33c",
+    "api_calls": 0,
+    "input_tokens": 14952,
+    "cached_input_tokens": 12032,
+    "output_tokens": 299,
+    "total_tokens": 15251,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 9534.91,
+    "sql_execution_elapsed_ms_total": 30.33,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e94aa6e012d8d33c/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e94aa6e012d8d33c/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e94aa6e012d8d33c/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..c1991064b830aa7d5016d0c5794896f19ee7bf37
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e94aa6e012d8d33c/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T16:08:03.143581+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 9534.91, "started_at": "2026-05-19T16:07:53.607645+00:00", "ended_at": "2026-05-19T16:08:03.142582+00:00", "prompt_metrics": {"chars": 9477, "bytes_utf8": 9477, "lines": 300, "estimated_tokens": null}, "response_metrics": {"chars": 407, "bytes_utf8": 407, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14952, "cached_input_tokens": 12032, "output_tokens": 299, "reasoning_output_tokens": 193}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"feature_14\\\",\\n       AVG(CAST(\\\"feature_5\\\" AS REAL)) OVER (PARTITION BY \\\"feature_14\\\") AS avg_measure\\nFROM \\\"n9\\\"\\nORDER BY avg_measure DESC;\",\"notes\":\"Used the specified Window Partition Average template with group_col=\\\"feature_14\\\" and measure_col=\\\"feature_5\\\". CAST was added because the schema stores numeric fields as TEXT.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e94aa6e012d8d33c/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e94aa6e012d8d33c/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..9a6f16829b0660b4dc9ae1b996c97308b4e5e363
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e94aa6e012d8d33c/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_e94aa6e012d8d33c",
+  "api_calls": 0,
+  "input_tokens": 14952,
+  "cached_input_tokens": 12032,
+  "output_tokens": 299,
+  "total_tokens": 15251,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 9534.91,
+  "sql_execution_elapsed_ms_total": 30.33,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_e94aa6e012d8d33c/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_eadfcbae38ae6a9f/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_eadfcbae38ae6a9f/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..bed77242be33557b6c4c948acbefd4bac7c6f7cb
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_eadfcbae38ae6a9f/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=feature_3.
+Result preview: [{"feature_3": "0", "row_count": 953}, {"feature_3": "100", "row_count": 309}, {"feature_3": "35", "row_count": 185}, {"feature_3": "46", "row_count": 177}, {"feature_3": "39", "row_count": 168}] Results were truncated.
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_eadfcbae38ae6a9f/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_eadfcbae38ae6a9f/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..b7a7ba3f707c96460c33645397e58954f0d331f6
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_eadfcbae38ae6a9f/generated_sql.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: subgroup_size_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_clickbench_group_count
+-- query_record_id: v2q_n9_eadfcbae38ae6a9f
+-- problem_id: v2p_n9_8e3fc3e95fcdae09
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_3", COUNT(*) AS "row_count"
+FROM "n9"
+GROUP BY "feature_3"
+ORDER BY "row_count" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_eadfcbae38ae6a9f/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_eadfcbae38ae6a9f/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..5b942b0b3707c7886d5c89c38bf656aa47a3e8e0
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_eadfcbae38ae6a9f/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_clickbench_group_count\nSELECT \"feature_3\", COUNT(*) AS \"row_count\"\nFROM \"n9\"\nGROUP BY \"feature_3\"\nORDER BY \"row_count\" DESC;", "result": "{\"query\": \"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"feature_3\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_3\\\"\\nORDER BY \\\"row_count\\\" DESC;\", \"columns\": [\"feature_3\", \"row_count\"], \"rows\": [{\"feature_3\": \"0\", \"row_count\": 953}, {\"feature_3\": \"100\", \"row_count\": 309}, {\"feature_3\": \"35\", \"row_count\": 185}, {\"feature_3\": \"46\", \"row_count\": 177}, {\"feature_3\": \"39\", \"row_count\": 168}, {\"feature_3\": \"40\", \"row_count\": 167}, {\"feature_3\": \"34\", \"row_count\": 167}, {\"feature_3\": \"38\", \"row_count\": 166}, {\"feature_3\": \"44\", \"row_count\": 161}, {\"feature_3\": \"43\", \"row_count\": 159}, {\"feature_3\": \"53\", \"row_count\": 157}, {\"feature_3\": \"52\", \"row_count\": 157}, {\"feature_3\": \"42\", \"row_count\": 157}, {\"feature_3\": \"30\", \"row_count\": 152}, {\"feature_3\": \"57\", \"row_count\": 150}, {\"feature_3\": \"47\", \"row_count\": 150}, {\"feature_3\": \"56\", \"row_count\": 149}, {\"feature_3\": \"41\", \"row_count\": 148}, {\"feature_3\": \"54\", \"row_count\": 146}, {\"feature_3\": \"50\", \"row_count\": 145}, {\"feature_3\": \"51\", \"row_count\": 144}, {\"feature_3\": \"49\", \"row_count\": 143}, {\"feature_3\": \"31\", \"row_count\": 142}, {\"feature_3\": \"60\", \"row_count\": 141}, {\"feature_3\": \"58\", \"row_count\": 141}, {\"feature_3\": \"55\", \"row_count\": 141}, {\"feature_3\": \"62\", \"row_count\": 139}, {\"feature_3\": \"36\", \"row_count\": 138}, {\"feature_3\": \"28\", \"row_count\": 138}, {\"feature_3\": \"33\", \"row_count\": 137}, {\"feature_3\": \"32\", \"row_count\": 137}, {\"feature_3\": \"26\", \"row_count\": 136}, {\"feature_3\": \"59\", \"row_count\": 134}, {\"feature_3\": \"29\", \"row_count\": 134}, {\"feature_3\": \"45\", \"row_count\": 132}, {\"feature_3\": \"37\", \"row_count\": 132}, {\"feature_3\": \"48\", \"row_count\": 131}, {\"feature_3\": \"24\", \"row_count\": 131}, {\"feature_3\": \"23\", \"row_count\": 125}, {\"feature_3\": \"20\", \"row_count\": 124}, {\"feature_3\": \"21\", \"row_count\": 119}, {\"feature_3\": \"25\", \"row_count\": 117}, {\"feature_3\": \"27\", \"row_count\": 115}, {\"feature_3\": \"22\", \"row_count\": 113}, {\"feature_3\": \"16\", \"row_count\": 110}, {\"feature_3\": \"61\", \"row_count\": 109}, {\"feature_3\": \"19\", \"row_count\": 107}, {\"feature_3\": \"18\", \"row_count\": 107}, {\"feature_3\": \"8\", \"row_count\": 103}, {\"feature_3\": \"17\", \"row_count\": 102}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 11.37}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_eadfcbae38ae6a9f/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_eadfcbae38ae6a9f/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..4db8ec31638f1062967333a6e1b5585e5921f899
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_eadfcbae38ae6a9f/run_manifest.json
@@ -0,0 +1,87 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:33:43.277053+00:00",
+  "ended_at": "2026-05-19T15:34:15.327291+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_eadfcbae38ae6a9f",
+    "problem_id": "v2p_n9_8e3fc3e95fcdae09",
+    "dataset_id": "n9",
+    "template_id": "tpl_clickbench_group_count",
+    "template_name": "Grouped Count by Category",
+    "family_id": "subgroup_structure",
+    "canonical_subitem_id": "subgroup_size_stability",
+    "intended_facet_id": "subgroup_distribution_shift",
+    "variant_semantic_role": "count_distribution",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=feature_3.",
+    "bindings": {
+      "group_col": "feature_3",
+      "top_k": 14,
+      "top_n": 6,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 100.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;",
+    "notes": [
+      "default_facets=subgroup_distribution_shift",
+      "template_selection_mode=rule",
+      "problem_index_within_template=8",
+      "sql_variant_index=1/1",
+      "binding_index=19"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 2,
+    "problem_index_within_template": 8,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_eadfcbae38ae6a9f.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_eadfcbae38ae6a9f",
+    "api_calls": 0,
+    "input_tokens": 14911,
+    "cached_input_tokens": 13696,
+    "output_tokens": 291,
+    "total_tokens": 15202,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 32032.51,
+    "sql_execution_elapsed_ms_total": 11.37,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_eadfcbae38ae6a9f/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_eadfcbae38ae6a9f/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_eadfcbae38ae6a9f/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..b37a151b34155a31b3eac7d0f95518a4b185b47b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_eadfcbae38ae6a9f/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:34:15.312865+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 32032.51, "started_at": "2026-05-19T15:33:43.278558+00:00", "ended_at": "2026-05-19T15:34:15.311106+00:00", "prompt_metrics": {"chars": 9297, "bytes_utf8": 9297, "lines": 298, "estimated_tokens": null}, "response_metrics": {"chars": 291, "bytes_utf8": 291, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14911, "cached_input_tokens": 13696, "output_tokens": 291, "reasoning_output_tokens": 205}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"feature_3\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_3\\\"\\nORDER BY \\\"row_count\\\" DESC;\",\"notes\":\"Applied the Grouped Count by Category template with group_col bound to \\\"feature_3\\\" on the single table \\\"n9\\\".\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_eadfcbae38ae6a9f/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_eadfcbae38ae6a9f/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..3847863379da38d948fc665448863786dae52f5f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_eadfcbae38ae6a9f/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_eadfcbae38ae6a9f",
+  "api_calls": 0,
+  "input_tokens": 14911,
+  "cached_input_tokens": 13696,
+  "output_tokens": 291,
+  "total_tokens": 15202,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 32032.51,
+  "sql_execution_elapsed_ms_total": 11.37,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_eadfcbae38ae6a9f/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_f2b1c2dfd33a98f6/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_f2b1c2dfd33a98f6/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..69a71473da2dc450295cc7fd311342384af99752
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_f2b1c2dfd33a98f6/run_manifest.json
@@ -0,0 +1,69 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T16:09:39.893915+00:00",
+  "ended_at": "2026-05-19T16:09:47.435234+00:00",
+  "status": "failed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_f2b1c2dfd33a98f6",
+    "problem_id": "v2p_n9_8813e3b4d11cf14e",
+    "dataset_id": "n9",
+    "template_id": "tpl_m4_window_partition_avg",
+    "template_name": "Window Partition Average",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "slice_level_consistency",
+    "intended_facet_id": "conditional_interaction_hotspots",
+    "variant_semantic_role": "ranked_signal_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Window Partition Average to probe slice_level_consistency with semantic role ranked_signal_view. Focus on group_col=feature_3, measure_col=feature_11.",
+    "bindings": {
+      "group_col": "feature_3",
+      "measure_col": "feature_11",
+      "top_k": 18,
+      "top_n": 6,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.05,
+      "baseline_multiplier": 1.75,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 4,
+      "measure_threshold": 89.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;",
+    "notes": [
+      "default_facets=conditional_interaction_hotspots",
+      "template_selection_mode=rule",
+      "problem_index_within_template=7",
+      "sql_variant_index=2/2",
+      "binding_index=138"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 12,
+    "problem_index_within_template": 7,
+    "sql_variant_index": 2,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "error": "AI CLI command failed with exit code 1: "
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_f2b1c2dfd33a98f6/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_f2b1c2dfd33a98f6/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..56e06bbc6b77720408c5cc00c986172acb35e635
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_f2b1c2dfd33a98f6/trace.jsonl
@@ -0,0 +1,2 @@
+{"timestamp": "2026-05-19T16:09:43.259476+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3362.62, "started_at": "2026-05-19T16:09:39.895862+00:00", "ended_at": "2026-05-19T16:09:43.258504+00:00", "prompt_metrics": {"chars": 9476, "bytes_utf8": 9476, "lines": 300, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e4100-024d-7913-825f-207da208f8e3\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}
+{"timestamp": "2026-05-19T16:09:47.435142+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3173.83, "started_at": "2026-05-19T16:09:44.260529+00:00", "ended_at": "2026-05-19T16:09:47.434387+00:00", "prompt_metrics": {"chars": 9476, "bytes_utf8": 9476, "lines": 300, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e4100-133f-74c2-9c84-e4c7610bfc79\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_f64c629fcaac3eed/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_f64c629fcaac3eed/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..9d715ce51416a773bbf68b4b4fd7e14c026c6d50
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_f64c629fcaac3eed/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=feature_15, measure_col=feature_16.
+Result preview: [{"feature_15": "80", "feature_1": "0", "total_measure": 119.0, "share_within_group": 64.67391304347827}, {"feature_15": "74", "feature_1": "0", "total_measure": 358.0, "share_within_group": 57.556270096463024}, {"feature_15": "59", "feature_1": "38", "total_measure": 162.0, "share_within_group": 55.86206896551724}, {"feature_15": "93", "feature_1": "100", "total_measure": 517.0, "share_within_group": 55.83153347732181}, {"feature_15": "65", "feature_1": "100", "total_measure": 416.0, "share_within_group": 50.8557457212714}] Results were truncated.
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_f64c629fcaac3eed/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_f64c629fcaac3eed/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..89d28dc121557528eb529f53f51a744f06a7a1ff
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_f64c629fcaac3eed/generated_sql.sql
@@ -0,0 +1,19 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: within_group_proportion
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_f64c629fcaac3eed
+-- problem_id: v2p_n9_29d57a6edc03a255
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_15", "feature_1",
+       SUM(CAST("feature_16" AS REAL)) AS "total_measure",
+       SUM(CAST("feature_16" AS REAL)) * 100.0 / SUM(SUM(CAST("feature_16" AS REAL))) OVER (PARTITION BY "feature_15") AS "share_within_group"
+FROM "n9"
+GROUP BY "feature_15", "feature_1"
+ORDER BY "share_within_group" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_f64c629fcaac3eed/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_f64c629fcaac3eed/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..2a22d9e06981ea4cc58f7106e9d35e914e3f785c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_f64c629fcaac3eed/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT \"feature_15\", \"feature_1\",\n       SUM(CAST(\"feature_16\" AS REAL)) AS \"total_measure\",\n       SUM(CAST(\"feature_16\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"feature_16\" AS REAL))) OVER (PARTITION BY \"feature_15\") AS \"share_within_group\"\nFROM \"n9\"\nGROUP BY \"feature_15\", \"feature_1\"\nORDER BY \"share_within_group\" DESC;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"feature_15\\\", \\\"feature_1\\\",\\n       SUM(CAST(\\\"feature_16\\\" AS REAL)) AS \\\"total_measure\\\",\\n       SUM(CAST(\\\"feature_16\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"feature_16\\\" AS REAL))) OVER (PARTITION BY \\\"feature_15\\\") AS \\\"share_within_group\\\"\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_15\\\", \\\"feature_1\\\"\\nORDER BY \\\"share_within_group\\\" DESC;\", \"columns\": [\"feature_15\", \"feature_1\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"feature_15\": \"80\", \"feature_1\": \"0\", \"total_measure\": 119.0, \"share_within_group\": 64.67391304347827}, {\"feature_15\": \"74\", \"feature_1\": \"0\", \"total_measure\": 358.0, \"share_within_group\": 57.556270096463024}, {\"feature_15\": \"59\", \"feature_1\": \"38\", \"total_measure\": 162.0, \"share_within_group\": 55.86206896551724}, {\"feature_15\": \"93\", \"feature_1\": \"100\", \"total_measure\": 517.0, \"share_within_group\": 55.83153347732181}, {\"feature_15\": \"65\", \"feature_1\": \"100\", \"total_measure\": 416.0, \"share_within_group\": 50.8557457212714}, {\"feature_15\": \"83\", \"feature_1\": \"100\", \"total_measure\": 536.0, \"share_within_group\": 48.33183047790803}, {\"feature_15\": \"96\", \"feature_1\": \"0\", \"total_measure\": 316.0, \"share_within_group\": 42.93478260869565}, {\"feature_15\": \"76\", \"feature_1\": \"0\", \"total_measure\": 341.0, \"share_within_group\": 41.48418491484185}, {\"feature_15\": \"95\", \"feature_1\": \"100\", \"total_measure\": 470.0, \"share_within_group\": 40.834057341442225}, {\"feature_15\": \"94\", \"feature_1\": \"100\", \"total_measure\": 568.0, \"share_within_group\": 39.091534755677905}, {\"feature_15\": \"98\", \"feature_1\": \"100\", \"total_measure\": 503.0, \"share_within_group\": 38.871715610510044}, {\"feature_15\": \"92\", \"feature_1\": \"0\", \"total_measure\": 536.0, \"share_within_group\": 38.84057971014493}, {\"feature_15\": \"99\", \"feature_1\": \"0\", \"total_measure\": 216.0, \"share_within_group\": 37.11340206185567}, {\"feature_15\": \"82\", \"feature_1\": \"0\", \"total_measure\": 226.0, \"share_within_group\": 35.70300157977883}, {\"feature_15\": \"87\", \"feature_1\": \"100\", \"total_measure\": 454.0, \"share_within_group\": 35.24844720496895}, {\"feature_15\": \"99\", \"feature_1\": \"100\", \"total_measure\": 185.0, \"share_within_group\": 31.786941580756015}, {\"feature_15\": \"78\", \"feature_1\": \"100\", \"total_measure\": 370.0, \"share_within_group\": 30.45267489711934}, {\"feature_15\": \"58\", \"feature_1\": \"0\", \"total_measure\": 267.0, \"share_within_group\": 30.34090909090909}, {\"feature_15\": \"66\", \"feature_1\": \"100\", \"total_measure\": 238.0, \"share_within_group\": 30.20304568527919}, {\"feature_15\": \"97\", \"feature_1\": \"100\", \"total_measure\": 298.0, \"share_within_group\": 29.592850049652434}, {\"feature_15\": \"77\", \"feature_1\": \"0\", \"total_measure\": 301.0, \"share_within_group\": 29.110251450676984}, {\"feature_15\": \"87\", \"feature_1\": \"0\", \"total_measure\": 373.0, \"share_within_group\": 28.959627329192546}, {\"feature_15\": \"57\", \"feature_1\": \"68\", \"total_measure\": 193.0, \"share_within_group\": 28.677563150074295}, {\"feature_15\": \"72\", \"feature_1\": \"100\", \"total_measure\": 281.0, \"share_within_group\": 28.644240570846076}, {\"feature_15\": \"3\", \"feature_1\": \"100\", \"total_measure\": 596.0, \"share_within_group\": 28.612578012481997}, {\"feature_15\": \"77\", \"feature_1\": \"100\", \"total_measure\": 287.0, \"share_within_group\": 27.756286266924565}, {\"feature_15\": \"69\", \"feature_1\": \"0\", \"total_measure\": 345.0, \"share_within_group\": 27.33755942947702}, {\"feature_15\": \"88\", \"feature_1\": \"100\", \"total_measure\": 550.0, \"share_within_group\": 26.92119432207538}, {\"feature_15\": \"89\", \"feature_1\": \"0\", \"total_measure\": 294.0, \"share_within_group\": 26.873857404021937}, {\"feature_15\": \"90\", \"feature_1\": \"0\", \"total_measure\": 393.0, \"share_within_group\": 26.69836956521739}, {\"feature_15\": \"63\", \"feature_1\": \"62\", \"total_measure\": 180.0, \"share_within_group\": 26.587887740029544}, {\"feature_15\": \"96\", \"feature_1\": \"100\", \"total_measure\": 195.0, \"share_within_group\": 26.494565217391305}, {\"feature_15\": \"73\", \"feature_1\": \"0\", \"total_measure\": 256.0, \"share_within_group\": 26.095820591233434}, {\"feature_15\": \"83\", \"feature_1\": \"0\", \"total_measure\": 261.0, \"share_within_group\": 23.53471596032462}, {\"feature_15\": \"100\", \"feature_1\": \"0\", \"total_measure\": 25333.0, \"share_within_group\": 23.39474534792446}, {\"feature_15\": \"91\", \"feature_1\": \"0\", \"total_measure\": 297.0, \"share_within_group\": 23.275862068965516}, {\"feature_15\": \"86\", \"feature_1\": \"0\", \"total_measure\": 267.0, \"share_within_group\": 23.257839721254356}, {\"feature_15\": \"85\", \"feature_1\": \"0\", \"total_measure\": 279.0, \"share_within_group\": 23.172757475083056}, {\"feature_15\": \"64\", \"feature_1\": \"100\", \"total_measure\": 190.0, \"share_within_group\": 23.142509135200974}, {\"feature_15\": \"97\", \"feature_1\": \"0\", \"total_measure\": 231.0, \"share_within_group\": 22.939424031777556}, {\"feature_15\": \"84\", \"feature_1\": \"100\", \"total_measure\": 299.0, \"share_within_group\": 22.583081570996978}, {\"feature_15\": \"79\", \"feature_1\": \"100\", \"total_measure\": 340.0, \"share_within_group\": 22.516556291390728}, {\"feature_15\": \"58\", \"feature_1\": \"72\", \"total_measure\": 198.0, \"share_within_group\": 22.5}, {\"feature_15\": \"11\", \"feature_1\": \"100\", \"total_measure\": 605.0, \"share_within_group\": 22.324723247232473}, {\"feature_15\": \"81\", \"feature_1\": \"100\", \"total_measure\": 180.0, \"share_within_group\": 22.19482120838471}, {\"feature_15\": \"41\", \"feature_1\": \"0\", \"total_measure\": 255.0, \"share_within_group\": 21.48272957034541}, {\"feature_15\": \"68\", \"feature_1\": \"0\", \"total_measure\": 109.0, \"share_within_group\": 21.456692913385826}, {\"feature_15\": \"54\", \"feature_1\": \"52\", \"total_measure\": 200.0, \"share_within_group\": 21.299254526091588}, {\"feature_15\": \"63\", \"feature_1\": \"0\", \"total_measure\": 142.0, \"share_within_group\": 20.974889217134418}, {\"feature_15\": \"91\", \"feature_1\": \"100\", \"total_measure\": 267.0, \"share_within_group\": 20.92476489028213}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 36.25}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_f64c629fcaac3eed/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_f64c629fcaac3eed/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..4fb0e4ea27a26dd77df82db5fd339b51e93232e1
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_f64c629fcaac3eed/run_manifest.json
@@ -0,0 +1,91 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:37:59.979771+00:00",
+  "ended_at": "2026-05-19T15:38:16.796088+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_f64c629fcaac3eed",
+    "problem_id": "v2p_n9_29d57a6edc03a255",
+    "dataset_id": "n9",
+    "template_id": "tpl_tpcds_within_group_share",
+    "template_name": "Within-Group Share of Total",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "dependency_strength_similarity",
+    "intended_facet_id": "pairwise_conditional_dependency",
+    "variant_semantic_role": "within_group_proportion",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=feature_15, measure_col=feature_16.",
+    "bindings": {
+      "group_col": "feature_15",
+      "measure_col": "feature_16",
+      "item_col": "feature_1",
+      "top_k": 16,
+      "top_n": 7,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.05,
+      "baseline_multiplier": 1.75,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 4,
+      "measure_threshold": 33.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "item_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;",
+    "notes": [
+      "default_facets=pairwise_conditional_dependency",
+      "template_selection_mode=rule",
+      "problem_index_within_template=8",
+      "sql_variant_index=2/2",
+      "binding_index=31"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 3,
+    "problem_index_within_template": 8,
+    "sql_variant_index": 2,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_f64c629fcaac3eed.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_f64c629fcaac3eed",
+    "api_calls": 0,
+    "input_tokens": 15060,
+    "cached_input_tokens": 12032,
+    "output_tokens": 865,
+    "total_tokens": 15925,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 16773.51,
+    "sql_execution_elapsed_ms_total": 36.25,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_f64c629fcaac3eed/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_f64c629fcaac3eed/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_f64c629fcaac3eed/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..bafe505c221299aa1b0fa61e4ad8b87f39193dde
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_f64c629fcaac3eed/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:38:16.756691+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 16773.51, "started_at": "2026-05-19T15:37:59.981583+00:00", "ended_at": "2026-05-19T15:38:16.755135+00:00", "prompt_metrics": {"chars": 9806, "bytes_utf8": 9806, "lines": 302, "estimated_tokens": null}, "response_metrics": {"chars": 629, "bytes_utf8": 629, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15060, "cached_input_tokens": 12032, "output_tokens": 865, "reasoning_output_tokens": 682}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"feature_15\\\", \\\"feature_1\\\",\\n       SUM(CAST(\\\"feature_16\\\" AS REAL)) AS \\\"total_measure\\\",\\n       SUM(CAST(\\\"feature_16\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"feature_16\\\" AS REAL))) OVER (PARTITION BY \\\"feature_15\\\") AS \\\"share_within_group\\\"\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_15\\\", \\\"feature_1\\\"\\nORDER BY \\\"share_within_group\\\" DESC;\",\"notes\":\"Applied the Within-Group Share of Total template with group_col=\\\"feature_15\\\", item_col=\\\"feature_1\\\", and measure_col=\\\"feature_16\\\". The measure column is cast from TEXT to REAL so SQLite aggregates it numerically.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_f64c629fcaac3eed/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_f64c629fcaac3eed/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..7ed20ee0ee24ba3f7b45d0c16d963cf819fb6f79
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_f64c629fcaac3eed/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_f64c629fcaac3eed",
+  "api_calls": 0,
+  "input_tokens": 15060,
+  "cached_input_tokens": 12032,
+  "output_tokens": 865,
+  "total_tokens": 15925,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 16773.51,
+  "sql_execution_elapsed_ms_total": 36.25,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_f64c629fcaac3eed/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_facd0269431f30bf/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_facd0269431f30bf/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..7673ebc515dd71c4b001c38d62a3b85b274f7f3d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_facd0269431f30bf/run_manifest.json
@@ -0,0 +1,67 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T16:05:57.743405+00:00",
+  "ended_at": "2026-05-19T16:06:05.591840+00:00",
+  "status": "failed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_facd0269431f30bf",
+    "problem_id": "v2p_n9_f48ead8d02d14876",
+    "dataset_id": "n9",
+    "template_id": "tpl_tail_low_support_group_count_v2",
+    "template_name": "Low-Support Group Count",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_set_consistency",
+    "intended_facet_id": "low_support_extremes",
+    "variant_semantic_role": "count_distribution",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Low-Support Group Count to probe tail_set_consistency with semantic role count_distribution. Focus on group_col=feature_4.",
+    "bindings": {
+      "group_col": "feature_4",
+      "top_k": 17,
+      "top_n": 6,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.05,
+      "baseline_multiplier": 1.75,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 4,
+      "measure_threshold": 97.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT\n    {group_col},\n    COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};",
+    "notes": [
+      "default_facets=low_support_extremes",
+      "template_selection_mode=rule",
+      "problem_index_within_template=3",
+      "sql_variant_index=2/2",
+      "binding_index=122"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 11,
+    "problem_index_within_template": 3,
+    "sql_variant_index": 2,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "error": "AI CLI command failed with exit code 1: "
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_facd0269431f30bf/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_facd0269431f30bf/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..4be49b5353815caa9a7e1417830d75c9c3f84708
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_facd0269431f30bf/trace.jsonl
@@ -0,0 +1,2 @@
+{"timestamp": "2026-05-19T16:06:01.341738+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3595.97, "started_at": "2026-05-19T16:05:57.744573+00:00", "ended_at": "2026-05-19T16:06:01.340580+00:00", "prompt_metrics": {"chars": 9378, "bytes_utf8": 9378, "lines": 298, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fc-9e78-7e73-ac0d-84a7b1c63401\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}
+{"timestamp": "2026-05-19T16:06:05.591748+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3247.22, "started_at": "2026-05-19T16:06:02.343686+00:00", "ended_at": "2026-05-19T16:06:05.590962+00:00", "prompt_metrics": {"chars": 9378, "bytes_utf8": 9378, "lines": 298, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fc-b0f4-7272-ac94-e564c07dcf6e\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fc0117fdb95c9de1/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fc0117fdb95c9de1/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..afd2594b29584b59b7eebd2b6c7930c07dc73ee4
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fc0117fdb95c9de1/final_answer.txt
@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=feature_13, measure_col=feature_14.
+Result preview: [{"feature_13": "50", "feature_15": "100", "total_measure": 4740.0, "share_within_group": 60.09127789046653}, {"feature_13": "42", "feature_15": "100", "total_measure": 3739.0, "share_within_group": 60.05460970125281}, {"feature_13": "46", "feature_15": "100", "total_measure": 3660.0, "share_within_group": 58.64444800512738}, {"feature_13": "41", "feature_15": "100", "total_measure": 4099.0, "share_within_group": 58.018400566171266}, {"feature_13": "35", "feature_15": "100", "total_measure": 2773.0, "share_within_group": 56.29313844904588}]
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fc0117fdb95c9de1/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fc0117fdb95c9de1/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..05a7d42d2c230b9cd15c9ff8f852892bde900103
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fc0117fdb95c9de1/generated_sql.sql
@@ -0,0 +1,20 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_fc0117fdb95c9de1
+-- problem_id: v2p_n9_7ccc8901a2d9c3e8
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_13", "feature_15",
+       SUM(CAST("feature_14" AS REAL)) AS total_measure,
+       SUM(CAST("feature_14" AS REAL)) * 100.0 / SUM(SUM(CAST("feature_14" AS REAL))) OVER (PARTITION BY "feature_13") AS share_within_group
+FROM "n9"
+GROUP BY "feature_13", "feature_15"
+ORDER BY share_within_group DESC
+LIMIT 14;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fc0117fdb95c9de1/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fc0117fdb95c9de1/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..b923b15564a10ba942854e296242e0fb2dfdbe99
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fc0117fdb95c9de1/query_results.jsonl
@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT \"feature_13\", \"feature_15\",\n       SUM(CAST(\"feature_14\" AS REAL)) AS total_measure,\n       SUM(CAST(\"feature_14\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"feature_14\" AS REAL))) OVER (PARTITION BY \"feature_13\") AS share_within_group\nFROM \"n9\"\nGROUP BY \"feature_13\", \"feature_15\"\nORDER BY share_within_group DESC\nLIMIT 14;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"feature_13\\\", \\\"feature_15\\\",\\n       SUM(CAST(\\\"feature_14\\\" AS REAL)) AS total_measure,\\n       SUM(CAST(\\\"feature_14\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"feature_14\\\" AS REAL))) OVER (PARTITION BY \\\"feature_13\\\") AS share_within_group\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_13\\\", \\\"feature_15\\\"\\nORDER BY share_within_group DESC\\nLIMIT 14;\", \"columns\": [\"feature_13\", \"feature_15\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"feature_13\": \"50\", \"feature_15\": \"100\", \"total_measure\": 4740.0, \"share_within_group\": 60.09127789046653}, {\"feature_13\": \"42\", \"feature_15\": \"100\", \"total_measure\": 3739.0, \"share_within_group\": 60.05460970125281}, {\"feature_13\": \"46\", \"feature_15\": \"100\", \"total_measure\": 3660.0, \"share_within_group\": 58.64444800512738}, {\"feature_13\": \"41\", \"feature_15\": \"100\", \"total_measure\": 4099.0, \"share_within_group\": 58.018400566171266}, {\"feature_13\": \"35\", \"feature_15\": \"100\", \"total_measure\": 2773.0, \"share_within_group\": 56.29313844904588}, {\"feature_13\": \"49\", \"feature_15\": \"100\", \"total_measure\": 4267.0, \"share_within_group\": 55.065169699316044}, {\"feature_13\": \"44\", \"feature_15\": \"100\", \"total_measure\": 3402.0, \"share_within_group\": 53.92296718972896}, {\"feature_13\": \"39\", \"feature_15\": \"100\", \"total_measure\": 2678.0, \"share_within_group\": 52.758077226162335}, {\"feature_13\": \"45\", \"feature_15\": \"100\", \"total_measure\": 4094.0, \"share_within_group\": 51.529263687854}, {\"feature_13\": \"31\", \"feature_15\": \"100\", \"total_measure\": 1716.0, \"share_within_group\": 51.14754098360656}, {\"feature_13\": \"38\", \"feature_15\": \"100\", \"total_measure\": 2554.0, \"share_within_group\": 50.694720127034536}, {\"feature_13\": \"10\", \"feature_15\": \"0\", \"total_measure\": 347.0, \"share_within_group\": 50.509461426491995}, {\"feature_13\": \"33\", \"feature_15\": \"100\", \"total_measure\": 1805.0, \"share_within_group\": 49.330418147034706}, {\"feature_13\": \"16\", \"feature_15\": \"100\", \"total_measure\": 676.0, \"share_within_group\": 48.808664259927795}], \"row_count_returned\": 14, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 25.42}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fc0117fdb95c9de1/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fc0117fdb95c9de1/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..fba7840e2c7c428e5737b18d2b777e539bbcad61
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fc0117fdb95c9de1/run_manifest.json
@@ -0,0 +1,91 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T15:36:53.821027+00:00",
+  "ended_at": "2026-05-19T15:37:04.920149+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_fc0117fdb95c9de1",
+    "problem_id": "v2p_n9_7ccc8901a2d9c3e8",
+    "dataset_id": "n9",
+    "template_id": "tpl_tpcds_within_group_share",
+    "template_name": "Within-Group Share of Total",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "dependency_strength_similarity",
+    "intended_facet_id": "pairwise_conditional_dependency",
+    "variant_semantic_role": "focused_target_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=feature_13, measure_col=feature_14.",
+    "bindings": {
+      "group_col": "feature_13",
+      "measure_col": "feature_14",
+      "item_col": "feature_15",
+      "top_k": 14,
+      "top_n": 4,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 47.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "item_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;",
+    "notes": [
+      "default_facets=pairwise_conditional_dependency",
+      "template_selection_mode=rule",
+      "problem_index_within_template=6",
+      "sql_variant_index=1/2",
+      "binding_index=29"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 3,
+    "problem_index_within_template": 6,
+    "sql_variant_index": 1,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_fc0117fdb95c9de1.sql",
+  "usage_summary": {
+    "dataset_id": "n9",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n9_fc0117fdb95c9de1",
+    "api_calls": 0,
+    "input_tokens": 15059,
+    "cached_input_tokens": 13696,
+    "output_tokens": 497,
+    "total_tokens": 15556,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 11067.91,
+    "sql_execution_elapsed_ms_total": 25.42,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fc0117fdb95c9de1/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fc0117fdb95c9de1/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fc0117fdb95c9de1/trace.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..e54768f5a596efa6e981016b7193f68f5937c50a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fc0117fdb95c9de1/trace.jsonl
@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:37:04.892324+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 11067.91, "started_at": "2026-05-19T15:36:53.823162+00:00", "ended_at": "2026-05-19T15:37:04.891109+00:00", "prompt_metrics": {"chars": 9800, "bytes_utf8": 9800, "lines": 302, "estimated_tokens": null}, "response_metrics": {"chars": 670, "bytes_utf8": 670, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15059, "cached_input_tokens": 13696, "output_tokens": 497, "reasoning_output_tokens": 303}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"feature_13\\\", \\\"feature_15\\\",\\n       SUM(CAST(\\\"feature_14\\\" AS REAL)) AS total_measure,\\n       SUM(CAST(\\\"feature_14\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"feature_14\\\" AS REAL))) OVER (PARTITION BY \\\"feature_13\\\") AS share_within_group\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_13\\\", \\\"feature_15\\\"\\nORDER BY share_within_group DESC\\nLIMIT 14;\",\"notes\":\"Applied the Within-Group Share of Total template with group_col=\\\"feature_13\\\", item_col=\\\"feature_15\\\", and measure_col=\\\"feature_14\\\". Cast \\\"feature_14\\\" to REAL because the SQLite schema stores features as TEXT. Added LIMIT 14 from the bound top_k value.\"}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fc0117fdb95c9de1/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fc0117fdb95c9de1/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..a7b88bab8336ec09ab0a9959da22f626d0218d54
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fc0117fdb95c9de1/usage_summary.json
@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n9",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n9_fc0117fdb95c9de1",
+  "api_calls": 0,
+  "input_tokens": 15059,
+  "cached_input_tokens": 13696,
+  "output_tokens": 497,
+  "total_tokens": 15556,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 1,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 11067.91,
+  "sql_execution_elapsed_ms_total": 25.42,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fc0117fdb95c9de1/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_ffde6eecd5041532/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_ffde6eecd5041532/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..00e68b27affbf1f495198f96a4c1f934cdfeef24
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_ffde6eecd5041532/final_answer.txt
@@ -0,0 +1 @@
+{"row_count": null, "preview_rows": [{"feature_7": "0", "support": 988, "avg_response": 71.75708502024291}, {"feature_7": "100", "support": 899, "avg_response": 18.413793103448278}, {"feature_7": "68", "support": 155, "avg_response": 32.10967741935484}, {"feature_7": "56", "support": 145, "avg_response": 31.986206896551725}, {"feature_7": "70", "support": 142, "avg_response": 30.823943661971832}]}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_ffde6eecd5041532/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_ffde6eecd5041532/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..736c713138c10ab8f9269c59d8f2c672a64d5435
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_ffde6eecd5041532/generated_sql.sql
@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: high_cardinality_response_stability
+-- intended_facet_id: target_cardinality_cross_section
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_cardinality_high_card_response_stability
+-- query_record_id: v2q_n9_ffde6eecd5041532
+-- problem_id: v2p_n9_e57314fedeadb9f8
+-- realization_mode: deterministic
+-- source_kind: deterministic
+SELECT
+    "feature_7",
+    COUNT(*) AS support,
+    AVG("feature_1") AS avg_response
+FROM "n9"
+GROUP BY "feature_7"
+HAVING COUNT(*) >= 5.0
+ORDER BY support DESC, avg_response DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_ffde6eecd5041532/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_ffde6eecd5041532/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..05cdc11222c7497d1b77aae0930d71e0a437022e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_ffde6eecd5041532/query_results.jsonl
@@ -0,0 +1 @@
+{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: n9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: high_cardinality_response_stability\n-- intended_facet_id: target_cardinality_cross_section\n-- variant_semantic_role: focused_target_view\n-- template_id: tpl_cardinality_high_card_response_stability\n-- query_record_id: v2q_n9_ffde6eecd5041532\n-- problem_id: v2p_n9_e57314fedeadb9f8\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n    \"feature_7\",\n    COUNT(*) AS support,\n    AVG(\"feature_1\") AS avg_response\nFROM \"n9\"\nGROUP BY \"feature_7\"\nHAVING COUNT(*) >= 5.0\nORDER BY support DESC, avg_response DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: n9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: high_cardinality_response_stability\\n-- intended_facet_id: target_cardinality_cross_section\\n-- variant_semantic_role: focused_target_view\\n-- template_id: tpl_cardinality_high_card_response_stability\\n-- query_record_id: v2q_n9_ffde6eecd5041532\\n-- problem_id: v2p_n9_e57314fedeadb9f8\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n    \\\"feature_7\\\",\\n    COUNT(*) AS support,\\n    AVG(\\\"feature_1\\\") AS avg_response\\nFROM \\\"n9\\\"\\nGROUP BY \\\"feature_7\\\"\\nHAVING COUNT(*) >= 5.0\\nORDER BY support DESC, avg_response DESC;\", \"columns\": [\"feature_7\", \"support\", \"avg_response\"], \"rows\": [{\"feature_7\": \"0\", \"support\": 988, \"avg_response\": 71.75708502024291}, {\"feature_7\": \"100\", \"support\": 899, \"avg_response\": 18.413793103448278}, {\"feature_7\": \"68\", \"support\": 155, \"avg_response\": 32.10967741935484}, {\"feature_7\": \"56\", \"support\": 145, \"avg_response\": 31.986206896551725}, {\"feature_7\": \"70\", \"support\": 142, \"avg_response\": 30.823943661971832}, {\"feature_7\": \"61\", \"support\": 142, \"avg_response\": 28.8943661971831}, {\"feature_7\": \"67\", \"support\": 139, \"avg_response\": 34.02158273381295}, {\"feature_7\": \"57\", \"support\": 139, \"avg_response\": 31.14388489208633}, {\"feature_7\": \"53\", \"support\": 139, \"avg_response\": 29.51798561151079}, {\"feature_7\": \"62\", \"support\": 138, \"avg_response\": 30.471014492753625}, {\"feature_7\": \"69\", \"support\": 136, \"avg_response\": 31.558823529411764}, {\"feature_7\": \"54\", \"support\": 135, \"avg_response\": 32.05185185185185}, {\"feature_7\": \"55\", \"support\": 134, \"avg_response\": 32.5}, {\"feature_7\": \"51\", \"support\": 134, \"avg_response\": 30.171641791044777}, {\"feature_7\": \"72\", \"support\": 133, \"avg_response\": 32.4812030075188}, {\"feature_7\": \"66\", \"support\": 133, \"avg_response\": 27.23308270676692}, {\"feature_7\": \"65\", \"support\": 131, \"avg_response\": 30.50381679389313}, {\"feature_7\": \"50\", \"support\": 128, \"avg_response\": 33.421875}, {\"feature_7\": \"74\", \"support\": 127, \"avg_response\": 35.1496062992126}, {\"feature_7\": \"59\", \"support\": 127, \"avg_response\": 34.826771653543304}, {\"feature_7\": \"52\", \"support\": 126, \"avg_response\": 31.896825396825395}, {\"feature_7\": \"63\", \"support\": 125, \"avg_response\": 33.736}, {\"feature_7\": \"60\", \"support\": 124, \"avg_response\": 33.33870967741935}, {\"feature_7\": \"41\", \"support\": 124, \"avg_response\": 29.85483870967742}, {\"feature_7\": \"73\", \"support\": 118, \"avg_response\": 24.78813559322034}, {\"feature_7\": \"45\", \"support\": 117, \"avg_response\": 33.61538461538461}, {\"feature_7\": \"58\", \"support\": 117, \"avg_response\": 33.452991452991455}, {\"feature_7\": \"71\", \"support\": 117, \"avg_response\": 32.2991452991453}, {\"feature_7\": \"44\", \"support\": 115, \"avg_response\": 37.85217391304348}, {\"feature_7\": \"43\", \"support\": 115, \"avg_response\": 30.339130434782607}, {\"feature_7\": \"42\", \"support\": 114, \"avg_response\": 31.912280701754387}, {\"feature_7\": \"46\", \"support\": 113, \"avg_response\": 34.13274336283186}, {\"feature_7\": \"64\", \"support\": 113, \"avg_response\": 28.38053097345133}, {\"feature_7\": \"39\", \"support\": 112, \"avg_response\": 36.205357142857146}, {\"feature_7\": \"75\", \"support\": 112, \"avg_response\": 33.517857142857146}, {\"feature_7\": \"47\", \"support\": 111, \"avg_response\": 35.693693693693696}, {\"feature_7\": \"49\", \"support\": 110, \"avg_response\": 34.89090909090909}, {\"feature_7\": \"38\", \"support\": 110, \"avg_response\": 33.3}, {\"feature_7\": \"34\", \"support\": 109, \"avg_response\": 39.908256880733944}, {\"feature_7\": \"77\", \"support\": 109, \"avg_response\": 33.11926605504587}, {\"feature_7\": \"40\", \"support\": 105, \"avg_response\": 38.63809523809524}, {\"feature_7\": \"76\", \"support\": 104, \"avg_response\": 27.490384615384617}, {\"feature_7\": \"35\", \"support\": 103, \"avg_response\": 35.57281553398058}, {\"feature_7\": \"36\", \"support\": 103, \"avg_response\": 34.90291262135922}, {\"feature_7\": \"79\", \"support\": 103, \"avg_response\": 33.70873786407767}, {\"feature_7\": \"37\", \"support\": 100, \"avg_response\": 36.97}, {\"feature_7\": \"32\", \"support\": 100, \"avg_response\": 33.97}, {\"feature_7\": \"78\", \"support\": 97, \"avg_response\": 32.93814432989691}, {\"feature_7\": \"48\", \"support\": 96, \"avg_response\": 30.447916666666668}, {\"feature_7\": \"81\", \"support\": 95, \"avg_response\": 30.53684210526316}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 5.28}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_ffde6eecd5041532/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_ffde6eecd5041532/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..9f07da847637cbd55ffd25245acb0b6c5f759cff
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_ffde6eecd5041532/run_manifest.json
@@ -0,0 +1,60 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T16:10:15.877148+00:00",
+  "ended_at": "2026-05-19T16:10:15.883162+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_ffde6eecd5041532",
+    "problem_id": "v2p_n9_e57314fedeadb9f8",
+    "dataset_id": "n9",
+    "template_id": "tpl_cardinality_high_card_response_stability",
+    "template_name": "High-Cardinality Response Stability",
+    "family_id": "cardinality_structure",
+    "canonical_subitem_id": "high_cardinality_response_stability",
+    "intended_facet_id": "target_cardinality_cross_section",
+    "variant_semantic_role": "focused_target_view",
+    "subitem_assignment_source": "template_fixed",
+    "source_kind": "deterministic",
+    "realization_mode": "deterministic",
+    "gate_priority": "deterministic",
+    "extended_family": true,
+    "question": "Use template High-Cardinality Response Stability to probe high_cardinality_response_stability with semantic role focused_target_view. Focus on measure_col=feature_1, key_col=feature_7.",
+    "bindings": {
+      "key_col": "feature_7",
+      "measure_col": "feature_1",
+      "min_support": 5
+    },
+    "binding_roles": [
+      "key_col",
+      "target_col"
+    ],
+    "coverage_target_min": "enumerate_all_applicable",
+    "runtime_sql_skeleton": "SELECT\n    {key_col},\n    COUNT(*) AS support,\n    AVG({measure_col}) AS avg_response\nFROM {table}\nGROUP BY {key_col}\nHAVING COUNT(*) >= {min_support}\nORDER BY support DESC, avg_response DESC;",
+    "notes": [
+      "default_facets=target_cardinality_cross_section",
+      "template_selection_mode=deterministic",
+      "problem_index_within_template=5",
+      "sql_variant_index=1/1"
+    ],
+    "template_selection_mode": "deterministic",
+    "selected_template_rank": 0,
+    "problem_index_within_template": 5,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_ffde6eecd5041532.sql",
+  "usage_summary": {
+    "engine": "template",
+    "input_tokens": 0,
+    "cached_input_tokens": 0,
+    "output_tokens": 0,
+    "total_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "none"
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_ffde6eecd5041532/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_ffde6eecd5041532/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_ffde6eecd5041532/usage_summary.json
@@ -0,0 +1,9 @@
+{
+  "engine": "template",
+  "input_tokens": 0,
+  "cached_input_tokens": 0,
+  "output_tokens": 0,
+  "total_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "none"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fff29ef63f9d7d5f/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fff29ef63f9d7d5f/final_answer.txt
new file mode 100644
index 0000000000000000000000000000000000000000..5c9fb4f506098082c9e5ee99cd0ee5254ace5a4c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fff29ef63f9d7d5f/final_answer.txt
@@ -0,0 +1 @@
+{"row_count": null, "preview_rows": [{"value_label": "0", "support": 1227, "support_share": 0.11162663755458516, "support_rank": 1}, {"value_label": "50", "support": 224, "support_share": 0.020378457059679767, "support_rank": 2}, {"value_label": "100", "support": 192, "support_share": 0.017467248908296942, "support_rank": 3}, {"value_label": "16", "support": 191, "support_share": 0.01737627365356623, "support_rank": 4}, {"value_label": "15", "support": 182, "support_share": 0.016557496360989812, "support_rank": 5}]}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fff29ef63f9d7d5f/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fff29ef63f9d7d5f/generated_sql.sql
new file mode 100644
index 0000000000000000000000000000000000000000..97c0156edbb93fdd68aa8b66221beee9b9ccf50e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fff29ef63f9d7d5f/generated_sql.sql
@@ -0,0 +1,25 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: support_concentration
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_cardinality_support_rank_profile
+-- query_record_id: v2q_n9_fff29ef63f9d7d5f
+-- problem_id: v2p_n9_05658db80fe1c3bc
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_12" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_12"
+)
+SELECT
+    value_label,
+    support,
+    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank
+FROM grouped
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fff29ef63f9d7d5f/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fff29ef63f9d7d5f/query_results.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..d6ef4e958cded1bc93420065e45823f05408226b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fff29ef63f9d7d5f/query_results.jsonl
@@ -0,0 +1 @@
+{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: n9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: support_rank_profile_consistency\n-- intended_facet_id: support_concentration\n-- variant_semantic_role: count_distribution\n-- template_id: tpl_cardinality_support_rank_profile\n-- query_record_id: v2q_n9_fff29ef63f9d7d5f\n-- problem_id: v2p_n9_05658db80fe1c3bc\n-- realization_mode: deterministic\n-- source_kind: deterministic\nWITH grouped AS (\n    SELECT \"feature_12\" AS value_label, COUNT(*) AS support\n    FROM \"n9\"\n    GROUP BY \"feature_12\"\n)\nSELECT\n    value_label,\n    support,\n    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\nFROM grouped\nORDER BY support DESC, value_label;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: n9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: support_rank_profile_consistency\\n-- intended_facet_id: support_concentration\\n-- variant_semantic_role: count_distribution\\n-- template_id: tpl_cardinality_support_rank_profile\\n-- query_record_id: v2q_n9_fff29ef63f9d7d5f\\n-- problem_id: v2p_n9_05658db80fe1c3bc\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nWITH grouped AS (\\n    SELECT \\\"feature_12\\\" AS value_label, COUNT(*) AS support\\n    FROM \\\"n9\\\"\\n    GROUP BY \\\"feature_12\\\"\\n)\\nSELECT\\n    value_label,\\n    support,\\n    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\\n    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\\nFROM grouped\\nORDER BY support DESC, value_label;\", \"columns\": [\"value_label\", \"support\", \"support_share\", \"support_rank\"], \"rows\": [{\"value_label\": \"0\", \"support\": 1227, \"support_share\": 0.11162663755458516, \"support_rank\": 1}, {\"value_label\": \"50\", \"support\": 224, \"support_share\": 0.020378457059679767, \"support_rank\": 2}, {\"value_label\": \"100\", \"support\": 192, \"support_share\": 0.017467248908296942, \"support_rank\": 3}, {\"value_label\": \"16\", \"support\": 191, \"support_share\": 0.01737627365356623, \"support_rank\": 4}, {\"value_label\": \"15\", \"support\": 182, \"support_share\": 0.016557496360989812, \"support_rank\": 5}, {\"value_label\": \"9\", \"support\": 168, \"support_share\": 0.015283842794759825, \"support_rank\": 6}, {\"value_label\": \"18\", \"support\": 167, \"support_share\": 0.015192867540029112, \"support_rank\": 7}, {\"value_label\": \"12\", \"support\": 161, \"support_share\": 0.014647016011644833, \"support_rank\": 8}, {\"value_label\": \"17\", \"support\": 161, \"support_share\": 0.014647016011644833, \"support_rank\": 9}, {\"value_label\": \"20\", \"support\": 156, \"support_share\": 0.014192139737991267, \"support_rank\": 10}, {\"value_label\": \"19\", \"support\": 155, \"support_share\": 0.014101164483260552, \"support_rank\": 11}, {\"value_label\": \"14\", \"support\": 154, \"support_share\": 0.01401018922852984, \"support_rank\": 12}, {\"value_label\": \"8\", \"support\": 154, \"support_share\": 0.01401018922852984, \"support_rank\": 13}, {\"value_label\": \"10\", \"support\": 153, \"support_share\": 0.013919213973799126, \"support_rank\": 14}, {\"value_label\": \"51\", \"support\": 152, \"support_share\": 0.013828238719068414, \"support_rank\": 15}, {\"value_label\": \"1\", \"support\": 149, \"support_share\": 0.013555312954876273, \"support_rank\": 16}, {\"value_label\": \"13\", \"support\": 147, \"support_share\": 0.013373362445414847, \"support_rank\": 17}, {\"value_label\": \"21\", \"support\": 147, \"support_share\": 0.013373362445414847, \"support_rank\": 18}, {\"value_label\": \"11\", \"support\": 145, \"support_share\": 0.01319141193595342, \"support_rank\": 19}, {\"value_label\": \"22\", \"support\": 138, \"support_share\": 0.012554585152838428, \"support_rank\": 20}, {\"value_label\": \"24\", \"support\": 138, \"support_share\": 0.012554585152838428, \"support_rank\": 21}, {\"value_label\": \"23\", \"support\": 137, \"support_share\": 0.012463609898107715, \"support_rank\": 22}, {\"value_label\": \"30\", \"support\": 135, \"support_share\": 0.012281659388646287, \"support_rank\": 23}, {\"value_label\": \"49\", \"support\": 135, \"support_share\": 0.012281659388646287, \"support_rank\": 24}, {\"value_label\": \"29\", \"support\": 130, \"support_share\": 0.011826783114992722, \"support_rank\": 25}, {\"value_label\": \"31\", \"support\": 130, \"support_share\": 0.011826783114992722, \"support_rank\": 26}, {\"value_label\": \"6\", \"support\": 130, \"support_share\": 0.011826783114992722, \"support_rank\": 27}, {\"value_label\": \"7\", \"support\": 128, \"support_share\": 0.011644832605531296, \"support_rank\": 28}, {\"value_label\": \"3\", \"support\": 127, \"support_share\": 0.011553857350800582, \"support_rank\": 29}, {\"value_label\": \"4\", \"support\": 126, \"support_share\": 0.01146288209606987, \"support_rank\": 30}, {\"value_label\": \"5\", \"support\": 126, \"support_share\": 0.01146288209606987, \"support_rank\": 31}, {\"value_label\": \"53\", \"support\": 125, \"support_share\": 0.011371906841339156, \"support_rank\": 32}, {\"value_label\": \"2\", \"support\": 121, \"support_share\": 0.011008005822416303, \"support_rank\": 33}, {\"value_label\": \"26\", \"support\": 121, \"support_share\": 0.011008005822416303, \"support_rank\": 34}, {\"value_label\": \"25\", \"support\": 120, \"support_share\": 0.010917030567685589, \"support_rank\": 35}, {\"value_label\": \"46\", \"support\": 120, \"support_share\": 0.010917030567685589, \"support_rank\": 36}, {\"value_label\": \"32\", \"support\": 119, \"support_share\": 0.010826055312954877, \"support_rank\": 37}, {\"value_label\": \"27\", \"support\": 117, \"support_share\": 0.01064410480349345, \"support_rank\": 38}, {\"value_label\": \"28\", \"support\": 117, \"support_share\": 0.01064410480349345, \"support_rank\": 39}, {\"value_label\": \"64\", \"support\": 115, \"support_share\": 0.010462154294032024, \"support_rank\": 40}, {\"value_label\": \"66\", \"support\": 115, \"support_share\": 0.010462154294032024, \"support_rank\": 41}, {\"value_label\": \"56\", \"support\": 113, \"support_share\": 0.010280203784570598, \"support_rank\": 42}, {\"value_label\": \"33\", \"support\": 110, \"support_share\": 0.010007278020378457, \"support_rank\": 43}, {\"value_label\": \"45\", \"support\": 108, \"support_share\": 0.009825327510917031, \"support_rank\": 44}, {\"value_label\": \"68\", \"support\": 107, \"support_share\": 0.009734352256186317, \"support_rank\": 45}, {\"value_label\": \"65\", \"support\": 104, \"support_share\": 0.009461426491994178, \"support_rank\": 46}, {\"value_label\": \"43\", \"support\": 103, \"support_share\": 0.009370451237263464, \"support_rank\": 47}, {\"value_label\": \"54\", \"support\": 103, \"support_share\": 0.009370451237263464, \"support_rank\": 48}, {\"value_label\": \"60\", \"support\": 103, \"support_share\": 0.009370451237263464, \"support_rank\": 49}, {\"value_label\": \"62\", \"support\": 103, \"support_share\": 0.009370451237263464, \"support_rank\": 50}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 4.65}"}
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fff29ef63f9d7d5f/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fff29ef63f9d7d5f/run_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..b53a3eb7725cdb94fd589c09c4fdaeb4662e7600
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fff29ef63f9d7d5f/run_manifest.json
@@ -0,0 +1,57 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n9",
+  "started_at": "2026-05-19T16:10:15.828872+00:00",
+  "ended_at": "2026-05-19T16:10:15.834325+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n9_fff29ef63f9d7d5f",
+    "problem_id": "v2p_n9_05658db80fe1c3bc",
+    "dataset_id": "n9",
+    "template_id": "tpl_cardinality_support_rank_profile",
+    "template_name": "Cardinality Support Rank Profile",
+    "family_id": "cardinality_structure",
+    "canonical_subitem_id": "support_rank_profile_consistency",
+    "intended_facet_id": "support_concentration",
+    "variant_semantic_role": "count_distribution",
+    "subitem_assignment_source": "template_fixed",
+    "source_kind": "deterministic",
+    "realization_mode": "deterministic",
+    "gate_priority": "deterministic",
+    "extended_family": true,
+    "question": "Use template Cardinality Support Rank Profile to probe support_rank_profile_consistency with semantic role count_distribution. Focus on group_col=feature_12.",
+    "bindings": {
+      "group_col": "feature_12"
+    },
+    "binding_roles": [
+      "group_col"
+    ],
+    "coverage_target_min": "enumerate_all_applicable",
+    "runtime_sql_skeleton": "WITH grouped AS (\n    SELECT {group_col} AS value_label, COUNT(*) AS support\n    FROM {table}\n    GROUP BY {group_col}\n)\nSELECT\n    value_label,\n    support,\n    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\nFROM grouped\nORDER BY support DESC, value_label;",
+    "notes": [
+      "default_facets=support_concentration,value_imbalance_profile",
+      "template_selection_mode=deterministic",
+      "problem_index_within_template=9",
+      "sql_variant_index=1/1"
+    ],
+    "template_selection_mode": "deterministic",
+    "selected_template_rank": 0,
+    "problem_index_within_template": 9,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_fff29ef63f9d7d5f.sql",
+  "usage_summary": {
+    "engine": "template",
+    "input_tokens": 0,
+    "cached_input_tokens": 0,
+    "output_tokens": 0,
+    "total_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "none"
+  }
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fff29ef63f9d7d5f/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fff29ef63f9d7d5f/usage_summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/artifacts/v2q_n9_fff29ef63f9d7d5f/usage_summary.json
@@ -0,0 +1,9 @@
+{
+  "engine": "template",
+  "input_tokens": 0,
+  "cached_input_tokens": 0,
+  "output_tokens": 0,
+  "total_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "none"
+}
\ No newline at end of file
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_0086d96e152bf87a.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_0086d96e152bf87a.sql
new file mode 100644
index 0000000000000000000000000000000000000000..295dbdcedaa4f7099822fc9c313916020fc9e978
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_0086d96e152bf87a.sql
@@ -0,0 +1,19 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_0086d96e152bf87a
+-- problem_id: v2p_n9_9842147e9bb0c023
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_16", "feature_2",
+       SUM(CAST("feature_1" AS REAL)) AS "total_measure",
+       SUM(CAST("feature_1" AS REAL)) * 100.0 / SUM(SUM(CAST("feature_1" AS REAL))) OVER (PARTITION BY "feature_16") AS "share_within_group"
+FROM "n9"
+GROUP BY "feature_16", "feature_2"
+ORDER BY "share_within_group" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_009274372ae62a75.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_009274372ae62a75.sql
new file mode 100644
index 0000000000000000000000000000000000000000..03f697071457eb8e9c15114cb55767be40fc6756
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_009274372ae62a75.sql
@@ -0,0 +1,23 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_set_consistency
+-- intended_facet_id: low_support_extremes
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_m4_quantile_tail_slice
+-- query_record_id: v2q_n9_009274372ae62a75
+-- problem_id: v2p_n9_a191fbf72222a3bd
+-- realization_mode: agent
+-- source_kind: agent
+WITH buckets AS (
+    SELECT
+        "feature_3",
+        NTILE(10) OVER (ORDER BY CAST("feature_3" AS INTEGER) DESC) AS tail_bucket
+    FROM "n9"
+)
+SELECT "feature_3"
+FROM buckets
+WHERE tail_bucket = 1
+ORDER BY CAST("feature_3" AS INTEGER) DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_0209729875e8a0e5.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_0209729875e8a0e5.sql
new file mode 100644
index 0000000000000000000000000000000000000000..2f824890474ada91c004eaeed0adbd6d923ed731
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_0209729875e8a0e5.sql
@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: within_group_proportion
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_0209729875e8a0e5
+-- problem_id: v2p_n9_9a370f3cc95b7209
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+  "feature_10",
+  "feature_12",
+  SUM(CAST("feature_11" AS REAL)) AS total_measure,
+  SUM(CAST("feature_11" AS REAL)) * 100.0 / NULLIF(SUM(SUM(CAST("feature_11" AS REAL))) OVER (PARTITION BY "feature_10"), 0) AS share_within_group
+FROM "n9"
+GROUP BY "feature_10", "feature_12"
+ORDER BY share_within_group DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_04c4c9066453fea0.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_04c4c9066453fea0.sql
new file mode 100644
index 0000000000000000000000000000000000000000..63d43ce9825cd708f3465495c73fc24c1b26ee14
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_04c4c9066453fea0.sql
@@ -0,0 +1,15 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_set_consistency
+-- intended_facet_id: low_support_extremes
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_threshold_rarity_cdf
+-- query_record_id: v2q_n9_04c4c9066453fea0
+-- problem_id: v2p_n9_82f2807f541ddc13
+-- realization_mode: agent
+-- source_kind: agent
+SELECT AVG(CASE WHEN CAST("feature_13" AS REAL) <= 68.0 THEN 1 ELSE 0 END) AS "empirical_cdf_at_threshold"
+FROM "n9";
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_052b0129b719c736.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_052b0129b719c736.sql
new file mode 100644
index 0000000000000000000000000000000000000000..928631b372d45173f95a4703fb5ec945e27ac69a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_052b0129b719c736.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_rank_order
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_n9_052b0129b719c736
+-- problem_id: v2p_n9_8ae7e1001b5fd4c5
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_7", SUM(CAST("feature_7" AS NUMERIC)) AS total_measure
+FROM "n9"
+GROUP BY "feature_7"
+ORDER BY total_measure DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_0646409f2deb6567.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_0646409f2deb6567.sql
new file mode 100644
index 0000000000000000000000000000000000000000..d2ac4297e7ca37a88796b7e6bae8c307fedb5d93
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_0646409f2deb6567.sql
@@ -0,0 +1,19 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_m4_group_condition_rate
+-- query_record_id: v2q_n9_0646409f2deb6567
+-- problem_id: v2p_n9_a0d445cb9abe6ba4
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+  "feature_1",
+  AVG(CASE WHEN "class" = '4' THEN 1.0 ELSE 0.0 END) AS "condition_rate"
+FROM "n9"
+GROUP BY "feature_1"
+ORDER BY "condition_rate" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_0b08cef145edec67.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_0b08cef145edec67.sql
new file mode 100644
index 0000000000000000000000000000000000000000..fc9a8ca9c8bdfde174ffb842fb9739216b0b4081
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_0b08cef145edec67.sql
@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: within_group_proportion
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_0b08cef145edec67
+-- problem_id: v2p_n9_1ff951ac51c8ade6
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+  "class",
+  "feature_3",
+  SUM(CAST("feature_2" AS REAL)) AS total_measure,
+  SUM(CAST("feature_2" AS REAL)) * 100.0 / SUM(SUM(CAST("feature_2" AS REAL))) OVER (PARTITION BY "class") AS share_within_group
+FROM "n9"
+GROUP BY "class", "feature_3"
+ORDER BY share_within_group DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_0ec4c3649d00fef8.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_0ec4c3649d00fef8.sql
new file mode 100644
index 0000000000000000000000000000000000000000..a5d04e1897798eacea07463d1af8b810b9bc4908
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_0ec4c3649d00fef8.sql
@@ -0,0 +1,19 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: within_group_proportion
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_0ec4c3649d00fef8
+-- problem_id: v2p_n9_c05389dab1ffac79
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_12", "feature_14",
+       SUM(CAST("feature_13" AS REAL)) AS total_measure,
+       SUM(CAST("feature_13" AS REAL)) * 100.0 / SUM(SUM(CAST("feature_13" AS REAL))) OVER (PARTITION BY "feature_12") AS share_within_group
+FROM "n9"
+GROUP BY "feature_12", "feature_14"
+ORDER BY share_within_group DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_109b942301d57cc9.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_109b942301d57cc9.sql
new file mode 100644
index 0000000000000000000000000000000000000000..9f9abe2b5c30db646842a180fa50dc0b41fcb14b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_109b942301d57cc9.sql
@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: high_cardinality_response_stability
+-- intended_facet_id: target_cardinality_cross_section
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_cardinality_high_card_response_stability
+-- query_record_id: v2q_n9_109b942301d57cc9
+-- problem_id: v2p_n9_4183abcb61c06446
+-- realization_mode: deterministic
+-- source_kind: deterministic
+SELECT
+    "feature_10",
+    COUNT(*) AS support,
+    AVG("feature_4") AS avg_response
+FROM "n9"
+GROUP BY "feature_10"
+HAVING COUNT(*) >= 5.0
+ORDER BY support DESC, avg_response DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_116f8ea312eb3030.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_116f8ea312eb3030.sql
new file mode 100644
index 0000000000000000000000000000000000000000..0b7558a592c37c55eec4b79b82c5cdecfb5b8ab5
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_116f8ea312eb3030.sql
@@ -0,0 +1,19 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_116f8ea312eb3030
+-- problem_id: v2p_n9_4f66528703683d39
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_15", "feature_1",
+       SUM(CAST("feature_16" AS REAL)) AS total_measure,
+       SUM(CAST("feature_16" AS REAL)) * 100.0 / SUM(SUM(CAST("feature_16" AS REAL))) OVER (PARTITION BY "feature_15") AS share_within_group
+FROM "n9"
+GROUP BY "feature_15", "feature_1"
+ORDER BY share_within_group DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_1197e7ba4c25c482.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_1197e7ba4c25c482.sql
new file mode 100644
index 0000000000000000000000000000000000000000..cbcbb2bc4411b41796d885a84925f2903a19cc93
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_1197e7ba4c25c482.sql
@@ -0,0 +1,25 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: support_concentration
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_cardinality_support_rank_profile
+-- query_record_id: v2q_n9_1197e7ba4c25c482
+-- problem_id: v2p_n9_0ceefa077675b5fb
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_3" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_3"
+)
+SELECT
+    value_label,
+    support,
+    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank
+FROM grouped
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_11aceec600252d5a.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_11aceec600252d5a.sql
new file mode 100644
index 0000000000000000000000000000000000000000..dcb48a35ceb5f0f2ce49e2e0d118c20c4616a72e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_11aceec600252d5a.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_rank_order
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_n9_11aceec600252d5a
+-- problem_id: v2p_n9_a8304f590c0be129
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_2", SUM(CAST("feature_2" AS REAL)) AS total_measure
+FROM "n9"
+GROUP BY "feature_2"
+ORDER BY total_measure DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_12f479947839f0dd.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_12f479947839f0dd.sql
new file mode 100644
index 0000000000000000000000000000000000000000..a71f5320763c26f3855bc993ab5823e58c047ba4
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_12f479947839f0dd.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_rank_order
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_n9_12f479947839f0dd
+-- problem_id: v2p_n9_09277f354cf026dc
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_5", SUM(CAST("feature_5" AS NUMERIC)) AS "total_measure"
+FROM "n9"
+GROUP BY "feature_5"
+ORDER BY "total_measure" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_14fa517d5e4edab1.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_14fa517d5e4edab1.sql
new file mode 100644
index 0000000000000000000000000000000000000000..f887e3852a0e0aed98f983fa972a618281b52b64
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_14fa517d5e4edab1.sql
@@ -0,0 +1,25 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: value_imbalance_profile
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_cardinality_support_rank_profile
+-- query_record_id: v2q_n9_14fa517d5e4edab1
+-- problem_id: v2p_n9_1b9cdc6ddc514908
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_10" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_10"
+)
+SELECT
+    value_label,
+    support,
+    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank
+FROM grouped
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_15678180ad917562.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_15678180ad917562.sql
new file mode 100644
index 0000000000000000000000000000000000000000..99c0dca2f19a25bc8bb11fbf27a0be98d7270f32
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_15678180ad917562.sql
@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: within_group_proportion
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_15678180ad917562
+-- problem_id: v2p_n9_9f46d1163eb14383
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+  "feature_1",
+  "feature_4",
+  SUM(CAST("feature_3" AS REAL)) AS total_measure,
+  SUM(CAST("feature_3" AS REAL)) * 100.0 / SUM(SUM(CAST("feature_3" AS REAL))) OVER (PARTITION BY "feature_1") AS share_within_group
+FROM "n9"
+GROUP BY "feature_1", "feature_4"
+ORDER BY share_within_group DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_16992fe8afda9285.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_16992fe8afda9285.sql
new file mode 100644
index 0000000000000000000000000000000000000000..457faa5cf0e6b82f9f797a01155b0bf26b56ac85
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_16992fe8afda9285.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_conditional_contrast
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_n9_16992fe8afda9285
+-- problem_id: v2p_n9_b9db580638f46b9a
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_3", SUM(CAST("feature_3" AS NUMERIC)) AS "total_measure"
+FROM "n9"
+GROUP BY "feature_3"
+ORDER BY "total_measure" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_1b9ae5269fe39f86.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_1b9ae5269fe39f86.sql
new file mode 100644
index 0000000000000000000000000000000000000000..96fd9dbed78cbb83d0bac69cbc2bdf756ccb5d4b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_1b9ae5269fe39f86.sql
@@ -0,0 +1,28 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: support_concentration
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_cardinality_distinct_share_profile
+-- query_record_id: v2q_n9_1b9ae5269fe39f86
+-- problem_id: v2p_n9_ecfeb614d88ae66e
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_9" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_9"
+), ranked AS (
+    SELECT
+        value_label,
+        support,
+        CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+        SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support
+    FROM grouped
+)
+SELECT *
+FROM ranked
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_1d9d55c5f7ad11f7.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_1d9d55c5f7ad11f7.sql
new file mode 100644
index 0000000000000000000000000000000000000000..3cf8dde43a6c02cc51d58cc9ea973ba99fbefa70
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_1d9d55c5f7ad11f7.sql
@@ -0,0 +1,26 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: filtered_stable_view
+-- template_id: tpl_tpch_relative_total_threshold
+-- query_record_id: v2q_n9_1d9d55c5f7ad11f7
+-- problem_id: v2p_n9_ce269b9d7d7d7ee3
+-- realization_mode: agent
+-- source_kind: agent
+WITH "grouped" AS (
+  SELECT "feature_11", SUM(CAST("feature_15" AS REAL)) AS "group_value"
+  FROM "n9"
+  GROUP BY "feature_11"
+), "total" AS (
+  SELECT SUM("group_value") AS "total_value"
+  FROM "grouped"
+)
+SELECT g."feature_11", g."group_value"
+FROM "grouped" AS g
+CROSS JOIN "total" AS t
+WHERE g."group_value" > t."total_value" * 0.05
+ORDER BY g."group_value" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_1de89bcde10c70dc.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_1de89bcde10c70dc.sql
new file mode 100644
index 0000000000000000000000000000000000000000..dfcf53b4ac8740d94688d3c27047e5e8ea183cc8
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_1de89bcde10c70dc.sql
@@ -0,0 +1,23 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_set_consistency
+-- intended_facet_id: low_support_extremes
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_m4_quantile_tail_slice
+-- query_record_id: v2q_n9_1de89bcde10c70dc
+-- problem_id: v2p_n9_757df9b92e4481d2
+-- realization_mode: agent
+-- source_kind: agent
+WITH "buckets" AS (
+  SELECT
+    "feature_13",
+    NTILE(10) OVER (ORDER BY CAST("feature_13" AS REAL) DESC) AS "tail_bucket"
+  FROM "n9"
+)
+SELECT "feature_13"
+FROM "buckets"
+WHERE "tail_bucket" = 1
+ORDER BY CAST("feature_13" AS REAL) DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_1e382e099d2383ee.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_1e382e099d2383ee.sql
new file mode 100644
index 0000000000000000000000000000000000000000..8ac810064794f339cf1c5867718d2d54141b933d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_1e382e099d2383ee.sql
@@ -0,0 +1,30 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_tpch_relative_total_threshold
+-- query_record_id: v2q_n9_1e382e099d2383ee
+-- problem_id: v2p_n9_e67bf7a36da9c605
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+    SELECT
+        "feature_13" AS "feature_13",
+        SUM(CAST("feature_1" AS REAL)) AS "group_value"
+    FROM "n9"
+    GROUP BY "feature_13"
+), total AS (
+    SELECT SUM("group_value") AS "total_value"
+    FROM grouped
+)
+SELECT
+    g."feature_13",
+    g."group_value"
+FROM grouped AS g
+CROSS JOIN total AS t
+WHERE g."group_value" > t."total_value" * 0.1
+ORDER BY g."group_value" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_1fa4c76f4bdb935b.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_1fa4c76f4bdb935b.sql
new file mode 100644
index 0000000000000000000000000000000000000000..7eebde61a6b17d06e2ce93fc273cf67d598802a6
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_1fa4c76f4bdb935b.sql
@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: high_cardinality_response_stability
+-- intended_facet_id: target_cardinality_cross_section
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_cardinality_high_card_response_stability
+-- query_record_id: v2q_n9_1fa4c76f4bdb935b
+-- problem_id: v2p_n9_92658bd5eff418fe
+-- realization_mode: deterministic
+-- source_kind: deterministic
+SELECT
+    "feature_8",
+    COUNT(*) AS support,
+    AVG("feature_2") AS avg_response
+FROM "n9"
+GROUP BY "feature_8"
+HAVING COUNT(*) >= 5.0
+ORDER BY support DESC, avg_response DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_224c71ff82b3fc3e.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_224c71ff82b3fc3e.sql
new file mode 100644
index 0000000000000000000000000000000000000000..e4f57083c64e4064d805204f4aee35cb73f2f980
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_224c71ff82b3fc3e.sql
@@ -0,0 +1,25 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: support_concentration
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_cardinality_support_rank_profile
+-- query_record_id: v2q_n9_224c71ff82b3fc3e
+-- problem_id: v2p_n9_134d94fea1d09454
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_1" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_1"
+)
+SELECT
+    value_label,
+    support,
+    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank
+FROM grouped
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_24a76703e0bafdaa.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_24a76703e0bafdaa.sql
new file mode 100644
index 0000000000000000000000000000000000000000..bf3476d6d8a3cbacbeacc358026f880e68241ed7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_24a76703e0bafdaa.sql
@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: high_cardinality_response_stability
+-- intended_facet_id: target_cardinality_cross_section
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_cardinality_high_card_response_stability
+-- query_record_id: v2q_n9_24a76703e0bafdaa
+-- problem_id: v2p_n9_e394315734e8a730
+-- realization_mode: deterministic
+-- source_kind: deterministic
+SELECT
+    "feature_9",
+    COUNT(*) AS support,
+    AVG("feature_3") AS avg_response
+FROM "n9"
+GROUP BY "feature_9"
+HAVING COUNT(*) >= 5.0
+ORDER BY support DESC, avg_response DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_25b0aadec309ff77.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_25b0aadec309ff77.sql
new file mode 100644
index 0000000000000000000000000000000000000000..90ed82ab9a91566a595cb168b07cbfe355e39a12
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_25b0aadec309ff77.sql
@@ -0,0 +1,63 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_n9_25b0aadec309ff77
+-- problem_id: v2p_n9_e84476588734dd18
+-- realization_mode: agent
+-- source_kind: agent
+WITH "ordered" AS (
+  SELECT
+    "feature_9" AS "feature_9",
+    CAST("feature_14" AS REAL) AS "measure",
+    ROW_NUMBER() OVER (
+      PARTITION BY "feature_9"
+      ORDER BY CAST("feature_14" AS REAL)
+    ) AS "rn",
+    COUNT(*) OVER (
+      PARTITION BY "feature_9"
+    ) AS "cnt"
+  FROM "n9"
+  WHERE "feature_9" IS NOT NULL
+    AND "feature_14" IS NOT NULL
+),
+"params" AS (
+  SELECT
+    "feature_9",
+    "cnt",
+    (1.0 + 0.9 * ("cnt" - 1)) AS "pos",
+    CAST((1.0 + 0.9 * ("cnt" - 1)) AS INTEGER) AS "lower_rn",
+    CASE
+      WHEN ABS((1.0 + 0.9 * ("cnt" - 1)) - CAST((1.0 + 0.9 * ("cnt" - 1)) AS INTEGER)) < 1e-12
+        THEN CAST((1.0 + 0.9 * ("cnt" - 1)) AS INTEGER)
+      ELSE CAST((1.0 + 0.9 * ("cnt" - 1)) AS INTEGER) + 1
+    END AS "upper_rn"
+  FROM "ordered"
+  GROUP BY "feature_9", "cnt"
+),
+"bounds" AS (
+  SELECT
+    p."feature_9" AS "feature_9",
+    p."pos" AS "pos",
+    p."lower_rn" AS "lower_rn",
+    p."upper_rn" AS "upper_rn",
+    MAX(CASE WHEN o."rn" = p."lower_rn" THEN o."measure" END) AS "lower_val",
+    MAX(CASE WHEN o."rn" = p."upper_rn" THEN o."measure" END) AS "upper_val"
+  FROM "params" AS p
+  JOIN "ordered" AS o
+    ON o."feature_9" = p."feature_9"
+  GROUP BY p."feature_9", p."pos", p."lower_rn", p."upper_rn"
+)
+SELECT
+  "feature_9",
+  CASE
+    WHEN "lower_rn" = "upper_rn" THEN "lower_val"
+    ELSE "lower_val" + ("pos" - "lower_rn") * ("upper_val" - "lower_val")
+  END AS "percentile_measure"
+FROM "bounds"
+ORDER BY "percentile_measure" DESC, CAST("feature_9" AS REAL) ASC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_26d46d9a01d4e949.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_26d46d9a01d4e949.sql
new file mode 100644
index 0000000000000000000000000000000000000000..14e61b862924141e6bf3dab55e879b3a54322fdf
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_26d46d9a01d4e949.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_n9_26d46d9a01d4e949
+-- problem_id: v2p_n9_58e5ab15cb8eb9ac
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_3", SUM(CAST("feature_3" AS REAL)) AS "total_measure"
+FROM "n9"
+GROUP BY "feature_3"
+ORDER BY "total_measure" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_2727e77385815a8a.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_2727e77385815a8a.sql
new file mode 100644
index 0000000000000000000000000000000000000000..96959ee2ab4170ad4fc176d45cb8a875fec2b292
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_2727e77385815a8a.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_n9_2727e77385815a8a
+-- problem_id: v2p_n9_8a0557d6f0befbd2
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_1", SUM(CAST("feature_1" AS REAL)) AS total_measure
+FROM "n9"
+GROUP BY "feature_1"
+ORDER BY total_measure DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_292f1052ac11dc32.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_292f1052ac11dc32.sql
new file mode 100644
index 0000000000000000000000000000000000000000..95f116091899dbc60e247f7d8bffe18ad5c2a3bf
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_292f1052ac11dc32.sql
@@ -0,0 +1,22 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_set_consistency
+-- intended_facet_id: low_support_extremes
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_m4_quantile_tail_slice
+-- query_record_id: v2q_n9_292f1052ac11dc32
+-- problem_id: v2p_n9_ec4420756e1917a2
+-- realization_mode: agent
+-- source_kind: agent
+WITH buckets AS (
+    SELECT "feature_5",
+           NTILE(10) OVER (ORDER BY CAST("feature_5" AS REAL) DESC) AS tail_bucket
+    FROM "n9"
+)
+SELECT "feature_5"
+FROM buckets
+WHERE tail_bucket = 1
+ORDER BY CAST("feature_5" AS REAL) DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_2a42db73da155156.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_2a42db73da155156.sql
new file mode 100644
index 0000000000000000000000000000000000000000..a161bc627dee381bd90e4cbe50ac24e2ff397047
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_2a42db73da155156.sql
@@ -0,0 +1,25 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: value_imbalance_profile
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_cardinality_support_rank_profile
+-- query_record_id: v2q_n9_2a42db73da155156
+-- problem_id: v2p_n9_9ee2c1440008eb6e
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_2" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_2"
+)
+SELECT
+    value_label,
+    support,
+    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank
+FROM grouped
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_2aff9828b186d1e8.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_2aff9828b186d1e8.sql
new file mode 100644
index 0000000000000000000000000000000000000000..d99d5fc3891ca57f9946a841736c83dfa744428a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_2aff9828b186d1e8.sql
@@ -0,0 +1,30 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: filtered_stable_view
+-- template_id: tpl_tpch_relative_total_threshold
+-- query_record_id: v2q_n9_2aff9828b186d1e8
+-- problem_id: v2p_n9_ff0e3bce9e2b88ce
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+  SELECT
+    "feature_7" AS "feature_7",
+    SUM(CAST("feature_11" AS REAL)) AS group_value
+  FROM "n9"
+  GROUP BY "feature_7"
+), total AS (
+  SELECT SUM(group_value) AS total_value
+  FROM grouped
+)
+SELECT
+  g."feature_7",
+  g.group_value
+FROM grouped AS g
+CROSS JOIN total AS t
+WHERE g.group_value > t.total_value * 0.05
+ORDER BY g.group_value DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_2b75aa0b8aa3bfb7.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_2b75aa0b8aa3bfb7.sql
new file mode 100644
index 0000000000000000000000000000000000000000..012b4d13c8c143f898b6da99d9726016d936a078
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_2b75aa0b8aa3bfb7.sql
@@ -0,0 +1,67 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_n9_2b75aa0b8aa3bfb7
+-- problem_id: v2p_n9_ddd723ae4bfdc109
+-- realization_mode: agent
+-- source_kind: agent
+WITH "ordered" AS (
+  SELECT
+    "feature_4",
+    CAST("feature_9" AS REAL) AS "measure",
+    ROW_NUMBER() OVER (
+      PARTITION BY "feature_4"
+      ORDER BY CAST("feature_9" AS REAL)
+    ) AS "rn",
+    COUNT(*) OVER (PARTITION BY "feature_4") AS "cnt"
+  FROM "n9"
+  WHERE "feature_4" IS NOT NULL
+    AND "feature_9" IS NOT NULL
+),
+"positions" AS (
+  SELECT DISTINCT
+    "feature_4",
+    "cnt",
+    (0.95 * ("cnt" - 1)) + 1.0 AS "pos",
+    CAST((0.95 * ("cnt" - 1)) + 1.0 AS INT) AS "lower_rn",
+    CAST((0.95 * ("cnt" - 1)) + 1.0 AS INT) +
+      CASE
+        WHEN ((0.95 * ("cnt" - 1)) + 1.0) > CAST((0.95 * ("cnt" - 1)) + 1.0 AS INT) THEN 1
+        ELSE 0
+      END AS "upper_rn"
+  FROM "ordered"
+),
+"bounds" AS (
+  SELECT
+    "p"."feature_4",
+    "p"."cnt",
+    "p"."pos",
+    "p"."lower_rn",
+    "p"."upper_rn",
+    MAX(CASE WHEN "o"."rn" = "p"."lower_rn" THEN "o"."measure" END) AS "lower_val",
+    MAX(CASE WHEN "o"."rn" = "p"."upper_rn" THEN "o"."measure" END) AS "upper_val"
+  FROM "positions" AS "p"
+  JOIN "ordered" AS "o"
+    ON "o"."feature_4" = "p"."feature_4"
+  GROUP BY
+    "p"."feature_4",
+    "p"."cnt",
+    "p"."pos",
+    "p"."lower_rn",
+    "p"."upper_rn"
+)
+SELECT
+  "feature_4",
+  CASE
+    WHEN "lower_rn" = "upper_rn" THEN "lower_val"
+    ELSE "lower_val" + ("pos" - "lower_rn") * ("upper_val" - "lower_val")
+  END AS "percentile_measure"
+FROM "bounds"
+WHERE "cnt" >= 5
+ORDER BY "percentile_measure" DESC, "feature_4";
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_2b9fdf6c69110044.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_2b9fdf6c69110044.sql
new file mode 100644
index 0000000000000000000000000000000000000000..ff4a56e5e7adf67282c990a6178b0bce7561b47c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_2b9fdf6c69110044.sql
@@ -0,0 +1,31 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: filtered_stable_view
+-- template_id: tpl_tpch_relative_total_threshold
+-- query_record_id: v2q_n9_2b9fdf6c69110044
+-- problem_id: v2p_n9_8a470b367eca46d6
+-- realization_mode: agent
+-- source_kind: agent
+WITH "grouped" AS (
+    SELECT
+        "feature_8",
+        SUM(CAST("feature_12" AS REAL)) AS "group_value"
+    FROM "n9"
+    GROUP BY "feature_8"
+),
+"total" AS (
+    SELECT SUM("group_value") AS "total_value"
+    FROM "grouped"
+)
+SELECT
+    g."feature_8",
+    g."group_value"
+FROM "grouped" AS g
+CROSS JOIN "total" AS t
+WHERE g."group_value" > t."total_value" * 0.1
+ORDER BY g."group_value" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_2ddfcbc7fbc591ce.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_2ddfcbc7fbc591ce.sql
new file mode 100644
index 0000000000000000000000000000000000000000..7f8e0c76c7052a585a0734aaa49f8f95c3e03201
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_2ddfcbc7fbc591ce.sql
@@ -0,0 +1,18 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: within_group_proportion
+-- template_id: tpl_m4_group_condition_rate
+-- query_record_id: v2q_n9_2ddfcbc7fbc591ce
+-- problem_id: v2p_n9_4890d40ecfa213bf
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_14",
+       AVG(CASE WHEN "class" = '2' THEN 1 ELSE 0 END) AS condition_rate
+FROM "n9"
+GROUP BY "feature_14"
+ORDER BY condition_rate DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_2eb311778966c44b.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_2eb311778966c44b.sql
new file mode 100644
index 0000000000000000000000000000000000000000..b1c6ce623a7736ad1a6e22638e8959a62e164684
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_2eb311778966c44b.sql
@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: high_cardinality_response_stability
+-- intended_facet_id: target_cardinality_cross_section
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_cardinality_high_card_response_stability
+-- query_record_id: v2q_n9_2eb311778966c44b
+-- problem_id: v2p_n9_0dade8db54cf6323
+-- realization_mode: deterministic
+-- source_kind: deterministic
+SELECT
+    "feature_15",
+    COUNT(*) AS support,
+    AVG("feature_4") AS avg_response
+FROM "n9"
+GROUP BY "feature_15"
+HAVING COUNT(*) >= 5.0
+ORDER BY support DESC, avg_response DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_32a48e1986c6d0a7.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_32a48e1986c6d0a7.sql
new file mode 100644
index 0000000000000000000000000000000000000000..4205c8adc550fcf4b3830dcad5912a924672d646
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_32a48e1986c6d0a7.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: subgroup_size_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_clickbench_group_count
+-- query_record_id: v2q_n9_32a48e1986c6d0a7
+-- problem_id: v2p_n9_a23486fcb3be17ad
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_2", COUNT(*) AS "row_count"
+FROM "n9"
+GROUP BY "feature_2"
+ORDER BY "row_count" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_32cf6aceee145bc7.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_32cf6aceee145bc7.sql
new file mode 100644
index 0000000000000000000000000000000000000000..02205a62b0917e418174be6450261d5d12275f70
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_32cf6aceee145bc7.sql
@@ -0,0 +1,15 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_set_consistency
+-- intended_facet_id: low_support_extremes
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_threshold_rarity_cdf
+-- query_record_id: v2q_n9_32cf6aceee145bc7
+-- problem_id: v2p_n9_96b36133cbdcb376
+-- realization_mode: agent
+-- source_kind: agent
+SELECT AVG(CASE WHEN CAST("feature_2" AS REAL) <= 100.0 THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold
+FROM "n9";
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_3686b40feb657bbe.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_3686b40feb657bbe.sql
new file mode 100644
index 0000000000000000000000000000000000000000..d72e00db6596a205417929321343572d2e036ae8
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_3686b40feb657bbe.sql
@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: within_group_proportion
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_3686b40feb657bbe
+-- problem_id: v2p_n9_dc29dcc2aa48ba35
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+  "feature_11",
+  "feature_13",
+  SUM(CAST("feature_12" AS REAL)) AS total_measure,
+  SUM(CAST("feature_12" AS REAL)) * 100.0 / NULLIF(SUM(SUM(CAST("feature_12" AS REAL))) OVER (PARTITION BY "feature_11"), 0) AS share_within_group
+FROM "n9"
+GROUP BY "feature_11", "feature_13"
+ORDER BY share_within_group DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_374881bc7d737e13.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_374881bc7d737e13.sql
new file mode 100644
index 0000000000000000000000000000000000000000..8b611de9828ab0ad271c6385127ba5037c98b791
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_374881bc7d737e13.sql
@@ -0,0 +1,20 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_tail_low_support_group_count_v2
+-- query_record_id: v2q_n9_374881bc7d737e13
+-- problem_id: v2p_n9_f9eb830d199de719
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+    "feature_7",
+    COUNT(*) AS "support"
+FROM "n9"
+GROUP BY "feature_7"
+ORDER BY "support" ASC, "feature_7"
+LIMIT 10;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_39cf333bfd031134.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_39cf333bfd031134.sql
new file mode 100644
index 0000000000000000000000000000000000000000..66675c3385cf2386babb04db4cfcbcbbfd4ae16c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_39cf333bfd031134.sql
@@ -0,0 +1,26 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_tpch_relative_total_threshold
+-- query_record_id: v2q_n9_39cf333bfd031134
+-- problem_id: v2p_n9_33c289b5e959e2e7
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+    SELECT "feature_10", SUM(CAST("feature_14" AS REAL)) AS group_value
+    FROM "n9"
+    GROUP BY "feature_10"
+), total AS (
+    SELECT SUM(group_value) AS total_value
+    FROM grouped
+)
+SELECT g."feature_10", g.group_value
+FROM grouped AS g
+CROSS JOIN total AS t
+WHERE g.group_value > t.total_value * 0.05
+ORDER BY g.group_value DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_3aaae6312f854d6a.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_3aaae6312f854d6a.sql
new file mode 100644
index 0000000000000000000000000000000000000000..e6dd58b4ffa7bb0d034704c959047c1c455049e8
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_3aaae6312f854d6a.sql
@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: high_cardinality_response_stability
+-- intended_facet_id: target_cardinality_cross_section
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_cardinality_high_card_response_stability
+-- query_record_id: v2q_n9_3aaae6312f854d6a
+-- problem_id: v2p_n9_d42b7297acf44215
+-- realization_mode: deterministic
+-- source_kind: deterministic
+SELECT
+    "feature_2",
+    COUNT(*) AS support,
+    AVG("feature_4") AS avg_response
+FROM "n9"
+GROUP BY "feature_2"
+HAVING COUNT(*) >= 5.0
+ORDER BY support DESC, avg_response DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_3c78db7d546d3bfe.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_3c78db7d546d3bfe.sql
new file mode 100644
index 0000000000000000000000000000000000000000..dced1ce6c29b00ddf712ec2eaa395c065120889c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_3c78db7d546d3bfe.sql
@@ -0,0 +1,47 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_n9_3c78db7d546d3bfe
+-- problem_id: v2p_n9_a22bd9a0346beff4
+-- realization_mode: agent
+-- source_kind: agent
+WITH "ranked" AS (
+  SELECT
+    "feature_6",
+    CAST("feature_11" AS REAL) AS "measure_value",
+    ROW_NUMBER() OVER (
+      PARTITION BY "feature_6"
+      ORDER BY CAST("feature_11" AS REAL)
+    ) AS "rn",
+    COUNT(*) OVER (
+      PARTITION BY "feature_6"
+    ) AS "cnt"
+  FROM "n9"
+  WHERE "feature_6" IS NOT NULL
+    AND "feature_11" IS NOT NULL
+),
+"target_rows" AS (
+  SELECT
+    "feature_6",
+    "measure_value",
+    "rn",
+    "cnt",
+    CAST((0.95 * "cnt") AS INTEGER) +
+      CASE
+        WHEN (0.95 * "cnt") > CAST((0.95 * "cnt") AS INTEGER) THEN 1
+        ELSE 0
+      END AS "target_rn"
+  FROM "ranked"
+)
+SELECT
+  "feature_6",
+  "measure_value" AS "percentile_measure"
+FROM "target_rows"
+WHERE "rn" = "target_rn"
+ORDER BY "percentile_measure" DESC, "feature_6";
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_3e5ea197b14f256d.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_3e5ea197b14f256d.sql
new file mode 100644
index 0000000000000000000000000000000000000000..76dd15611683e27544aa5ad721dcb1b6901c74bc
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_3e5ea197b14f256d.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_conditional_contrast
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_n9_3e5ea197b14f256d
+-- problem_id: v2p_n9_6b3639abfed850a8
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_6", SUM(CAST("feature_6" AS NUMERIC)) AS total_measure
+FROM "n9"
+GROUP BY "feature_6"
+ORDER BY total_measure DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_3e7e9ca7687ee50b.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_3e7e9ca7687ee50b.sql
new file mode 100644
index 0000000000000000000000000000000000000000..9467da14ada137c6ba4de5f85e79a2ee1d718529
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_3e7e9ca7687ee50b.sql
@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: within_group_proportion
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_3e7e9ca7687ee50b
+-- problem_id: v2p_n9_8f10f270ae73308c
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+  "feature_14",
+  "feature_16",
+  SUM(CAST("feature_15" AS REAL)) AS total_measure,
+  SUM(CAST("feature_15" AS REAL)) * 100.0 / SUM(SUM(CAST("feature_15" AS REAL))) OVER (PARTITION BY "feature_14") AS share_within_group
+FROM "n9"
+GROUP BY "feature_14", "feature_16"
+ORDER BY share_within_group DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_4071f2dee311e284.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_4071f2dee311e284.sql
new file mode 100644
index 0000000000000000000000000000000000000000..673f3c1be72608887945696f259df67564c9d47e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_4071f2dee311e284.sql
@@ -0,0 +1,20 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_tail_low_support_group_count_v2
+-- query_record_id: v2q_n9_4071f2dee311e284
+-- problem_id: v2p_n9_9b771978c46c4bef
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+    "feature_3",
+    COUNT(*) AS "support"
+FROM "n9"
+GROUP BY "feature_3"
+ORDER BY "support" ASC, "feature_3"
+LIMIT 16;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_412e5289d0794c43.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_412e5289d0794c43.sql
new file mode 100644
index 0000000000000000000000000000000000000000..5ec9e94accb0c44930f22265294286cca8b8f7fe
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_412e5289d0794c43.sql
@@ -0,0 +1,28 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: support_concentration
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_cardinality_distinct_share_profile
+-- query_record_id: v2q_n9_412e5289d0794c43
+-- problem_id: v2p_n9_855c65ff05382b46
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_12" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_12"
+), ranked AS (
+    SELECT
+        value_label,
+        support,
+        CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+        SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support
+    FROM grouped
+)
+SELECT *
+FROM ranked
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_422a1de8e51993a5.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_422a1de8e51993a5.sql
new file mode 100644
index 0000000000000000000000000000000000000000..509a3cd163e8a299445088ce6c245096d11e9cfe
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_422a1de8e51993a5.sql
@@ -0,0 +1,26 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: filtered_stable_view
+-- template_id: tpl_tpch_relative_total_threshold
+-- query_record_id: v2q_n9_422a1de8e51993a5
+-- problem_id: v2p_n9_10d74a2661374c73
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+  SELECT "feature_9", SUM(CAST("feature_13" AS REAL)) AS group_value
+  FROM "n9"
+  GROUP BY "feature_9"
+), total AS (
+  SELECT SUM(group_value) AS total_value
+  FROM grouped
+)
+SELECT g."feature_9", g.group_value
+FROM grouped AS g
+CROSS JOIN total AS t
+WHERE g.group_value > t.total_value * 0.05
+ORDER BY g.group_value DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_43313e963e22625a.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_43313e963e22625a.sql
new file mode 100644
index 0000000000000000000000000000000000000000..d6c403f7fedc795524ba49b81f3208deb1f8c5bf
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_43313e963e22625a.sql
@@ -0,0 +1,24 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: direction_consistency
+-- intended_facet_id: conditional_rate_shift
+-- variant_semantic_role: contrastive_conditional_view
+-- template_id: tpl_m4_group_ratio_two_conditions
+-- query_record_id: v2q_n9_43313e963e22625a
+-- problem_id: v2p_n9_b1a0e91fe9b25707
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+    SELECT "feature_3",
+           SUM(CASE WHEN "class" = '2' THEN 1 ELSE 0 END) AS numerator_count,
+           SUM(CASE WHEN "class" = '4' THEN 1 ELSE 0 END) AS denominator_count
+    FROM "n9"
+    GROUP BY "feature_3"
+)
+SELECT "feature_3",
+       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio
+FROM grouped
+ORDER BY condition_ratio DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_45c63e1f77f22194.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_45c63e1f77f22194.sql
new file mode 100644
index 0000000000000000000000000000000000000000..335fb005b9f46c47697da59ac6fd0b6adb064e5e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_45c63e1f77f22194.sql
@@ -0,0 +1,20 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_set_consistency
+-- intended_facet_id: low_support_extremes
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_tail_low_support_group_count_v2
+-- query_record_id: v2q_n9_45c63e1f77f22194
+-- problem_id: v2p_n9_720d0f7618ed1cc6
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+    "feature_6",
+    COUNT(*) AS "support"
+FROM "n9"
+GROUP BY "feature_6"
+ORDER BY "support" ASC, "feature_6"
+LIMIT 14;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_49e2f541fc7596a2.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_49e2f541fc7596a2.sql
new file mode 100644
index 0000000000000000000000000000000000000000..dd7d9cca2728f41ef1afe3ff66abe0a142c2ec41
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_49e2f541fc7596a2.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: subgroup_size_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_clickbench_group_count
+-- query_record_id: v2q_n9_49e2f541fc7596a2
+-- problem_id: v2p_n9_636f98d40bd047c2
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_13", COUNT(*) AS row_count
+FROM "n9"
+GROUP BY "feature_13"
+ORDER BY row_count DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_4ae578da22c929d1.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_4ae578da22c929d1.sql
new file mode 100644
index 0000000000000000000000000000000000000000..43a0f5af37329d6723abd0f799291902d8d82b59
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_4ae578da22c929d1.sql
@@ -0,0 +1,24 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: direction_consistency
+-- intended_facet_id: conditional_rate_shift
+-- variant_semantic_role: contrastive_conditional_view
+-- template_id: tpl_m4_group_ratio_two_conditions
+-- query_record_id: v2q_n9_4ae578da22c929d1
+-- problem_id: v2p_n9_6363107d279d93c4
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+    SELECT "feature_7",
+           SUM(CASE WHEN "class" = '2' THEN 1 ELSE 0 END) AS numerator_count,
+           SUM(CASE WHEN "class" = '4' THEN 1 ELSE 0 END) AS denominator_count
+    FROM "n9"
+    GROUP BY "feature_7"
+)
+SELECT "feature_7",
+       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio
+FROM grouped
+ORDER BY condition_ratio DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_4bdc3aac2e64bc3f.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_4bdc3aac2e64bc3f.sql
new file mode 100644
index 0000000000000000000000000000000000000000..35dd33e8818167f3a5d8e9b7a5233ebc1231a1e2
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_4bdc3aac2e64bc3f.sql
@@ -0,0 +1,28 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: support_concentration
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_cardinality_distinct_share_profile
+-- query_record_id: v2q_n9_4bdc3aac2e64bc3f
+-- problem_id: v2p_n9_a4d8cb007601ef11
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_3" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_3"
+), ranked AS (
+    SELECT
+        value_label,
+        support,
+        CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+        SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support
+    FROM grouped
+)
+SELECT *
+FROM ranked
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_4eb0ead15b5f9504.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_4eb0ead15b5f9504.sql
new file mode 100644
index 0000000000000000000000000000000000000000..942e07e0d222981e4bd6b9c17339a0ff9e2239ce
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_4eb0ead15b5f9504.sql
@@ -0,0 +1,20 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_tail_low_support_group_count_v2
+-- query_record_id: v2q_n9_4eb0ead15b5f9504
+-- problem_id: v2p_n9_da7e09dc647caa06
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+    "feature_5",
+    COUNT(*) AS support
+FROM "n9"
+GROUP BY "feature_5"
+ORDER BY support ASC, "feature_5"
+LIMIT 18;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_4ffbe007bffba04b.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_4ffbe007bffba04b.sql
new file mode 100644
index 0000000000000000000000000000000000000000..2da5e372ada37b68a886f19a3093d396a97ff5d8
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_4ffbe007bffba04b.sql
@@ -0,0 +1,56 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_n9_4ffbe007bffba04b
+-- problem_id: v2p_n9_fc2b88ccc78fa045
+-- realization_mode: agent
+-- source_kind: agent
+WITH "ordered" AS (
+  SELECT
+    "feature_3" AS "group_col",
+    CAST("feature_8" AS REAL) AS "measure_val",
+    ROW_NUMBER() OVER (
+      PARTITION BY "feature_3"
+      ORDER BY CAST("feature_8" AS REAL)
+    ) AS "rn",
+    COUNT(*) OVER (
+      PARTITION BY "feature_3"
+    ) AS "cnt"
+  FROM "n9"
+  WHERE "feature_3" IS NOT NULL
+    AND "feature_8" IS NOT NULL
+),
+"positions" AS (
+  SELECT DISTINCT
+    "group_col",
+    (1.0 + ("cnt" - 1) * 0.95) AS "pos",
+    CAST((1.0 + ("cnt" - 1) * 0.95) AS INTEGER) AS "lower_rn",
+    CASE
+      WHEN (1.0 + ("cnt" - 1) * 0.95) = CAST((1.0 + ("cnt" - 1) * 0.95) AS INTEGER)
+        THEN CAST((1.0 + ("cnt" - 1) * 0.95) AS INTEGER)
+      ELSE CAST((1.0 + ("cnt" - 1) * 0.95) AS INTEGER) + 1
+    END AS "upper_rn"
+  FROM "ordered"
+)
+SELECT
+  p."group_col" AS "feature_3",
+  CASE
+    WHEN p."lower_rn" = p."upper_rn" THEN MAX(CASE WHEN o."rn" = p."lower_rn" THEN o."measure_val" END)
+    ELSE
+      MAX(CASE WHEN o."rn" = p."lower_rn" THEN o."measure_val" END) +
+      (p."pos" - p."lower_rn") * (
+        MAX(CASE WHEN o."rn" = p."upper_rn" THEN o."measure_val" END) -
+        MAX(CASE WHEN o."rn" = p."lower_rn" THEN o."measure_val" END)
+      )
+  END AS "percentile_measure"
+FROM "positions" AS p
+JOIN "ordered" AS o
+  ON o."group_col" = p."group_col"
+GROUP BY p."group_col", p."pos", p."lower_rn", p."upper_rn"
+ORDER BY "percentile_measure" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_52ce09dd6e4995e7.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_52ce09dd6e4995e7.sql
new file mode 100644
index 0000000000000000000000000000000000000000..c28a055b9951550161777d512894e7a05f7248a0
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_52ce09dd6e4995e7.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_conditional_contrast
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_n9_52ce09dd6e4995e7
+-- problem_id: v2p_n9_bf36a0c5193f9100
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_9", SUM(CAST("feature_9" AS REAL)) AS "total_measure"
+FROM "n9"
+GROUP BY "feature_9"
+ORDER BY "total_measure" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_53d3b8da9673c547.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_53d3b8da9673c547.sql
new file mode 100644
index 0000000000000000000000000000000000000000..bfca3c16da0d723d63ea7fd024e34dbd40f1fe46
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_53d3b8da9673c547.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_conditional_contrast
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_n9_53d3b8da9673c547
+-- problem_id: v2p_n9_02a6d81e31ae030b
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_2", SUM(CAST("feature_2" AS REAL)) AS total_measure
+FROM "n9"
+GROUP BY "feature_2"
+ORDER BY total_measure DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_53efae862dc8d800.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_53efae862dc8d800.sql
new file mode 100644
index 0000000000000000000000000000000000000000..4db6e64d69d9354bdb356861758b784a44be532d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_53efae862dc8d800.sql
@@ -0,0 +1,25 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: support_concentration
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_cardinality_support_rank_profile
+-- query_record_id: v2q_n9_53efae862dc8d800
+-- problem_id: v2p_n9_6833cb775d202bdf
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_15" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_15"
+)
+SELECT
+    value_label,
+    support,
+    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank
+FROM grouped
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_5439ef3aaead0361.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_5439ef3aaead0361.sql
new file mode 100644
index 0000000000000000000000000000000000000000..f73e9a67fa48630ac2d291a33e7877b91f308850
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_5439ef3aaead0361.sql
@@ -0,0 +1,29 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_5439ef3aaead0361
+-- problem_id: v2p_n9_f1fe8922a9905e8e
+-- realization_mode: agent
+-- source_kind: agent
+WITH "grouped" AS (
+  SELECT
+    "feature_8",
+    "feature_10",
+    SUM(CAST("feature_9" AS REAL)) AS "total_measure"
+  FROM "n9"
+  GROUP BY "feature_8", "feature_10"
+)
+SELECT
+  "feature_8",
+  "feature_10",
+  "total_measure",
+  "total_measure" * 100.0 / SUM("total_measure") OVER (PARTITION BY "feature_8") AS "share_within_group"
+FROM "grouped"
+ORDER BY "share_within_group" DESC
+LIMIT 19;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_543b8570fff58ef8.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_543b8570fff58ef8.sql
new file mode 100644
index 0000000000000000000000000000000000000000..a2da004e801984248a3a7ca2d11e8ee1314d996b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_543b8570fff58ef8.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_n9_543b8570fff58ef8
+-- problem_id: v2p_n9_e33e6e3c3d7cdfa2
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_9", SUM(CAST("feature_9" AS REAL)) AS total_measure
+FROM "n9"
+GROUP BY "feature_9"
+ORDER BY total_measure DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_55adc71151b1e66e.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_55adc71151b1e66e.sql
new file mode 100644
index 0000000000000000000000000000000000000000..05339fbfcc5ebd39ea1cff066e00942ffc21f17a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_55adc71151b1e66e.sql
@@ -0,0 +1,23 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_55adc71151b1e66e
+-- problem_id: v2p_n9_c3e711b993738580
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+  "feature_14",
+  "feature_16",
+  SUM(CAST("feature_15" AS REAL)) AS "total_measure",
+  SUM(CAST("feature_15" AS REAL)) * 100.0
+    / SUM(SUM(CAST("feature_15" AS REAL))) OVER (PARTITION BY "feature_14") AS "share_within_group"
+FROM "n9"
+GROUP BY "feature_14", "feature_16"
+ORDER BY "share_within_group" DESC
+LIMIT 15;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_55f4f921dbe66dcd.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_55f4f921dbe66dcd.sql
new file mode 100644
index 0000000000000000000000000000000000000000..54ff777f763c5b10eb44a777694512f4a21c824c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_55f4f921dbe66dcd.sql
@@ -0,0 +1,22 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_set_consistency
+-- intended_facet_id: low_support_extremes
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_m4_quantile_tail_slice
+-- query_record_id: v2q_n9_55f4f921dbe66dcd
+-- problem_id: v2p_n9_e02651a051af41bc
+-- realization_mode: agent
+-- source_kind: agent
+WITH buckets AS (
+    SELECT "feature_1",
+           NTILE(10) OVER (ORDER BY CAST("feature_1" AS REAL) DESC) AS tail_bucket
+    FROM "n9"
+)
+SELECT "feature_1"
+FROM buckets
+WHERE tail_bucket = 1
+ORDER BY CAST("feature_1" AS REAL) DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_56730f90dda0c039.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_56730f90dda0c039.sql
new file mode 100644
index 0000000000000000000000000000000000000000..7f038d60504859aa868f086a1218c160fb9dee08
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_56730f90dda0c039.sql
@@ -0,0 +1,38 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_n9_56730f90dda0c039
+-- problem_id: v2p_n9_22038214cd3c7bd8
+-- realization_mode: agent
+-- source_kind: agent
+WITH "ranked" AS (
+  SELECT
+    "feature_7" AS "group_col",
+    CAST("feature_12" AS REAL) AS "measure_value",
+    CUME_DIST() OVER (
+      PARTITION BY "feature_7"
+      ORDER BY CAST("feature_12" AS REAL)
+    ) AS "cum_dist"
+  FROM "n9"
+  WHERE "feature_7" IS NOT NULL
+    AND "feature_12" IS NOT NULL
+),
+"percentile_points" AS (
+  SELECT
+    "group_col",
+    MIN("measure_value") AS "percentile_measure"
+  FROM "ranked"
+  WHERE "cum_dist" >= 0.9
+  GROUP BY "group_col"
+)
+SELECT
+  "group_col" AS "feature_7",
+  "percentile_measure"
+FROM "percentile_points"
+ORDER BY "percentile_measure" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_5aa5ecb5e24ac4ae.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_5aa5ecb5e24ac4ae.sql
new file mode 100644
index 0000000000000000000000000000000000000000..65152650b21b84c2ca0a8748347e105e5fffb83a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_5aa5ecb5e24ac4ae.sql
@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: high_cardinality_response_stability
+-- intended_facet_id: target_cardinality_cross_section
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_cardinality_high_card_response_stability
+-- query_record_id: v2q_n9_5aa5ecb5e24ac4ae
+-- problem_id: v2p_n9_2d40ed07c245820c
+-- realization_mode: deterministic
+-- source_kind: deterministic
+SELECT
+    "feature_4",
+    COUNT(*) AS support,
+    AVG("feature_2") AS avg_response
+FROM "n9"
+GROUP BY "feature_4"
+HAVING COUNT(*) >= 5.0
+ORDER BY support DESC, avg_response DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_5be208a8a0379c86.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_5be208a8a0379c86.sql
new file mode 100644
index 0000000000000000000000000000000000000000..a893b552e3d9ffc7a2a86d4d7d3a2bb67cbe1ceb
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_5be208a8a0379c86.sql
@@ -0,0 +1,18 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: slice_level_consistency
+-- intended_facet_id: conditional_interaction_hotspots
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_c2_filtered_group_count_2d
+-- query_record_id: v2q_n9_5be208a8a0379c86
+-- problem_id: v2p_n9_5c34dbc4543cdda9
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_4", "feature_16", COUNT(*) AS "row_count"
+FROM "n9"
+WHERE CAST("feature_6" AS REAL) >= 86.0
+GROUP BY "feature_4", "feature_16"
+ORDER BY "row_count" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_5c320426b90027c6.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_5c320426b90027c6.sql
new file mode 100644
index 0000000000000000000000000000000000000000..b69aa71361203a8455425d395b629696c6e19d6f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_5c320426b90027c6.sql
@@ -0,0 +1,19 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: slice_level_consistency
+-- intended_facet_id: conditional_interaction_hotspots
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_c2_filtered_group_count_2d
+-- query_record_id: v2q_n9_5c320426b90027c6
+-- problem_id: v2p_n9_bc15a2e46a1322ed
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_4", "feature_15", COUNT(*) AS "row_count"
+FROM "n9"
+WHERE CAST("feature_5" AS REAL) >= 78.0
+GROUP BY "feature_4", "feature_15"
+ORDER BY "row_count" DESC
+LIMIT 6;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_5c5f89dd28c2e8ae.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_5c5f89dd28c2e8ae.sql
new file mode 100644
index 0000000000000000000000000000000000000000..57fab840f3f4909352f53f17aee5bda04029279a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_5c5f89dd28c2e8ae.sql
@@ -0,0 +1,18 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: direction_consistency
+-- intended_facet_id: conditional_rate_shift
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_m4_group_condition_rate
+-- query_record_id: v2q_n9_5c5f89dd28c2e8ae
+-- problem_id: v2p_n9_f59eacc1e9d72505
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_2",
+       AVG(CASE WHEN "class" = '2' THEN 1 ELSE 0 END) AS condition_rate
+FROM "n9"
+GROUP BY "feature_2"
+ORDER BY condition_rate DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_5e4de333ec1e3b54.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_5e4de333ec1e3b54.sql
new file mode 100644
index 0000000000000000000000000000000000000000..32b96984e8cbb60618d0162790e4f46970ba451f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_5e4de333ec1e3b54.sql
@@ -0,0 +1,76 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_n9_5e4de333ec1e3b54
+-- problem_id: v2p_n9_1419025a59f14835
+-- realization_mode: agent
+-- source_kind: agent
+WITH "base" AS (
+  SELECT
+    "feature_9",
+    CAST("feature_14" AS REAL) AS "measure"
+  FROM "n9"
+  WHERE "feature_9" IS NOT NULL
+    AND "feature_14" IS NOT NULL
+),
+"ranked" AS (
+  SELECT
+    "feature_9",
+    "measure",
+    ROW_NUMBER() OVER (
+      PARTITION BY "feature_9"
+      ORDER BY "measure"
+    ) AS "rn",
+    COUNT(*) OVER (
+      PARTITION BY "feature_9"
+    ) AS "cnt"
+  FROM "base"
+),
+"targets" AS (
+  SELECT DISTINCT
+    "feature_9",
+    "cnt",
+    1.0 + (0.95 * ("cnt" - 1)) AS "pos"
+  FROM "ranked"
+),
+"positions" AS (
+  SELECT
+    "feature_9",
+    "pos",
+    CAST("pos" AS INTEGER) AS "lower_rn",
+    CASE
+      WHEN ABS("pos" - CAST("pos" AS INTEGER)) < 1e-12 THEN CAST("pos" AS INTEGER)
+      ELSE CAST("pos" AS INTEGER) + 1
+    END AS "upper_rn"
+  FROM "targets"
+),
+"bounds" AS (
+  SELECT
+    p."feature_9",
+    p."pos",
+    p."lower_rn",
+    p."upper_rn",
+    lr."measure" AS "lower_measure",
+    ur."measure" AS "upper_measure"
+  FROM "positions" AS p
+  JOIN "ranked" AS lr
+    ON lr."feature_9" = p."feature_9"
+   AND lr."rn" = p."lower_rn"
+  JOIN "ranked" AS ur
+    ON ur."feature_9" = p."feature_9"
+   AND ur."rn" = p."upper_rn"
+)
+SELECT
+  "feature_9",
+  CASE
+    WHEN "lower_rn" = "upper_rn" THEN "lower_measure"
+    ELSE "lower_measure" + (("pos" - "lower_rn") * ("upper_measure" - "lower_measure"))
+  END AS "percentile_measure"
+FROM "bounds"
+ORDER BY "percentile_measure" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_600638f83ecb65a3.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_600638f83ecb65a3.sql
new file mode 100644
index 0000000000000000000000000000000000000000..4a42d4c17bfd91b70f09ef71fefeb3a6b15772db
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_600638f83ecb65a3.sql
@@ -0,0 +1,25 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: support_concentration
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_cardinality_support_rank_profile
+-- query_record_id: v2q_n9_600638f83ecb65a3
+-- problem_id: v2p_n9_23df0cf15e38f384
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_6" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_6"
+)
+SELECT
+    value_label,
+    support,
+    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank
+FROM grouped
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_6143539db4c6b126.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_6143539db4c6b126.sql
new file mode 100644
index 0000000000000000000000000000000000000000..a9f98b2ea318a6f30a1f53dd578a20cde084f75b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_6143539db4c6b126.sql
@@ -0,0 +1,15 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_set_consistency
+-- intended_facet_id: low_support_extremes
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_threshold_rarity_cdf
+-- query_record_id: v2q_n9_6143539db4c6b126
+-- problem_id: v2p_n9_e7e40418c024d312
+-- realization_mode: agent
+-- source_kind: agent
+SELECT AVG(CASE WHEN CAST("feature_14" AS REAL) <= 47.0 THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold
+FROM "n9";
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_62fea1f2a060f22d.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_62fea1f2a060f22d.sql
new file mode 100644
index 0000000000000000000000000000000000000000..de4610e662398b0d84d46fbee3512618ede501a0
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_62fea1f2a060f22d.sql
@@ -0,0 +1,26 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: filtered_stable_view
+-- template_id: tpl_tpch_relative_total_threshold
+-- query_record_id: v2q_n9_62fea1f2a060f22d
+-- problem_id: v2p_n9_1bf65e2680b76f84
+-- realization_mode: agent
+-- source_kind: agent
+WITH "grouped" AS (
+  SELECT "feature_5", SUM(CAST("feature_9" AS REAL)) AS "group_value"
+  FROM "n9"
+  GROUP BY "feature_5"
+), "total" AS (
+  SELECT SUM("group_value") AS "total_value"
+  FROM "grouped"
+)
+SELECT g."feature_5", g."group_value"
+FROM "grouped" AS g
+CROSS JOIN "total" AS t
+WHERE g."group_value" > t."total_value" * 0.05
+ORDER BY g."group_value" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_64a2d4d4dcbbab9b.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_64a2d4d4dcbbab9b.sql
new file mode 100644
index 0000000000000000000000000000000000000000..4a7a4fb2c02f408967cfd0dcc726f83c961c443b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_64a2d4d4dcbbab9b.sql
@@ -0,0 +1,38 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_n9_64a2d4d4dcbbab9b
+-- problem_id: v2p_n9_6be6539cf6587990
+-- realization_mode: agent
+-- source_kind: agent
+WITH "ranked" AS (
+  SELECT
+    "feature_1",
+    CAST("feature_6" AS REAL) AS "measure_value",
+    CUME_DIST() OVER (
+      PARTITION BY "feature_1"
+      ORDER BY CAST("feature_6" AS REAL)
+    ) AS "cume_dist_value"
+  FROM "n9"
+  WHERE "feature_1" IS NOT NULL
+    AND "feature_6" IS NOT NULL
+),
+"percentiles" AS (
+  SELECT
+    "feature_1",
+    MIN("measure_value") AS "percentile_measure"
+  FROM "ranked"
+  WHERE "cume_dist_value" >= 0.9
+  GROUP BY "feature_1"
+)
+SELECT
+  "feature_1",
+  "percentile_measure"
+FROM "percentiles"
+ORDER BY "percentile_measure" DESC, "feature_1";
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_64b9f2eb7d353f2e.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_64b9f2eb7d353f2e.sql
new file mode 100644
index 0000000000000000000000000000000000000000..dd9855c54b5f7a8d6ec5f18ee025ba57330bb344
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_64b9f2eb7d353f2e.sql
@@ -0,0 +1,18 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: slice_level_consistency
+-- intended_facet_id: conditional_interaction_hotspots
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_c2_filtered_group_count_2d
+-- query_record_id: v2q_n9_64b9f2eb7d353f2e
+-- problem_id: v2p_n9_84db75e47d9a4f7b
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_4", "feature_13", COUNT(*) AS "row_count"
+FROM "n9"
+WHERE CAST("feature_3" AS REAL) >= 58.0
+GROUP BY "feature_4", "feature_13"
+ORDER BY "row_count" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_669793c2a10d1d63.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_669793c2a10d1d63.sql
new file mode 100644
index 0000000000000000000000000000000000000000..baead257bad25be0836ecf2bf7387ec603688b6e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_669793c2a10d1d63.sql
@@ -0,0 +1,25 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: support_concentration
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_cardinality_support_rank_profile
+-- query_record_id: v2q_n9_669793c2a10d1d63
+-- problem_id: v2p_n9_d605285577a01e2b
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_9" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_9"
+)
+SELECT
+    value_label,
+    support,
+    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank
+FROM grouped
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_66d15541665feda3.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_66d15541665feda3.sql
new file mode 100644
index 0000000000000000000000000000000000000000..5101998d1f8a89e4a4863f92ad8a9ef5c962ff3e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_66d15541665feda3.sql
@@ -0,0 +1,25 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: value_imbalance_profile
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_cardinality_support_rank_profile
+-- query_record_id: v2q_n9_66d15541665feda3
+-- problem_id: v2p_n9_3b8473c4cad49fb3
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_13" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_13"
+)
+SELECT
+    value_label,
+    support,
+    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank
+FROM grouped
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_696c5d29dead1190.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_696c5d29dead1190.sql
new file mode 100644
index 0000000000000000000000000000000000000000..d056b58545b4a3b7e838d90f0720869d419b60f1
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_696c5d29dead1190.sql
@@ -0,0 +1,61 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_n9_696c5d29dead1190
+-- problem_id: v2p_n9_39f42ed8ede56e7e
+-- realization_mode: agent
+-- source_kind: agent
+WITH "__ordered" AS (
+  SELECT
+    "class",
+    CAST("feature_5" AS REAL) AS "measure_value",
+    ROW_NUMBER() OVER (
+      PARTITION BY "class"
+      ORDER BY CAST("feature_5" AS REAL)
+    ) AS "rn",
+    COUNT(*) OVER (
+      PARTITION BY "class"
+    ) AS "cnt"
+  FROM "n9"
+  WHERE "class" IS NOT NULL
+    AND "feature_5" IS NOT NULL
+),
+"__positions" AS (
+  SELECT
+    "class",
+    "measure_value",
+    "rn",
+    ((0.9 * ("cnt" - 1)) + 1.0) AS "pos",
+    CAST(((0.9 * ("cnt" - 1)) + 1.0) AS INTEGER) AS "lower_rn",
+    CASE
+      WHEN ((0.9 * ("cnt" - 1)) + 1.0) = CAST(((0.9 * ("cnt" - 1)) + 1.0) AS INTEGER)
+        THEN CAST(((0.9 * ("cnt" - 1)) + 1.0) AS INTEGER)
+      ELSE CAST(((0.9 * ("cnt" - 1)) + 1.0) AS INTEGER) + 1
+    END AS "upper_rn"
+  FROM "__ordered"
+),
+"__aggregated" AS (
+  SELECT
+    "class",
+    MAX("pos") AS "pos",
+    MAX("lower_rn") AS "lower_rn",
+    MAX("upper_rn") AS "upper_rn",
+    MAX(CASE WHEN "rn" = "lower_rn" THEN "measure_value" END) AS "lower_value",
+    MAX(CASE WHEN "rn" = "upper_rn" THEN "measure_value" END) AS "upper_value"
+  FROM "__positions"
+  GROUP BY "class"
+)
+SELECT
+  "class",
+  CASE
+    WHEN "lower_rn" = "upper_rn" THEN "lower_value"
+    ELSE "lower_value" + ("pos" - "lower_rn") * ("upper_value" - "lower_value")
+  END AS "percentile_measure"
+FROM "__aggregated"
+ORDER BY "percentile_measure" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_698d9795e0779fe2.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_698d9795e0779fe2.sql
new file mode 100644
index 0000000000000000000000000000000000000000..58184bc89074c0697a3be1f1144090bf3ab0adbe
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_698d9795e0779fe2.sql
@@ -0,0 +1,24 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: direction_consistency
+-- intended_facet_id: conditional_rate_shift
+-- variant_semantic_role: contrastive_conditional_view
+-- template_id: tpl_m4_group_ratio_two_conditions
+-- query_record_id: v2q_n9_698d9795e0779fe2
+-- problem_id: v2p_n9_4597f25618fa6c5e
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+    SELECT "feature_5",
+           SUM(CASE WHEN "class" = '2' THEN 1 ELSE 0 END) AS numerator_count,
+           SUM(CASE WHEN "class" = '4' THEN 1 ELSE 0 END) AS denominator_count
+    FROM "n9"
+    GROUP BY "feature_5"
+)
+SELECT "feature_5",
+       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio
+FROM grouped
+ORDER BY condition_ratio DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_6b244ee546038269.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_6b244ee546038269.sql
new file mode 100644
index 0000000000000000000000000000000000000000..95926e2db47015399be7ebaef1ab82c586b6b3ce
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_6b244ee546038269.sql
@@ -0,0 +1,23 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_set_consistency
+-- intended_facet_id: low_support_extremes
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_m4_quantile_tail_slice
+-- query_record_id: v2q_n9_6b244ee546038269
+-- problem_id: v2p_n9_58eba46f45845d60
+-- realization_mode: agent
+-- source_kind: agent
+WITH "buckets" AS (
+    SELECT
+        CAST("feature_15" AS INTEGER) AS "feature_15",
+        NTILE(10) OVER (ORDER BY CAST("feature_15" AS INTEGER) DESC) AS "tail_bucket"
+    FROM "n9"
+)
+SELECT "feature_15"
+FROM "buckets"
+WHERE "tail_bucket" = 1
+ORDER BY "feature_15" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_6c6df2e940326b15.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_6c6df2e940326b15.sql
new file mode 100644
index 0000000000000000000000000000000000000000..b62ca339e49b02988b07a46013cc924d97dde65b
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_6c6df2e940326b15.sql
@@ -0,0 +1,22 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_set_consistency
+-- intended_facet_id: low_support_extremes
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_m4_quantile_tail_slice
+-- query_record_id: v2q_n9_6c6df2e940326b15
+-- problem_id: v2p_n9_4fdf003f96d9b191
+-- realization_mode: agent
+-- source_kind: agent
+WITH buckets AS (
+    SELECT CAST("feature_4" AS REAL) AS "feature_4",
+           NTILE(10) OVER (ORDER BY CAST("feature_4" AS REAL) DESC) AS "tail_bucket"
+    FROM "n9"
+)
+SELECT "feature_4"
+FROM buckets
+WHERE "tail_bucket" = 1
+ORDER BY "feature_4" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_77b82fc148cb125f.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_77b82fc148cb125f.sql
new file mode 100644
index 0000000000000000000000000000000000000000..13bb613ff8801b1eeb66e861f7601e3bfb9eb76d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_77b82fc148cb125f.sql
@@ -0,0 +1,24 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: direction_consistency
+-- intended_facet_id: conditional_rate_shift
+-- variant_semantic_role: contrastive_conditional_view
+-- template_id: tpl_m4_group_ratio_two_conditions
+-- query_record_id: v2q_n9_77b82fc148cb125f
+-- problem_id: v2p_n9_bff7f0c7084b1f58
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+    SELECT "feature_9",
+           SUM(CASE WHEN "class" = '2' THEN 1 ELSE 0 END) AS numerator_count,
+           SUM(CASE WHEN "class" = '4' THEN 1 ELSE 0 END) AS denominator_count
+    FROM "n9"
+    GROUP BY "feature_9"
+)
+SELECT "feature_9",
+       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio
+FROM grouped
+ORDER BY condition_ratio DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_7872fd8b4797f83d.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_7872fd8b4797f83d.sql
new file mode 100644
index 0000000000000000000000000000000000000000..31e1959ff8a416184b3dcbf994f25bb182be9c33
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_7872fd8b4797f83d.sql
@@ -0,0 +1,31 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_tpch_relative_total_threshold
+-- query_record_id: v2q_n9_7872fd8b4797f83d
+-- problem_id: v2p_n9_482109c03c62f8ed
+-- realization_mode: agent
+-- source_kind: agent
+WITH "grouped" AS (
+  SELECT
+    "feature_6",
+    SUM(CAST("feature_10" AS REAL)) AS "group_value"
+  FROM "n9"
+  GROUP BY "feature_6"
+),
+"total" AS (
+  SELECT SUM("group_value") AS "total_value"
+  FROM "grouped"
+)
+SELECT
+  g."feature_6",
+  g."group_value"
+FROM "grouped" AS g
+CROSS JOIN "total" AS t
+WHERE g."group_value" > t."total_value" * 0.05
+ORDER BY g."group_value" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_79f6d2c0a420d0c0.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_79f6d2c0a420d0c0.sql
new file mode 100644
index 0000000000000000000000000000000000000000..515279007b733581d11a72f2955610b642320329
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_79f6d2c0a420d0c0.sql
@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: high_cardinality_response_stability
+-- intended_facet_id: target_cardinality_cross_section
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_cardinality_high_card_response_stability
+-- query_record_id: v2q_n9_79f6d2c0a420d0c0
+-- problem_id: v2p_n9_948b2bedbf1ffdea
+-- realization_mode: deterministic
+-- source_kind: deterministic
+SELECT
+    "feature_12",
+    COUNT(*) AS support,
+    AVG("feature_1") AS avg_response
+FROM "n9"
+GROUP BY "feature_12"
+HAVING COUNT(*) >= 5.0
+ORDER BY support DESC, avg_response DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_7b094f86425ab76d.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_7b094f86425ab76d.sql
new file mode 100644
index 0000000000000000000000000000000000000000..12b48b6919b5f6f31066a2e65854d4b4399e3b9a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_7b094f86425ab76d.sql
@@ -0,0 +1,20 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_tail_low_support_group_count_v2
+-- query_record_id: v2q_n9_7b094f86425ab76d
+-- problem_id: v2p_n9_52a613b3efe49ecf
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+    "feature_9",
+    COUNT(*) AS support
+FROM "n9"
+GROUP BY "feature_9"
+ORDER BY support ASC, "feature_9"
+LIMIT 17;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_7b9d7c673f0f635c.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_7b9d7c673f0f635c.sql
new file mode 100644
index 0000000000000000000000000000000000000000..4edb1cff12446908c6d01732f76816bff6802b54
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_7b9d7c673f0f635c.sql
@@ -0,0 +1,19 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: within_group_proportion
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_7b9d7c673f0f635c
+-- problem_id: v2p_n9_64cfb43409e31360
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_16", "feature_2",
+       SUM(CAST("feature_1" AS REAL)) AS total_measure,
+       SUM(CAST("feature_1" AS REAL)) * 100.0 / SUM(SUM(CAST("feature_1" AS REAL))) OVER (PARTITION BY "feature_16") AS share_within_group
+FROM "n9"
+GROUP BY "feature_16", "feature_2"
+ORDER BY share_within_group DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_7d2fbbac0e070940.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_7d2fbbac0e070940.sql
new file mode 100644
index 0000000000000000000000000000000000000000..0038d25149585efb6ab230900359619217b0adb7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_7d2fbbac0e070940.sql
@@ -0,0 +1,23 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_set_consistency
+-- intended_facet_id: low_support_extremes
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_m4_quantile_tail_slice
+-- query_record_id: v2q_n9_7d2fbbac0e070940
+-- problem_id: v2p_n9_55cd5843b5109ad7
+-- realization_mode: agent
+-- source_kind: agent
+WITH buckets AS (
+    SELECT
+        "feature_2",
+        NTILE(10) OVER (ORDER BY CAST("feature_2" AS REAL) DESC) AS tail_bucket
+    FROM "n9"
+)
+SELECT "feature_2"
+FROM buckets
+WHERE tail_bucket = 1
+ORDER BY CAST("feature_2" AS REAL) DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_7e97a63641733b89.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_7e97a63641733b89.sql
new file mode 100644
index 0000000000000000000000000000000000000000..62d952c7fdfb709c7335eb5da89a60d934b755e3
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_7e97a63641733b89.sql
@@ -0,0 +1,30 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_n9_7e97a63641733b89
+-- problem_id: v2p_n9_e343c6b824d3fa8c
+-- realization_mode: agent
+-- source_kind: agent
+WITH "ranked" AS (
+  SELECT
+    "feature_5",
+    CAST("feature_10" AS REAL) AS "measure_value",
+    CUME_DIST() OVER (
+      PARTITION BY "feature_5"
+      ORDER BY CAST("feature_10" AS REAL)
+    ) AS "cum_dist"
+  FROM "n9"
+)
+SELECT
+  "feature_5",
+  MIN("measure_value") AS "percentile_measure"
+FROM "ranked"
+WHERE "cum_dist" >= 0.9
+GROUP BY "feature_5"
+ORDER BY "percentile_measure" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_7f2c9cb98bebdea7.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_7f2c9cb98bebdea7.sql
new file mode 100644
index 0000000000000000000000000000000000000000..307ee2abca12f38a08e3697c4decc86db587d0a3
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_7f2c9cb98bebdea7.sql
@@ -0,0 +1,24 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: direction_consistency
+-- intended_facet_id: conditional_rate_shift
+-- variant_semantic_role: contrastive_conditional_view
+-- template_id: tpl_m4_group_ratio_two_conditions
+-- query_record_id: v2q_n9_7f2c9cb98bebdea7
+-- problem_id: v2p_n9_57d852f025a294d5
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+    SELECT "feature_6",
+           SUM(CASE WHEN "class" = '2' THEN 1 ELSE 0 END) AS numerator_count,
+           SUM(CASE WHEN "class" = '4' THEN 1 ELSE 0 END) AS denominator_count
+    FROM "n9"
+    GROUP BY "feature_6"
+)
+SELECT "feature_6",
+       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio
+FROM grouped
+ORDER BY condition_ratio DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_7f8a0603780a1a99.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_7f8a0603780a1a99.sql
new file mode 100644
index 0000000000000000000000000000000000000000..707de573ae43febe7ab3b2400ac03406392e1656
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_7f8a0603780a1a99.sql
@@ -0,0 +1,28 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: support_concentration
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_cardinality_distinct_share_profile
+-- query_record_id: v2q_n9_7f8a0603780a1a99
+-- problem_id: v2p_n9_85d22479c1fc7083
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_6" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_6"
+), ranked AS (
+    SELECT
+        value_label,
+        support,
+        CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+        SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support
+    FROM grouped
+)
+SELECT *
+FROM ranked
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8018cd36f1aa3207.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8018cd36f1aa3207.sql
new file mode 100644
index 0000000000000000000000000000000000000000..a962fbdc5a45b9de31097e95b3ea8d5d788bcc96
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8018cd36f1aa3207.sql
@@ -0,0 +1,15 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_set_consistency
+-- intended_facet_id: low_support_extremes
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_threshold_rarity_cdf
+-- query_record_id: v2q_n9_8018cd36f1aa3207
+-- problem_id: v2p_n9_68ff71d8ab8b1789
+-- realization_mode: agent
+-- source_kind: agent
+SELECT AVG(CASE WHEN CAST("feature_16" AS REAL) <= 51.0 THEN 1 ELSE 0 END) AS "empirical_cdf_at_threshold"
+FROM "n9";
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8055a54c784a3fc2.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8055a54c784a3fc2.sql
new file mode 100644
index 0000000000000000000000000000000000000000..b0b39e97e8476bfca6b86eb1d78b4e7c93fddec6
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8055a54c784a3fc2.sql
@@ -0,0 +1,18 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: slice_level_consistency
+-- intended_facet_id: conditional_interaction_hotspots
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_c2_filtered_group_count_2d
+-- query_record_id: v2q_n9_8055a54c784a3fc2
+-- problem_id: v2p_n9_c7d7f61c3c424697
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_4", "feature_10", COUNT(*) AS row_count
+FROM "n9"
+WHERE "class" = '0'
+GROUP BY "feature_4", "feature_10"
+ORDER BY row_count DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8217a985c2e7d337.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8217a985c2e7d337.sql
new file mode 100644
index 0000000000000000000000000000000000000000..de34530ac15dcc452677f13771fb304e83098132
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8217a985c2e7d337.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: subgroup_size_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_clickbench_group_count
+-- query_record_id: v2q_n9_8217a985c2e7d337
+-- problem_id: v2p_n9_f2e42a3aaa4d0801
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "class", COUNT(*) AS "row_count"
+FROM "n9"
+GROUP BY "class"
+ORDER BY "row_count" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_834804424cb72fa9.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_834804424cb72fa9.sql
new file mode 100644
index 0000000000000000000000000000000000000000..7acfaf636252f07e5497dff6a30905431f776c3d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_834804424cb72fa9.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: subgroup_size_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_clickbench_group_count
+-- query_record_id: v2q_n9_834804424cb72fa9
+-- problem_id: v2p_n9_dcfd6e19e94f3a38
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_15", COUNT(*) AS "row_count"
+FROM "n9"
+GROUP BY "feature_15"
+ORDER BY "row_count" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_86a2386bd005c5f4.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_86a2386bd005c5f4.sql
new file mode 100644
index 0000000000000000000000000000000000000000..89d456be6d225e0785b08d5eb1d8c262b925b107
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_86a2386bd005c5f4.sql
@@ -0,0 +1,28 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: value_imbalance_profile
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_cardinality_distinct_share_profile
+-- query_record_id: v2q_n9_86a2386bd005c5f4
+-- problem_id: v2p_n9_850642349848658b
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_16" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_16"
+), ranked AS (
+    SELECT
+        value_label,
+        support,
+        CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+        SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support
+    FROM grouped
+)
+SELECT *
+FROM ranked
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_87e7f001cbe6b23b.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_87e7f001cbe6b23b.sql
new file mode 100644
index 0000000000000000000000000000000000000000..10de6b4e7241aa815b35c5e69e86b1e82c4e9fb1
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_87e7f001cbe6b23b.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_n9_87e7f001cbe6b23b
+-- problem_id: v2p_n9_f030a33bacaa9755
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_6", SUM(CAST("feature_6" AS NUMERIC)) AS total_measure
+FROM "n9"
+GROUP BY "feature_6"
+ORDER BY total_measure DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8a436fccc17a0e52.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8a436fccc17a0e52.sql
new file mode 100644
index 0000000000000000000000000000000000000000..8fec112f83caf0d927a4cc8d3d7b8db1abc83fe2
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8a436fccc17a0e52.sql
@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: high_cardinality_response_stability
+-- intended_facet_id: target_cardinality_cross_section
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_cardinality_high_card_response_stability
+-- query_record_id: v2q_n9_8a436fccc17a0e52
+-- problem_id: v2p_n9_8b7ad4185b203658
+-- realization_mode: deterministic
+-- source_kind: deterministic
+SELECT
+    "feature_14",
+    COUNT(*) AS support,
+    AVG("feature_3") AS avg_response
+FROM "n9"
+GROUP BY "feature_14"
+HAVING COUNT(*) >= 5.0
+ORDER BY support DESC, avg_response DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8afa10369311830e.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8afa10369311830e.sql
new file mode 100644
index 0000000000000000000000000000000000000000..19bf6b23abfb9b8e42fe3f116311b187b23c88fc
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8afa10369311830e.sql
@@ -0,0 +1,25 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: value_imbalance_profile
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_cardinality_support_rank_profile
+-- query_record_id: v2q_n9_8afa10369311830e
+-- problem_id: v2p_n9_a750f4406a8c68b4
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_5" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_5"
+)
+SELECT
+    value_label,
+    support,
+    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank
+FROM grouped
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8b1b87b2fecc9e09.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8b1b87b2fecc9e09.sql
new file mode 100644
index 0000000000000000000000000000000000000000..3bc3ff211df2fb6914aac7d86680624c5d216e77
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8b1b87b2fecc9e09.sql
@@ -0,0 +1,31 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_tpch_relative_total_threshold
+-- query_record_id: v2q_n9_8b1b87b2fecc9e09
+-- problem_id: v2p_n9_05b03706d147d4f4
+-- realization_mode: agent
+-- source_kind: agent
+WITH "grouped" AS (
+    SELECT
+        "feature_11",
+        SUM(CAST("feature_15" AS REAL)) AS "group_value"
+    FROM "n9"
+    GROUP BY "feature_11"
+),
+"total" AS (
+    SELECT SUM("group_value") AS "total_value"
+    FROM "grouped"
+)
+SELECT
+    g."feature_11",
+    g."group_value"
+FROM "grouped" AS g
+CROSS JOIN "total" AS t
+WHERE g."group_value" > t."total_value" * 0.1
+ORDER BY g."group_value" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8e1d994c189ea724.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8e1d994c189ea724.sql
new file mode 100644
index 0000000000000000000000000000000000000000..57035fc0aec4144db0208be5909192c46c264511
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8e1d994c189ea724.sql
@@ -0,0 +1,18 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: slice_level_consistency
+-- intended_facet_id: conditional_interaction_hotspots
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_c2_filtered_group_count_2d
+-- query_record_id: v2q_n9_8e1d994c189ea724
+-- problem_id: v2p_n9_0120310f39e4dd18
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_4", "feature_14", COUNT(*) AS row_count
+FROM "n9"
+WHERE CAST("feature_4" AS REAL) >= 100.0
+GROUP BY "feature_4", "feature_14"
+ORDER BY row_count DESC, "feature_4", "feature_14";
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8e2ef544a2699965.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8e2ef544a2699965.sql
new file mode 100644
index 0000000000000000000000000000000000000000..e26c6a39dbdef0aa8023bbecd033f5b6ec115ae5
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8e2ef544a2699965.sql
@@ -0,0 +1,22 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: within_group_proportion
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_8e2ef544a2699965
+-- problem_id: v2p_n9_77eb3a5f0dbf4cf3
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+  "feature_8",
+  "feature_10",
+  SUM(CAST("feature_9" AS REAL)) AS total_measure,
+  SUM(CAST("feature_9" AS REAL)) * 100.0 / SUM(SUM(CAST("feature_9" AS REAL))) OVER (PARTITION BY "feature_8") AS share_within_group
+FROM "n9"
+GROUP BY "feature_8", "feature_10"
+ORDER BY share_within_group DESC
+LIMIT 14;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8fb8cc3b4d18fbc4.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8fb8cc3b4d18fbc4.sql
new file mode 100644
index 0000000000000000000000000000000000000000..cd0de46c58d4bb2c7af3123f9acf1cb709347ffe
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8fb8cc3b4d18fbc4.sql
@@ -0,0 +1,23 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_set_consistency
+-- intended_facet_id: low_support_extremes
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_m4_quantile_tail_slice
+-- query_record_id: v2q_n9_8fb8cc3b4d18fbc4
+-- problem_id: v2p_n9_d824a8446a4806aa
+-- realization_mode: agent
+-- source_kind: agent
+WITH "buckets" AS (
+  SELECT
+    CAST("feature_14" AS REAL) AS "feature_14",
+    NTILE(10) OVER (ORDER BY CAST("feature_14" AS REAL) DESC) AS "tail_bucket"
+  FROM "n9"
+)
+SELECT "feature_14"
+FROM "buckets"
+WHERE "tail_bucket" = 1
+ORDER BY "feature_14" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8fba9afb5d5100c2.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8fba9afb5d5100c2.sql
new file mode 100644
index 0000000000000000000000000000000000000000..27ebc4ba27fc194a010a5d80ae0a66c0a413d434
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_8fba9afb5d5100c2.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_conditional_contrast
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_n9_8fba9afb5d5100c2
+-- problem_id: v2p_n9_3f4cd1cf460fc81b
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_5", SUM(CAST("feature_5" AS INTEGER)) AS "total_measure"
+FROM "n9"
+GROUP BY "feature_5"
+ORDER BY "total_measure" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_9173874fab20c730.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_9173874fab20c730.sql
new file mode 100644
index 0000000000000000000000000000000000000000..e63c1cb41bc36481180e5b320b4d09c7ea2aaa27
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_9173874fab20c730.sql
@@ -0,0 +1,18 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: direction_consistency
+-- intended_facet_id: conditional_rate_shift
+-- variant_semantic_role: within_group_proportion
+-- template_id: tpl_m4_group_condition_rate
+-- query_record_id: v2q_n9_9173874fab20c730
+-- problem_id: v2p_n9_5ca1cf7a62b1bca9
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "class",
+       AVG(CASE WHEN "class" = '4' THEN 1 ELSE 0 END) AS condition_rate
+FROM "n9"
+GROUP BY "class"
+ORDER BY condition_rate DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_92494a79eccf8e23.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_92494a79eccf8e23.sql
new file mode 100644
index 0000000000000000000000000000000000000000..4fc431a6efc6d1e3f92e9accbde111acc2141111
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_92494a79eccf8e23.sql
@@ -0,0 +1,31 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_tpch_relative_total_threshold
+-- query_record_id: v2q_n9_92494a79eccf8e23
+-- problem_id: v2p_n9_466e67f3a2d19526
+-- realization_mode: agent
+-- source_kind: agent
+WITH "grouped" AS (
+  SELECT
+    "feature_7",
+    SUM(CAST("feature_11" AS REAL)) AS "group_value"
+  FROM "n9"
+  GROUP BY "feature_7"
+),
+"total" AS (
+  SELECT SUM("group_value") AS "total_value"
+  FROM "grouped"
+)
+SELECT
+  g."feature_7",
+  g."group_value"
+FROM "grouped" AS g
+CROSS JOIN "total" AS t
+WHERE g."group_value" > t."total_value" * 0.1
+ORDER BY g."group_value" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_924ff65dde50a4a3.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_924ff65dde50a4a3.sql
new file mode 100644
index 0000000000000000000000000000000000000000..e9f2cce32a1308590b0f26675bcd88e17bdfdb40
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_924ff65dde50a4a3.sql
@@ -0,0 +1,19 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_924ff65dde50a4a3
+-- problem_id: v2p_n9_7a1120b5cd091363
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_10", "feature_12",
+       SUM(CAST("feature_11" AS REAL)) AS total_measure,
+       SUM(CAST("feature_11" AS REAL)) * 100.0 / SUM(SUM(CAST("feature_11" AS REAL))) OVER (PARTITION BY "feature_10") AS share_within_group
+FROM "n9"
+GROUP BY "feature_10", "feature_12"
+ORDER BY share_within_group DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_95ac53b6c9bdb05f.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_95ac53b6c9bdb05f.sql
new file mode 100644
index 0000000000000000000000000000000000000000..ce73abdae1cb330e2c8b3ffdeba220db7e1d0238
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_95ac53b6c9bdb05f.sql
@@ -0,0 +1,18 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: within_group_proportion
+-- template_id: tpl_m4_group_condition_rate
+-- query_record_id: v2q_n9_95ac53b6c9bdb05f
+-- problem_id: v2p_n9_b35bc3a5d799f2c6
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_12",
+       AVG(CASE WHEN "class" = '2' THEN 1 ELSE 0 END) AS "condition_rate"
+FROM "n9"
+GROUP BY "feature_12"
+ORDER BY "condition_rate" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_981d43287b097165.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_981d43287b097165.sql
new file mode 100644
index 0000000000000000000000000000000000000000..d1a143ce142a36e6e61e3adb21969b5c08d6d982
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_981d43287b097165.sql
@@ -0,0 +1,31 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: filtered_stable_view
+-- template_id: tpl_tpch_relative_total_threshold
+-- query_record_id: v2q_n9_981d43287b097165
+-- problem_id: v2p_n9_bb08c2a9f8d6753c
+-- realization_mode: agent
+-- source_kind: agent
+WITH "grouped" AS (
+  SELECT
+    "feature_12",
+    SUM(CAST("feature_16" AS REAL)) AS "group_value"
+  FROM "n9"
+  GROUP BY "feature_12"
+),
+"total" AS (
+  SELECT SUM("group_value") AS "total_value"
+  FROM "grouped"
+)
+SELECT
+  g."feature_12",
+  g."group_value"
+FROM "grouped" AS g
+CROSS JOIN "total" AS t
+WHERE g."group_value" > t."total_value" * 0.1
+ORDER BY g."group_value" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_9a62b46e99f2dc1e.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_9a62b46e99f2dc1e.sql
new file mode 100644
index 0000000000000000000000000000000000000000..903ef8746fad78fe42cb43fa42466fcfdf7bd6eb
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_9a62b46e99f2dc1e.sql
@@ -0,0 +1,23 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_9a62b46e99f2dc1e
+-- problem_id: v2p_n9_8f75b5420170d1c4
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+  "feature_9",
+  "feature_11",
+  SUM(CAST("feature_10" AS REAL)) AS total_measure,
+  SUM(CAST("feature_10" AS REAL)) * 100.0
+    / SUM(SUM(CAST("feature_10" AS REAL))) OVER (PARTITION BY "feature_9") AS share_within_group
+FROM "n9"
+GROUP BY "feature_9", "feature_11"
+ORDER BY share_within_group DESC
+LIMIT 10;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_9c8e90dc3daf9774.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_9c8e90dc3daf9774.sql
new file mode 100644
index 0000000000000000000000000000000000000000..ae8acf3e0b8ee63a8cf5860e786bacce8c17b702
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_9c8e90dc3daf9774.sql
@@ -0,0 +1,28 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: value_imbalance_profile
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_cardinality_distinct_share_profile
+-- query_record_id: v2q_n9_9c8e90dc3daf9774
+-- problem_id: v2p_n9_5838c767b8fef0aa
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_8" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_8"
+), ranked AS (
+    SELECT
+        value_label,
+        support,
+        CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+        SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support
+    FROM grouped
+)
+SELECT *
+FROM ranked
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_9cb4a0a0192b45c0.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_9cb4a0a0192b45c0.sql
new file mode 100644
index 0000000000000000000000000000000000000000..60e00a4e951d11eb5c7a85bae997b3e7c2f885a2
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_9cb4a0a0192b45c0.sql
@@ -0,0 +1,20 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_tail_low_support_group_count_v2
+-- query_record_id: v2q_n9_9cb4a0a0192b45c0
+-- problem_id: v2p_n9_be44fd477ab114ef
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+    "feature_7",
+    COUNT(*) AS "support"
+FROM "n9"
+GROUP BY "feature_7"
+ORDER BY "support" ASC, "feature_7"
+LIMIT 15;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_9e6f038061c97750.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_9e6f038061c97750.sql
new file mode 100644
index 0000000000000000000000000000000000000000..8bf4b92d802a16f2dadf4d75bbd4c136da25fe3f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_9e6f038061c97750.sql
@@ -0,0 +1,41 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_n9_9e6f038061c97750
+-- problem_id: v2p_n9_bc8cb896c6617d43
+-- realization_mode: agent
+-- source_kind: agent
+WITH "ranked" AS (
+  SELECT
+    "feature_2",
+    CAST("feature_7" AS REAL) AS "measure_value",
+    ROW_NUMBER() OVER (
+      PARTITION BY "feature_2"
+      ORDER BY CAST("feature_7" AS REAL)
+    ) AS "rn",
+    COUNT(*) OVER (PARTITION BY "feature_2") AS "cnt"
+  FROM "n9"
+  WHERE "feature_2" IS NOT NULL
+    AND "feature_7" IS NOT NULL
+),
+"thresholded" AS (
+  SELECT
+    "feature_2",
+    "measure_value",
+    "rn",
+    CAST(((95 * "cnt") + 99) / 100 AS INTEGER) AS "target_rn"
+  FROM "ranked"
+)
+SELECT
+  "feature_2",
+  MIN("measure_value") AS "percentile_measure"
+FROM "thresholded"
+WHERE "rn" >= "target_rn"
+GROUP BY "feature_2"
+ORDER BY "percentile_measure" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_9ec07526fd321cfd.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_9ec07526fd321cfd.sql
new file mode 100644
index 0000000000000000000000000000000000000000..a75c89972cc84aa73cc1a48ba74560f73ae0b2e9
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_9ec07526fd321cfd.sql
@@ -0,0 +1,18 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: direction_consistency
+-- intended_facet_id: conditional_rate_shift
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_m4_group_condition_rate
+-- query_record_id: v2q_n9_9ec07526fd321cfd
+-- problem_id: v2p_n9_f73f9789bbf1c976
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_15",
+       AVG(CASE WHEN "class" = '2' THEN 1 ELSE 0 END) AS condition_rate
+FROM "n9"
+GROUP BY "feature_15"
+ORDER BY condition_rate DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_9f9eb99ee7644eed.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_9f9eb99ee7644eed.sql
new file mode 100644
index 0000000000000000000000000000000000000000..81685b52de5873700bad66b8867013679a97b28d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_9f9eb99ee7644eed.sql
@@ -0,0 +1,20 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_set_consistency
+-- intended_facet_id: low_support_extremes
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_tail_low_support_group_count_v2
+-- query_record_id: v2q_n9_9f9eb99ee7644eed
+-- problem_id: v2p_n9_511ca8d605f10420
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+    "feature_8",
+    COUNT(*) AS "support"
+FROM "n9"
+GROUP BY "feature_8"
+ORDER BY "support" ASC, "feature_8"
+LIMIT 16;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_a0c39fbd259bf92e.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_a0c39fbd259bf92e.sql
new file mode 100644
index 0000000000000000000000000000000000000000..c73336e2f787e410b22570231fb7f1b0aaa59a53
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_a0c39fbd259bf92e.sql
@@ -0,0 +1,24 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: direction_consistency
+-- intended_facet_id: conditional_rate_shift
+-- variant_semantic_role: contrastive_conditional_view
+-- template_id: tpl_m4_group_ratio_two_conditions
+-- query_record_id: v2q_n9_a0c39fbd259bf92e
+-- problem_id: v2p_n9_2196724412659ac6
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+    SELECT "feature_8",
+           SUM(CASE WHEN "class" = '2' THEN 1 ELSE 0 END) AS numerator_count,
+           SUM(CASE WHEN "class" = '4' THEN 1 ELSE 0 END) AS denominator_count
+    FROM "n9"
+    GROUP BY "feature_8"
+)
+SELECT "feature_8",
+       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio
+FROM grouped
+ORDER BY condition_ratio DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_a0d0df6c31921147.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_a0d0df6c31921147.sql
new file mode 100644
index 0000000000000000000000000000000000000000..e6c5d6e0e851d773192bf6dc9185defec589e07e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_a0d0df6c31921147.sql
@@ -0,0 +1,15 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_set_consistency
+-- intended_facet_id: low_support_extremes
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_threshold_rarity_cdf
+-- query_record_id: v2q_n9_a0d0df6c31921147
+-- problem_id: v2p_n9_12181171f623022a
+-- realization_mode: agent
+-- source_kind: agent
+SELECT AVG(CASE WHEN CAST("feature_1" AS REAL) <= 65.0 THEN 1 ELSE 0 END) AS "empirical_cdf_at_threshold"
+FROM "n9";
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_a23b19dfa3304199.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_a23b19dfa3304199.sql
new file mode 100644
index 0000000000000000000000000000000000000000..7c2987e7b92284114736059b9b5de3432eccff71
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_a23b19dfa3304199.sql
@@ -0,0 +1,38 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_n9_a23b19dfa3304199
+-- problem_id: v2p_n9_7452745ed429bbbf
+-- realization_mode: agent
+-- source_kind: agent
+WITH "ranked" AS (
+  SELECT
+    "feature_1",
+    CAST("feature_6" AS REAL) AS "measure_value",
+    ROW_NUMBER() OVER (
+      PARTITION BY "feature_1"
+      ORDER BY CAST("feature_6" AS REAL)
+    ) AS "rn",
+    COUNT(*) OVER (
+      PARTITION BY "feature_1"
+    ) AS "cnt"
+  FROM "n9"
+),
+"percentile_points" AS (
+  SELECT
+    "feature_1",
+    "measure_value" AS "percentile_measure"
+  FROM "ranked"
+  WHERE "rn" = CAST(((95 * "cnt") + 99) / 100 AS INTEGER)
+)
+SELECT
+  "feature_1",
+  "percentile_measure"
+FROM "percentile_points"
+ORDER BY "percentile_measure" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_a5b87ec462d5b0c3.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_a5b87ec462d5b0c3.sql
new file mode 100644
index 0000000000000000000000000000000000000000..bd96801589518d8ac1e9a49609d35c07182640da
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_a5b87ec462d5b0c3.sql
@@ -0,0 +1,18 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: direction_consistency
+-- intended_facet_id: conditional_rate_shift
+-- variant_semantic_role: within_group_proportion
+-- template_id: tpl_m4_group_condition_rate
+-- query_record_id: v2q_n9_a5b87ec462d5b0c3
+-- problem_id: v2p_n9_51b0809e6de3dd52
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_15",
+       AVG(CASE WHEN "class" = '4' THEN 1 ELSE 0 END) AS "condition_rate"
+FROM "n9"
+GROUP BY "feature_15"
+ORDER BY "condition_rate" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_a74cb57be4775838.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_a74cb57be4775838.sql
new file mode 100644
index 0000000000000000000000000000000000000000..3ba754e67d7d5bac2e06770f9df3b100f0fe4b6a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_a74cb57be4775838.sql
@@ -0,0 +1,31 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_tpch_relative_total_threshold
+-- query_record_id: v2q_n9_a74cb57be4775838
+-- problem_id: v2p_n9_10c0c86611857971
+-- realization_mode: agent
+-- source_kind: agent
+WITH "grouped" AS (
+  SELECT
+    "feature_12",
+    SUM(CAST("feature_16" AS REAL)) AS "group_value"
+  FROM "n9"
+  GROUP BY "feature_12"
+),
+"total" AS (
+  SELECT SUM("group_value") AS "total_value"
+  FROM "grouped"
+)
+SELECT
+  "grouped"."feature_12",
+  "grouped"."group_value"
+FROM "grouped"
+CROSS JOIN "total"
+WHERE "grouped"."group_value" > "total"."total_value" * 0.05
+ORDER BY "grouped"."group_value" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_a7d1ea22b39647cc.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_a7d1ea22b39647cc.sql
new file mode 100644
index 0000000000000000000000000000000000000000..beb975229c93252b9fb799edba6584ff477de178
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_a7d1ea22b39647cc.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_rank_order
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_n9_a7d1ea22b39647cc
+-- problem_id: v2p_n9_1c5f3c8023413fb5
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_1", SUM(CAST("feature_1" AS REAL)) AS "total_measure"
+FROM "n9"
+GROUP BY "feature_1"
+ORDER BY "total_measure" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_a84af20ba7cbfc88.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_a84af20ba7cbfc88.sql
new file mode 100644
index 0000000000000000000000000000000000000000..7cab5dffdc2a7d2b788e967c32482088524019d1
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_a84af20ba7cbfc88.sql
@@ -0,0 +1,28 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: value_imbalance_profile
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_cardinality_distinct_share_profile
+-- query_record_id: v2q_n9_a84af20ba7cbfc88
+-- problem_id: v2p_n9_d512f1c2b24f15cb
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_13" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_13"
+), ranked AS (
+    SELECT
+        value_label,
+        support,
+        CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+        SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support
+    FROM grouped
+)
+SELECT *
+FROM ranked
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_afe7268b45844569.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_afe7268b45844569.sql
new file mode 100644
index 0000000000000000000000000000000000000000..192ac50ebeade6954e3ad52d993d07c3caccffaa
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_afe7268b45844569.sql
@@ -0,0 +1,24 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: direction_consistency
+-- intended_facet_id: conditional_rate_shift
+-- variant_semantic_role: contrastive_conditional_view
+-- template_id: tpl_m4_group_ratio_two_conditions
+-- query_record_id: v2q_n9_afe7268b45844569
+-- problem_id: v2p_n9_d413f72fa4117bbc
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+    SELECT "feature_10",
+           SUM(CASE WHEN "class" = '2' THEN 1 ELSE 0 END) AS numerator_count,
+           SUM(CASE WHEN "class" = '4' THEN 1 ELSE 0 END) AS denominator_count
+    FROM "n9"
+    GROUP BY "feature_10"
+)
+SELECT "feature_10",
+       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio
+FROM grouped
+ORDER BY condition_ratio DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_b4b5dd5e9a74aa20.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_b4b5dd5e9a74aa20.sql
new file mode 100644
index 0000000000000000000000000000000000000000..46ec2195bcc2863a42b0f52942bfd03241b66ad0
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_b4b5dd5e9a74aa20.sql
@@ -0,0 +1,18 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: direction_consistency
+-- intended_facet_id: conditional_rate_shift
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_m4_group_condition_rate
+-- query_record_id: v2q_n9_b4b5dd5e9a74aa20
+-- problem_id: v2p_n9_09e24e8e16328141
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "class",
+       AVG(CASE WHEN "class" = '2' THEN 1 ELSE 0 END) AS condition_rate
+FROM "n9"
+GROUP BY "class"
+ORDER BY condition_rate DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_b4e0cf02e50549ea.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_b4e0cf02e50549ea.sql
new file mode 100644
index 0000000000000000000000000000000000000000..e102f94a46ef0d3098661cbfbfc614f11eb2c108
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_b4e0cf02e50549ea.sql
@@ -0,0 +1,26 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_tpch_relative_total_threshold
+-- query_record_id: v2q_n9_b4e0cf02e50549ea
+-- problem_id: v2p_n9_96325291073298c2
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+    SELECT "feature_5", SUM(CAST("feature_9" AS REAL)) AS group_value
+    FROM "n9"
+    GROUP BY "feature_5"
+), total AS (
+    SELECT SUM(group_value) AS total_value
+    FROM grouped
+)
+SELECT g."feature_5", g.group_value
+FROM grouped AS g
+CROSS JOIN total AS t
+WHERE g.group_value > t.total_value * 0.1
+ORDER BY g.group_value DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_b60ec2bf50067512.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_b60ec2bf50067512.sql
new file mode 100644
index 0000000000000000000000000000000000000000..0bbe9f9720976bce5cede16f755056896bcee061
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_b60ec2bf50067512.sql
@@ -0,0 +1,28 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: support_concentration
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_cardinality_distinct_share_profile
+-- query_record_id: v2q_n9_b60ec2bf50067512
+-- problem_id: v2p_n9_b8ed6689c276d13f
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_15" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_15"
+), ranked AS (
+    SELECT
+        value_label,
+        support,
+        CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+        SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support
+    FROM grouped
+)
+SELECT *
+FROM ranked
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_b84da52a29d01370.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_b84da52a29d01370.sql
new file mode 100644
index 0000000000000000000000000000000000000000..0edb2f93dc51d4338d0fa300c4b641f900f835b3
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_b84da52a29d01370.sql
@@ -0,0 +1,25 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: value_imbalance_profile
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_cardinality_support_rank_profile
+-- query_record_id: v2q_n9_b84da52a29d01370
+-- problem_id: v2p_n9_eab9655253da74ea
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_16" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_16"
+)
+SELECT
+    value_label,
+    support,
+    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank
+FROM grouped
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_bb8de1438d36f116.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_bb8de1438d36f116.sql
new file mode 100644
index 0000000000000000000000000000000000000000..530574830ca77fa6717c55333cb93bf607fb4637
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_bb8de1438d36f116.sql
@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: high_cardinality_response_stability
+-- intended_facet_id: target_cardinality_cross_section
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_cardinality_high_card_response_stability
+-- query_record_id: v2q_n9_bb8de1438d36f116
+-- problem_id: v2p_n9_f8bbcc636b2d27e6
+-- realization_mode: deterministic
+-- source_kind: deterministic
+SELECT
+    "feature_13",
+    COUNT(*) AS support,
+    AVG("feature_2") AS avg_response
+FROM "n9"
+GROUP BY "feature_13"
+HAVING COUNT(*) >= 5.0
+ORDER BY support DESC, avg_response DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_bd47bbbc13b96c1a.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_bd47bbbc13b96c1a.sql
new file mode 100644
index 0000000000000000000000000000000000000000..338886e804e52a06b2fdf3bb313ea75295c5eb1e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_bd47bbbc13b96c1a.sql
@@ -0,0 +1,22 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_bd47bbbc13b96c1a
+-- problem_id: v2p_n9_c68367ca9930b295
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+  "feature_11",
+  "feature_13",
+  SUM(CAST("feature_12" AS REAL)) AS total_measure,
+  SUM(CAST("feature_12" AS REAL)) * 100.0 / SUM(SUM(CAST("feature_12" AS REAL))) OVER (PARTITION BY "feature_11") AS share_within_group
+FROM "n9"
+GROUP BY "feature_11", "feature_13"
+ORDER BY share_within_group DESC
+LIMIT 12;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_be1ab57c80f13a2a.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_be1ab57c80f13a2a.sql
new file mode 100644
index 0000000000000000000000000000000000000000..5c3685505604f95c4c2a54f389c61fb02463b04a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_be1ab57c80f13a2a.sql
@@ -0,0 +1,28 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: value_imbalance_profile
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_cardinality_distinct_share_profile
+-- query_record_id: v2q_n9_be1ab57c80f13a2a
+-- problem_id: v2p_n9_ed51d6f34721a2ac
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_2" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_2"
+), ranked AS (
+    SELECT
+        value_label,
+        support,
+        CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+        SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support
+    FROM grouped
+)
+SELECT *
+FROM ranked
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_bea6c4bb7fa71d20.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_bea6c4bb7fa71d20.sql
new file mode 100644
index 0000000000000000000000000000000000000000..dbcf903afa70dad92cfbef2281c8fee9040bc443
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_bea6c4bb7fa71d20.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_conditional_contrast
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_n9_bea6c4bb7fa71d20
+-- problem_id: v2p_n9_1099886d4a54da63
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_8", SUM(CAST("feature_8" AS NUMERIC)) AS "total_measure"
+FROM "n9"
+GROUP BY "feature_8"
+ORDER BY "total_measure" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_bf3884ef1ab0617a.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_bf3884ef1ab0617a.sql
new file mode 100644
index 0000000000000000000000000000000000000000..05588908563a396c7680acc6ba847eb712ae5f29
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_bf3884ef1ab0617a.sql
@@ -0,0 +1,59 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_n9_bf3884ef1ab0617a
+-- problem_id: v2p_n9_6cbcdd48dfecd17b
+-- realization_mode: agent
+-- source_kind: agent
+WITH "ordered" AS (
+  SELECT
+    "feature_5" AS "group_col",
+    CAST("feature_10" AS REAL) AS "measure_col",
+    ROW_NUMBER() OVER (
+      PARTITION BY "feature_5"
+      ORDER BY CAST("feature_10" AS REAL)
+    ) AS "rn",
+    COUNT(*) OVER (
+      PARTITION BY "feature_5"
+    ) AS "cnt"
+  FROM "n9"
+  WHERE "feature_5" IS NOT NULL
+    AND "feature_10" IS NOT NULL
+),
+"percentile_prep" AS (
+  SELECT
+    "group_col",
+    "measure_col",
+    "rn",
+    "cnt",
+    (0.95 * ("cnt" - 1)) + 1.0 AS "pos",
+    CAST((0.95 * ("cnt" - 1)) + 1.0 AS INTEGER) AS "lower_rn",
+    CASE
+      WHEN ((0.95 * ("cnt" - 1)) + 1.0) = CAST((0.95 * ("cnt" - 1)) + 1.0 AS INTEGER)
+        THEN CAST((0.95 * ("cnt" - 1)) + 1.0 AS INTEGER)
+      ELSE CAST((0.95 * ("cnt" - 1)) + 1.0 AS INTEGER) + 1
+    END AS "upper_rn"
+  FROM "ordered"
+  WHERE "cnt" >= 5
+)
+SELECT
+  "group_col" AS "feature_5",
+  CASE
+    WHEN MAX("lower_rn") = MAX("upper_rn") THEN
+      MAX(CASE WHEN "rn" = "lower_rn" THEN "measure_col" END)
+    ELSE
+      MAX(CASE WHEN "rn" = "lower_rn" THEN "measure_col" END) +
+      (MAX("pos") - MAX("lower_rn")) * (
+        MAX(CASE WHEN "rn" = "upper_rn" THEN "measure_col" END) -
+        MAX(CASE WHEN "rn" = "lower_rn" THEN "measure_col" END)
+      )
+  END AS "percentile_measure"
+FROM "percentile_prep"
+GROUP BY "group_col"
+ORDER BY "percentile_measure" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_bf7c17439abc0503.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_bf7c17439abc0503.sql
new file mode 100644
index 0000000000000000000000000000000000000000..b1196acf4a1a709715ebce3398d7becf273ad45e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_bf7c17439abc0503.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_n9_bf7c17439abc0503
+-- problem_id: v2p_n9_e3cc197b4e8de94f
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_4", SUM(CAST("feature_4" AS REAL)) AS total_measure
+FROM "n9"
+GROUP BY "feature_4"
+ORDER BY total_measure DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_c3e0fbce48684752.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_c3e0fbce48684752.sql
new file mode 100644
index 0000000000000000000000000000000000000000..7d987c25fc183635dba0aec886897a6940471c34
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_c3e0fbce48684752.sql
@@ -0,0 +1,26 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: filtered_stable_view
+-- template_id: tpl_tpch_relative_total_threshold
+-- query_record_id: v2q_n9_c3e0fbce48684752
+-- problem_id: v2p_n9_38055fcac0a748d7
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+    SELECT "feature_6", SUM(CAST("feature_10" AS REAL)) AS group_value
+    FROM "n9"
+    GROUP BY "feature_6"
+), total AS (
+    SELECT SUM(group_value) AS total_value
+    FROM grouped
+)
+SELECT g."feature_6", g.group_value
+FROM grouped AS g
+CROSS JOIN total AS t
+WHERE g.group_value > t.total_value * 0.1
+ORDER BY g.group_value DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_c421da0d9c0dc129.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_c421da0d9c0dc129.sql
new file mode 100644
index 0000000000000000000000000000000000000000..1ee3100c06bd5bd317110c453e50efcb162942f9
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_c421da0d9c0dc129.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: subgroup_size_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_clickbench_group_count
+-- query_record_id: v2q_n9_c421da0d9c0dc129
+-- problem_id: v2p_n9_f2492a490073b82a
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_14", COUNT(*) AS row_count
+FROM "n9"
+GROUP BY "feature_14"
+ORDER BY row_count DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_c429c829ba4276ee.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_c429c829ba4276ee.sql
new file mode 100644
index 0000000000000000000000000000000000000000..2ccf5cf4a649726d5f0e7c2e019b2885e8be7f25
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_c429c829ba4276ee.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_rank_order
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_n9_c429c829ba4276ee
+-- problem_id: v2p_n9_47617819d122ce03
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_4", SUM(CAST("feature_4" AS INTEGER)) AS "total_measure"
+FROM "n9"
+GROUP BY "feature_4"
+ORDER BY "total_measure" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_c518757c15e9b81c.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_c518757c15e9b81c.sql
new file mode 100644
index 0000000000000000000000000000000000000000..8b7aceeb2bd30548394e261fb0a327519f3c15df
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_c518757c15e9b81c.sql
@@ -0,0 +1,18 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: slice_level_consistency
+-- intended_facet_id: conditional_interaction_hotspots
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_c2_filtered_group_count_2d
+-- query_record_id: v2q_n9_c518757c15e9b81c
+-- problem_id: v2p_n9_beb718169fa657f3
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_4", "feature_8", COUNT(*) AS row_count
+FROM "n9"
+WHERE CAST("feature_15" AS REAL) >= 100.0
+GROUP BY "feature_4", "feature_8"
+ORDER BY row_count DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_c5c4236c1cb3293f.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_c5c4236c1cb3293f.sql
new file mode 100644
index 0000000000000000000000000000000000000000..1d3b3b526926ffbfe6a34495a244b9701ad72e48
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_c5c4236c1cb3293f.sql
@@ -0,0 +1,15 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_set_consistency
+-- intended_facet_id: low_support_extremes
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_threshold_rarity_cdf
+-- query_record_id: v2q_n9_c5c4236c1cb3293f
+-- problem_id: v2p_n9_6237790a55ada2a9
+-- realization_mode: agent
+-- source_kind: agent
+SELECT AVG(CASE WHEN CAST("feature_3" AS REAL) <= 58.0 THEN 1 ELSE 0 END) AS "empirical_cdf_at_threshold"
+FROM "n9";
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_c6ca8dcc4bd2d03c.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_c6ca8dcc4bd2d03c.sql
new file mode 100644
index 0000000000000000000000000000000000000000..0ad29280234c4d11effd8c81ab87a53faf15d791
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_c6ca8dcc4bd2d03c.sql
@@ -0,0 +1,26 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: filtered_stable_view
+-- template_id: tpl_tpch_relative_total_threshold
+-- query_record_id: v2q_n9_c6ca8dcc4bd2d03c
+-- problem_id: v2p_n9_93c326343243397b
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+    SELECT "feature_13", SUM(CAST("feature_1" AS REAL)) AS group_value
+    FROM "n9"
+    GROUP BY "feature_13"
+), total AS (
+    SELECT SUM(group_value) AS total_value
+    FROM grouped
+)
+SELECT g."feature_13", g.group_value
+FROM grouped AS g
+CROSS JOIN total AS t
+WHERE g.group_value > t.total_value * 0.05
+ORDER BY g.group_value DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_c9c0bd481266cabb.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_c9c0bd481266cabb.sql
new file mode 100644
index 0000000000000000000000000000000000000000..4f765141bae1400d69d6db66411fda33e377b7ca
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_c9c0bd481266cabb.sql
@@ -0,0 +1,64 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_n9_c9c0bd481266cabb
+-- problem_id: v2p_n9_4d20ee7acaa09e02
+-- realization_mode: agent
+-- source_kind: agent
+WITH "ranked" AS (
+  SELECT
+    "feature_8" AS "group_value",
+    CAST("feature_13" AS REAL) AS "measure_value",
+    ROW_NUMBER() OVER (
+      PARTITION BY "feature_8"
+      ORDER BY CAST("feature_13" AS REAL)
+    ) AS "rn",
+    COUNT(*) OVER (
+      PARTITION BY "feature_8"
+    ) AS "n"
+  FROM "n9"
+  WHERE "feature_8" IS NOT NULL
+    AND "feature_13" IS NOT NULL
+),
+"prep" AS (
+  SELECT
+    "group_value",
+    "measure_value",
+    "rn",
+    "n",
+    (1.0 + 0.9 * ("n" - 1)) AS "r",
+    CAST((1.0 + 0.9 * ("n" - 1)) AS INTEGER) AS "lo",
+    CASE
+      WHEN (1.0 + 0.9 * ("n" - 1)) = CAST((1.0 + 0.9 * ("n" - 1)) AS INTEGER)
+        THEN CAST((1.0 + 0.9 * ("n" - 1)) AS INTEGER)
+      ELSE CAST((1.0 + 0.9 * ("n" - 1)) AS INTEGER) + 1
+    END AS "hi"
+  FROM "ranked"
+),
+"percentiles" AS (
+  SELECT
+    "group_value",
+    CASE
+      WHEN MAX("lo") = MAX("hi") THEN MAX(CASE WHEN "rn" = "lo" THEN "measure_value" END)
+      ELSE
+        MAX(CASE WHEN "rn" = "lo" THEN "measure_value" END) +
+        (MAX("r") - MAX("lo")) * (
+          MAX(CASE WHEN "rn" = "hi" THEN "measure_value" END) -
+          MAX(CASE WHEN "rn" = "lo" THEN "measure_value" END)
+        )
+    END AS "percentile_measure"
+  FROM "prep"
+  GROUP BY "group_value"
+  HAVING MAX("n") >= 5
+)
+SELECT
+  "group_value" AS "feature_8",
+  "percentile_measure"
+FROM "percentiles"
+ORDER BY "percentile_measure" DESC, "feature_8";
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_ca6673e8d6820e54.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_ca6673e8d6820e54.sql
new file mode 100644
index 0000000000000000000000000000000000000000..593ac495753fcf99e369fbc601c6ab07b9a5832f
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_ca6673e8d6820e54.sql
@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: high_cardinality_response_stability
+-- intended_facet_id: target_cardinality_cross_section
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_cardinality_high_card_response_stability
+-- query_record_id: v2q_n9_ca6673e8d6820e54
+-- problem_id: v2p_n9_1c8612c39e7dcac4
+-- realization_mode: deterministic
+-- source_kind: deterministic
+SELECT
+    "feature_5",
+    COUNT(*) AS support,
+    AVG("feature_4") AS avg_response
+FROM "n9"
+GROUP BY "feature_5"
+HAVING COUNT(*) >= 5.0
+ORDER BY support DESC, avg_response DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_cb93d30f6e25f3a4.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_cb93d30f6e25f3a4.sql
new file mode 100644
index 0000000000000000000000000000000000000000..3ba6b8f64e0c4a8e7c681606faf2189de1588b28
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_cb93d30f6e25f3a4.sql
@@ -0,0 +1,19 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_cb93d30f6e25f3a4
+-- problem_id: v2p_n9_f7b916dc2286e142
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "class", "feature_3",
+       SUM(CAST("feature_2" AS REAL)) AS total_measure,
+       SUM(CAST("feature_2" AS REAL)) * 100.0 / SUM(SUM(CAST("feature_2" AS REAL))) OVER (PARTITION BY "class") AS share_within_group
+FROM "n9"
+GROUP BY "class", "feature_3"
+ORDER BY share_within_group DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d0a697d698aaf8b9.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d0a697d698aaf8b9.sql
new file mode 100644
index 0000000000000000000000000000000000000000..6cb82512e0633732de71a164e21b7da5d5b5b8ee
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d0a697d698aaf8b9.sql
@@ -0,0 +1,19 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_d0a697d698aaf8b9
+-- problem_id: v2p_n9_69c2f72812dac872
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_12", "feature_14",
+       SUM(CAST("feature_13" AS REAL)) AS total_measure,
+       SUM(CAST("feature_13" AS REAL)) * 100.0 / SUM(SUM(CAST("feature_13" AS REAL))) OVER (PARTITION BY "feature_12") AS share_within_group
+FROM "n9"
+GROUP BY "feature_12", "feature_14"
+ORDER BY share_within_group DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d232a388de08c479.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d232a388de08c479.sql
new file mode 100644
index 0000000000000000000000000000000000000000..8373903c2a80ea2379f04d75fb44cf8f6431777a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d232a388de08c479.sql
@@ -0,0 +1,19 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_m4_group_condition_rate
+-- query_record_id: v2q_n9_d232a388de08c479
+-- problem_id: v2p_n9_7f52ea62302bcf9f
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+  "feature_14",
+  AVG(CASE WHEN "class" = '4' THEN 1 ELSE 0 END) AS "condition_rate"
+FROM "n9"
+GROUP BY "feature_14"
+ORDER BY "condition_rate" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d39556c99d6ba666.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d39556c99d6ba666.sql
new file mode 100644
index 0000000000000000000000000000000000000000..1e2b544bf19b4ea9d1175fb8e9b49e24bdbc8461
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d39556c99d6ba666.sql
@@ -0,0 +1,26 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: filtered_stable_view
+-- template_id: tpl_tpch_relative_total_threshold
+-- query_record_id: v2q_n9_d39556c99d6ba666
+-- problem_id: v2p_n9_7bf5f7edac33df01
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+    SELECT "feature_14", SUM(CAST("feature_2" AS REAL)) AS group_value
+    FROM "n9"
+    GROUP BY "feature_14"
+), total AS (
+    SELECT SUM(group_value) AS total_value
+    FROM grouped
+)
+SELECT g."feature_14", g.group_value
+FROM grouped AS g
+CROSS JOIN total AS t
+WHERE g.group_value > t.total_value * 0.1
+ORDER BY g.group_value DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d4355a2605bef303.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d4355a2605bef303.sql
new file mode 100644
index 0000000000000000000000000000000000000000..d8cce86c15127040c4c30996ddb5603e578f64cd
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d4355a2605bef303.sql
@@ -0,0 +1,28 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: value_imbalance_profile
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_cardinality_distinct_share_profile
+-- query_record_id: v2q_n9_d4355a2605bef303
+-- problem_id: v2p_n9_7eb83550af1e6b99
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_10" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_10"
+), ranked AS (
+    SELECT
+        value_label,
+        support,
+        CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+        SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support
+    FROM grouped
+)
+SELECT *
+FROM ranked
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d62159ffcc757d29.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d62159ffcc757d29.sql
new file mode 100644
index 0000000000000000000000000000000000000000..d2c75196864534dbad8ce9fa53e72b31c97a3f29
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d62159ffcc757d29.sql
@@ -0,0 +1,26 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: filtered_stable_view
+-- template_id: tpl_tpch_relative_total_threshold
+-- query_record_id: v2q_n9_d62159ffcc757d29
+-- problem_id: v2p_n9_fc7583bde9473d0b
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+  SELECT "feature_10", SUM(CAST("feature_14" AS REAL)) AS group_value
+  FROM "n9"
+  GROUP BY "feature_10"
+), total AS (
+  SELECT SUM(group_value) AS total_value
+  FROM grouped
+)
+SELECT g."feature_10", g.group_value
+FROM grouped AS g
+CROSS JOIN total AS t
+WHERE g.group_value > t.total_value * 0.1
+ORDER BY g.group_value DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d64bf21a8efbc3ef.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d64bf21a8efbc3ef.sql
new file mode 100644
index 0000000000000000000000000000000000000000..fe94fb4ea5ba3df745d5bb10b229c2606315b5ba
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d64bf21a8efbc3ef.sql
@@ -0,0 +1,18 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: slice_level_consistency
+-- intended_facet_id: conditional_interaction_hotspots
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_c2_filtered_group_count_2d
+-- query_record_id: v2q_n9_d64bf21a8efbc3ef
+-- problem_id: v2p_n9_5df33407c1f57390
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_4", "feature_11", COUNT(*) AS "row_count"
+FROM "n9"
+WHERE CAST("feature_1" AS REAL) >= 65.0
+GROUP BY "feature_4", "feature_11"
+ORDER BY "row_count" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d66b137ae99dd77e.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d66b137ae99dd77e.sql
new file mode 100644
index 0000000000000000000000000000000000000000..8f77bdfab06fdfcdc42adbf9ccc371ca3443ae7a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d66b137ae99dd77e.sql
@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: within_group_proportion
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_d66b137ae99dd77e
+-- problem_id: v2p_n9_70e0a2b7690171fa
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+  "feature_9",
+  "feature_11",
+  SUM(CAST("feature_10" AS REAL)) AS "total_measure",
+  SUM(CAST("feature_10" AS REAL)) * 100.0 / SUM(SUM(CAST("feature_10" AS REAL))) OVER (PARTITION BY "feature_9") AS "share_within_group"
+FROM "n9"
+GROUP BY "feature_9", "feature_11"
+ORDER BY "share_within_group" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d6ddfc6f63d88a1b.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d6ddfc6f63d88a1b.sql
new file mode 100644
index 0000000000000000000000000000000000000000..11160d0e4daa4ed84e5c938f342dd15fd225a592
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d6ddfc6f63d88a1b.sql
@@ -0,0 +1,26 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_tpch_relative_total_threshold
+-- query_record_id: v2q_n9_d6ddfc6f63d88a1b
+-- problem_id: v2p_n9_787e898de670ace1
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+    SELECT "feature_8", SUM(CAST("feature_12" AS REAL)) AS group_value
+    FROM "n9"
+    GROUP BY "feature_8"
+), total AS (
+    SELECT SUM(group_value) AS total_value
+    FROM grouped
+)
+SELECT g."feature_8", g.group_value
+FROM grouped AS g
+CROSS JOIN total AS t
+WHERE g.group_value > t.total_value * 0.05
+ORDER BY g.group_value DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d86e59f7cdb11a2b.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d86e59f7cdb11a2b.sql
new file mode 100644
index 0000000000000000000000000000000000000000..49b692ef2fbd5eab159085a06ed8768f4bd01359
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d86e59f7cdb11a2b.sql
@@ -0,0 +1,19 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: direction_consistency
+-- intended_facet_id: conditional_rate_shift
+-- variant_semantic_role: filtered_stable_view
+-- template_id: tpl_m4_window_partition_avg
+-- query_record_id: v2q_n9_d86e59f7cdb11a2b
+-- problem_id: v2p_n9_a72f66bf71e5201f
+-- realization_mode: agent
+-- source_kind: agent
+SELECT DISTINCT "class",
+       AVG(CAST("feature_8" AS REAL)) OVER (PARTITION BY "class") AS avg_measure
+FROM "n9"
+WHERE "class" IS NOT NULL
+  AND "feature_8" IS NOT NULL
+ORDER BY avg_measure DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d916104f5c417d43.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d916104f5c417d43.sql
new file mode 100644
index 0000000000000000000000000000000000000000..aa811ce2cae1fb5f8e94b19310be93180169f25d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_d916104f5c417d43.sql
@@ -0,0 +1,45 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_n9_d916104f5c417d43
+-- problem_id: v2p_n9_18e44b5c3caecf62
+-- realization_mode: agent
+-- source_kind: agent
+WITH "ranked" AS (
+  SELECT
+    "class",
+    CAST("feature_5" AS REAL) AS "measure_value",
+    ROW_NUMBER() OVER (
+      PARTITION BY "class"
+      ORDER BY CAST("feature_5" AS REAL)
+    ) AS "rn",
+    COUNT(*) OVER (
+      PARTITION BY "class"
+    ) AS "cnt"
+  FROM "n9"
+  WHERE "class" IS NOT NULL
+    AND "feature_5" IS NOT NULL
+),
+"percentile_points" AS (
+  SELECT
+    "class",
+    "measure_value" AS "percentile_measure",
+    ROW_NUMBER() OVER (
+      PARTITION BY "class"
+      ORDER BY "rn"
+    ) AS "pick_rn"
+  FROM "ranked"
+  WHERE "rn" >= CAST(((95 * "cnt") + 99) / 100 AS INTEGER)
+)
+SELECT
+  "class",
+  "percentile_measure"
+FROM "percentile_points"
+WHERE "pick_rn" = 1
+ORDER BY "percentile_measure" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_daceb7717246fb73.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_daceb7717246fb73.sql
new file mode 100644
index 0000000000000000000000000000000000000000..2038cd3180047cb87d6d35045c9bed23d323756d
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_daceb7717246fb73.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_n9_daceb7717246fb73
+-- problem_id: v2p_n9_c962513f809f95f9
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_7", SUM(CAST("feature_7" AS REAL)) AS total_measure
+FROM "n9"
+GROUP BY "feature_7"
+ORDER BY total_measure DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_dfa9a6f1954c3b7e.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_dfa9a6f1954c3b7e.sql
new file mode 100644
index 0000000000000000000000000000000000000000..050cc0e132b14a250b3e688ab50c772552d817ed
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_dfa9a6f1954c3b7e.sql
@@ -0,0 +1,68 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_n9_dfa9a6f1954c3b7e
+-- problem_id: v2p_n9_20d3e6b3e42a8672
+-- realization_mode: agent
+-- source_kind: agent
+WITH "ordered" AS (
+  SELECT
+    "feature_3" AS "feature_3",
+    CAST("feature_8" AS REAL) AS "measure_value",
+    ROW_NUMBER() OVER (
+      PARTITION BY "feature_3"
+      ORDER BY CAST("feature_8" AS REAL)
+    ) AS "rn",
+    COUNT(*) OVER (
+      PARTITION BY "feature_3"
+    ) AS "n"
+  FROM "n9"
+  WHERE "feature_3" IS NOT NULL
+    AND "feature_8" IS NOT NULL
+),
+"eligible" AS (
+  SELECT DISTINCT
+    "feature_3",
+    "n",
+    (1.0 + 0.9 * ("n" - 1)) AS "target_rn",
+    CAST((1.0 + 0.9 * ("n" - 1)) AS INTEGER) AS "frn",
+    CASE
+      WHEN (1.0 + 0.9 * ("n" - 1)) = CAST((1.0 + 0.9 * ("n" - 1)) AS INTEGER)
+        THEN CAST((1.0 + 0.9 * ("n" - 1)) AS INTEGER)
+      ELSE CAST((1.0 + 0.9 * ("n" - 1)) AS INTEGER) + 1
+    END AS "crn"
+  FROM "ordered"
+  WHERE "n" >= 5
+),
+"picked" AS (
+  SELECT
+    o."feature_3",
+    e."target_rn",
+    e."frn",
+    e."crn",
+    MAX(CASE WHEN o."rn" = e."frn" THEN o."measure_value" END) AS "lower_value",
+    MAX(CASE WHEN o."rn" = e."crn" THEN o."measure_value" END) AS "upper_value"
+  FROM "ordered" AS o
+  INNER JOIN "eligible" AS e
+    ON o."feature_3" = e."feature_3"
+  GROUP BY
+    o."feature_3",
+    e."target_rn",
+    e."frn",
+    e."crn"
+)
+SELECT
+  "feature_3",
+  CASE
+    WHEN "frn" = "crn" THEN "lower_value"
+    ELSE "lower_value" + ("target_rn" - "frn") * ("upper_value" - "lower_value")
+  END AS "percentile_measure"
+FROM "picked"
+ORDER BY "percentile_measure" DESC
+LIMIT 12;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_dfc49103d5d0e0cf.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_dfc49103d5d0e0cf.sql
new file mode 100644
index 0000000000000000000000000000000000000000..b524ab64f4c81fc51b2418b4210429a83d9b50f9
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_dfc49103d5d0e0cf.sql
@@ -0,0 +1,24 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: direction_consistency
+-- intended_facet_id: conditional_rate_shift
+-- variant_semantic_role: contrastive_conditional_view
+-- template_id: tpl_m4_group_ratio_two_conditions
+-- query_record_id: v2q_n9_dfc49103d5d0e0cf
+-- problem_id: v2p_n9_fbe5168fa549f985
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+    SELECT "feature_4",
+           SUM(CASE WHEN "class" = '2' THEN 1 ELSE 0 END) AS numerator_count,
+           SUM(CASE WHEN "class" = '4' THEN 1 ELSE 0 END) AS denominator_count
+    FROM "n9"
+    GROUP BY "feature_4"
+)
+SELECT "feature_4",
+       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio
+FROM grouped
+ORDER BY condition_ratio DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_e1d9a6bafe125200.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_e1d9a6bafe125200.sql
new file mode 100644
index 0000000000000000000000000000000000000000..13745f7f08bd8a810ec9ca0bb9d29b4e30be4085
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_e1d9a6bafe125200.sql
@@ -0,0 +1,22 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: within_group_proportion
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_e1d9a6bafe125200
+-- problem_id: v2p_n9_b521ef087718ecc4
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+  "feature_13",
+  "feature_15",
+  SUM(CAST("feature_14" AS REAL)) AS total_measure,
+  SUM(CAST("feature_14" AS REAL)) * 100.0 / SUM(SUM(CAST("feature_14" AS REAL))) OVER (PARTITION BY "feature_13") AS share_within_group
+FROM "n9"
+GROUP BY "feature_13", "feature_15"
+ORDER BY share_within_group DESC
+LIMIT 19;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_e20292875979cc05.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_e20292875979cc05.sql
new file mode 100644
index 0000000000000000000000000000000000000000..4ab18ea617b2b9f74a77a167ca51988fd65c9c7c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_e20292875979cc05.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: direction_consistency
+-- intended_facet_id: conditional_rate_shift
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_m4_window_partition_avg
+-- query_record_id: v2q_n9_e20292875979cc05
+-- problem_id: v2p_n9_54ae026af1feb860
+-- realization_mode: agent
+-- source_kind: agent
+SELECT DISTINCT "class",
+       AVG(CAST("feature_8" AS REAL)) OVER (PARTITION BY "class") AS avg_measure
+FROM "n9"
+ORDER BY avg_measure DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_e5e996e21b5329e8.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_e5e996e21b5329e8.sql
new file mode 100644
index 0000000000000000000000000000000000000000..3c1fbd55fde015a0873dd956974514aa6c66b90c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_e5e996e21b5329e8.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_rank_order
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_n9_e5e996e21b5329e8
+-- problem_id: v2p_n9_2cb3b041f007ef8f
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_8", SUM(CAST("feature_8" AS REAL)) AS total_measure
+FROM "n9"
+GROUP BY "feature_8"
+ORDER BY total_measure DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_e6c306e2a75a0567.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_e6c306e2a75a0567.sql
new file mode 100644
index 0000000000000000000000000000000000000000..4d1a177c532709b0063d257452da691dbeca7592
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_e6c306e2a75a0567.sql
@@ -0,0 +1,70 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_n9_e6c306e2a75a0567
+-- problem_id: v2p_n9_7cc9699b0756386f
+-- realization_mode: agent
+-- source_kind: agent
+WITH "__base" AS (
+  SELECT
+    "feature_7",
+    CAST("feature_12" AS REAL) AS "measure_value"
+  FROM "n9"
+  WHERE "feature_7" IS NOT NULL
+    AND "feature_12" IS NOT NULL
+),
+"__ordered" AS (
+  SELECT
+    "feature_7",
+    "measure_value",
+    ROW_NUMBER() OVER (
+      PARTITION BY "feature_7"
+      ORDER BY "measure_value"
+    ) AS "rn",
+    COUNT(*) OVER (
+      PARTITION BY "feature_7"
+    ) AS "cnt"
+  FROM "__base"
+),
+"__bounds" AS (
+  SELECT
+    "feature_7",
+    MAX("cnt") AS "cnt",
+    1.0 + (MAX("cnt") - 1.0) * 0.95 AS "pos",
+    CAST(1.0 + (MAX("cnt") - 1.0) * 0.95 AS INTEGER) AS "lower_rn",
+    CAST(1.0 + (MAX("cnt") - 1.0) * 0.95 AS INTEGER) +
+      CASE
+        WHEN (1.0 + (MAX("cnt") - 1.0) * 0.95) > CAST(1.0 + (MAX("cnt") - 1.0) * 0.95 AS INTEGER) THEN 1
+        ELSE 0
+      END AS "upper_rn"
+  FROM "__ordered"
+  GROUP BY "feature_7"
+  HAVING MAX("cnt") >= 5
+)
+SELECT
+  o."feature_7",
+  CASE
+    WHEN b."lower_rn" = b."upper_rn" THEN
+      MAX(CASE WHEN o."rn" = b."lower_rn" THEN o."measure_value" END)
+    ELSE
+      MAX(CASE WHEN o."rn" = b."lower_rn" THEN o."measure_value" END) +
+      (b."pos" - b."lower_rn") * (
+        MAX(CASE WHEN o."rn" = b."upper_rn" THEN o."measure_value" END) -
+        MAX(CASE WHEN o."rn" = b."lower_rn" THEN o."measure_value" END)
+      )
+  END AS "percentile_measure"
+FROM "__ordered" AS o
+JOIN "__bounds" AS b
+  ON o."feature_7" = b."feature_7"
+GROUP BY
+  o."feature_7",
+  b."pos",
+  b."lower_rn",
+  b."upper_rn"
+ORDER BY "percentile_measure" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_e729a248d43a4026.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_e729a248d43a4026.sql
new file mode 100644
index 0000000000000000000000000000000000000000..b72ea71ab89f7be9f6e20c02d42762ad4ae33109
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_e729a248d43a4026.sql
@@ -0,0 +1,18 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: slice_level_consistency
+-- intended_facet_id: conditional_interaction_hotspots
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_c2_filtered_group_count_2d
+-- query_record_id: v2q_n9_e729a248d43a4026
+-- problem_id: v2p_n9_8f6d69eb0851971d
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_4", "feature_9", COUNT(*) AS row_count
+FROM "n9"
+WHERE CAST("feature_16" AS REAL) >= 51.0
+GROUP BY "feature_4", "feature_9"
+ORDER BY row_count DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_e741d950a0d49134.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_e741d950a0d49134.sql
new file mode 100644
index 0000000000000000000000000000000000000000..71140b4db099f38f31d2ca9b11f3acd30a700339
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_e741d950a0d49134.sql
@@ -0,0 +1,25 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: value_imbalance_profile
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_cardinality_support_rank_profile
+-- query_record_id: v2q_n9_e741d950a0d49134
+-- problem_id: v2p_n9_4e02f09e322b137f
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_8" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_8"
+)
+SELECT
+    value_label,
+    support,
+    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank
+FROM grouped
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_e772ce8ed4c8ee71.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_e772ce8ed4c8ee71.sql
new file mode 100644
index 0000000000000000000000000000000000000000..b149535a7027a7ffd335849c829e2d217c2a41c7
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_e772ce8ed4c8ee71.sql
@@ -0,0 +1,28 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: support_concentration
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_cardinality_distinct_share_profile
+-- query_record_id: v2q_n9_e772ce8ed4c8ee71
+-- problem_id: v2p_n9_be52a332eaa20855
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_1" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_1"
+), ranked AS (
+    SELECT
+        value_label,
+        support,
+        CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+        SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support
+    FROM grouped
+)
+SELECT *
+FROM ranked
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_e94aa6e012d8d33c.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_e94aa6e012d8d33c.sql
new file mode 100644
index 0000000000000000000000000000000000000000..5538814f19b6788fa523c2326d676dbf9aa9cfa4
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_e94aa6e012d8d33c.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: slice_level_consistency
+-- intended_facet_id: conditional_interaction_hotspots
+-- variant_semantic_role: filtered_stable_view
+-- template_id: tpl_m4_window_partition_avg
+-- query_record_id: v2q_n9_e94aa6e012d8d33c
+-- problem_id: v2p_n9_f64c6ea983d7118c
+-- realization_mode: agent
+-- source_kind: agent
+SELECT DISTINCT "feature_14",
+       AVG(CAST("feature_5" AS REAL)) OVER (PARTITION BY "feature_14") AS avg_measure
+FROM "n9"
+ORDER BY avg_measure DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_ea89d21353c80cf2.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_ea89d21353c80cf2.sql
new file mode 100644
index 0000000000000000000000000000000000000000..185dd2a39d32af2a5cced719debd2a16d11f273a
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_ea89d21353c80cf2.sql
@@ -0,0 +1,15 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_set_consistency
+-- intended_facet_id: low_support_extremes
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_threshold_rarity_cdf
+-- query_record_id: v2q_n9_ea89d21353c80cf2
+-- problem_id: v2p_n9_f24f3dac6f5fff1b
+-- realization_mode: agent
+-- source_kind: agent
+SELECT AVG(CASE WHEN CAST("feature_15" AS REAL) <= 100.0 THEN 1 ELSE 0 END) AS "empirical_cdf_at_threshold"
+FROM "n9";
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_eadfcbae38ae6a9f.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_eadfcbae38ae6a9f.sql
new file mode 100644
index 0000000000000000000000000000000000000000..b7a7ba3f707c96460c33645397e58954f0d331f6
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_eadfcbae38ae6a9f.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: subgroup_size_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_clickbench_group_count
+-- query_record_id: v2q_n9_eadfcbae38ae6a9f
+-- problem_id: v2p_n9_8e3fc3e95fcdae09
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_3", COUNT(*) AS "row_count"
+FROM "n9"
+GROUP BY "feature_3"
+ORDER BY "row_count" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_ee68e050f4954059.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_ee68e050f4954059.sql
new file mode 100644
index 0000000000000000000000000000000000000000..e49ecdcd7a6d7ff8a5ca5dbdafc19afb254024a2
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_ee68e050f4954059.sql
@@ -0,0 +1,18 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: slice_level_consistency
+-- intended_facet_id: conditional_interaction_hotspots
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_c2_filtered_group_count_2d
+-- query_record_id: v2q_n9_ee68e050f4954059
+-- problem_id: v2p_n9_a40f093260ba585b
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_4", "feature_12", COUNT(*) AS "row_count"
+FROM "n9"
+WHERE CAST("feature_2" AS REAL) >= 100.0
+GROUP BY "feature_4", "feature_12"
+ORDER BY "row_count" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_eef9b6c1f9418df7.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_eef9b6c1f9418df7.sql
new file mode 100644
index 0000000000000000000000000000000000000000..206f0f955fc7377ad8cc395094b22b59875e1039
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_eef9b6c1f9418df7.sql
@@ -0,0 +1,26 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_tpch_relative_total_threshold
+-- query_record_id: v2q_n9_eef9b6c1f9418df7
+-- problem_id: v2p_n9_0e96c3ae7d863b44
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+    SELECT "feature_9", SUM(CAST("feature_13" AS REAL)) AS group_value
+    FROM "n9"
+    GROUP BY "feature_9"
+), total AS (
+    SELECT SUM(group_value) AS total_value
+    FROM grouped
+)
+SELECT g."feature_9", g.group_value
+FROM grouped AS g
+CROSS JOIN total AS t
+WHERE g.group_value > t.total_value * 0.1
+ORDER BY g.group_value DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_f10689617a003e3d.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_f10689617a003e3d.sql
new file mode 100644
index 0000000000000000000000000000000000000000..6e6be1438a0fc98186c9fb391e8e31ed84174c44
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_f10689617a003e3d.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: subgroup_size_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_clickbench_group_count
+-- query_record_id: v2q_n9_f10689617a003e3d
+-- problem_id: v2p_n9_4507391c29fbc82e
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_1", COUNT(*) AS row_count
+FROM "n9"
+GROUP BY "feature_1"
+ORDER BY row_count DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_f4506e3dfaee1d4d.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_f4506e3dfaee1d4d.sql
new file mode 100644
index 0000000000000000000000000000000000000000..6a9719df4aefbe87a0e6d4d746c98d230564ed1e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_f4506e3dfaee1d4d.sql
@@ -0,0 +1,18 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_m4_group_condition_rate
+-- query_record_id: v2q_n9_f4506e3dfaee1d4d
+-- problem_id: v2p_n9_1286a6844b3d891a
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_12",
+       AVG(CASE WHEN "class" = '4' THEN 1 ELSE 0 END) AS "condition_rate"
+FROM "n9"
+GROUP BY "feature_12"
+ORDER BY "condition_rate" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_f596b5fec512d245.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_f596b5fec512d245.sql
new file mode 100644
index 0000000000000000000000000000000000000000..91ae0e2da50209ce703a2cac74ef436624a5310c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_f596b5fec512d245.sql
@@ -0,0 +1,19 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_f596b5fec512d245
+-- problem_id: v2p_n9_4ad644c9f56a6d74
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_1", "feature_4",
+       SUM(CAST("feature_3" AS REAL)) AS "total_measure",
+       SUM(CAST("feature_3" AS REAL)) * 100.0 / SUM(SUM(CAST("feature_3" AS REAL))) OVER (PARTITION BY "feature_1") AS "share_within_group"
+FROM "n9"
+GROUP BY "feature_1", "feature_4"
+ORDER BY "share_within_group" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_f5e1eebe605c95f0.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_f5e1eebe605c95f0.sql
new file mode 100644
index 0000000000000000000000000000000000000000..518bde324ce86af0122c1ca32908463a219300fe
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_f5e1eebe605c95f0.sql
@@ -0,0 +1,18 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: within_group_proportion
+-- template_id: tpl_m4_group_condition_rate
+-- query_record_id: v2q_n9_f5e1eebe605c95f0
+-- problem_id: v2p_n9_1c693c15d5c7309f
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_16",
+       AVG(CASE WHEN "class" = '2' THEN 1 ELSE 0 END) AS condition_rate
+FROM "n9"
+GROUP BY "feature_16"
+ORDER BY condition_rate DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_f64c629fcaac3eed.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_f64c629fcaac3eed.sql
new file mode 100644
index 0000000000000000000000000000000000000000..89d28dc121557528eb529f53f51a744f06a7a1ff
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_f64c629fcaac3eed.sql
@@ -0,0 +1,19 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: within_group_proportion
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_f64c629fcaac3eed
+-- problem_id: v2p_n9_29d57a6edc03a255
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_15", "feature_1",
+       SUM(CAST("feature_16" AS REAL)) AS "total_measure",
+       SUM(CAST("feature_16" AS REAL)) * 100.0 / SUM(SUM(CAST("feature_16" AS REAL))) OVER (PARTITION BY "feature_15") AS "share_within_group"
+FROM "n9"
+GROUP BY "feature_15", "feature_1"
+ORDER BY "share_within_group" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_f68981d7e5f043de.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_f68981d7e5f043de.sql
new file mode 100644
index 0000000000000000000000000000000000000000..a8433e2bfabda1e926f8f5611c66fe71b9ce6567
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_f68981d7e5f043de.sql
@@ -0,0 +1,31 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_tpch_relative_total_threshold
+-- query_record_id: v2q_n9_f68981d7e5f043de
+-- problem_id: v2p_n9_3f975c644de900b6
+-- realization_mode: agent
+-- source_kind: agent
+WITH "grouped" AS (
+  SELECT
+    "feature_14",
+    SUM(CAST("feature_2" AS REAL)) AS "group_value"
+  FROM "n9"
+  GROUP BY "feature_14"
+),
+"total" AS (
+  SELECT SUM("group_value") AS "total_value"
+  FROM "grouped"
+)
+SELECT
+  g."feature_14",
+  g."group_value"
+FROM "grouped" AS g
+CROSS JOIN "total" AS t
+WHERE g."group_value" > t."total_value" * 0.05
+ORDER BY g."group_value" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_f985f160ec9b97bf.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_f985f160ec9b97bf.sql
new file mode 100644
index 0000000000000000000000000000000000000000..702a8072565672ab4219aa29d1b485b410f0fde5
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_f985f160ec9b97bf.sql
@@ -0,0 +1,20 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_set_consistency
+-- intended_facet_id: low_support_extremes
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_tail_low_support_group_count_v2
+-- query_record_id: v2q_n9_f985f160ec9b97bf
+-- problem_id: v2p_n9_a3e1a8ac77cc9afc
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+  "feature_4",
+  COUNT(*) AS "support"
+FROM "n9"
+GROUP BY "feature_4"
+ORDER BY "support" ASC, "feature_4"
+LIMIT 12;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_fc0117fdb95c9de1.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_fc0117fdb95c9de1.sql
new file mode 100644
index 0000000000000000000000000000000000000000..05a7d42d2c230b9cd15c9ff8f852892bde900103
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_fc0117fdb95c9de1.sql
@@ -0,0 +1,20 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_n9_fc0117fdb95c9de1
+-- problem_id: v2p_n9_7ccc8901a2d9c3e8
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_13", "feature_15",
+       SUM(CAST("feature_14" AS REAL)) AS total_measure,
+       SUM(CAST("feature_14" AS REAL)) * 100.0 / SUM(SUM(CAST("feature_14" AS REAL))) OVER (PARTITION BY "feature_13") AS share_within_group
+FROM "n9"
+GROUP BY "feature_13", "feature_15"
+ORDER BY share_within_group DESC
+LIMIT 14;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_fc2e1b951048317b.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_fc2e1b951048317b.sql
new file mode 100644
index 0000000000000000000000000000000000000000..7b5dfd2c599f51240e0bbd1f9658f32e5ee8885c
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_fc2e1b951048317b.sql
@@ -0,0 +1,22 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_set_consistency
+-- intended_facet_id: low_support_extremes
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_m4_quantile_tail_slice
+-- query_record_id: v2q_n9_fc2e1b951048317b
+-- problem_id: v2p_n9_ad5ef7f2b77764be
+-- realization_mode: agent
+-- source_kind: agent
+WITH buckets AS (
+    SELECT CAST("feature_16" AS REAL) AS "feature_16",
+           NTILE(10) OVER (ORDER BY CAST("feature_16" AS REAL) DESC) AS "tail_bucket"
+    FROM "n9"
+)
+SELECT "feature_16"
+FROM buckets
+WHERE "tail_bucket" = 1
+ORDER BY "feature_16" DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_fc69058e0c04deb5.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_fc69058e0c04deb5.sql
new file mode 100644
index 0000000000000000000000000000000000000000..12209e235e2f23e1272969079c6f8cea0719b875
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_fc69058e0c04deb5.sql
@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: subgroup_structure
+-- canonical_subitem_id: subgroup_size_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_clickbench_group_count
+-- query_record_id: v2q_n9_fc69058e0c04deb5
+-- problem_id: v2p_n9_1c4daf76e597ba91
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_16", COUNT(*) AS row_count
+FROM "n9"
+GROUP BY "feature_16"
+ORDER BY row_count DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_fd2b48bd5846e5f3.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_fd2b48bd5846e5f3.sql
new file mode 100644
index 0000000000000000000000000000000000000000..269ec64a442e2721037753913f238c08c316b095
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_fd2b48bd5846e5f3.sql
@@ -0,0 +1,28 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: value_imbalance_profile
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_cardinality_distinct_share_profile
+-- query_record_id: v2q_n9_fd2b48bd5846e5f3
+-- problem_id: v2p_n9_082a34fa24319087
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_5" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_5"
+), ranked AS (
+    SELECT
+        value_label,
+        support,
+        CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+        SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support
+    FROM grouped
+)
+SELECT *
+FROM ranked
+ORDER BY support DESC, value_label;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_fe31b5886cd52dc2.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_fe31b5886cd52dc2.sql
new file mode 100644
index 0000000000000000000000000000000000000000..231048d8d82f891ca74de5e364d7964479fe81be
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_fe31b5886cd52dc2.sql
@@ -0,0 +1,18 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: direction_consistency
+-- intended_facet_id: conditional_rate_shift
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_m4_group_condition_rate
+-- query_record_id: v2q_n9_fe31b5886cd52dc2
+-- problem_id: v2p_n9_bfd5284e9de40536
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "feature_13",
+       AVG(CASE WHEN "class" = '2' THEN 1 ELSE 0 END) AS condition_rate
+FROM "n9"
+GROUP BY "feature_13"
+ORDER BY condition_rate DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_ff314eb7d17a9865.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_ff314eb7d17a9865.sql
new file mode 100644
index 0000000000000000000000000000000000000000..b05b6008086884650a06d282a9136c4e7fc560d2
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_ff314eb7d17a9865.sql
@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: high_cardinality_response_stability
+-- intended_facet_id: target_cardinality_cross_section
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_cardinality_high_card_response_stability
+-- query_record_id: v2q_n9_ff314eb7d17a9865
+-- problem_id: v2p_n9_d4aa41902519318a
+-- realization_mode: deterministic
+-- source_kind: deterministic
+SELECT
+    "feature_1",
+    COUNT(*) AS support,
+    AVG("feature_2") AS avg_response
+FROM "n9"
+GROUP BY "feature_1"
+HAVING COUNT(*) >= 5.0
+ORDER BY support DESC, avg_response DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_ff45febb889fd477.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_ff45febb889fd477.sql
new file mode 100644
index 0000000000000000000000000000000000000000..afc14f2aa37d7d2c5035cef258417d8c532626b3
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_ff45febb889fd477.sql
@@ -0,0 +1,57 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_n9_ff45febb889fd477
+-- problem_id: v2p_n9_7dd9efbb3bea95a1
+-- realization_mode: agent
+-- source_kind: agent
+WITH "ordered" AS (
+  SELECT
+    "feature_6" AS "group_col",
+    CAST("feature_11" AS REAL) AS "measure",
+    ROW_NUMBER() OVER (
+      PARTITION BY "feature_6"
+      ORDER BY CAST("feature_11" AS REAL)
+    ) AS "rn",
+    COUNT(*) OVER (PARTITION BY "feature_6") AS "cnt"
+  FROM "n9"
+  WHERE "feature_6" IS NOT NULL
+    AND "feature_11" IS NOT NULL
+),
+"params" AS (
+  SELECT
+    "group_col",
+    "cnt",
+    1 + CAST((9 * ("cnt" - 1)) / 10 AS INTEGER) AS "lower_rn",
+    1 + CAST((9 * ("cnt" - 1)) / 10 AS INTEGER)
+      + CASE WHEN ((9 * ("cnt" - 1)) % 10) = 0 THEN 0 ELSE 1 END AS "upper_rn",
+    ((9 * ("cnt" - 1)) % 10) / 10.0 AS "frac"
+  FROM (
+    SELECT DISTINCT "group_col", "cnt"
+    FROM "ordered"
+  )
+  WHERE "cnt" >= 5
+)
+SELECT
+  p."group_col" AS "feature_6",
+  CASE
+    WHEN p."upper_rn" = p."lower_rn" THEN
+      MAX(CASE WHEN o."rn" = p."lower_rn" THEN o."measure" END)
+    ELSE
+      MAX(CASE WHEN o."rn" = p."lower_rn" THEN o."measure" END) +
+      p."frac" * (
+        MAX(CASE WHEN o."rn" = p."upper_rn" THEN o."measure" END) -
+        MAX(CASE WHEN o."rn" = p."lower_rn" THEN o."measure" END)
+      )
+  END AS "percentile_measure"
+FROM "params" AS p
+JOIN "ordered" AS o
+  ON o."group_col" = p."group_col"
+GROUP BY p."group_col", p."cnt", p."lower_rn", p."upper_rn", p."frac"
+ORDER BY "percentile_measure" DESC, CAST(p."group_col" AS INTEGER) ASC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_ff6d4453fa647527.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_ff6d4453fa647527.sql
new file mode 100644
index 0000000000000000000000000000000000000000..3977c6e4a4e97b2b0bc2ed85c4b6f6f0f8063302
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_ff6d4453fa647527.sql
@@ -0,0 +1,15 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_set_consistency
+-- intended_facet_id: low_support_extremes
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_threshold_rarity_cdf
+-- query_record_id: v2q_n9_ff6d4453fa647527
+-- problem_id: v2p_n9_38262ecb27032771
+-- realization_mode: agent
+-- source_kind: agent
+SELECT AVG(CASE WHEN CAST("feature_5" AS REAL) <= 78.0 THEN 1 ELSE 0 END) AS "empirical_cdf_at_threshold"
+FROM "n9";
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_ffde6eecd5041532.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_ffde6eecd5041532.sql
new file mode 100644
index 0000000000000000000000000000000000000000..736c713138c10ab8f9269c59d8f2c672a64d5435
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_ffde6eecd5041532.sql
@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: high_cardinality_response_stability
+-- intended_facet_id: target_cardinality_cross_section
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_cardinality_high_card_response_stability
+-- query_record_id: v2q_n9_ffde6eecd5041532
+-- problem_id: v2p_n9_e57314fedeadb9f8
+-- realization_mode: deterministic
+-- source_kind: deterministic
+SELECT
+    "feature_7",
+    COUNT(*) AS support,
+    AVG("feature_1") AS avg_response
+FROM "n9"
+GROUP BY "feature_7"
+HAVING COUNT(*) >= 5.0
+ORDER BY support DESC, avg_response DESC;
diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_fff29ef63f9d7d5f.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_fff29ef63f9d7d5f.sql
new file mode 100644
index 0000000000000000000000000000000000000000..97c0156edbb93fdd68aa8b66221beee9b9ccf50e
--- /dev/null
+++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/n9/sql/v2q_n9_fff29ef63f9d7d5f.sql
@@ -0,0 +1,25 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n9
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: support_concentration
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_cardinality_support_rank_profile
+-- query_record_id: v2q_n9_fff29ef63f9d7d5f
+-- problem_id: v2p_n9_05658db80fe1c3bc
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "feature_12" AS value_label, COUNT(*) AS support
+    FROM "n9"
+    GROUP BY "feature_12"
+)
+SELECT
+    value_label,
+    support,
+    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank
+FROM grouped
+ORDER BY support DESC, value_label;