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Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0148d341df5f5dce/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": "2026-05-19T16:09:45.224985+00:00",
+  "ended_at": "2026-05-19T16:09:48.516865+00:00",
+  "elapsed_ms": 3291.84,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16428,
+    "bytes_utf8": 16428,
+    "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"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0148d341df5f5dce/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": "2026-05-19T16:09:49.518862+00:00",
+  "ended_at": "2026-05-19T16:09:52.839297+00:00",
+  "elapsed_ms": 3320.41,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16428,
+    "bytes_utf8": 16428,
+    "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"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0148d341df5f5dce/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=Survey_Date, measure_col=Efficiency_Rating.",
+  "planned_template_id": "tpl_m4_window_partition_avg",
+  "bindings": {
+    "group_col": "Survey_Date",
+    "measure_col": "Efficiency_Rating",
+    "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": 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 DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0148d341df5f5dce/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=Survey_Date, measure_col=Efficiency_Rating.",
+  "planned_template_id": "tpl_m4_window_partition_avg",
+  "bindings": {
+    "group_col": "Survey_Date",
+    "measure_col": "Efficiency_Rating",
+    "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": 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 DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0148d341df5f5dce/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4100-1703-7952-8567-4ba8e9d6b182"}
+{"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."}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0148d341df5f5dce/cli/sql_response_attempt_1.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4100-1703-7952-8567-4ba8e9d6b182"}
+{"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."}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0148d341df5f5dce/cli/sql_response_attempt_2.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4100-2801-7b02-933b-4e243a7e27f7"}
+{"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."}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0148d341df5f5dce/cli/sql_response_attempt_2.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e4100-2801-7b02-933b-4e243a7e27f7"}
+{"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."}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/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=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:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/sql_response_attempt_1.raw.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."}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_17bd5a0052c8c6ae/cli/sql_response_attempt_2.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f2-4bf0-7ae2-a687-b2374712fe33"}
+{"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    \\\"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.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16729,"cached_input_tokens":15744,"output_tokens":3116,"reasoning_output_tokens":2388}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1a526838d64cf612/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16936, "bytes_utf8": 16936, "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": 730, "bytes_utf8": 730, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16831, "cached_input_tokens": 15744, "output_tokens": 417, "reasoning_output_tokens": 228}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1a526838d64cf612/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_1a526838d64cf612",
+    "api_calls": 0,
+    "input_tokens": 16831,
+    "cached_input_tokens": 15744,
+    "output_tokens": 417,
+    "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": 9942.42,
+    "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_1a526838d64cf612/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1a526838d64cf612/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": "2026-05-19T15:50:28.545018+00:00",
+  "ended_at": "2026-05-19T15:50:38.487466+00:00",
+  "elapsed_ms": 9942.42,
+  "prompt_metrics": {
+    "chars": 16936,
+    "bytes_utf8": 16936,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1097,
+    "bytes_utf8": 1097,
+    "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": 730,
+      "bytes_utf8": 730,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16831,
+      "cached_input_tokens": 15744,
+      "output_tokens": 417,
+      "reasoning_output_tokens": 228
+    }
+  },
+  "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"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1a526838d64cf612/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=Team_Collaboration_Frequency, measure_col=Commute_Time_Minutes.",
+  "planned_template_id": "tpl_tpch_relative_total_threshold",
+  "bindings": {
+    "group_col": "Team_Collaboration_Frequency",
+    "measure_col": "Commute_Time_Minutes",
+    "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": 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": "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:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1a526838d64cf612/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40ee-70c9-7501-900e-1964b8b5e070"}
+{"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 \\\"Team_Collaboration_Frequency\\\", SUM(CAST(\\\"Commute_Time_Minutes\\\" AS REAL)) AS group_value\\n    FROM \\\"m1\\\"\\n    GROUP BY \\\"Team_Collaboration_Frequency\\\"\\n), total AS (\\n    SELECT SUM(group_value) AS total_value\\n    FROM grouped\\n)\\nSELECT g.\\\"Team_Collaboration_Frequency\\\", 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 template with group_col bound to \\\"Team_Collaboration_Frequency\\\" and measure_col bound to \\\"Commute_Time_Minutes\\\". CAST to REAL is included because the schema stores numeric values as TEXT in SQLite.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16831,"cached_input_tokens":15744,"output_tokens":417,"reasoning_output_tokens":228}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1a526838d64cf612/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tpch_relative_total_threshold\nWITH grouped AS (\n    SELECT \"Team_Collaboration_Frequency\", SUM(CAST(\"Commute_Time_Minutes\" AS REAL)) AS group_value\n    FROM \"m1\"\n    GROUP BY \"Team_Collaboration_Frequency\"\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.\"Team_Collaboration_Frequency\", 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 template with group_col bound to \"Team_Collaboration_Frequency\" and measure_col bound to \"Commute_Time_Minutes\". CAST to REAL is included because the schema stores numeric values as TEXT in SQLite."}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2994e13b03622d40/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16748, "bytes_utf8": 16748, "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": 640, "bytes_utf8": 640, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16800, "cached_input_tokens": 12032, "output_tokens": 677, "reasoning_output_tokens": 504}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2994e13b03622d40/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_2994e13b03622d40",
+    "api_calls": 0,
+    "input_tokens": 16800,
+    "cached_input_tokens": 12032,
+    "output_tokens": 677,
+    "total_tokens": 17477,
+    "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": 16366.55,
+    "sql_execution_elapsed_ms_total": 4.83,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2994e13b03622d40/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2994e13b03622d40/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": "2026-05-19T15:34:30.898368+00:00",
+  "ended_at": "2026-05-19T15:34:47.264963+00:00",
+  "elapsed_ms": 16366.55,
+  "prompt_metrics": {
+    "chars": 16748,
+    "bytes_utf8": 16748,
+    "lines": 458,
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+  },
+  "stdout_metrics": {
+    "chars": 1026,
+    "bytes_utf8": 1026,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
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+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 640,
+      "bytes_utf8": 640,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16800,
+      "cached_input_tokens": 12032,
+      "output_tokens": 677,
+      "reasoning_output_tokens": 504
+    }
+  },
+  "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"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_2994e13b03622d40/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"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."}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_41c2b25901cf37fd/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": "2026-05-19T16:04:54.277302+00:00",
+  "ended_at": "2026-05-19T16:04:59.934444+00:00",
+  "elapsed_ms": 5657.12,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16629,
+    "bytes_utf8": 16629,
+    "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"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_41c2b25901cf37fd/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": "2026-05-19T16:05:00.936895+00:00",
+  "ended_at": "2026-05-19T16:05:04.245465+00:00",
+  "elapsed_ms": 3308.52,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16629,
+    "bytes_utf8": 16629,
+    "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"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_41c2b25901cf37fd/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=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": "Daily",
+    "positive_value": "Daily",
+    "negative_value": "Few times per week",
+    "top_k": 12,
+    "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},\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:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_41c2b25901cf37fd/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=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": "Daily",
+    "positive_value": "Daily",
+    "negative_value": "Few times per week",
+    "top_k": 12,
+    "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},\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:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_41c2b25901cf37fd/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fb-a683-7050-8975-c053cbf3ced1"}
+{"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."}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_41c2b25901cf37fd/cli/sql_response_attempt_1.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fb-a683-7050-8975-c053cbf3ced1"}
+{"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."}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_41c2b25901cf37fd/cli/sql_response_attempt_2.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fb-c0a0-7073-944e-97a2759bf2c7"}
+{"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."}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_41c2b25901cf37fd/cli/sql_response_attempt_2.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fb-c0a0-7073-944e-97a2759bf2c7"}
+{"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."}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_48f2c4cc35e98cf6/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16501, "bytes_utf8": 16501, "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": 524, "bytes_utf8": 524, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16736, "cached_input_tokens": 12032, "output_tokens": 358, "reasoning_output_tokens": 213}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_48f2c4cc35e98cf6/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_48f2c4cc35e98cf6",
+    "api_calls": 0,
+    "input_tokens": 16736,
+    "cached_input_tokens": 12032,
+    "output_tokens": 358,
+    "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": 17404.23,
+    "sql_execution_elapsed_ms_total": 2.89,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_48f2c4cc35e98cf6/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_48f2c4cc35e98cf6/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": "2026-05-19T15:45:06.992662+00:00",
+  "ended_at": "2026-05-19T15:45:24.396922+00:00",
+  "elapsed_ms": 17404.23,
+  "prompt_metrics": {
+    "chars": 16501,
+    "bytes_utf8": 16501,
+    "lines": 454,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1555,
+    "bytes_utf8": 1555,
+    "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": 524,
+      "bytes_utf8": 524,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16736,
+      "cached_input_tokens": 12032,
+      "output_tokens": 358,
+      "reasoning_output_tokens": 213
+    }
+  },
+  "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"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_48f2c4cc35e98cf6/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=Quality_Score.",
+  "planned_template_id": "tpl_m4_quantile_tail_slice",
+  "bindings": {
+    "measure_col": "Quality_Score",
+    "top_k": 12,
+    "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": "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:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_48f2c4cc35e98cf6/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,6 @@
+{"type":"thread.started","thread_id":"019e40e9-88cc-7c70-9b12-78c97731d104"}
+{"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 1986945, Requested 17371. Please try again in 129ms. 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":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_quantile_tail_slice\\nWITH buckets AS (\\n    SELECT\\n        \\\"Quality_Score\\\",\\n        NTILE(10) OVER (ORDER BY CAST(\\\"Quality_Score\\\" AS REAL) DESC) AS tail_bucket\\n    FROM \\\"m1\\\"\\n    WHERE \\\"Quality_Score\\\" IS NOT NULL\\n)\\nSELECT \\\"Quality_Score\\\"\\nFROM buckets\\nWHERE tail_bucket = 1\\nORDER BY CAST(\\\"Quality_Score\\\" AS REAL) DESC;\",\"notes\":\"Applied the Quantile Tail Slice template with \\\"Quality_Score\\\" as the measure column, casting it to REAL because the schema stores it as TEXT.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16736,"cached_input_tokens":12032,"output_tokens":358,"reasoning_output_tokens":213}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_48f2c4cc35e98cf6/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_m4_quantile_tail_slice\nWITH buckets AS (\n    SELECT\n        \"Quality_Score\",\n        NTILE(10) OVER (ORDER BY CAST(\"Quality_Score\" AS REAL) DESC) AS tail_bucket\n    FROM \"m1\"\n    WHERE \"Quality_Score\" IS NOT NULL\n)\nSELECT \"Quality_Score\"\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY CAST(\"Quality_Score\" AS REAL) DESC;","notes":"Applied the Quantile Tail Slice template with \"Quality_Score\" as the measure column, casting it to REAL because the schema stores it as TEXT."}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5fa3a8520733259f/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16734, "bytes_utf8": 16734, "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": 671, "bytes_utf8": 671, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16799, "cached_input_tokens": 15744, "output_tokens": 1148, "reasoning_output_tokens": 958}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5fa3a8520733259f/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_5fa3a8520733259f",
+    "api_calls": 0,
+    "input_tokens": 16799,
+    "cached_input_tokens": 15744,
+    "output_tokens": 1148,
+    "total_tokens": 17947,
+    "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": 21328.56,
+    "sql_execution_elapsed_ms_total": 5.36,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5fa3a8520733259f/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5fa3a8520733259f/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": "2026-05-19T15:39:59.045348+00:00",
+  "ended_at": "2026-05-19T15:40:20.373948+00:00",
+  "elapsed_ms": 21328.56,
+  "prompt_metrics": {
+    "chars": 16734,
+    "bytes_utf8": 16734,
+    "lines": 458,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1088,
+    "bytes_utf8": 1088,
+    "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": 671,
+      "bytes_utf8": 671,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16799,
+      "cached_input_tokens": 15744,
+      "output_tokens": 1148,
+      "reasoning_output_tokens": 958
+    }
+  },
+  "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"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5fa3a8520733259f/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=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": 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": 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": "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:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5fa3a8520733259f/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40e4-d5be-7b53-996f-734b168bfaad"}
+{"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  \\\"Survey_Date\\\",\\n  \\\"total_measure\\\",\\n  \\\"total_measure\\\" * 100.0 / SUM(\\\"total_measure\\\") OVER (PARTITION BY \\\"Gender\\\") AS \\\"share_within_group\\\"\\nFROM (\\n  SELECT\\n    \\\"Gender\\\",\\n    \\\"Survey_Date\\\",\\n    SUM(CAST(\\\"Quality_Score\\\" AS REAL)) AS \\\"total_measure\\\"\\n  FROM \\\"m1\\\"\\n  GROUP BY \\\"Gender\\\", \\\"Survey_Date\\\"\\n)\\nORDER BY \\\"share_within_group\\\" DESC;\",\"notes\":\"Uses the planned Within-Group Share of Total template with group_col=\\\"Gender\\\", item_col=\\\"Survey_Date\\\", and measure_col=\\\"Quality_Score\\\". \\\"Quality_Score\\\" is cast to REAL because the schema stores it as TEXT.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16799,"cached_input_tokens":15744,"output_tokens":1148,"reasoning_output_tokens":958}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_5fa3a8520733259f/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tpcds_within_group_share\nSELECT\n  \"Gender\",\n  \"Survey_Date\",\n  \"total_measure\",\n  \"total_measure\" * 100.0 / SUM(\"total_measure\") OVER (PARTITION BY \"Gender\") AS \"share_within_group\"\nFROM (\n  SELECT\n    \"Gender\",\n    \"Survey_Date\",\n    SUM(CAST(\"Quality_Score\" AS REAL)) AS \"total_measure\"\n  FROM \"m1\"\n  GROUP BY \"Gender\", \"Survey_Date\"\n)\nORDER BY \"share_within_group\" DESC;","notes":"Uses the planned Within-Group Share of Total template with group_col=\"Gender\", item_col=\"Survey_Date\", and measure_col=\"Quality_Score\". \"Quality_Score\" is cast to REAL because the schema stores it as TEXT."}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_880f452f0c5961bf/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 17179, "bytes_utf8": 17179, "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": 846, "bytes_utf8": 846, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16898, "cached_input_tokens": 15744, "output_tokens": 695, "reasoning_output_tokens": 464}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_880f452f0c5961bf/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_880f452f0c5961bf",
+    "api_calls": 0,
+    "input_tokens": 16898,
+    "cached_input_tokens": 15744,
+    "output_tokens": 695,
+    "total_tokens": 17593,
+    "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": 20787.65,
+    "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_880f452f0c5961bf/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}