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Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_00fd7129d54cd1a0/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 6520, "bytes_utf8": 6520, "lines": 207, "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": 494, "bytes_utf8": 494, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13940, "cached_input_tokens": 12672, "output_tokens": 310, "reasoning_output_tokens": 173}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_00fd7129d54cd1a0/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": "c7",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c7_00fd7129d54cd1a0",
+    "api_calls": 0,
+    "input_tokens": 13940,
+    "cached_input_tokens": 12672,
+    "output_tokens": 310,
+    "total_tokens": 14250,
+    "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": 8043.46,
+    "sql_execution_elapsed_ms_total": 8.98,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_00fd7129d54cd1a0/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_00fd7129d54cd1a0/cli/sql_attempt_1.metadata.json

@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:33:56.958682+00:00",
+  "ended_at": "2026-05-19T15:34:05.002192+00:00",
+  "elapsed_ms": 8043.46,
+  "prompt_metrics": {
+    "chars": 6520,
+    "bytes_utf8": 6520,
+    "lines": 207,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 853,
+    "bytes_utf8": 853,
+    "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": 494,
+      "bytes_utf8": 494,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 13940,
+      "cached_input_tokens": 12672,
+      "output_tokens": 310,
+      "reasoning_output_tokens": 173
+    }
+  },
+  "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_b/c7/artifacts/v2q_c7_00fd7129d54cd1a0/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,207 @@
+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: c7
+- dataset_name: C7
+- table_name: c7
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 8 feature columns and target `class`.
+- task_type: classification
+- target_column: class
+- main_row_count: 12960
+- important_fields:
+- parents: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for parents.
+- has_nurs: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for has nurs.
+- form: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for form.
+- children: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for children.
+- housing: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for housing.
+- finance: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for finance.
+- social: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for social.
+- health: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for health.
+- class: role=target, type=categorical_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for class.
+- useful_field_combinations: [['parents', 'has_nurs', 'class'], ['parents', 'parents', 'class']]
+- fields_requiring_caution: ['class']
+- source_url: https://www.openml.org/d/26
+
+SQLite schema snapshot:
+{
+  "table_name": "c7",
+  "quoted_table_name": "\"c7\"",
+  "row_count": 12960,
+  "columns": [
+    {
+      "name": "parents",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "has_nurs",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "form",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "housing",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "finance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "social",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "health",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "class",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "parents": "usual",
+      "has_nurs": "proper",
+      "form": "complete",
+      "children": "1",
+      "housing": "convenient",
+      "finance": "convenient",
+      "social": "nonprob",
+      "health": "recommended",
+      "class": "recommend"
+    },
+    {
+      "parents": "usual",
+      "has_nurs": "proper",
+      "form": "complete",
+      "children": "1",
+      "housing": "convenient",
+      "finance": "convenient",
+      "social": "nonprob",
+      "health": "priority",
+      "class": "priority"
+    },
+    {
+      "parents": "usual",
+      "has_nurs": "proper",
+      "form": "complete",
+      "children": "1",
+      "housing": "convenient",
+      "finance": "convenient",
+      "social": "nonprob",
+      "health": "not_recom",
+      "class": "not_recom"
+    },
+    {
+      "parents": "usual",
+      "has_nurs": "proper",
+      "form": "complete",
+      "children": "1",
+      "housing": "convenient",
+      "finance": "convenient",
+      "social": "slightly_prob",
+      "health": "recommended",
+      "class": "recommend"
+    },
+    {
+      "parents": "usual",
+      "has_nurs": "proper",
+      "form": "complete",
+      "children": "1",
+      "housing": "convenient",
+      "finance": "convenient",
+      "social": "slightly_prob",
+      "health": "priority",
+      "class": "priority"
+    }
+  ]
+}
+
+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": "c7",
+  "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=has_nurs, condition_col=has_nurs.",
+  "planned_template_id": "tpl_m4_group_condition_rate",
+  "bindings": {
+    "group_col": "has_nurs",
+    "condition_col": "has_nurs",
+    "condition_value": "improper",
+    "positive_value": "critical",
+    "negative_value": "improper",
+    "top_k": 18,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 0.0,
+    "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_b/c7/artifacts/v2q_c7_00fd7129d54cd1a0/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40df-4f6f-7ff1-8ed6-2644e6e9fdb6"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"has_nurs\\\",\\n       AVG(CASE WHEN \\\"has_nurs\\\" = 'improper' THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"c7\\\"\\nGROUP BY \\\"has_nurs\\\"\\nORDER BY \\\"condition_rate\\\" DESC;\",\"notes\":\"Applied the Grouped Condition Rate template with both group_col and condition_col bound to \\\"has_nurs\\\" and condition_value bound to 'improper'. This measures, for each has_nurs category, the share of rows in that same category equal to 'improper'.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":13940,"cached_input_tokens":12672,"output_tokens":310,"reasoning_output_tokens":173}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_00fd7129d54cd1a0/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_m4_group_condition_rate\nSELECT \"has_nurs\",\n       AVG(CASE WHEN \"has_nurs\" = 'improper' THEN 1 ELSE 0 END) AS \"condition_rate\"\nFROM \"c7\"\nGROUP BY \"has_nurs\"\nORDER BY \"condition_rate\" DESC;","notes":"Applied the Grouped Condition Rate template with both group_col and condition_col bound to \"has_nurs\" and condition_value bound to 'improper'. This measures, for each has_nurs category, the share of rows in that same category equal to 'improper'."}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_025a43508b7af3dc/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 6520, "bytes_utf8": 6520, "lines": 207, "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": 567, "bytes_utf8": 567, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13935, "cached_input_tokens": 12672, "output_tokens": 486, "reasoning_output_tokens": 336}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_025a43508b7af3dc/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": "c7",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c7_025a43508b7af3dc",
+    "api_calls": 0,
+    "input_tokens": 13935,
+    "cached_input_tokens": 12672,
+    "output_tokens": 486,
+    "total_tokens": 14421,
+    "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": 9455.46,
+    "sql_execution_elapsed_ms_total": 6.03,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_025a43508b7af3dc/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_025a43508b7af3dc/cli/sql_attempt_1.metadata.json

@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:33:36.134519+00:00",
+  "ended_at": "2026-05-19T15:33:45.590041+00:00",
+  "elapsed_ms": 9455.46,
+  "prompt_metrics": {
+    "chars": 6520,
+    "bytes_utf8": 6520,
+    "lines": 207,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 927,
+    "bytes_utf8": 927,
+    "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": 567,
+      "bytes_utf8": 567,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 13935,
+      "cached_input_tokens": 12672,
+      "output_tokens": 486,
+      "reasoning_output_tokens": 336
+    }
+  },
+  "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_b/c7/artifacts/v2q_c7_025a43508b7af3dc/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,207 @@
+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: c7
+- dataset_name: C7
+- table_name: c7
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 8 feature columns and target `class`.
+- task_type: classification
+- target_column: class
+- main_row_count: 12960
+- important_fields:
+- parents: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for parents.
+- has_nurs: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for has nurs.
+- form: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for form.
+- children: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for children.
+- housing: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for housing.
+- finance: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for finance.
+- social: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for social.
+- health: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for health.
+- class: role=target, type=categorical_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for class.
+- useful_field_combinations: [['parents', 'has_nurs', 'class'], ['parents', 'parents', 'class']]
+- fields_requiring_caution: ['class']
+- source_url: https://www.openml.org/d/26
+
+SQLite schema snapshot:
+{
+  "table_name": "c7",
+  "quoted_table_name": "\"c7\"",
+  "row_count": 12960,
+  "columns": [
+    {
+      "name": "parents",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "has_nurs",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "form",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "housing",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "finance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "social",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "health",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "class",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "parents": "usual",
+      "has_nurs": "proper",
+      "form": "complete",
+      "children": "1",
+      "housing": "convenient",
+      "finance": "convenient",
+      "social": "nonprob",
+      "health": "recommended",
+      "class": "recommend"
+    },
+    {
+      "parents": "usual",
+      "has_nurs": "proper",
+      "form": "complete",
+      "children": "1",
+      "housing": "convenient",
+      "finance": "convenient",
+      "social": "nonprob",
+      "health": "priority",
+      "class": "priority"
+    },
+    {
+      "parents": "usual",
+      "has_nurs": "proper",
+      "form": "complete",
+      "children": "1",
+      "housing": "convenient",
+      "finance": "convenient",
+      "social": "nonprob",
+      "health": "not_recom",
+      "class": "not_recom"
+    },
+    {
+      "parents": "usual",
+      "has_nurs": "proper",
+      "form": "complete",
+      "children": "1",
+      "housing": "convenient",
+      "finance": "convenient",
+      "social": "slightly_prob",
+      "health": "recommended",
+      "class": "recommend"
+    },
+    {
+      "parents": "usual",
+      "has_nurs": "proper",
+      "form": "complete",
+      "children": "1",
+      "housing": "convenient",
+      "finance": "convenient",
+      "social": "slightly_prob",
+      "health": "priority",
+      "class": "priority"
+    }
+  ]
+}
+
+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": "c7",
+  "question": "Use template Grouped Condition Rate to probe direction_consistency with semantic role within_group_proportion. Focus on group_col=parents, condition_col=parents.",
+  "planned_template_id": "tpl_m4_group_condition_rate",
+  "bindings": {
+    "group_col": "parents",
+    "condition_col": "parents",
+    "condition_value": "pretentious",
+    "positive_value": "great_pret",
+    "negative_value": "pretentious",
+    "top_k": 17,
+    "top_n": 7,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 0.0,
+    "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_b/c7/artifacts/v2q_c7_025a43508b7af3dc/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40de-fe18-7550-977d-2dea8dbbf443"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT\\n  \\\"parents\\\",\\n  AVG(CASE WHEN \\\"parents\\\" = 'pretentious' THEN 1.0 ELSE 0.0 END) AS \\\"condition_rate\\\"\\nFROM \\\"c7\\\"\\nGROUP BY \\\"parents\\\"\\nORDER BY \\\"condition_rate\\\" DESC;\",\"notes\":\"Applied the Grouped Condition Rate template with both group_col and condition_col bound to \\\"parents\\\" and condition_value set to 'pretentious'. Because the grouping column matches the condition column, the result is a within-group proportion that is 1.0 for the 'pretentious' group and 0.0 for all other parent groups.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":13935,"cached_input_tokens":12672,"output_tokens":486,"reasoning_output_tokens":336}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_025a43508b7af3dc/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_m4_group_condition_rate\nSELECT\n  \"parents\",\n  AVG(CASE WHEN \"parents\" = 'pretentious' THEN 1.0 ELSE 0.0 END) AS \"condition_rate\"\nFROM \"c7\"\nGROUP BY \"parents\"\nORDER BY \"condition_rate\" DESC;","notes":"Applied the Grouped Condition Rate template with both group_col and condition_col bound to \"parents\" and condition_value set to 'pretentious'. Because the grouping column matches the condition column, the result is a within-group proportion that is 1.0 for the 'pretentious' group and 0.0 for all other parent groups."}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_02ae4f76f7745eed/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Filtered Top-k Distinct Coverage to probe internal_profile_stability with semantic role filtered_stable_view. Focus on group_col=social.
+Result preview: [{"social": "nonprob", "distinct_entities": 1}]

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_02ae4f76f7745eed/generated_sql.sql

@@ -0,0 +1,19 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_b
+-- sql_source_dataset_id: c7
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: filtered_stable_view
+-- template_id: tpl_clickbench_filtered_distinct_topk
+-- query_record_id: v2q_c7_02ae4f76f7745eed
+-- problem_id: v2p_c7_0182f97b82dab147
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "social", COUNT(DISTINCT "social") AS distinct_entities
+FROM "c7"
+WHERE "social" = 'nonprob'
+GROUP BY "social"
+ORDER BY distinct_entities DESC
+LIMIT 12;

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_02ae4f76f7745eed/query_results.jsonl

@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_clickbench_filtered_distinct_topk\nSELECT \"social\", COUNT(DISTINCT \"social\") AS distinct_entities\nFROM \"c7\"\nWHERE \"social\" = 'nonprob'\nGROUP BY \"social\"\nORDER BY distinct_entities DESC\nLIMIT 12;", "result": "{\"query\": \"-- template_id: tpl_clickbench_filtered_distinct_topk\\nSELECT \\\"social\\\", COUNT(DISTINCT \\\"social\\\") AS distinct_entities\\nFROM \\\"c7\\\"\\nWHERE \\\"social\\\" = 'nonprob'\\nGROUP BY \\\"social\\\"\\nORDER BY distinct_entities DESC\\nLIMIT 12;\", \"columns\": [\"social\", \"distinct_entities\"], \"rows\": [{\"social\": \"nonprob\", \"distinct_entities\": 1}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 3.01}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_02ae4f76f7745eed/run_manifest.json

@@ -0,0 +1,93 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "c7",
+  "started_at": "2026-05-19T15:54:56.167895+00:00",
+  "ended_at": "2026-05-19T15:55:05.323289+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c7_02ae4f76f7745eed",
+    "problem_id": "v2p_c7_0182f97b82dab147",
+    "dataset_id": "c7",
+    "template_id": "tpl_clickbench_filtered_distinct_topk",
+    "template_name": "Filtered Top-k Distinct Coverage",
+    "family_id": "subgroup_structure",
+    "canonical_subitem_id": "internal_profile_stability",
+    "intended_facet_id": "subgroup_distribution_shift",
+    "variant_semantic_role": "filtered_stable_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "support",
+    "extended_family": false,
+    "question": "Use template Filtered Top-k Distinct Coverage to probe internal_profile_stability with semantic role filtered_stable_view. Focus on group_col=social.",
+    "bindings": {
+      "group_col": "social",
+      "predicate_col": "social",
+      "predicate_op": "=",
+      "predicate_value": "nonprob",
+      "entity_col": "social",
+      "top_k": 12,
+      "top_n": 3,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 0.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "entity_col",
+      "predicate_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, COUNT(DISTINCT {entity_col}) AS distinct_entities\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}\nORDER BY distinct_entities DESC\nLIMIT {top_k};",
+    "notes": [
+      "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast",
+      "template_selection_mode=rule",
+      "problem_index_within_template=1",
+      "sql_variant_index=1/2",
+      "binding_index=132"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 12,
+    "problem_index_within_template": 1,
+    "sql_variant_index": 1,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c7/sql/v2q_c7_02ae4f76f7745eed.sql",
+  "usage_summary": {
+    "dataset_id": "c7",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c7_02ae4f76f7745eed",
+    "api_calls": 0,
+    "input_tokens": 13950,
+    "cached_input_tokens": 12672,
+    "output_tokens": 352,
+    "total_tokens": 14302,
+    "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": 9145.64,
+    "sql_execution_elapsed_ms_total": 3.01,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_02ae4f76f7745eed/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_02ae4f76f7745eed/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:55:05.318354+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 9145.64, "started_at": "2026-05-19T15:54:56.171594+00:00", "ended_at": "2026-05-19T15:55:05.317278+00:00", "prompt_metrics": {"chars": 6578, "bytes_utf8": 6578, "lines": 208, "estimated_tokens": null}, "response_metrics": {"chars": 540, "bytes_utf8": 540, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13950, "cached_input_tokens": 12672, "output_tokens": 352, "reasoning_output_tokens": 216}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_clickbench_filtered_distinct_topk\\nSELECT \\\"social\\\", COUNT(DISTINCT \\\"social\\\") AS distinct_entities\\nFROM \\\"c7\\\"\\nWHERE \\\"social\\\" = 'nonprob'\\nGROUP BY \\\"social\\\"\\nORDER BY distinct_entities DESC\\nLIMIT 12;\",\"notes\":\"Used the required template and fixed bindings exactly as provided. Because \\\"group_col\\\", \\\"entity_col\\\", and \\\"predicate_col\\\" are all \\\"social\\\" and the filter is \\\"social\\\" = 'nonprob', this query will return at most one grouped value with a distinct count of 1 when matching rows exist.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_02ae4f76f7745eed/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "c7",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_c7_02ae4f76f7745eed",
+  "api_calls": 0,
+  "input_tokens": 13950,
+  "cached_input_tokens": 12672,
+  "output_tokens": 352,
+  "total_tokens": 14302,
+  "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": 9145.64,
+  "sql_execution_elapsed_ms_total": 3.01,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_02ae4f76f7745eed/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_034b189bd3aaf62a/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 6361, "bytes_utf8": 6361, "lines": 204, "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": 445, "bytes_utf8": 445, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13895, "cached_input_tokens": 12032, "output_tokens": 315, "reasoning_output_tokens": 206}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_034b189bd3aaf62a/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": "c7",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c7_034b189bd3aaf62a",
+    "api_calls": 0,
+    "input_tokens": 13895,
+    "cached_input_tokens": 12032,
+    "output_tokens": 315,
+    "total_tokens": 14210,
+    "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": 11678.11,
+    "sql_execution_elapsed_ms_total": 10.9,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_034b189bd3aaf62a/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_034b189bd3aaf62a/cli/sql_attempt_1.metadata.json

@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:29:36.452235+00:00",
+  "ended_at": "2026-05-19T15:29:48.130378+00:00",
+  "elapsed_ms": 11678.11,
+  "prompt_metrics": {
+    "chars": 6361,
+    "bytes_utf8": 6361,
+    "lines": 204,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 800,
+    "bytes_utf8": 800,
+    "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": 445,
+      "bytes_utf8": 445,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 13895,
+      "cached_input_tokens": 12032,
+      "output_tokens": 315,
+      "reasoning_output_tokens": 206
+    }
+  },
+  "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_b/c7/artifacts/v2q_c7_034b189bd3aaf62a/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,204 @@
+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: c7
+- dataset_name: C7
+- table_name: c7
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 8 feature columns and target `class`.
+- task_type: classification
+- target_column: class
+- main_row_count: 12960
+- important_fields:
+- parents: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for parents.
+- has_nurs: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for has nurs.
+- form: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for form.
+- children: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for children.
+- housing: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for housing.
+- finance: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for finance.
+- social: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for social.
+- health: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for health.
+- class: role=target, type=categorical_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for class.
+- useful_field_combinations: [['parents', 'has_nurs', 'class'], ['parents', 'parents', 'class']]
+- fields_requiring_caution: ['class']
+- source_url: https://www.openml.org/d/26
+
+SQLite schema snapshot:
+{
+  "table_name": "c7",
+  "quoted_table_name": "\"c7\"",
+  "row_count": 12960,
+  "columns": [
+    {
+      "name": "parents",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "has_nurs",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "form",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "housing",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "finance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "social",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "health",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "class",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "parents": "usual",
+      "has_nurs": "proper",
+      "form": "complete",
+      "children": "1",
+      "housing": "convenient",
+      "finance": "convenient",
+      "social": "nonprob",
+      "health": "recommended",
+      "class": "recommend"
+    },
+    {
+      "parents": "usual",
+      "has_nurs": "proper",
+      "form": "complete",
+      "children": "1",
+      "housing": "convenient",
+      "finance": "convenient",
+      "social": "nonprob",
+      "health": "priority",
+      "class": "priority"
+    },
+    {
+      "parents": "usual",
+      "has_nurs": "proper",
+      "form": "complete",
+      "children": "1",
+      "housing": "convenient",
+      "finance": "convenient",
+      "social": "nonprob",
+      "health": "not_recom",
+      "class": "not_recom"
+    },
+    {
+      "parents": "usual",
+      "has_nurs": "proper",
+      "form": "complete",
+      "children": "1",
+      "housing": "convenient",
+      "finance": "convenient",
+      "social": "slightly_prob",
+      "health": "recommended",
+      "class": "recommend"
+    },
+    {
+      "parents": "usual",
+      "has_nurs": "proper",
+      "form": "complete",
+      "children": "1",
+      "housing": "convenient",
+      "finance": "convenient",
+      "social": "slightly_prob",
+      "health": "priority",
+      "class": "priority"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_clickbench_group_distinct_topk",
+    "template_name": "Top-k Groups by Distinct Entity Coverage",
+    "primary_family": "subgroup_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT {group_col}, COUNT(DISTINCT {entity_col}) AS distinct_entities\nFROM {table}\nGROUP BY {group_col}\nORDER BY distinct_entities DESC\nLIMIT {top_k};",
+    "required_roles": [
+      "group_col",
+      "entity_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "c7",
+  "question": "Use template Top-k Groups by Distinct Entity Coverage to probe internal_profile_stability with semantic role ranked_signal_view. Focus on group_col=social.",
+  "planned_template_id": "tpl_clickbench_group_distinct_topk",
+  "bindings": {
+    "group_col": "social",
+    "entity_col": "social",
+    "top_k": 11,
+    "top_n": 5,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 0.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, COUNT(DISTINCT {entity_col}) AS distinct_entities\nFROM {table}\nGROUP BY {group_col}\nORDER BY distinct_entities DESC\nLIMIT {top_k};"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_034b189bd3aaf62a/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40db-55be-7861-9f3d-64bcf39f1206"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_clickbench_group_distinct_topk\\nSELECT \\\"social\\\", COUNT(DISTINCT \\\"social\\\") AS distinct_entities\\nFROM \\\"c7\\\"\\nGROUP BY \\\"social\\\"\\nORDER BY distinct_entities DESC\\nLIMIT 11;\",\"notes\":\"Applied the required template with group_col=\\\"social\\\" and entity_col=\\\"social\\\" as bound. Because the grouped column and distinct-count column are the same, each non-NULL social group will typically have distinct_entities = 1.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":13895,"cached_input_tokens":12032,"output_tokens":315,"reasoning_output_tokens":206}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_034b189bd3aaf62a/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_clickbench_group_distinct_topk\nSELECT \"social\", COUNT(DISTINCT \"social\") AS distinct_entities\nFROM \"c7\"\nGROUP BY \"social\"\nORDER BY distinct_entities DESC\nLIMIT 11;","notes":"Applied the required template with group_col=\"social\" and entity_col=\"social\" as bound. Because the grouped column and distinct-count column are the same, each non-NULL social group will typically have distinct_entities = 1."}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_03967842cb8b6b0b/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=children, condition_col=children.
+Result preview: [{"children": "2", "condition_rate": 1.0}, {"children": "more", "condition_rate": 0.0}, {"children": "3", "condition_rate": 0.0}, {"children": "1", "condition_rate": 0.0}]

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_03967842cb8b6b0b/generated_sql.sql

@@ -0,0 +1,18 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_b
+-- sql_source_dataset_id: c7
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_m4_group_condition_rate
+-- query_record_id: v2q_c7_03967842cb8b6b0b
+-- problem_id: v2p_c7_3e1c67ef42353896
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "children",
+       AVG(CASE WHEN "children" = '2' THEN 1 ELSE 0 END) AS "condition_rate"
+FROM "c7"
+GROUP BY "children"
+ORDER BY "condition_rate" DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_03967842cb8b6b0b/query_results.jsonl

@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_condition_rate\nSELECT \"children\",\n       AVG(CASE WHEN \"children\" = '2' THEN 1 ELSE 0 END) AS \"condition_rate\"\nFROM \"c7\"\nGROUP BY \"children\"\nORDER BY \"condition_rate\" DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"children\\\",\\n       AVG(CASE WHEN \\\"children\\\" = '2' THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"c7\\\"\\nGROUP BY \\\"children\\\"\\nORDER BY \\\"condition_rate\\\" DESC;\", \"columns\": [\"children\", \"condition_rate\"], \"rows\": [{\"children\": \"2\", \"condition_rate\": 1.0}, {\"children\": \"more\", \"condition_rate\": 0.0}, {\"children\": \"3\", \"condition_rate\": 0.0}, {\"children\": \"1\", \"condition_rate\": 0.0}], \"row_count_returned\": 4, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 8.33}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_03967842cb8b6b0b/run_manifest.json

@@ -0,0 +1,92 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "c7",
+  "started_at": "2026-05-19T15:34:35.085596+00:00",
+  "ended_at": "2026-05-19T15:34:50.704683+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c7_03967842cb8b6b0b",
+    "problem_id": "v2p_c7_3e1c67ef42353896",
+    "dataset_id": "c7",
+    "template_id": "tpl_m4_group_condition_rate",
+    "template_name": "Grouped Condition Rate",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "dependency_strength_similarity",
+    "intended_facet_id": "pairwise_conditional_dependency",
+    "variant_semantic_role": "focused_target_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=children, condition_col=children.",
+    "bindings": {
+      "group_col": "children",
+      "condition_col": "children",
+      "condition_value": "2",
+      "positive_value": "1",
+      "negative_value": "2",
+      "top_k": 15,
+      "top_n": 6,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.05,
+      "baseline_multiplier": 1.75,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 4,
+      "measure_threshold": 0.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "condition_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;",
+    "notes": [
+      "default_facets=pairwise_conditional_dependency",
+      "template_selection_mode=rule",
+      "problem_index_within_template=7",
+      "sql_variant_index=2/2",
+      "binding_index=30"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 3,
+    "problem_index_within_template": 7,
+    "sql_variant_index": 2,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c7/sql/v2q_c7_03967842cb8b6b0b.sql",
+  "usage_summary": {
+    "dataset_id": "c7",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c7_03967842cb8b6b0b",
+    "api_calls": 0,
+    "input_tokens": 13930,
+    "cached_input_tokens": 12672,
+    "output_tokens": 425,
+    "total_tokens": 14355,
+    "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": 15603.46,
+    "sql_execution_elapsed_ms_total": 8.33,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_03967842cb8b6b0b/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_03967842cb8b6b0b/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:34:50.693224+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 15603.46, "started_at": "2026-05-19T15:34:35.088497+00:00", "ended_at": "2026-05-19T15:34:50.692045+00:00", "prompt_metrics": {"chars": 6499, "bytes_utf8": 6499, "lines": 207, "estimated_tokens": null}, "response_metrics": {"chars": 530, "bytes_utf8": 530, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13930, "cached_input_tokens": 12672, "output_tokens": 425, "reasoning_output_tokens": 296}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"children\\\",\\n       AVG(CASE WHEN \\\"children\\\" = '2' THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"c7\\\"\\nGROUP BY \\\"children\\\"\\nORDER BY \\\"condition_rate\\\" DESC;\",\"notes\":\"Applied the provided Grouped Condition Rate template with group_col=\\\"children\\\" and condition_col=\\\"children\\\" using condition_value='2'. Because the grouping and condition columns are the same, this measures whether each children group equals '2', yielding a self-condition rate per group.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_03967842cb8b6b0b/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "c7",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_c7_03967842cb8b6b0b",
+  "api_calls": 0,
+  "input_tokens": 13930,
+  "cached_input_tokens": 12672,
+  "output_tokens": 425,
+  "total_tokens": 14355,
+  "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": 15603.46,
+  "sql_execution_elapsed_ms_total": 8.33,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_03967842cb8b6b0b/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_04102e27247e1d92/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 6550, "bytes_utf8": 6550, "lines": 208, "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": 380, "bytes_utf8": 380, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13959, "cached_input_tokens": 12672, "output_tokens": 236, "reasoning_output_tokens": 129}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_04102e27247e1d92/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": "c7",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c7_04102e27247e1d92",
+    "api_calls": 0,
+    "input_tokens": 13959,
+    "cached_input_tokens": 12672,
+    "output_tokens": 236,
+    "total_tokens": 14195,
+    "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": 7786.25,
+    "sql_execution_elapsed_ms_total": 6.48,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_04102e27247e1d92/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_04102e27247e1d92/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": "2026-05-19T15:38:53.584451+00:00",
+  "ended_at": "2026-05-19T15:39:01.370745+00:00",
+  "elapsed_ms": 7786.25,
+  "prompt_metrics": {
+    "chars": 6550,
+    "bytes_utf8": 6550,
+    "lines": 208,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 751,
+    "bytes_utf8": 751,
+    "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": 380,
+      "bytes_utf8": 380,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 13959,
+      "cached_input_tokens": 12672,
+      "output_tokens": 236,
+      "reasoning_output_tokens": 129
+    }
+  },
+  "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_b/c7/artifacts/v2q_c7_04102e27247e1d92/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,208 @@
+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: c7
+- dataset_name: C7
+- table_name: c7
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 8 feature columns and target `class`.
+- task_type: classification
+- target_column: class
+- main_row_count: 12960
+- important_fields:
+- parents: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for parents.
+- has_nurs: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for has nurs.
+- form: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for form.
+- children: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for children.
+- housing: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for housing.
+- finance: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for finance.
+- social: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for social.
+- health: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for health.
+- class: role=target, type=categorical_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for class.
+- useful_field_combinations: [['parents', 'has_nurs', 'class'], ['parents', 'parents', 'class']]
+- fields_requiring_caution: ['class']
+- source_url: https://www.openml.org/d/26
+
+SQLite schema snapshot:
+{
+  "table_name": "c7",
+  "quoted_table_name": "\"c7\"",
+  "row_count": 12960,
+  "columns": [
+    {
+      "name": "parents",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "has_nurs",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "form",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "housing",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "finance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "social",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "health",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "class",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "parents": "usual",
+      "has_nurs": "proper",
+      "form": "complete",
+      "children": "1",
+      "housing": "convenient",
+      "finance": "convenient",
+      "social": "nonprob",
+      "health": "recommended",
+      "class": "recommend"
+    },
+    {
+      "parents": "usual",
+      "has_nurs": "proper",
+      "form": "complete",
+      "children": "1",
+      "housing": "convenient",
+      "finance": "convenient",
+      "social": "nonprob",
+      "health": "priority",
+      "class": "priority"
+    },
+    {
+      "parents": "usual",
+      "has_nurs": "proper",
+      "form": "complete",
+      "children": "1",
+      "housing": "convenient",
+      "finance": "convenient",
+      "social": "nonprob",
+      "health": "not_recom",
+      "class": "not_recom"
+    },
+    {
+      "parents": "usual",
+      "has_nurs": "proper",
+      "form": "complete",
+      "children": "1",
+      "housing": "convenient",
+      "finance": "convenient",
+      "social": "slightly_prob",
+      "health": "recommended",
+      "class": "recommend"
+    },
+    {
+      "parents": "usual",
+      "has_nurs": "proper",
+      "form": "complete",
+      "children": "1",
+      "housing": "convenient",
+      "finance": "convenient",
+      "social": "slightly_prob",
+      "health": "priority",
+      "class": "priority"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_c2_filtered_group_count_2d",
+    "template_name": "Filtered Two-Dimensional Group Count",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;",
+    "required_roles": [
+      "group_col",
+      "group_col_2",
+      "predicate_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "c7",
+  "question": "Use template Filtered Two-Dimensional Group Count to probe slice_level_consistency with semantic role count_distribution. Focus on group_col=form, group_col_2=class.",
+  "planned_template_id": "tpl_c2_filtered_group_count_2d",
+  "bindings": {
+    "group_col": "form",
+    "group_col_2": "class",
+    "predicate_col": "form",
+    "predicate_op": "=",
+    "predicate_value": "complete",
+    "top_k": 11,
+    "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": 0.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_04102e27247e1d92/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40e3-d61a-7510-8a99-f139f40a81e6"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_c2_filtered_group_count_2d\\nSELECT \\\"form\\\", \\\"class\\\", COUNT(*) AS row_count\\nFROM \\\"c7\\\"\\nWHERE \\\"form\\\" = 'complete'\\nGROUP BY \\\"form\\\", \\\"class\\\"\\nORDER BY row_count DESC;\",\"notes\":\"Applies the requested filtered two-dimensional group count template on table \\\"c7\\\", grouping by \\\"form\\\" and \\\"class\\\" with the fixed filter \\\"form\\\" = 'complete'.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":13959,"cached_input_tokens":12672,"output_tokens":236,"reasoning_output_tokens":129}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_04102e27247e1d92/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_c2_filtered_group_count_2d\nSELECT \"form\", \"class\", COUNT(*) AS row_count\nFROM \"c7\"\nWHERE \"form\" = 'complete'\nGROUP BY \"form\", \"class\"\nORDER BY row_count DESC;","notes":"Applies the requested filtered two-dimensional group count template on table \"c7\", grouping by \"form\" and \"class\" with the fixed filter \"form\" = 'complete'."}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_04223e355625648d/query_results.jsonl

@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tail_target_rate_extremes_v2\nSELECT\n    \"form\",\n    COUNT(*) AS support,\n    AVG(CASE WHEN \"class\" = 'spec_prior' THEN 1 ELSE 0 END) AS focus_rate\nFROM \"c7\"\nGROUP BY \"form\"\nHAVING COUNT(*) >= 4\nORDER BY focus_rate DESC, support ASC\nLIMIT 17;", "result": "{\"query\": \"-- template_id: tpl_tail_target_rate_extremes_v2\\nSELECT\\n    \\\"form\\\",\\n    COUNT(*) AS support,\\n    AVG(CASE WHEN \\\"class\\\" = 'spec_prior' THEN 1 ELSE 0 END) AS focus_rate\\nFROM \\\"c7\\\"\\nGROUP BY \\\"form\\\"\\nHAVING COUNT(*) >= 4\\nORDER BY focus_rate DESC, support ASC\\nLIMIT 17;\", \"columns\": [\"form\", \"support\", \"focus_rate\"], \"rows\": [{\"form\": \"foster\", \"support\": 3240, \"focus_rate\": 0.3506172839506173}, {\"form\": \"incomplete\", \"support\": 3240, \"focus_rate\": 0.32469135802469135}, {\"form\": \"completed\", \"support\": 3240, \"focus_rate\": 0.29876543209876544}, {\"form\": \"complete\", \"support\": 3240, \"focus_rate\": 0.2740740740740741}], \"row_count_returned\": 4, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 5.93}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_04223e355625648d/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "c7",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_c7_04223e355625648d",
+  "api_calls": 0,
+  "input_tokens": 13984,
+  "cached_input_tokens": 12032,
+  "output_tokens": 370,
+  "total_tokens": 14354,
+  "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": 10526.44,
+  "sql_execution_elapsed_ms_total": 5.93,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_04223e355625648d/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_056b629c2c6e1405/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Filtered Top-k Group Count to probe subgroup_size_stability with semantic role filtered_stable_view. Focus on group_col=children.
+Result preview: [{"children": "more", "support": 3240}]

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_056b629c2c6e1405/generated_sql.sql

@@ -0,0 +1,19 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_b
+-- sql_source_dataset_id: c7
+-- family_id: subgroup_structure
+-- canonical_subitem_id: subgroup_size_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: filtered_stable_view
+-- template_id: tpl_clickbench_filtered_topk_group_count
+-- query_record_id: v2q_c7_056b629c2c6e1405
+-- problem_id: v2p_c7_84d44f4e2b40ce5d
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "children", COUNT(*) AS support
+FROM "c7"
+WHERE "children" = 'more'
+GROUP BY "children"
+ORDER BY support DESC
+LIMIT 11;

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_056b629c2c6e1405/query_results.jsonl

@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_clickbench_filtered_topk_group_count\nSELECT \"children\", COUNT(*) AS support\nFROM \"c7\"\nWHERE \"children\" = 'more'\nGROUP BY \"children\"\nORDER BY support DESC\nLIMIT 11;", "result": "{\"query\": \"-- template_id: tpl_clickbench_filtered_topk_group_count\\nSELECT \\\"children\\\", COUNT(*) AS support\\nFROM \\\"c7\\\"\\nWHERE \\\"children\\\" = 'more'\\nGROUP BY \\\"children\\\"\\nORDER BY support DESC\\nLIMIT 11;\", \"columns\": [\"children\", \"support\"], \"rows\": [{\"children\": \"more\", \"support\": 3240}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 3.44}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_056b629c2c6e1405/run_manifest.json

@@ -0,0 +1,91 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "c7",
+  "started_at": "2026-05-19T15:51:48.857290+00:00",
+  "ended_at": "2026-05-19T15:51:55.988836+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c7_056b629c2c6e1405",
+    "problem_id": "v2p_c7_84d44f4e2b40ce5d",
+    "dataset_id": "c7",
+    "template_id": "tpl_clickbench_filtered_topk_group_count",
+    "template_name": "Filtered Top-k Group Count",
+    "family_id": "subgroup_structure",
+    "canonical_subitem_id": "subgroup_size_stability",
+    "intended_facet_id": "subgroup_distribution_shift",
+    "variant_semantic_role": "filtered_stable_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Filtered Top-k Group Count to probe subgroup_size_stability with semantic role filtered_stable_view. Focus on group_col=children.",
+    "bindings": {
+      "group_col": "children",
+      "predicate_col": "children",
+      "predicate_op": "=",
+      "predicate_value": "more",
+      "top_k": 11,
+      "top_n": 6,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 0.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "predicate_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, COUNT(*) AS support\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}\nORDER BY support DESC\nLIMIT {top_k};",
+    "notes": [
+      "default_facets=subgroup_distribution_shift",
+      "template_selection_mode=rule",
+      "problem_index_within_template=4",
+      "sql_variant_index=1/2",
+      "binding_index=111"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 10,
+    "problem_index_within_template": 4,
+    "sql_variant_index": 1,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c7/sql/v2q_c7_056b629c2c6e1405.sql",
+  "usage_summary": {
+    "dataset_id": "c7",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c7_056b629c2c6e1405",
+    "api_calls": 0,
+    "input_tokens": 13918,
+    "cached_input_tokens": 12032,
+    "output_tokens": 227,
+    "total_tokens": 14145,
+    "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": 7121.46,
+    "sql_execution_elapsed_ms_total": 3.44,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_056b629c2c6e1405/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_056b629c2c6e1405/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:51:55.982783+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 7121.46, "started_at": "2026-05-19T15:51:48.859773+00:00", "ended_at": "2026-05-19T15:51:55.981279+00:00", "prompt_metrics": {"chars": 6439, "bytes_utf8": 6439, "lines": 206, "estimated_tokens": null}, "response_metrics": {"chars": 369, "bytes_utf8": 369, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13918, "cached_input_tokens": 12032, "output_tokens": 227, "reasoning_output_tokens": 130}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_clickbench_filtered_topk_group_count\\nSELECT \\\"children\\\", COUNT(*) AS support\\nFROM \\\"c7\\\"\\nWHERE \\\"children\\\" = 'more'\\nGROUP BY \\\"children\\\"\\nORDER BY support DESC\\nLIMIT 11;\",\"notes\":\"Applied the provided Filtered Top-k Group Count template with group_col=\\\"children\\\", predicate_col=\\\"children\\\", predicate_value='more', and top_k=11.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_056b629c2c6e1405/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "c7",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_c7_056b629c2c6e1405",
+  "api_calls": 0,
+  "input_tokens": 13918,
+  "cached_input_tokens": 12032,
+  "output_tokens": 227,
+  "total_tokens": 14145,
+  "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": 7121.46,
+  "sql_execution_elapsed_ms_total": 3.44,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_056b629c2c6e1405/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_06702609eb08cf6e/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 6509, "bytes_utf8": 6509, "lines": 207, "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": 439, "bytes_utf8": 439, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13934, "cached_input_tokens": 12032, "output_tokens": 319, "reasoning_output_tokens": 205}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_06702609eb08cf6e/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": "c7",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c7_06702609eb08cf6e",
+    "api_calls": 0,
+    "input_tokens": 13934,
+    "cached_input_tokens": 12032,
+    "output_tokens": 319,
+    "total_tokens": 14253,
+    "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": 9104.45,
+    "sql_execution_elapsed_ms_total": 4.58,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c7/artifacts/v2q_c7_06702609eb08cf6e/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}