Add files using upload-large-folder tool

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_020e0a2a5441efb1/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 11858, "bytes_utf8": 11858, "lines": 394, "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": 527, "bytes_utf8": 527, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15961, "cached_input_tokens": 14720, "output_tokens": 521, "reasoning_output_tokens": 370}}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_020e0a2a5441efb1/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": "c14",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c14_020e0a2a5441efb1",
+    "api_calls": 0,
+    "input_tokens": 15961,
+    "cached_input_tokens": 14720,
+    "output_tokens": 521,
+    "total_tokens": 16482,
+    "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": 15925.65,
+    "sql_execution_elapsed_ms_total": 403.47,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_020e0a2a5441efb1/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_020e0a2a5441efb1/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": "2026-05-19T15:45:35.383369+00:00",
+  "ended_at": "2026-05-19T15:45:51.309038+00:00",
+  "elapsed_ms": 15925.65,
+  "prompt_metrics": {
+    "chars": 11858,
+    "bytes_utf8": 11858,
+    "lines": 394,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1223,
+    "bytes_utf8": 1223,
+    "lines": 5,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 527,
+      "bytes_utf8": 527,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 15961,
+      "cached_input_tokens": 14720,
+      "output_tokens": 521,
+      "reasoning_output_tokens": 370
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_020e0a2a5441efb1/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,394 @@
+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: c14
+- dataset_name: Cat In The Dat
+- table_name: c14
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 24 feature columns and target `target`.
+- task_type: classification
+- target_column: target
+- main_row_count: 300000
+- important_fields:
+- id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for id.
+- bin_0: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 0.
+- bin_1: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 1.
+- bin_2: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 2.
+- bin_3: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 3.
+- bin_4: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 4.
+- nom_0: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 0.
+- nom_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 1.
+- nom_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 2.
+- nom_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 3.
+- nom_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 4.
+- nom_5: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 5.
+- nom_6: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 6.
+- nom_7: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 7.
+- nom_8: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 8.
+- nom_9: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 9.
+- ord_0: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for ord 0.
+- ord_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 1.
+- ord_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 2.
+- ord_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 3.
+- ord_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 4.
+- ord_5: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for ord 5.
+- day: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for day.
+- month: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for month.
+- target: role=target, type=binary_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target.
+- useful_field_combinations: [['bin_0', 'bin_1', 'target'], ['bin_0', 'ord_0', 'target'], ['bin_0', 'bin_0', 'target']]
+- fields_requiring_caution: ['target', 'nom_5', 'nom_6', 'nom_7']
+- source_url: https://www.kaggle.com/c/cat-in-the-dat
+
+SQLite schema snapshot:
+{
+  "table_name": "c14",
+  "quoted_table_name": "\"c14\"",
+  "row_count": 300000,
+  "columns": [
+    {
+      "name": "id",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_0",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_3",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_4",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_0",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_3",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_4",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_5",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_6",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_7",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_8",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_9",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_0",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_3",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_4",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_5",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "day",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "month",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "target",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "id": "0",
+      "bin_0": "0",
+      "bin_1": "0",
+      "bin_2": "0",
+      "bin_3": "T",
+      "bin_4": "Y",
+      "nom_0": "Green",
+      "nom_1": "Triangle",
+      "nom_2": "Snake",
+      "nom_3": "Finland",
+      "nom_4": "Bassoon",
+      "nom_5": "50f116bcf",
+      "nom_6": "3ac1b8814",
+      "nom_7": "68f6ad3e9",
+      "nom_8": "c389000ab",
+      "nom_9": "2f4cb3d51",
+      "ord_0": "2",
+      "ord_1": "Grandmaster",
+      "ord_2": "Cold",
+      "ord_3": "h",
+      "ord_4": "D",
+      "ord_5": "kr",
+      "day": "2",
+      "month": "2",
+      "target": "0"
+    },
+    {
+      "id": "1",
+      "bin_0": "0",
+      "bin_1": "1",
+      "bin_2": "0",
+      "bin_3": "T",
+      "bin_4": "Y",
+      "nom_0": "Green",
+      "nom_1": "Trapezoid",
+      "nom_2": "Hamster",
+      "nom_3": "Russia",
+      "nom_4": "Piano",
+      "nom_5": "b3b4d25d0",
+      "nom_6": "fbcb50fc1",
+      "nom_7": "3b6dd5612",
+      "nom_8": "4cd920251",
+      "nom_9": "f83c56c21",
+      "ord_0": "1",
+      "ord_1": "Grandmaster",
+      "ord_2": "Hot",
+      "ord_3": "a",
+      "ord_4": "A",
+      "ord_5": "bF",
+      "day": "7",
+      "month": "8",
+      "target": "0"
+    },
+    {
+      "id": "2",
+      "bin_0": "0",
+      "bin_1": "0",
+      "bin_2": "0",
+      "bin_3": "F",
+      "bin_4": "Y",
+      "nom_0": "Blue",
+      "nom_1": "Trapezoid",
+      "nom_2": "Lion",
+      "nom_3": "Russia",
+      "nom_4": "Theremin",
+      "nom_5": "3263bdce5",
+      "nom_6": "0922e3cb8",
+      "nom_7": "a6a36f527",
+      "nom_8": "de9c9f684",
+      "nom_9": "ae6800dd0",
+      "ord_0": "1",
+      "ord_1": "Expert",
+      "ord_2": "Lava Hot",
+      "ord_3": "h",
+      "ord_4": "R",
+      "ord_5": "Jc",
+      "day": "7",
+      "month": "2",
+      "target": "0"
+    },
+    {
+      "id": "3",
+      "bin_0": "0",
+      "bin_1": "1",
+      "bin_2": "0",
+      "bin_3": "F",
+      "bin_4": "Y",
+      "nom_0": "Red",
+      "nom_1": "Trapezoid",
+      "nom_2": "Snake",
+      "nom_3": "Canada",
+      "nom_4": "Oboe",
+      "nom_5": "f12246592",
+      "nom_6": "50d7ad46a",
+      "nom_7": "ec69236eb",
+      "nom_8": "4ade6ab69",
+      "nom_9": "8270f0d71",
+      "ord_0": "1",
+      "ord_1": "Grandmaster",
+      "ord_2": "Boiling Hot",
+      "ord_3": "i",
+      "ord_4": "D",
+      "ord_5": "kW",
+      "day": "2",
+      "month": "1",
+      "target": "1"
+    },
+    {
+      "id": "4",
+      "bin_0": "0",
+      "bin_1": "0",
+      "bin_2": "0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Trapezoid",
+      "nom_2": "Lion",
+      "nom_3": "Canada",
+      "nom_4": "Oboe",
+      "nom_5": "5b0f5acd5",
+      "nom_6": "1fe17a1fd",
+      "nom_7": "04ddac2be",
+      "nom_8": "cb43ab175",
+      "nom_9": "b164b72a7",
+      "ord_0": "1",
+      "ord_1": "Grandmaster",
+      "ord_2": "Freezing",
+      "ord_3": "a",
+      "ord_4": "R",
+      "ord_5": "qP",
+      "day": "7",
+      "month": "8",
+      "target": "0"
+    }
+  ]
+}
+
+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": "c14",
+  "question": "Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=ord_0.",
+  "planned_template_id": "tpl_m4_quantile_tail_slice",
+  "bindings": {
+    "measure_col": "ord_0",
+    "top_k": 11,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 2.5,
+    "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_d/c14/artifacts/v2q_c14_020e0a2a5441efb1/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,5 @@
+{"type":"thread.started","thread_id":"019e40e9-f7a5-70a1-a8c9-f72c59338905"}
+{"type":"turn.started"}
+{"type":"error","message":"Reconnecting... 2/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 2000000, Requested 16596. Please try again in 497ms. 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 \\\"ord_0\\\",\\n           NTILE(10) OVER (ORDER BY CAST(\\\"ord_0\\\" AS INTEGER) DESC) AS tail_bucket\\n    FROM \\\"c14\\\"\\n)\\nSELECT \\\"ord_0\\\"\\nFROM buckets\\nWHERE tail_bucket = 1\\nORDER BY CAST(\\\"ord_0\\\" AS INTEGER) DESC;\",\"notes\":\"Used the planned Quantile Tail Slice template with measure_col bound to \\\"ord_0\\\" and num_tiles=10. CAST to INTEGER is applied for correct numeric tail ordering because \\\"ord_0\\\" is stored as TEXT in the SQLite schema.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":15961,"cached_input_tokens":14720,"output_tokens":521,"reasoning_output_tokens":370}}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_020e0a2a5441efb1/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_m4_quantile_tail_slice\nWITH buckets AS (\n    SELECT \"ord_0\",\n           NTILE(10) OVER (ORDER BY CAST(\"ord_0\" AS INTEGER) DESC) AS tail_bucket\n    FROM \"c14\"\n)\nSELECT \"ord_0\"\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY CAST(\"ord_0\" AS INTEGER) DESC;","notes":"Used the planned Quantile Tail Slice template with measure_col bound to \"ord_0\" and num_tiles=10. CAST to INTEGER is applied for correct numeric tail ordering because \"ord_0\" is stored as TEXT in the SQLite schema."}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_07a800fb6dea0c53/cli/sql_attempt_1.metadata.json

@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:06:17.124402+00:00",
+  "ended_at": "2026-05-19T16:06:20.105880+00:00",
+  "elapsed_ms": 2981.44,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 11948,
+    "bytes_utf8": 11948,
+    "lines": 399,
+    "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_d/c14/artifacts/v2q_c14_07a800fb6dea0c53/cli/sql_attempt_2.metadata.json

@@ -0,0 +1,43 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:06:21.108332+00:00",
+  "ended_at": "2026-05-19T16:06:24.480195+00:00",
+  "elapsed_ms": 3371.82,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 11948,
+    "bytes_utf8": 11948,
+    "lines": 399,
+    "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_d/c14/artifacts/v2q_c14_07a800fb6dea0c53/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,399 @@
+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: c14
+- dataset_name: Cat In The Dat
+- table_name: c14
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 24 feature columns and target `target`.
+- task_type: classification
+- target_column: target
+- main_row_count: 300000
+- important_fields:
+- id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for id.
+- bin_0: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 0.
+- bin_1: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 1.
+- bin_2: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 2.
+- bin_3: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 3.
+- bin_4: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 4.
+- nom_0: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 0.
+- nom_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 1.
+- nom_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 2.
+- nom_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 3.
+- nom_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 4.
+- nom_5: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 5.
+- nom_6: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 6.
+- nom_7: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 7.
+- nom_8: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 8.
+- nom_9: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 9.
+- ord_0: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for ord 0.
+- ord_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 1.
+- ord_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 2.
+- ord_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 3.
+- ord_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 4.
+- ord_5: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for ord 5.
+- day: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for day.
+- month: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for month.
+- target: role=target, type=binary_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target.
+- useful_field_combinations: [['bin_0', 'bin_1', 'target'], ['bin_0', 'ord_0', 'target'], ['bin_0', 'bin_0', 'target']]
+- fields_requiring_caution: ['target', 'nom_5', 'nom_6', 'nom_7']
+- source_url: https://www.kaggle.com/c/cat-in-the-dat
+
+SQLite schema snapshot:
+{
+  "table_name": "c14",
+  "quoted_table_name": "\"c14\"",
+  "row_count": 300000,
+  "columns": [
+    {
+      "name": "id",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_0",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_3",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_4",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_0",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_3",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_4",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_5",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_6",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_7",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_8",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_9",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_0",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_3",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_4",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_5",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "day",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "month",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "target",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "id": "0",
+      "bin_0": "0",
+      "bin_1": "0",
+      "bin_2": "0",
+      "bin_3": "T",
+      "bin_4": "Y",
+      "nom_0": "Green",
+      "nom_1": "Triangle",
+      "nom_2": "Snake",
+      "nom_3": "Finland",
+      "nom_4": "Bassoon",
+      "nom_5": "50f116bcf",
+      "nom_6": "3ac1b8814",
+      "nom_7": "68f6ad3e9",
+      "nom_8": "c389000ab",
+      "nom_9": "2f4cb3d51",
+      "ord_0": "2",
+      "ord_1": "Grandmaster",
+      "ord_2": "Cold",
+      "ord_3": "h",
+      "ord_4": "D",
+      "ord_5": "kr",
+      "day": "2",
+      "month": "2",
+      "target": "0"
+    },
+    {
+      "id": "1",
+      "bin_0": "0",
+      "bin_1": "1",
+      "bin_2": "0",
+      "bin_3": "T",
+      "bin_4": "Y",
+      "nom_0": "Green",
+      "nom_1": "Trapezoid",
+      "nom_2": "Hamster",
+      "nom_3": "Russia",
+      "nom_4": "Piano",
+      "nom_5": "b3b4d25d0",
+      "nom_6": "fbcb50fc1",
+      "nom_7": "3b6dd5612",
+      "nom_8": "4cd920251",
+      "nom_9": "f83c56c21",
+      "ord_0": "1",
+      "ord_1": "Grandmaster",
+      "ord_2": "Hot",
+      "ord_3": "a",
+      "ord_4": "A",
+      "ord_5": "bF",
+      "day": "7",
+      "month": "8",
+      "target": "0"
+    },
+    {
+      "id": "2",
+      "bin_0": "0",
+      "bin_1": "0",
+      "bin_2": "0",
+      "bin_3": "F",
+      "bin_4": "Y",
+      "nom_0": "Blue",
+      "nom_1": "Trapezoid",
+      "nom_2": "Lion",
+      "nom_3": "Russia",
+      "nom_4": "Theremin",
+      "nom_5": "3263bdce5",
+      "nom_6": "0922e3cb8",
+      "nom_7": "a6a36f527",
+      "nom_8": "de9c9f684",
+      "nom_9": "ae6800dd0",
+      "ord_0": "1",
+      "ord_1": "Expert",
+      "ord_2": "Lava Hot",
+      "ord_3": "h",
+      "ord_4": "R",
+      "ord_5": "Jc",
+      "day": "7",
+      "month": "2",
+      "target": "0"
+    },
+    {
+      "id": "3",
+      "bin_0": "0",
+      "bin_1": "1",
+      "bin_2": "0",
+      "bin_3": "F",
+      "bin_4": "Y",
+      "nom_0": "Red",
+      "nom_1": "Trapezoid",
+      "nom_2": "Snake",
+      "nom_3": "Canada",
+      "nom_4": "Oboe",
+      "nom_5": "f12246592",
+      "nom_6": "50d7ad46a",
+      "nom_7": "ec69236eb",
+      "nom_8": "4ade6ab69",
+      "nom_9": "8270f0d71",
+      "ord_0": "1",
+      "ord_1": "Grandmaster",
+      "ord_2": "Boiling Hot",
+      "ord_3": "i",
+      "ord_4": "D",
+      "ord_5": "kW",
+      "day": "2",
+      "month": "1",
+      "target": "1"
+    },
+    {
+      "id": "4",
+      "bin_0": "0",
+      "bin_1": "0",
+      "bin_2": "0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Trapezoid",
+      "nom_2": "Lion",
+      "nom_3": "Canada",
+      "nom_4": "Oboe",
+      "nom_5": "5b0f5acd5",
+      "nom_6": "1fe17a1fd",
+      "nom_7": "04ddac2be",
+      "nom_8": "cb43ab175",
+      "nom_9": "b164b72a7",
+      "ord_0": "1",
+      "ord_1": "Grandmaster",
+      "ord_2": "Freezing",
+      "ord_3": "a",
+      "ord_4": "R",
+      "ord_5": "qP",
+      "day": "7",
+      "month": "8",
+      "target": "0"
+    }
+  ]
+}
+
+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": "c14",
+  "question": "Use template Grouped Condition Rate to probe direction_consistency with semantic role focused_target_view. Focus on group_col=ord_1, condition_col=ord_1.",
+  "planned_template_id": "tpl_m4_group_condition_rate",
+  "bindings": {
+    "group_col": "ord_1",
+    "condition_col": "ord_1",
+    "condition_value": "Grandmaster",
+    "positive_value": "Grandmaster",
+    "negative_value": "Contributor",
+    "top_k": 11,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 2.5,
+    "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_d/c14/artifacts/v2q_c14_07a800fb6dea0c53/cli/sql_prompt_attempt_2.txt

@@ -0,0 +1,399 @@
+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: c14
+- dataset_name: Cat In The Dat
+- table_name: c14
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 24 feature columns and target `target`.
+- task_type: classification
+- target_column: target
+- main_row_count: 300000
+- important_fields:
+- id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for id.
+- bin_0: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 0.
+- bin_1: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 1.
+- bin_2: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 2.
+- bin_3: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 3.
+- bin_4: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 4.
+- nom_0: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 0.
+- nom_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 1.
+- nom_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 2.
+- nom_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 3.
+- nom_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 4.
+- nom_5: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 5.
+- nom_6: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 6.
+- nom_7: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 7.
+- nom_8: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 8.
+- nom_9: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 9.
+- ord_0: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for ord 0.
+- ord_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 1.
+- ord_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 2.
+- ord_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 3.
+- ord_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 4.
+- ord_5: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for ord 5.
+- day: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for day.
+- month: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for month.
+- target: role=target, type=binary_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target.
+- useful_field_combinations: [['bin_0', 'bin_1', 'target'], ['bin_0', 'ord_0', 'target'], ['bin_0', 'bin_0', 'target']]
+- fields_requiring_caution: ['target', 'nom_5', 'nom_6', 'nom_7']
+- source_url: https://www.kaggle.com/c/cat-in-the-dat
+
+SQLite schema snapshot:
+{
+  "table_name": "c14",
+  "quoted_table_name": "\"c14\"",
+  "row_count": 300000,
+  "columns": [
+    {
+      "name": "id",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_0",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_3",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_4",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_0",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_3",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_4",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_5",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_6",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_7",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_8",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_9",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_0",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_3",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_4",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_5",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "day",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "month",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "target",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "id": "0",
+      "bin_0": "0",
+      "bin_1": "0",
+      "bin_2": "0",
+      "bin_3": "T",
+      "bin_4": "Y",
+      "nom_0": "Green",
+      "nom_1": "Triangle",
+      "nom_2": "Snake",
+      "nom_3": "Finland",
+      "nom_4": "Bassoon",
+      "nom_5": "50f116bcf",
+      "nom_6": "3ac1b8814",
+      "nom_7": "68f6ad3e9",
+      "nom_8": "c389000ab",
+      "nom_9": "2f4cb3d51",
+      "ord_0": "2",
+      "ord_1": "Grandmaster",
+      "ord_2": "Cold",
+      "ord_3": "h",
+      "ord_4": "D",
+      "ord_5": "kr",
+      "day": "2",
+      "month": "2",
+      "target": "0"
+    },
+    {
+      "id": "1",
+      "bin_0": "0",
+      "bin_1": "1",
+      "bin_2": "0",
+      "bin_3": "T",
+      "bin_4": "Y",
+      "nom_0": "Green",
+      "nom_1": "Trapezoid",
+      "nom_2": "Hamster",
+      "nom_3": "Russia",
+      "nom_4": "Piano",
+      "nom_5": "b3b4d25d0",
+      "nom_6": "fbcb50fc1",
+      "nom_7": "3b6dd5612",
+      "nom_8": "4cd920251",
+      "nom_9": "f83c56c21",
+      "ord_0": "1",
+      "ord_1": "Grandmaster",
+      "ord_2": "Hot",
+      "ord_3": "a",
+      "ord_4": "A",
+      "ord_5": "bF",
+      "day": "7",
+      "month": "8",
+      "target": "0"
+    },
+    {
+      "id": "2",
+      "bin_0": "0",
+      "bin_1": "0",
+      "bin_2": "0",
+      "bin_3": "F",
+      "bin_4": "Y",
+      "nom_0": "Blue",
+      "nom_1": "Trapezoid",
+      "nom_2": "Lion",
+      "nom_3": "Russia",
+      "nom_4": "Theremin",
+      "nom_5": "3263bdce5",
+      "nom_6": "0922e3cb8",
+      "nom_7": "a6a36f527",
+      "nom_8": "de9c9f684",
+      "nom_9": "ae6800dd0",
+      "ord_0": "1",
+      "ord_1": "Expert",
+      "ord_2": "Lava Hot",
+      "ord_3": "h",
+      "ord_4": "R",
+      "ord_5": "Jc",
+      "day": "7",
+      "month": "2",
+      "target": "0"
+    },
+    {
+      "id": "3",
+      "bin_0": "0",
+      "bin_1": "1",
+      "bin_2": "0",
+      "bin_3": "F",
+      "bin_4": "Y",
+      "nom_0": "Red",
+      "nom_1": "Trapezoid",
+      "nom_2": "Snake",
+      "nom_3": "Canada",
+      "nom_4": "Oboe",
+      "nom_5": "f12246592",
+      "nom_6": "50d7ad46a",
+      "nom_7": "ec69236eb",
+      "nom_8": "4ade6ab69",
+      "nom_9": "8270f0d71",
+      "ord_0": "1",
+      "ord_1": "Grandmaster",
+      "ord_2": "Boiling Hot",
+      "ord_3": "i",
+      "ord_4": "D",
+      "ord_5": "kW",
+      "day": "2",
+      "month": "1",
+      "target": "1"
+    },
+    {
+      "id": "4",
+      "bin_0": "0",
+      "bin_1": "0",
+      "bin_2": "0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Trapezoid",
+      "nom_2": "Lion",
+      "nom_3": "Canada",
+      "nom_4": "Oboe",
+      "nom_5": "5b0f5acd5",
+      "nom_6": "1fe17a1fd",
+      "nom_7": "04ddac2be",
+      "nom_8": "cb43ab175",
+      "nom_9": "b164b72a7",
+      "ord_0": "1",
+      "ord_1": "Grandmaster",
+      "ord_2": "Freezing",
+      "ord_3": "a",
+      "ord_4": "R",
+      "ord_5": "qP",
+      "day": "7",
+      "month": "8",
+      "target": "0"
+    }
+  ]
+}
+
+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": "c14",
+  "question": "Use template Grouped Condition Rate to probe direction_consistency with semantic role focused_target_view. Focus on group_col=ord_1, condition_col=ord_1.",
+  "planned_template_id": "tpl_m4_group_condition_rate",
+  "bindings": {
+    "group_col": "ord_1",
+    "condition_col": "ord_1",
+    "condition_value": "Grandmaster",
+    "positive_value": "Grandmaster",
+    "negative_value": "Contributor",
+    "top_k": 11,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 2.5,
+    "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_d/c14/artifacts/v2q_c14_07a800fb6dea0c53/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fc-ea20-7500-960d-e8d8c0657793"}
+{"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_d/c14/artifacts/v2q_c14_07a800fb6dea0c53/cli/sql_response_attempt_1.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fc-ea20-7500-960d-e8d8c0657793"}
+{"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_d/c14/artifacts/v2q_c14_07a800fb6dea0c53/cli/sql_response_attempt_2.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fc-f9b7-7053-8a49-879c9ee82008"}
+{"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_d/c14/artifacts/v2q_c14_07a800fb6dea0c53/cli/sql_response_attempt_2.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fc-f9b7-7053-8a49-879c9ee82008"}
+{"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_d/c14/artifacts/v2q_c14_0fcdf90112f27537/cli/sql_attempt_1.metadata.json

@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:06:58.480065+00:00",
+  "ended_at": "2026-05-19T16:07:01.520528+00:00",
+  "elapsed_ms": 3040.43,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 11921,
+    "bytes_utf8": 11921,
+    "lines": 399,
+    "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_d/c14/artifacts/v2q_c14_0fcdf90112f27537/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": "2026-05-19T16:07:02.522102+00:00",
+  "ended_at": "2026-05-19T16:07:05.317115+00:00",
+  "elapsed_ms": 2794.98,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 11921,
+    "bytes_utf8": 11921,
+    "lines": 399,
+    "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_d/c14/artifacts/v2q_c14_0fcdf90112f27537/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,399 @@
+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: c14
+- dataset_name: Cat In The Dat
+- table_name: c14
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 24 feature columns and target `target`.
+- task_type: classification
+- target_column: target
+- main_row_count: 300000
+- important_fields:
+- id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for id.
+- bin_0: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 0.
+- bin_1: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 1.
+- bin_2: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 2.
+- bin_3: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 3.
+- bin_4: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 4.
+- nom_0: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 0.
+- nom_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 1.
+- nom_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 2.
+- nom_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 3.
+- nom_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 4.
+- nom_5: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 5.
+- nom_6: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 6.
+- nom_7: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 7.
+- nom_8: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 8.
+- nom_9: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 9.
+- ord_0: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for ord 0.
+- ord_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 1.
+- ord_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 2.
+- ord_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 3.
+- ord_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 4.
+- ord_5: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for ord 5.
+- day: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for day.
+- month: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for month.
+- target: role=target, type=binary_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target.
+- useful_field_combinations: [['bin_0', 'bin_1', 'target'], ['bin_0', 'ord_0', 'target'], ['bin_0', 'bin_0', 'target']]
+- fields_requiring_caution: ['target', 'nom_5', 'nom_6', 'nom_7']
+- source_url: https://www.kaggle.com/c/cat-in-the-dat
+
+SQLite schema snapshot:
+{
+  "table_name": "c14",
+  "quoted_table_name": "\"c14\"",
+  "row_count": 300000,
+  "columns": [
+    {
+      "name": "id",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_0",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_3",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_4",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_0",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_3",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_4",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_5",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_6",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_7",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_8",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_9",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_0",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_3",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_4",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_5",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "day",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "month",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "target",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "id": "0",
+      "bin_0": "0",
+      "bin_1": "0",
+      "bin_2": "0",
+      "bin_3": "T",
+      "bin_4": "Y",
+      "nom_0": "Green",
+      "nom_1": "Triangle",
+      "nom_2": "Snake",
+      "nom_3": "Finland",
+      "nom_4": "Bassoon",
+      "nom_5": "50f116bcf",
+      "nom_6": "3ac1b8814",
+      "nom_7": "68f6ad3e9",
+      "nom_8": "c389000ab",
+      "nom_9": "2f4cb3d51",
+      "ord_0": "2",
+      "ord_1": "Grandmaster",
+      "ord_2": "Cold",
+      "ord_3": "h",
+      "ord_4": "D",
+      "ord_5": "kr",
+      "day": "2",
+      "month": "2",
+      "target": "0"
+    },
+    {
+      "id": "1",
+      "bin_0": "0",
+      "bin_1": "1",
+      "bin_2": "0",
+      "bin_3": "T",
+      "bin_4": "Y",
+      "nom_0": "Green",
+      "nom_1": "Trapezoid",
+      "nom_2": "Hamster",
+      "nom_3": "Russia",
+      "nom_4": "Piano",
+      "nom_5": "b3b4d25d0",
+      "nom_6": "fbcb50fc1",
+      "nom_7": "3b6dd5612",
+      "nom_8": "4cd920251",
+      "nom_9": "f83c56c21",
+      "ord_0": "1",
+      "ord_1": "Grandmaster",
+      "ord_2": "Hot",
+      "ord_3": "a",
+      "ord_4": "A",
+      "ord_5": "bF",
+      "day": "7",
+      "month": "8",
+      "target": "0"
+    },
+    {
+      "id": "2",
+      "bin_0": "0",
+      "bin_1": "0",
+      "bin_2": "0",
+      "bin_3": "F",
+      "bin_4": "Y",
+      "nom_0": "Blue",
+      "nom_1": "Trapezoid",
+      "nom_2": "Lion",
+      "nom_3": "Russia",
+      "nom_4": "Theremin",
+      "nom_5": "3263bdce5",
+      "nom_6": "0922e3cb8",
+      "nom_7": "a6a36f527",
+      "nom_8": "de9c9f684",
+      "nom_9": "ae6800dd0",
+      "ord_0": "1",
+      "ord_1": "Expert",
+      "ord_2": "Lava Hot",
+      "ord_3": "h",
+      "ord_4": "R",
+      "ord_5": "Jc",
+      "day": "7",
+      "month": "2",
+      "target": "0"
+    },
+    {
+      "id": "3",
+      "bin_0": "0",
+      "bin_1": "1",
+      "bin_2": "0",
+      "bin_3": "F",
+      "bin_4": "Y",
+      "nom_0": "Red",
+      "nom_1": "Trapezoid",
+      "nom_2": "Snake",
+      "nom_3": "Canada",
+      "nom_4": "Oboe",
+      "nom_5": "f12246592",
+      "nom_6": "50d7ad46a",
+      "nom_7": "ec69236eb",
+      "nom_8": "4ade6ab69",
+      "nom_9": "8270f0d71",
+      "ord_0": "1",
+      "ord_1": "Grandmaster",
+      "ord_2": "Boiling Hot",
+      "ord_3": "i",
+      "ord_4": "D",
+      "ord_5": "kW",
+      "day": "2",
+      "month": "1",
+      "target": "1"
+    },
+    {
+      "id": "4",
+      "bin_0": "0",
+      "bin_1": "0",
+      "bin_2": "0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Trapezoid",
+      "nom_2": "Lion",
+      "nom_3": "Canada",
+      "nom_4": "Oboe",
+      "nom_5": "5b0f5acd5",
+      "nom_6": "1fe17a1fd",
+      "nom_7": "04ddac2be",
+      "nom_8": "cb43ab175",
+      "nom_9": "b164b72a7",
+      "ord_0": "1",
+      "ord_1": "Grandmaster",
+      "ord_2": "Freezing",
+      "ord_3": "a",
+      "ord_4": "R",
+      "ord_5": "qP",
+      "day": "7",
+      "month": "8",
+      "target": "0"
+    }
+  ]
+}
+
+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": "c14",
+  "question": "Use template Grouped Condition Rate to probe direction_consistency with semantic role within_group_proportion. Focus on group_col=ord_3, condition_col=day.",
+  "planned_template_id": "tpl_m4_group_condition_rate",
+  "bindings": {
+    "group_col": "ord_3",
+    "condition_col": "day",
+    "condition_value": "2",
+    "positive_value": "1",
+    "negative_value": "2",
+    "top_k": 18,
+    "top_n": 7,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 9.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       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_d/c14/artifacts/v2q_c14_0fcdf90112f27537/cli/sql_prompt_attempt_2.txt

@@ -0,0 +1,399 @@
+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: c14
+- dataset_name: Cat In The Dat
+- table_name: c14
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 24 feature columns and target `target`.
+- task_type: classification
+- target_column: target
+- main_row_count: 300000
+- important_fields:
+- id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for id.
+- bin_0: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 0.
+- bin_1: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 1.
+- bin_2: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 2.
+- bin_3: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 3.
+- bin_4: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 4.
+- nom_0: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 0.
+- nom_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 1.
+- nom_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 2.
+- nom_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 3.
+- nom_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 4.
+- nom_5: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 5.
+- nom_6: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 6.
+- nom_7: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 7.
+- nom_8: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 8.
+- nom_9: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 9.
+- ord_0: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for ord 0.
+- ord_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 1.
+- ord_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 2.
+- ord_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 3.
+- ord_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 4.
+- ord_5: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for ord 5.
+- day: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for day.
+- month: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for month.
+- target: role=target, type=binary_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target.
+- useful_field_combinations: [['bin_0', 'bin_1', 'target'], ['bin_0', 'ord_0', 'target'], ['bin_0', 'bin_0', 'target']]
+- fields_requiring_caution: ['target', 'nom_5', 'nom_6', 'nom_7']
+- source_url: https://www.kaggle.com/c/cat-in-the-dat
+
+SQLite schema snapshot:
+{
+  "table_name": "c14",
+  "quoted_table_name": "\"c14\"",
+  "row_count": 300000,
+  "columns": [
+    {
+      "name": "id",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_0",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_3",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_4",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_0",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_3",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_4",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_5",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_6",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_7",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_8",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_9",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_0",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_3",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_4",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_5",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "day",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "month",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "target",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "id": "0",
+      "bin_0": "0",
+      "bin_1": "0",
+      "bin_2": "0",
+      "bin_3": "T",
+      "bin_4": "Y",
+      "nom_0": "Green",
+      "nom_1": "Triangle",
+      "nom_2": "Snake",
+      "nom_3": "Finland",
+      "nom_4": "Bassoon",
+      "nom_5": "50f116bcf",
+      "nom_6": "3ac1b8814",
+      "nom_7": "68f6ad3e9",
+      "nom_8": "c389000ab",
+      "nom_9": "2f4cb3d51",
+      "ord_0": "2",
+      "ord_1": "Grandmaster",
+      "ord_2": "Cold",
+      "ord_3": "h",
+      "ord_4": "D",
+      "ord_5": "kr",
+      "day": "2",
+      "month": "2",
+      "target": "0"
+    },
+    {
+      "id": "1",
+      "bin_0": "0",
+      "bin_1": "1",
+      "bin_2": "0",
+      "bin_3": "T",
+      "bin_4": "Y",
+      "nom_0": "Green",
+      "nom_1": "Trapezoid",
+      "nom_2": "Hamster",
+      "nom_3": "Russia",
+      "nom_4": "Piano",
+      "nom_5": "b3b4d25d0",
+      "nom_6": "fbcb50fc1",
+      "nom_7": "3b6dd5612",
+      "nom_8": "4cd920251",
+      "nom_9": "f83c56c21",
+      "ord_0": "1",
+      "ord_1": "Grandmaster",
+      "ord_2": "Hot",
+      "ord_3": "a",
+      "ord_4": "A",
+      "ord_5": "bF",
+      "day": "7",
+      "month": "8",
+      "target": "0"
+    },
+    {
+      "id": "2",
+      "bin_0": "0",
+      "bin_1": "0",
+      "bin_2": "0",
+      "bin_3": "F",
+      "bin_4": "Y",
+      "nom_0": "Blue",
+      "nom_1": "Trapezoid",
+      "nom_2": "Lion",
+      "nom_3": "Russia",
+      "nom_4": "Theremin",
+      "nom_5": "3263bdce5",
+      "nom_6": "0922e3cb8",
+      "nom_7": "a6a36f527",
+      "nom_8": "de9c9f684",
+      "nom_9": "ae6800dd0",
+      "ord_0": "1",
+      "ord_1": "Expert",
+      "ord_2": "Lava Hot",
+      "ord_3": "h",
+      "ord_4": "R",
+      "ord_5": "Jc",
+      "day": "7",
+      "month": "2",
+      "target": "0"
+    },
+    {
+      "id": "3",
+      "bin_0": "0",
+      "bin_1": "1",
+      "bin_2": "0",
+      "bin_3": "F",
+      "bin_4": "Y",
+      "nom_0": "Red",
+      "nom_1": "Trapezoid",
+      "nom_2": "Snake",
+      "nom_3": "Canada",
+      "nom_4": "Oboe",
+      "nom_5": "f12246592",
+      "nom_6": "50d7ad46a",
+      "nom_7": "ec69236eb",
+      "nom_8": "4ade6ab69",
+      "nom_9": "8270f0d71",
+      "ord_0": "1",
+      "ord_1": "Grandmaster",
+      "ord_2": "Boiling Hot",
+      "ord_3": "i",
+      "ord_4": "D",
+      "ord_5": "kW",
+      "day": "2",
+      "month": "1",
+      "target": "1"
+    },
+    {
+      "id": "4",
+      "bin_0": "0",
+      "bin_1": "0",
+      "bin_2": "0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Trapezoid",
+      "nom_2": "Lion",
+      "nom_3": "Canada",
+      "nom_4": "Oboe",
+      "nom_5": "5b0f5acd5",
+      "nom_6": "1fe17a1fd",
+      "nom_7": "04ddac2be",
+      "nom_8": "cb43ab175",
+      "nom_9": "b164b72a7",
+      "ord_0": "1",
+      "ord_1": "Grandmaster",
+      "ord_2": "Freezing",
+      "ord_3": "a",
+      "ord_4": "R",
+      "ord_5": "qP",
+      "day": "7",
+      "month": "8",
+      "target": "0"
+    }
+  ]
+}
+
+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": "c14",
+  "question": "Use template Grouped Condition Rate to probe direction_consistency with semantic role within_group_proportion. Focus on group_col=ord_3, condition_col=day.",
+  "planned_template_id": "tpl_m4_group_condition_rate",
+  "bindings": {
+    "group_col": "ord_3",
+    "condition_col": "day",
+    "condition_value": "2",
+    "positive_value": "1",
+    "negative_value": "2",
+    "top_k": 18,
+    "top_n": 7,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 9.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       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_d/c14/artifacts/v2q_c14_0fcdf90112f27537/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fd-8baf-76f3-b641-af32d03b54c6"}
+{"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_d/c14/artifacts/v2q_c14_0fcdf90112f27537/cli/sql_response_attempt_1.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fd-8baf-76f3-b641-af32d03b54c6"}
+{"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_d/c14/artifacts/v2q_c14_0fcdf90112f27537/cli/sql_response_attempt_2.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fd-9b8a-7da0-934d-8b2f9a49d4dd"}
+{"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_d/c14/artifacts/v2q_c14_0fcdf90112f27537/cli/sql_response_attempt_2.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fd-9b8a-7da0-934d-8b2f9a49d4dd"}
+{"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_d/c14/artifacts/v2q_c14_1067b4904090010b/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 12086, "bytes_utf8": 12086, "lines": 398, "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": 579, "bytes_utf8": 579, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16025, "cached_input_tokens": 14720, "output_tokens": 695, "reasoning_output_tokens": 516}}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_1067b4904090010b/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": "c14",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c14_1067b4904090010b",
+    "api_calls": 0,
+    "input_tokens": 16025,
+    "cached_input_tokens": 14720,
+    "output_tokens": 695,
+    "total_tokens": 16720,
+    "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": 13305.46,
+    "sql_execution_elapsed_ms_total": 405.91,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_1067b4904090010b/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_1067b4904090010b/cli/sql_attempt_1.metadata.json

@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:36:50.363064+00:00",
+  "ended_at": "2026-05-19T15:37:03.668553+00:00",
+  "elapsed_ms": 13305.46,
+  "prompt_metrics": {
+    "chars": 12086,
+    "bytes_utf8": 12086,
+    "lines": 398,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 966,
+    "bytes_utf8": 966,
+    "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": 579,
+      "bytes_utf8": 579,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16025,
+      "cached_input_tokens": 14720,
+      "output_tokens": 695,
+      "reasoning_output_tokens": 516
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_1067b4904090010b/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,398 @@
+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: c14
+- dataset_name: Cat In The Dat
+- table_name: c14
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 24 feature columns and target `target`.
+- task_type: classification
+- target_column: target
+- main_row_count: 300000
+- important_fields:
+- id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for id.
+- bin_0: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 0.
+- bin_1: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 1.
+- bin_2: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 2.
+- bin_3: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 3.
+- bin_4: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 4.
+- nom_0: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 0.
+- nom_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 1.
+- nom_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 2.
+- nom_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 3.
+- nom_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 4.
+- nom_5: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 5.
+- nom_6: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 6.
+- nom_7: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 7.
+- nom_8: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 8.
+- nom_9: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 9.
+- ord_0: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for ord 0.
+- ord_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 1.
+- ord_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 2.
+- ord_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 3.
+- ord_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 4.
+- ord_5: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for ord 5.
+- day: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for day.
+- month: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for month.
+- target: role=target, type=binary_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target.
+- useful_field_combinations: [['bin_0', 'bin_1', 'target'], ['bin_0', 'ord_0', 'target'], ['bin_0', 'bin_0', 'target']]
+- fields_requiring_caution: ['target', 'nom_5', 'nom_6', 'nom_7']
+- source_url: https://www.kaggle.com/c/cat-in-the-dat
+
+SQLite schema snapshot:
+{
+  "table_name": "c14",
+  "quoted_table_name": "\"c14\"",
+  "row_count": 300000,
+  "columns": [
+    {
+      "name": "id",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_0",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_3",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_4",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_0",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_3",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_4",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_5",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_6",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_7",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_8",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_9",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_0",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_3",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_4",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_5",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "day",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "month",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "target",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "id": "0",
+      "bin_0": "0",
+      "bin_1": "0",
+      "bin_2": "0",
+      "bin_3": "T",
+      "bin_4": "Y",
+      "nom_0": "Green",
+      "nom_1": "Triangle",
+      "nom_2": "Snake",
+      "nom_3": "Finland",
+      "nom_4": "Bassoon",
+      "nom_5": "50f116bcf",
+      "nom_6": "3ac1b8814",
+      "nom_7": "68f6ad3e9",
+      "nom_8": "c389000ab",
+      "nom_9": "2f4cb3d51",
+      "ord_0": "2",
+      "ord_1": "Grandmaster",
+      "ord_2": "Cold",
+      "ord_3": "h",
+      "ord_4": "D",
+      "ord_5": "kr",
+      "day": "2",
+      "month": "2",
+      "target": "0"
+    },
+    {
+      "id": "1",
+      "bin_0": "0",
+      "bin_1": "1",
+      "bin_2": "0",
+      "bin_3": "T",
+      "bin_4": "Y",
+      "nom_0": "Green",
+      "nom_1": "Trapezoid",
+      "nom_2": "Hamster",
+      "nom_3": "Russia",
+      "nom_4": "Piano",
+      "nom_5": "b3b4d25d0",
+      "nom_6": "fbcb50fc1",
+      "nom_7": "3b6dd5612",
+      "nom_8": "4cd920251",
+      "nom_9": "f83c56c21",
+      "ord_0": "1",
+      "ord_1": "Grandmaster",
+      "ord_2": "Hot",
+      "ord_3": "a",
+      "ord_4": "A",
+      "ord_5": "bF",
+      "day": "7",
+      "month": "8",
+      "target": "0"
+    },
+    {
+      "id": "2",
+      "bin_0": "0",
+      "bin_1": "0",
+      "bin_2": "0",
+      "bin_3": "F",
+      "bin_4": "Y",
+      "nom_0": "Blue",
+      "nom_1": "Trapezoid",
+      "nom_2": "Lion",
+      "nom_3": "Russia",
+      "nom_4": "Theremin",
+      "nom_5": "3263bdce5",
+      "nom_6": "0922e3cb8",
+      "nom_7": "a6a36f527",
+      "nom_8": "de9c9f684",
+      "nom_9": "ae6800dd0",
+      "ord_0": "1",
+      "ord_1": "Expert",
+      "ord_2": "Lava Hot",
+      "ord_3": "h",
+      "ord_4": "R",
+      "ord_5": "Jc",
+      "day": "7",
+      "month": "2",
+      "target": "0"
+    },
+    {
+      "id": "3",
+      "bin_0": "0",
+      "bin_1": "1",
+      "bin_2": "0",
+      "bin_3": "F",
+      "bin_4": "Y",
+      "nom_0": "Red",
+      "nom_1": "Trapezoid",
+      "nom_2": "Snake",
+      "nom_3": "Canada",
+      "nom_4": "Oboe",
+      "nom_5": "f12246592",
+      "nom_6": "50d7ad46a",
+      "nom_7": "ec69236eb",
+      "nom_8": "4ade6ab69",
+      "nom_9": "8270f0d71",
+      "ord_0": "1",
+      "ord_1": "Grandmaster",
+      "ord_2": "Boiling Hot",
+      "ord_3": "i",
+      "ord_4": "D",
+      "ord_5": "kW",
+      "day": "2",
+      "month": "1",
+      "target": "1"
+    },
+    {
+      "id": "4",
+      "bin_0": "0",
+      "bin_1": "0",
+      "bin_2": "0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Trapezoid",
+      "nom_2": "Lion",
+      "nom_3": "Canada",
+      "nom_4": "Oboe",
+      "nom_5": "5b0f5acd5",
+      "nom_6": "1fe17a1fd",
+      "nom_7": "04ddac2be",
+      "nom_8": "cb43ab175",
+      "nom_9": "b164b72a7",
+      "ord_0": "1",
+      "ord_1": "Grandmaster",
+      "ord_2": "Freezing",
+      "ord_3": "a",
+      "ord_4": "R",
+      "ord_5": "qP",
+      "day": "7",
+      "month": "8",
+      "target": "0"
+    }
+  ]
+}
+
+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": "c14",
+  "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=ord_0, measure_col=id.",
+  "planned_template_id": "tpl_tpcds_within_group_share",
+  "bindings": {
+    "group_col": "ord_0",
+    "measure_col": "id",
+    "item_col": "nom_9",
+    "top_k": 18,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 150351.84,
+    "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_d/c14/artifacts/v2q_c14_1067b4904090010b/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40e1-f4cc-7e30-8b04-d4b0c31fcc7d"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n  \\\"ord_0\\\",\\n  \\\"nom_9\\\",\\n  SUM(CAST(\\\"id\\\" AS INTEGER)) AS total_measure,\\n  SUM(CAST(\\\"id\\\" AS INTEGER)) * 100.0 / SUM(SUM(CAST(\\\"id\\\" AS INTEGER))) OVER (PARTITION BY \\\"ord_0\\\") AS share_within_group\\nFROM \\\"c14\\\"\\nGROUP BY \\\"ord_0\\\", \\\"nom_9\\\"\\nORDER BY share_within_group DESC\\nLIMIT 18;\",\"notes\":\"Used the planned template with group_col=\\\"ord_0\\\", item_col=\\\"nom_9\\\", and measure_col=\\\"id\\\". Cast \\\"id\\\" to INTEGER because it is stored as TEXT in the SQLite schema but represents numeric identifier values.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16025,"cached_input_tokens":14720,"output_tokens":695,"reasoning_output_tokens":516}}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_1067b4904090010b/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tpcds_within_group_share\nSELECT\n  \"ord_0\",\n  \"nom_9\",\n  SUM(CAST(\"id\" AS INTEGER)) AS total_measure,\n  SUM(CAST(\"id\" AS INTEGER)) * 100.0 / SUM(SUM(CAST(\"id\" AS INTEGER))) OVER (PARTITION BY \"ord_0\") AS share_within_group\nFROM \"c14\"\nGROUP BY \"ord_0\", \"nom_9\"\nORDER BY share_within_group DESC\nLIMIT 18;","notes":"Used the planned template with group_col=\"ord_0\", item_col=\"nom_9\", and measure_col=\"id\". Cast \"id\" to INTEGER because it is stored as TEXT in the SQLite schema but represents numeric identifier values."}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_119b90b4149dcde9/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 12086, "bytes_utf8": 12086, "lines": 398, "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": 549, "bytes_utf8": 549, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16025, "cached_input_tokens": 14720, "output_tokens": 694, "reasoning_output_tokens": 516}}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_119b90b4149dcde9/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": "c14",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c14_119b90b4149dcde9",
+    "api_calls": 0,
+    "input_tokens": 16025,
+    "cached_input_tokens": 14720,
+    "output_tokens": 694,
+    "total_tokens": 16719,
+    "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": 15903.89,
+    "sql_execution_elapsed_ms_total": 323.35,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_119b90b4149dcde9/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_119b90b4149dcde9/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": "2026-05-19T15:38:46.201752+00:00",
+  "ended_at": "2026-05-19T15:39:02.105664+00:00",
+  "elapsed_ms": 15903.89,
+  "prompt_metrics": {
+    "chars": 12086,
+    "bytes_utf8": 12086,
+    "lines": 398,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 935,
+    "bytes_utf8": 935,
+    "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": 549,
+      "bytes_utf8": 549,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16025,
+      "cached_input_tokens": 14720,
+      "output_tokens": 694,
+      "reasoning_output_tokens": 516
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_119b90b4149dcde9/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,398 @@
+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: c14
+- dataset_name: Cat In The Dat
+- table_name: c14
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 24 feature columns and target `target`.
+- task_type: classification
+- target_column: target
+- main_row_count: 300000
+- important_fields:
+- id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for id.
+- bin_0: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 0.
+- bin_1: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 1.
+- bin_2: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 2.
+- bin_3: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 3.
+- bin_4: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 4.
+- nom_0: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 0.
+- nom_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 1.
+- nom_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 2.
+- nom_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 3.
+- nom_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 4.
+- nom_5: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 5.
+- nom_6: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 6.
+- nom_7: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 7.
+- nom_8: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 8.
+- nom_9: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 9.
+- ord_0: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for ord 0.
+- ord_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 1.
+- ord_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 2.
+- ord_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 3.
+- ord_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 4.
+- ord_5: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for ord 5.
+- day: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for day.
+- month: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for month.
+- target: role=target, type=binary_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target.
+- useful_field_combinations: [['bin_0', 'bin_1', 'target'], ['bin_0', 'ord_0', 'target'], ['bin_0', 'bin_0', 'target']]
+- fields_requiring_caution: ['target', 'nom_5', 'nom_6', 'nom_7']
+- source_url: https://www.kaggle.com/c/cat-in-the-dat
+
+SQLite schema snapshot:
+{
+  "table_name": "c14",
+  "quoted_table_name": "\"c14\"",
+  "row_count": 300000,
+  "columns": [
+    {
+      "name": "id",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_0",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_3",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_4",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_0",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_3",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_4",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_5",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_6",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_7",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_8",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_9",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_0",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_3",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_4",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_5",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "day",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "month",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "target",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "id": "0",
+      "bin_0": "0",
+      "bin_1": "0",
+      "bin_2": "0",
+      "bin_3": "T",
+      "bin_4": "Y",
+      "nom_0": "Green",
+      "nom_1": "Triangle",
+      "nom_2": "Snake",
+      "nom_3": "Finland",
+      "nom_4": "Bassoon",
+      "nom_5": "50f116bcf",
+      "nom_6": "3ac1b8814",
+      "nom_7": "68f6ad3e9",
+      "nom_8": "c389000ab",
+      "nom_9": "2f4cb3d51",
+      "ord_0": "2",
+      "ord_1": "Grandmaster",
+      "ord_2": "Cold",
+      "ord_3": "h",
+      "ord_4": "D",
+      "ord_5": "kr",
+      "day": "2",
+      "month": "2",
+      "target": "0"
+    },
+    {
+      "id": "1",
+      "bin_0": "0",
+      "bin_1": "1",
+      "bin_2": "0",
+      "bin_3": "T",
+      "bin_4": "Y",
+      "nom_0": "Green",
+      "nom_1": "Trapezoid",
+      "nom_2": "Hamster",
+      "nom_3": "Russia",
+      "nom_4": "Piano",
+      "nom_5": "b3b4d25d0",
+      "nom_6": "fbcb50fc1",
+      "nom_7": "3b6dd5612",
+      "nom_8": "4cd920251",
+      "nom_9": "f83c56c21",
+      "ord_0": "1",
+      "ord_1": "Grandmaster",
+      "ord_2": "Hot",
+      "ord_3": "a",
+      "ord_4": "A",
+      "ord_5": "bF",
+      "day": "7",
+      "month": "8",
+      "target": "0"
+    },
+    {
+      "id": "2",
+      "bin_0": "0",
+      "bin_1": "0",
+      "bin_2": "0",
+      "bin_3": "F",
+      "bin_4": "Y",
+      "nom_0": "Blue",
+      "nom_1": "Trapezoid",
+      "nom_2": "Lion",
+      "nom_3": "Russia",
+      "nom_4": "Theremin",
+      "nom_5": "3263bdce5",
+      "nom_6": "0922e3cb8",
+      "nom_7": "a6a36f527",
+      "nom_8": "de9c9f684",
+      "nom_9": "ae6800dd0",
+      "ord_0": "1",
+      "ord_1": "Expert",
+      "ord_2": "Lava Hot",
+      "ord_3": "h",
+      "ord_4": "R",
+      "ord_5": "Jc",
+      "day": "7",
+      "month": "2",
+      "target": "0"
+    },
+    {
+      "id": "3",
+      "bin_0": "0",
+      "bin_1": "1",
+      "bin_2": "0",
+      "bin_3": "F",
+      "bin_4": "Y",
+      "nom_0": "Red",
+      "nom_1": "Trapezoid",
+      "nom_2": "Snake",
+      "nom_3": "Canada",
+      "nom_4": "Oboe",
+      "nom_5": "f12246592",
+      "nom_6": "50d7ad46a",
+      "nom_7": "ec69236eb",
+      "nom_8": "4ade6ab69",
+      "nom_9": "8270f0d71",
+      "ord_0": "1",
+      "ord_1": "Grandmaster",
+      "ord_2": "Boiling Hot",
+      "ord_3": "i",
+      "ord_4": "D",
+      "ord_5": "kW",
+      "day": "2",
+      "month": "1",
+      "target": "1"
+    },
+    {
+      "id": "4",
+      "bin_0": "0",
+      "bin_1": "0",
+      "bin_2": "0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Trapezoid",
+      "nom_2": "Lion",
+      "nom_3": "Canada",
+      "nom_4": "Oboe",
+      "nom_5": "5b0f5acd5",
+      "nom_6": "1fe17a1fd",
+      "nom_7": "04ddac2be",
+      "nom_8": "cb43ab175",
+      "nom_9": "b164b72a7",
+      "ord_0": "1",
+      "ord_1": "Grandmaster",
+      "ord_2": "Freezing",
+      "ord_3": "a",
+      "ord_4": "R",
+      "ord_5": "qP",
+      "day": "7",
+      "month": "8",
+      "target": "0"
+    }
+  ]
+}
+
+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": "c14",
+  "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=ord_4, measure_col=id.",
+  "planned_template_id": "tpl_tpcds_within_group_share",
+  "bindings": {
+    "group_col": "ord_4",
+    "measure_col": "id",
+    "item_col": "nom_5",
+    "top_k": 17,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 150351.84,
+    "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_d/c14/artifacts/v2q_c14_119b90b4149dcde9/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40e3-b95c-7ce1-89a5-93ce0166a012"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n  \\\"ord_4\\\",\\n  \\\"nom_5\\\",\\n  SUM(CAST(\\\"id\\\" AS NUMERIC)) AS total_measure,\\n  SUM(CAST(\\\"id\\\" AS NUMERIC)) * 100.0 / SUM(SUM(CAST(\\\"id\\\" AS NUMERIC))) OVER (PARTITION BY \\\"ord_4\\\") AS share_within_group\\nFROM \\\"c14\\\"\\nGROUP BY \\\"ord_4\\\", \\\"nom_5\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Applied the planned template with group_col=\\\"ord_4\\\", item_col=\\\"nom_5\\\", and measure_col=\\\"id\\\". Cast \\\"id\\\" to NUMERIC because it is stored as TEXT in the SQLite schema but used in SUM().\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16025,"cached_input_tokens":14720,"output_tokens":694,"reasoning_output_tokens":516}}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_119b90b4149dcde9/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tpcds_within_group_share\nSELECT\n  \"ord_4\",\n  \"nom_5\",\n  SUM(CAST(\"id\" AS NUMERIC)) AS total_measure,\n  SUM(CAST(\"id\" AS NUMERIC)) * 100.0 / SUM(SUM(CAST(\"id\" AS NUMERIC))) OVER (PARTITION BY \"ord_4\") AS share_within_group\nFROM \"c14\"\nGROUP BY \"ord_4\", \"nom_5\"\nORDER BY share_within_group DESC;","notes":"Applied the planned template with group_col=\"ord_4\", item_col=\"nom_5\", and measure_col=\"id\". Cast \"id\" to NUMERIC because it is stored as TEXT in the SQLite schema but used in SUM()."}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_11fe2ec9113dbbdb/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 11859, "bytes_utf8": 11859, "lines": 396, "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": 1785, "bytes_utf8": 1785, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15948, "cached_input_tokens": 14720, "output_tokens": 4035, "reasoning_output_tokens": 3401}}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_11fe2ec9113dbbdb/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": "c14",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c14_11fe2ec9113dbbdb",
+    "api_calls": 0,
+    "input_tokens": 15948,
+    "cached_input_tokens": 14720,
+    "output_tokens": 4035,
+    "total_tokens": 19983,
+    "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": 56980.11,
+    "sql_execution_elapsed_ms_total": 909.81,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_11fe2ec9113dbbdb/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_11fe2ec9113dbbdb/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": "2026-05-19T15:53:34.408854+00:00",
+  "ended_at": "2026-05-19T15:54:31.389028+00:00",
+  "elapsed_ms": 56980.11,
+  "prompt_metrics": {
+    "chars": 11859,
+    "bytes_utf8": 11859,
+    "lines": 396,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 2385,
+    "bytes_utf8": 2385,
+    "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": 1785,
+      "bytes_utf8": 1785,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 15948,
+      "cached_input_tokens": 14720,
+      "output_tokens": 4035,
+      "reasoning_output_tokens": 3401
+    }
+  },
+  "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_d/c14/artifacts/v2q_c14_11fe2ec9113dbbdb/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,396 @@
+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: c14
+- dataset_name: Cat In The Dat
+- table_name: c14
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 24 feature columns and target `target`.
+- task_type: classification
+- target_column: target
+- main_row_count: 300000
+- important_fields:
+- id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for id.
+- bin_0: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 0.
+- bin_1: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 1.
+- bin_2: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 2.
+- bin_3: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 3.
+- bin_4: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for bin 4.
+- nom_0: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 0.
+- nom_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 1.
+- nom_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 2.
+- nom_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 3.
+- nom_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for nom 4.
+- nom_5: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 5.
+- nom_6: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 6.
+- nom_7: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 7.
+- nom_8: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 8.
+- nom_9: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for nom 9.
+- ord_0: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for ord 0.
+- ord_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 1.
+- ord_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 2.
+- ord_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 3.
+- ord_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ord 4.
+- ord_5: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for ord 5.
+- day: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for day.
+- month: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for month.
+- target: role=target, type=binary_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target.
+- useful_field_combinations: [['bin_0', 'bin_1', 'target'], ['bin_0', 'ord_0', 'target'], ['bin_0', 'bin_0', 'target']]
+- fields_requiring_caution: ['target', 'nom_5', 'nom_6', 'nom_7']
+- source_url: https://www.kaggle.com/c/cat-in-the-dat
+
+SQLite schema snapshot:
+{
+  "table_name": "c14",
+  "quoted_table_name": "\"c14\"",
+  "row_count": 300000,
+  "columns": [
+    {
+      "name": "id",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_0",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_3",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "bin_4",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_0",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_3",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_4",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_5",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_6",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_7",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_8",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "nom_9",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_0",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_3",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_4",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ord_5",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "day",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "month",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "target",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "id": "0",
+      "bin_0": "0",
+      "bin_1": "0",
+      "bin_2": "0",
+      "bin_3": "T",
+      "bin_4": "Y",
+      "nom_0": "Green",
+      "nom_1": "Triangle",
+      "nom_2": "Snake",
+      "nom_3": "Finland",
+      "nom_4": "Bassoon",
+      "nom_5": "50f116bcf",
+      "nom_6": "3ac1b8814",
+      "nom_7": "68f6ad3e9",
+      "nom_8": "c389000ab",
+      "nom_9": "2f4cb3d51",
+      "ord_0": "2",
+      "ord_1": "Grandmaster",
+      "ord_2": "Cold",
+      "ord_3": "h",
+      "ord_4": "D",
+      "ord_5": "kr",
+      "day": "2",
+      "month": "2",
+      "target": "0"
+    },
+    {
+      "id": "1",
+      "bin_0": "0",
+      "bin_1": "1",
+      "bin_2": "0",
+      "bin_3": "T",
+      "bin_4": "Y",
+      "nom_0": "Green",
+      "nom_1": "Trapezoid",
+      "nom_2": "Hamster",
+      "nom_3": "Russia",
+      "nom_4": "Piano",
+      "nom_5": "b3b4d25d0",
+      "nom_6": "fbcb50fc1",
+      "nom_7": "3b6dd5612",
+      "nom_8": "4cd920251",
+      "nom_9": "f83c56c21",
+      "ord_0": "1",
+      "ord_1": "Grandmaster",
+      "ord_2": "Hot",
+      "ord_3": "a",
+      "ord_4": "A",
+      "ord_5": "bF",
+      "day": "7",
+      "month": "8",
+      "target": "0"
+    },
+    {
+      "id": "2",
+      "bin_0": "0",
+      "bin_1": "0",
+      "bin_2": "0",
+      "bin_3": "F",
+      "bin_4": "Y",
+      "nom_0": "Blue",
+      "nom_1": "Trapezoid",
+      "nom_2": "Lion",
+      "nom_3": "Russia",
+      "nom_4": "Theremin",
+      "nom_5": "3263bdce5",
+      "nom_6": "0922e3cb8",
+      "nom_7": "a6a36f527",
+      "nom_8": "de9c9f684",
+      "nom_9": "ae6800dd0",
+      "ord_0": "1",
+      "ord_1": "Expert",
+      "ord_2": "Lava Hot",
+      "ord_3": "h",
+      "ord_4": "R",
+      "ord_5": "Jc",
+      "day": "7",
+      "month": "2",
+      "target": "0"
+    },
+    {
+      "id": "3",
+      "bin_0": "0",
+      "bin_1": "1",
+      "bin_2": "0",
+      "bin_3": "F",
+      "bin_4": "Y",
+      "nom_0": "Red",
+      "nom_1": "Trapezoid",
+      "nom_2": "Snake",
+      "nom_3": "Canada",
+      "nom_4": "Oboe",
+      "nom_5": "f12246592",
+      "nom_6": "50d7ad46a",
+      "nom_7": "ec69236eb",
+      "nom_8": "4ade6ab69",
+      "nom_9": "8270f0d71",
+      "ord_0": "1",
+      "ord_1": "Grandmaster",
+      "ord_2": "Boiling Hot",
+      "ord_3": "i",
+      "ord_4": "D",
+      "ord_5": "kW",
+      "day": "2",
+      "month": "1",
+      "target": "1"
+    },
+    {
+      "id": "4",
+      "bin_0": "0",
+      "bin_1": "0",
+      "bin_2": "0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Trapezoid",
+      "nom_2": "Lion",
+      "nom_3": "Canada",
+      "nom_4": "Oboe",
+      "nom_5": "5b0f5acd5",
+      "nom_6": "1fe17a1fd",
+      "nom_7": "04ddac2be",
+      "nom_8": "cb43ab175",
+      "nom_9": "b164b72a7",
+      "ord_0": "1",
+      "ord_1": "Grandmaster",
+      "ord_2": "Freezing",
+      "ord_3": "a",
+      "ord_4": "R",
+      "ord_5": "qP",
+      "day": "7",
+      "month": "8",
+      "target": "0"
+    }
+  ]
+}
+
+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": "c14",
+  "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=ord_3, measure_col=ord_0.",
+  "planned_template_id": "tpl_grouped_percentile_point",
+  "bindings": {
+    "group_col": "ord_3",
+    "measure_col": "ord_0",
+    "top_k": 10,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 2.5,
+    "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_d/c14/artifacts/v2q_c14_11fe2ec9113dbbdb/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f1-46c4-72a0-b370-95d502f9ac16"}
+{"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    \\\"ord_3\\\" AS \\\"group_col\\\",\\n    CAST(\\\"ord_0\\\" AS REAL) AS \\\"measure\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"ord_3\\\"\\n      ORDER BY CAST(\\\"ord_0\\\" AS REAL)\\n    ) AS \\\"rn\\\"\\n  FROM \\\"c14\\\"\\n  WHERE \\\"ord_3\\\" IS NOT NULL\\n    AND \\\"ord_0\\\" IS NOT NULL\\n),\\n\\\"params\\\" AS (\\n  SELECT\\n    \\\"group_col\\\",\\n    COUNT(*) AS \\\"n\\\",\\n    1.0 + 0.9 * (COUNT(*) - 1) AS \\\"pos\\\",\\n    CAST(1.0 + 0.9 * (COUNT(*) - 1) AS INTEGER) AS \\\"lower_rn\\\",\\n    CASE\\n      WHEN (1.0 + 0.9 * (COUNT(*) - 1)) > CAST(1.0 + 0.9 * (COUNT(*) - 1) AS INTEGER)\\n        THEN CAST(1.0 + 0.9 * (COUNT(*) - 1) AS INTEGER) + 1\\n      ELSE CAST(1.0 + 0.9 * (COUNT(*) - 1) AS INTEGER)\\n    END AS \\\"upper_rn\\\"\\n  FROM \\\"ordered\\\"\\n  GROUP BY \\\"group_col\\\"\\n  HAVING COUNT(*) >= 5\\n),\\n\\\"bounds\\\" AS (\\n  SELECT\\n    p.\\\"group_col\\\",\\n    p.\\\"pos\\\",\\n    p.\\\"lower_rn\\\",\\n    p.\\\"upper_rn\\\",\\n    MAX(CASE WHEN o.\\\"rn\\\" = p.\\\"lower_rn\\\" THEN o.\\\"measure\\\" END) AS \\\"lower_val\\\",\\n    MAX(CASE WHEN o.\\\"rn\\\" = p.\\\"upper_rn\\\" THEN o.\\\"measure\\\" END) AS \\\"upper_val\\\"\\n  FROM \\\"params\\\" AS p\\n  JOIN \\\"ordered\\\" AS o\\n    ON o.\\\"group_col\\\" = p.\\\"group_col\\\"\\n  GROUP BY\\n    p.\\\"group_col\\\",\\n    p.\\\"pos\\\",\\n    p.\\\"lower_rn\\\",\\n    p.\\\"upper_rn\\\"\\n)\\nSELECT\\n  \\\"group_col\\\" AS \\\"ord_3\\\",\\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;\",\"notes\":\"Emulates SQLite-incompatible PERCENTILE_CONT(0.9) with window functions, grouped by \\\"ord_3\\\", casting text-stored \\\"ord_0\\\" to REAL, and keeps only groups with at least 5 rows.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":15948,"cached_input_tokens":14720,"output_tokens":4035,"reasoning_output_tokens":3401}}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_11fe2ec9113dbbdb/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_grouped_percentile_point\nWITH \"ordered\" AS (\n  SELECT\n    \"ord_3\" AS \"group_col\",\n    CAST(\"ord_0\" AS REAL) AS \"measure\",\n    ROW_NUMBER() OVER (\n      PARTITION BY \"ord_3\"\n      ORDER BY CAST(\"ord_0\" AS REAL)\n    ) AS \"rn\"\n  FROM \"c14\"\n  WHERE \"ord_3\" IS NOT NULL\n    AND \"ord_0\" IS NOT NULL\n),\n\"params\" AS (\n  SELECT\n    \"group_col\",\n    COUNT(*) AS \"n\",\n    1.0 + 0.9 * (COUNT(*) - 1) AS \"pos\",\n    CAST(1.0 + 0.9 * (COUNT(*) - 1) AS INTEGER) AS \"lower_rn\",\n    CASE\n      WHEN (1.0 + 0.9 * (COUNT(*) - 1)) > CAST(1.0 + 0.9 * (COUNT(*) - 1) AS INTEGER)\n        THEN CAST(1.0 + 0.9 * (COUNT(*) - 1) AS INTEGER) + 1\n      ELSE CAST(1.0 + 0.9 * (COUNT(*) - 1) AS INTEGER)\n    END AS \"upper_rn\"\n  FROM \"ordered\"\n  GROUP BY \"group_col\"\n  HAVING COUNT(*) >= 5\n),\n\"bounds\" AS (\n  SELECT\n    p.\"group_col\",\n    p.\"pos\",\n    p.\"lower_rn\",\n    p.\"upper_rn\",\n    MAX(CASE WHEN o.\"rn\" = p.\"lower_rn\" THEN o.\"measure\" END) AS \"lower_val\",\n    MAX(CASE WHEN o.\"rn\" = p.\"upper_rn\" THEN o.\"measure\" END) AS \"upper_val\"\n  FROM \"params\" AS p\n  JOIN \"ordered\" AS o\n    ON o.\"group_col\" = p.\"group_col\"\n  GROUP BY\n    p.\"group_col\",\n    p.\"pos\",\n    p.\"lower_rn\",\n    p.\"upper_rn\"\n)\nSELECT\n  \"group_col\" AS \"ord_3\",\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;","notes":"Emulates SQLite-incompatible PERCENTILE_CONT(0.9) with window functions, grouped by \"ord_3\", casting text-stored \"ord_0\" to REAL, and keeps only groups with at least 5 rows."}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_12843844aacf57af/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": "2026-05-19T16:09:46.773539+00:00",
+  "ended_at": "2026-05-19T16:09:50.036706+00:00",
+  "elapsed_ms": 3263.13,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 11684,
+    "bytes_utf8": 11684,
+    "lines": 394,
+    "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_d/c14/artifacts/v2q_c14_12843844aacf57af/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": "2026-05-19T16:09:51.038436+00:00",
+  "ended_at": "2026-05-19T16:09:54.239236+00:00",
+  "elapsed_ms": 3200.76,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 11684,
+    "bytes_utf8": 11684,
+    "lines": 394,
+    "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"
+}