Add files using upload-large-folder tool

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_047e3a987f760c35/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 12684, "bytes_utf8": 12684, "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": 760, "bytes_utf8": 760, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16175, "cached_input_tokens": 12032, "output_tokens": 1230, "reasoning_output_tokens": 978}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_047e3a987f760c35/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": "c15",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c15_047e3a987f760c35",
+    "api_calls": 0,
+    "input_tokens": 16175,
+    "cached_input_tokens": 12032,
+    "output_tokens": 1230,
+    "total_tokens": 17405,
+    "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": 20788.01,
+    "sql_execution_elapsed_ms_total": 715.22,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_047e3a987f760c35/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_047e3a987f760c35/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": "2026-05-19T15:38:14.258880+00:00",
+  "ended_at": "2026-05-19T15:38:35.046918+00:00",
+  "elapsed_ms": 20788.01,
+  "prompt_metrics": {
+    "chars": 12684,
+    "bytes_utf8": 12684,
+    "lines": 398,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1188,
+    "bytes_utf8": 1188,
+    "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": 760,
+      "bytes_utf8": 760,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16175,
+      "cached_input_tokens": 12032,
+      "output_tokens": 1230,
+      "reasoning_output_tokens": 978
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_047e3a987f760c35/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: c15
+- dataset_name: Cat In The Dat Ii
+- table_name: c15
+- 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: 600000
+- 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=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for bin 0.
+- bin_1: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for bin 1.
+- bin_2: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for bin 2.
+- bin_3: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for bin 3.
+- bin_4: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for bin 4.
+- nom_0: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 0.
+- nom_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 1.
+- nom_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 2.
+- nom_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 3.
+- nom_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 4.
+- nom_5: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 5.
+- nom_6: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 6.
+- nom_7: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 7.
+- nom_8: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 8.
+- nom_9: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 9.
+- ord_0: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for ord 0.
+- ord_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 1.
+- ord_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 2.
+- ord_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 3.
+- ord_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 4.
+- ord_5: role=feature, type=categorical_nominal. tags=['condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 5.
+- day: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for day.
+- month: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] 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', 'bin_0', 'target']]
+- fields_requiring_caution: ['target', 'nom_5', 'nom_6', 'nom_7', 'bin_0', 'bin_1', 'bin_2']
+- source_url: https://www.kaggle.com/c/cat-in-the-dat-ii
+
+SQLite schema snapshot:
+{
+  "table_name": "c15",
+  "quoted_table_name": "\"c15\"",
+  "row_count": 600000,
+  "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": "0.0",
+      "bin_1": "0.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Trapezoid",
+      "nom_2": "Hamster",
+      "nom_3": "Russia",
+      "nom_4": "Bassoon",
+      "nom_5": "de4c57ee2",
+      "nom_6": "a64bc7ddf",
+      "nom_7": "598080a91",
+      "nom_8": "0256c7a4b",
+      "nom_9": "02e7c8990",
+      "ord_0": "3.0",
+      "ord_1": "Contributor",
+      "ord_2": "Hot",
+      "ord_3": "c",
+      "ord_4": "U",
+      "ord_5": "Pw",
+      "day": "6.0",
+      "month": "3.0",
+      "target": "0"
+    },
+    {
+      "id": "1",
+      "bin_0": "1.0",
+      "bin_1": "1.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "Y",
+      "nom_0": "Red",
+      "nom_1": "Star",
+      "nom_2": "Axolotl",
+      "nom_3": "",
+      "nom_4": "Theremin",
+      "nom_5": "2bb3c3e5c",
+      "nom_6": "3a3a936e8",
+      "nom_7": "1dddb8473",
+      "nom_8": "52ead350c",
+      "nom_9": "f37df64af",
+      "ord_0": "3.0",
+      "ord_1": "Grandmaster",
+      "ord_2": "Warm",
+      "ord_3": "e",
+      "ord_4": "X",
+      "ord_5": "pE",
+      "day": "7.0",
+      "month": "7.0",
+      "target": "0"
+    },
+    {
+      "id": "2",
+      "bin_0": "0.0",
+      "bin_1": "1.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "",
+      "nom_2": "Hamster",
+      "nom_3": "Canada",
+      "nom_4": "Bassoon",
+      "nom_5": "b574c9841",
+      "nom_6": "708248125",
+      "nom_7": "5ddc9a726",
+      "nom_8": "745b909d1",
+      "nom_9": "",
+      "ord_0": "3.0",
+      "ord_1": "",
+      "ord_2": "Freezing",
+      "ord_3": "n",
+      "ord_4": "P",
+      "ord_5": "eN",
+      "day": "5.0",
+      "month": "9.0",
+      "target": "0"
+    },
+    {
+      "id": "3",
+      "bin_0": "",
+      "bin_1": "0.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Circle",
+      "nom_2": "Hamster",
+      "nom_3": "Finland",
+      "nom_4": "Theremin",
+      "nom_5": "673bdf1f6",
+      "nom_6": "23edb8da3",
+      "nom_7": "3a33ef960",
+      "nom_8": "bdaa56dd1",
+      "nom_9": "f9d456e57",
+      "ord_0": "1.0",
+      "ord_1": "Novice",
+      "ord_2": "Lava Hot",
+      "ord_3": "a",
+      "ord_4": "C",
+      "ord_5": "",
+      "day": "3.0",
+      "month": "3.0",
+      "target": "0"
+    },
+    {
+      "id": "4",
+      "bin_0": "0.0",
+      "bin_1": "",
+      "bin_2": "0.0",
+      "bin_3": "T",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Triangle",
+      "nom_2": "Hamster",
+      "nom_3": "Costa Rica",
+      "nom_4": "",
+      "nom_5": "777d1ac2c",
+      "nom_6": "3a7975e46",
+      "nom_7": "bc9cc2a94",
+      "nom_8": "",
+      "nom_9": "c5361037c",
+      "ord_0": "3.0",
+      "ord_1": "Grandmaster",
+      "ord_2": "Cold",
+      "ord_3": "h",
+      "ord_4": "C",
+      "ord_5": "OZ",
+      "day": "5.0",
+      "month": "12.0",
+      "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": "c15",
+  "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": 502184.84,
+    "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_b/c15/artifacts/v2q_c15_047e3a987f760c35/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40e3-3c70-70d3-aab0-00d639e5eefd"}
+{"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 REAL)) AS \\\"total_measure\\\",\\n  SUM(CAST(\\\"id\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"id\\\" AS REAL))) OVER (PARTITION BY \\\"ord_0\\\") AS \\\"share_within_group\\\"\\nFROM \\\"c15\\\"\\nWHERE \\\"ord_0\\\" IS NOT NULL AND \\\"ord_0\\\" <> ''\\n  AND \\\"nom_9\\\" IS NOT NULL AND \\\"nom_9\\\" <> ''\\n  AND \\\"id\\\" IS NOT NULL AND \\\"id\\\" <> ''\\nGROUP BY \\\"ord_0\\\", \\\"nom_9\\\"\\nHAVING COUNT(*) >= 4\\nORDER BY \\\"share_within_group\\\" DESC\\nLIMIT 18;\",\"notes\":\"Uses the requested template with group_col=\\\"ord_0\\\", item_col=\\\"nom_9\\\", and measure_col=\\\"id\\\". \\\"id\\\" is cast from TEXT to REAL for SQLite aggregation, blank values are excluded, and min_support/top_k bindings are applied.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16175,"cached_input_tokens":12032,"output_tokens":1230,"reasoning_output_tokens":978}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_047e3a987f760c35/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 REAL)) AS \"total_measure\",\n  SUM(CAST(\"id\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"id\" AS REAL))) OVER (PARTITION BY \"ord_0\") AS \"share_within_group\"\nFROM \"c15\"\nWHERE \"ord_0\" IS NOT NULL AND \"ord_0\" <> ''\n  AND \"nom_9\" IS NOT NULL AND \"nom_9\" <> ''\n  AND \"id\" IS NOT NULL AND \"id\" <> ''\nGROUP BY \"ord_0\", \"nom_9\"\nHAVING COUNT(*) >= 4\nORDER BY \"share_within_group\" DESC\nLIMIT 18;","notes":"Uses the requested template with group_col=\"ord_0\", item_col=\"nom_9\", and measure_col=\"id\". \"id\" is cast from TEXT to REAL for SQLite aggregation, blank values are excluded, and min_support/top_k bindings are applied."}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_1293c5e4aae53d22/cli/sql_attempt_1.metadata.json

@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:08:03.518019+00:00",
+  "ended_at": "2026-05-19T16:08:06.938032+00:00",
+  "elapsed_ms": 3419.94,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 12222,
+    "bytes_utf8": 12222,
+    "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_b/c15/artifacts/v2q_c15_1293c5e4aae53d22/cli/sql_attempt_2.metadata.json

@@ -0,0 +1,43 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:08:07.940428+00:00",
+  "ended_at": "2026-05-19T16:08:11.027887+00:00",
+  "elapsed_ms": 3087.41,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 12222,
+    "bytes_utf8": 12222,
+    "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"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_1293c5e4aae53d22/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: c15
+- dataset_name: Cat In The Dat Ii
+- table_name: c15
+- 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: 600000
+- 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=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for bin 0.
+- bin_1: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for bin 1.
+- bin_2: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for bin 2.
+- bin_3: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for bin 3.
+- bin_4: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for bin 4.
+- nom_0: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 0.
+- nom_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 1.
+- nom_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 2.
+- nom_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 3.
+- nom_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 4.
+- nom_5: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 5.
+- nom_6: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 6.
+- nom_7: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 7.
+- nom_8: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 8.
+- nom_9: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 9.
+- ord_0: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for ord 0.
+- ord_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 1.
+- ord_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 2.
+- ord_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 3.
+- ord_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 4.
+- ord_5: role=feature, type=categorical_nominal. tags=['condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 5.
+- day: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for day.
+- month: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] 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', 'bin_0', 'target']]
+- fields_requiring_caution: ['target', 'nom_5', 'nom_6', 'nom_7', 'bin_0', 'bin_1', 'bin_2']
+- source_url: https://www.kaggle.com/c/cat-in-the-dat-ii
+
+SQLite schema snapshot:
+{
+  "table_name": "c15",
+  "quoted_table_name": "\"c15\"",
+  "row_count": 600000,
+  "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": "0.0",
+      "bin_1": "0.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Trapezoid",
+      "nom_2": "Hamster",
+      "nom_3": "Russia",
+      "nom_4": "Bassoon",
+      "nom_5": "de4c57ee2",
+      "nom_6": "a64bc7ddf",
+      "nom_7": "598080a91",
+      "nom_8": "0256c7a4b",
+      "nom_9": "02e7c8990",
+      "ord_0": "3.0",
+      "ord_1": "Contributor",
+      "ord_2": "Hot",
+      "ord_3": "c",
+      "ord_4": "U",
+      "ord_5": "Pw",
+      "day": "6.0",
+      "month": "3.0",
+      "target": "0"
+    },
+    {
+      "id": "1",
+      "bin_0": "1.0",
+      "bin_1": "1.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "Y",
+      "nom_0": "Red",
+      "nom_1": "Star",
+      "nom_2": "Axolotl",
+      "nom_3": "",
+      "nom_4": "Theremin",
+      "nom_5": "2bb3c3e5c",
+      "nom_6": "3a3a936e8",
+      "nom_7": "1dddb8473",
+      "nom_8": "52ead350c",
+      "nom_9": "f37df64af",
+      "ord_0": "3.0",
+      "ord_1": "Grandmaster",
+      "ord_2": "Warm",
+      "ord_3": "e",
+      "ord_4": "X",
+      "ord_5": "pE",
+      "day": "7.0",
+      "month": "7.0",
+      "target": "0"
+    },
+    {
+      "id": "2",
+      "bin_0": "0.0",
+      "bin_1": "1.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "",
+      "nom_2": "Hamster",
+      "nom_3": "Canada",
+      "nom_4": "Bassoon",
+      "nom_5": "b574c9841",
+      "nom_6": "708248125",
+      "nom_7": "5ddc9a726",
+      "nom_8": "745b909d1",
+      "nom_9": "",
+      "ord_0": "3.0",
+      "ord_1": "",
+      "ord_2": "Freezing",
+      "ord_3": "n",
+      "ord_4": "P",
+      "ord_5": "eN",
+      "day": "5.0",
+      "month": "9.0",
+      "target": "0"
+    },
+    {
+      "id": "3",
+      "bin_0": "",
+      "bin_1": "0.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Circle",
+      "nom_2": "Hamster",
+      "nom_3": "Finland",
+      "nom_4": "Theremin",
+      "nom_5": "673bdf1f6",
+      "nom_6": "23edb8da3",
+      "nom_7": "3a33ef960",
+      "nom_8": "bdaa56dd1",
+      "nom_9": "f9d456e57",
+      "ord_0": "1.0",
+      "ord_1": "Novice",
+      "ord_2": "Lava Hot",
+      "ord_3": "a",
+      "ord_4": "C",
+      "ord_5": "",
+      "day": "3.0",
+      "month": "3.0",
+      "target": "0"
+    },
+    {
+      "id": "4",
+      "bin_0": "0.0",
+      "bin_1": "",
+      "bin_2": "0.0",
+      "bin_3": "T",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Triangle",
+      "nom_2": "Hamster",
+      "nom_3": "Costa Rica",
+      "nom_4": "",
+      "nom_5": "777d1ac2c",
+      "nom_6": "3a7975e46",
+      "nom_7": "bc9cc2a94",
+      "nom_8": "",
+      "nom_9": "c5361037c",
+      "ord_0": "3.0",
+      "ord_1": "Grandmaster",
+      "ord_2": "Cold",
+      "ord_3": "h",
+      "ord_4": "C",
+      "ord_5": "OZ",
+      "day": "5.0",
+      "month": "12.0",
+      "target": "0"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_threshold_rarity_cdf",
+    "template_name": "Threshold Rarity CDF",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};",
+    "required_roles": [
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "c15",
+  "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=id.",
+  "planned_template_id": "tpl_threshold_rarity_cdf",
+  "bindings": {
+    "measure_col": "id",
+    "top_k": 12,
+    "top_n": 3,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 509036.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_1293c5e4aae53d22/cli/sql_prompt_attempt_2.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: c15
+- dataset_name: Cat In The Dat Ii
+- table_name: c15
+- 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: 600000
+- 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=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for bin 0.
+- bin_1: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for bin 1.
+- bin_2: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for bin 2.
+- bin_3: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for bin 3.
+- bin_4: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for bin 4.
+- nom_0: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 0.
+- nom_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 1.
+- nom_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 2.
+- nom_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 3.
+- nom_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 4.
+- nom_5: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 5.
+- nom_6: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 6.
+- nom_7: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 7.
+- nom_8: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 8.
+- nom_9: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 9.
+- ord_0: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for ord 0.
+- ord_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 1.
+- ord_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 2.
+- ord_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 3.
+- ord_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 4.
+- ord_5: role=feature, type=categorical_nominal. tags=['condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 5.
+- day: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for day.
+- month: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] 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', 'bin_0', 'target']]
+- fields_requiring_caution: ['target', 'nom_5', 'nom_6', 'nom_7', 'bin_0', 'bin_1', 'bin_2']
+- source_url: https://www.kaggle.com/c/cat-in-the-dat-ii
+
+SQLite schema snapshot:
+{
+  "table_name": "c15",
+  "quoted_table_name": "\"c15\"",
+  "row_count": 600000,
+  "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": "0.0",
+      "bin_1": "0.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Trapezoid",
+      "nom_2": "Hamster",
+      "nom_3": "Russia",
+      "nom_4": "Bassoon",
+      "nom_5": "de4c57ee2",
+      "nom_6": "a64bc7ddf",
+      "nom_7": "598080a91",
+      "nom_8": "0256c7a4b",
+      "nom_9": "02e7c8990",
+      "ord_0": "3.0",
+      "ord_1": "Contributor",
+      "ord_2": "Hot",
+      "ord_3": "c",
+      "ord_4": "U",
+      "ord_5": "Pw",
+      "day": "6.0",
+      "month": "3.0",
+      "target": "0"
+    },
+    {
+      "id": "1",
+      "bin_0": "1.0",
+      "bin_1": "1.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "Y",
+      "nom_0": "Red",
+      "nom_1": "Star",
+      "nom_2": "Axolotl",
+      "nom_3": "",
+      "nom_4": "Theremin",
+      "nom_5": "2bb3c3e5c",
+      "nom_6": "3a3a936e8",
+      "nom_7": "1dddb8473",
+      "nom_8": "52ead350c",
+      "nom_9": "f37df64af",
+      "ord_0": "3.0",
+      "ord_1": "Grandmaster",
+      "ord_2": "Warm",
+      "ord_3": "e",
+      "ord_4": "X",
+      "ord_5": "pE",
+      "day": "7.0",
+      "month": "7.0",
+      "target": "0"
+    },
+    {
+      "id": "2",
+      "bin_0": "0.0",
+      "bin_1": "1.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "",
+      "nom_2": "Hamster",
+      "nom_3": "Canada",
+      "nom_4": "Bassoon",
+      "nom_5": "b574c9841",
+      "nom_6": "708248125",
+      "nom_7": "5ddc9a726",
+      "nom_8": "745b909d1",
+      "nom_9": "",
+      "ord_0": "3.0",
+      "ord_1": "",
+      "ord_2": "Freezing",
+      "ord_3": "n",
+      "ord_4": "P",
+      "ord_5": "eN",
+      "day": "5.0",
+      "month": "9.0",
+      "target": "0"
+    },
+    {
+      "id": "3",
+      "bin_0": "",
+      "bin_1": "0.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Circle",
+      "nom_2": "Hamster",
+      "nom_3": "Finland",
+      "nom_4": "Theremin",
+      "nom_5": "673bdf1f6",
+      "nom_6": "23edb8da3",
+      "nom_7": "3a33ef960",
+      "nom_8": "bdaa56dd1",
+      "nom_9": "f9d456e57",
+      "ord_0": "1.0",
+      "ord_1": "Novice",
+      "ord_2": "Lava Hot",
+      "ord_3": "a",
+      "ord_4": "C",
+      "ord_5": "",
+      "day": "3.0",
+      "month": "3.0",
+      "target": "0"
+    },
+    {
+      "id": "4",
+      "bin_0": "0.0",
+      "bin_1": "",
+      "bin_2": "0.0",
+      "bin_3": "T",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Triangle",
+      "nom_2": "Hamster",
+      "nom_3": "Costa Rica",
+      "nom_4": "",
+      "nom_5": "777d1ac2c",
+      "nom_6": "3a7975e46",
+      "nom_7": "bc9cc2a94",
+      "nom_8": "",
+      "nom_9": "c5361037c",
+      "ord_0": "3.0",
+      "ord_1": "Grandmaster",
+      "ord_2": "Cold",
+      "ord_3": "h",
+      "ord_4": "C",
+      "ord_5": "OZ",
+      "day": "5.0",
+      "month": "12.0",
+      "target": "0"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_threshold_rarity_cdf",
+    "template_name": "Threshold Rarity CDF",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};",
+    "required_roles": [
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "c15",
+  "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=id.",
+  "planned_template_id": "tpl_threshold_rarity_cdf",
+  "bindings": {
+    "measure_col": "id",
+    "top_k": 12,
+    "top_n": 3,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 509036.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_1293c5e4aae53d22/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fe-89ad-7ae0-bd2f-9b28aa2b35f2"}
+{"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_b/c15/artifacts/v2q_c15_1293c5e4aae53d22/cli/sql_response_attempt_1.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fe-89ad-7ae0-bd2f-9b28aa2b35f2"}
+{"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_b/c15/artifacts/v2q_c15_1293c5e4aae53d22/cli/sql_response_attempt_2.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fe-9b1d-78e1-b482-af4ec00e1e82"}
+{"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_b/c15/artifacts/v2q_c15_1293c5e4aae53d22/cli/sql_response_attempt_2.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fe-9b1d-78e1-b482-af4ec00e1e82"}
+{"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_b/c15/artifacts/v2q_c15_1344c21725fcec52/cli/conversation.jsonl

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+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 12454, "bytes_utf8": 12454, "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": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "status": "failed", "error": "AI CLI command failed with exit code 1: "}
+{"attempt": 2, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_2.txt", "metrics": {"chars": 12454, "bytes_utf8": 12454, "lines": 396, "estimated_tokens": null}}
+{"attempt": 2, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_2.txt", "raw_content_path": "cli/sql_response_attempt_2.raw.txt", "stderr_path": "cli/sql_stderr_attempt_2.txt", "metrics": {"chars": 853, "bytes_utf8": 853, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16094, "cached_input_tokens": 12032, "output_tokens": 1276, "reasoning_output_tokens": 1008}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_1344c21725fcec52/cli/session_summary.json

@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 2,
+  "usage_summary": {
+    "dataset_id": "c15",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c15_1344c21725fcec52",
+    "api_calls": 0,
+    "input_tokens": 16094,
+    "cached_input_tokens": 12032,
+    "output_tokens": 1276,
+    "total_tokens": 17370,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 2,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 27021.57,
+    "sql_execution_elapsed_ms_total": 1459.67,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_1344c21725fcec52/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_1344c21725fcec52/cli/sql_attempt_1.metadata.json

@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:58:28.552978+00:00",
+  "ended_at": "2026-05-19T15:58:31.578869+00:00",
+  "elapsed_ms": 3025.86,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 12454,
+    "bytes_utf8": 12454,
+    "lines": 396,
+    "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_b/c15/artifacts/v2q_c15_1344c21725fcec52/cli/sql_attempt_2.metadata.json

@@ -0,0 +1,45 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:58:32.581025+00:00",
+  "ended_at": "2026-05-19T15:58:56.576781+00:00",
+  "elapsed_ms": 23995.71,
+  "prompt_metrics": {
+    "chars": 12454,
+    "bytes_utf8": 12454,
+    "lines": 396,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1318,
+    "bytes_utf8": 1318,
+    "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": 853,
+      "bytes_utf8": 853,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16094,
+      "cached_input_tokens": 12032,
+      "output_tokens": 1276,
+      "reasoning_output_tokens": 1008
+    }
+  },
+  "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_b/c15/artifacts/v2q_c15_1344c21725fcec52/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: c15
+- dataset_name: Cat In The Dat Ii
+- table_name: c15
+- 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: 600000
+- 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=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for bin 0.
+- bin_1: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for bin 1.
+- bin_2: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for bin 2.
+- bin_3: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for bin 3.
+- bin_4: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for bin 4.
+- nom_0: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 0.
+- nom_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 1.
+- nom_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 2.
+- nom_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 3.
+- nom_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 4.
+- nom_5: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 5.
+- nom_6: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 6.
+- nom_7: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 7.
+- nom_8: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 8.
+- nom_9: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 9.
+- ord_0: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for ord 0.
+- ord_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 1.
+- ord_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 2.
+- ord_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 3.
+- ord_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 4.
+- ord_5: role=feature, type=categorical_nominal. tags=['condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 5.
+- day: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for day.
+- month: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] 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', 'bin_0', 'target']]
+- fields_requiring_caution: ['target', 'nom_5', 'nom_6', 'nom_7', 'bin_0', 'bin_1', 'bin_2']
+- source_url: https://www.kaggle.com/c/cat-in-the-dat-ii
+
+SQLite schema snapshot:
+{
+  "table_name": "c15",
+  "quoted_table_name": "\"c15\"",
+  "row_count": 600000,
+  "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": "0.0",
+      "bin_1": "0.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Trapezoid",
+      "nom_2": "Hamster",
+      "nom_3": "Russia",
+      "nom_4": "Bassoon",
+      "nom_5": "de4c57ee2",
+      "nom_6": "a64bc7ddf",
+      "nom_7": "598080a91",
+      "nom_8": "0256c7a4b",
+      "nom_9": "02e7c8990",
+      "ord_0": "3.0",
+      "ord_1": "Contributor",
+      "ord_2": "Hot",
+      "ord_3": "c",
+      "ord_4": "U",
+      "ord_5": "Pw",
+      "day": "6.0",
+      "month": "3.0",
+      "target": "0"
+    },
+    {
+      "id": "1",
+      "bin_0": "1.0",
+      "bin_1": "1.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "Y",
+      "nom_0": "Red",
+      "nom_1": "Star",
+      "nom_2": "Axolotl",
+      "nom_3": "",
+      "nom_4": "Theremin",
+      "nom_5": "2bb3c3e5c",
+      "nom_6": "3a3a936e8",
+      "nom_7": "1dddb8473",
+      "nom_8": "52ead350c",
+      "nom_9": "f37df64af",
+      "ord_0": "3.0",
+      "ord_1": "Grandmaster",
+      "ord_2": "Warm",
+      "ord_3": "e",
+      "ord_4": "X",
+      "ord_5": "pE",
+      "day": "7.0",
+      "month": "7.0",
+      "target": "0"
+    },
+    {
+      "id": "2",
+      "bin_0": "0.0",
+      "bin_1": "1.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "",
+      "nom_2": "Hamster",
+      "nom_3": "Canada",
+      "nom_4": "Bassoon",
+      "nom_5": "b574c9841",
+      "nom_6": "708248125",
+      "nom_7": "5ddc9a726",
+      "nom_8": "745b909d1",
+      "nom_9": "",
+      "ord_0": "3.0",
+      "ord_1": "",
+      "ord_2": "Freezing",
+      "ord_3": "n",
+      "ord_4": "P",
+      "ord_5": "eN",
+      "day": "5.0",
+      "month": "9.0",
+      "target": "0"
+    },
+    {
+      "id": "3",
+      "bin_0": "",
+      "bin_1": "0.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Circle",
+      "nom_2": "Hamster",
+      "nom_3": "Finland",
+      "nom_4": "Theremin",
+      "nom_5": "673bdf1f6",
+      "nom_6": "23edb8da3",
+      "nom_7": "3a33ef960",
+      "nom_8": "bdaa56dd1",
+      "nom_9": "f9d456e57",
+      "ord_0": "1.0",
+      "ord_1": "Novice",
+      "ord_2": "Lava Hot",
+      "ord_3": "a",
+      "ord_4": "C",
+      "ord_5": "",
+      "day": "3.0",
+      "month": "3.0",
+      "target": "0"
+    },
+    {
+      "id": "4",
+      "bin_0": "0.0",
+      "bin_1": "",
+      "bin_2": "0.0",
+      "bin_3": "T",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Triangle",
+      "nom_2": "Hamster",
+      "nom_3": "Costa Rica",
+      "nom_4": "",
+      "nom_5": "777d1ac2c",
+      "nom_6": "3a7975e46",
+      "nom_7": "bc9cc2a94",
+      "nom_8": "",
+      "nom_9": "c5361037c",
+      "ord_0": "3.0",
+      "ord_1": "Grandmaster",
+      "ord_2": "Cold",
+      "ord_3": "h",
+      "ord_4": "C",
+      "ord_5": "OZ",
+      "day": "5.0",
+      "month": "12.0",
+      "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": "c15",
+  "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=day, measure_col=bin_2.",
+  "planned_template_id": "tpl_grouped_percentile_point",
+  "bindings": {
+    "group_col": "day",
+    "measure_col": "bin_2",
+    "top_k": 12,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 0.75,
+    "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_b/c15/artifacts/v2q_c15_1344c21725fcec52/cli/sql_prompt_attempt_2.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: c15
+- dataset_name: Cat In The Dat Ii
+- table_name: c15
+- 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: 600000
+- 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=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for bin 0.
+- bin_1: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for bin 1.
+- bin_2: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for bin 2.
+- bin_3: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for bin 3.
+- bin_4: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for bin 4.
+- nom_0: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 0.
+- nom_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 1.
+- nom_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 2.
+- nom_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 3.
+- nom_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 4.
+- nom_5: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 5.
+- nom_6: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 6.
+- nom_7: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 7.
+- nom_8: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 8.
+- nom_9: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 9.
+- ord_0: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for ord 0.
+- ord_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 1.
+- ord_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 2.
+- ord_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 3.
+- ord_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 4.
+- ord_5: role=feature, type=categorical_nominal. tags=['condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 5.
+- day: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for day.
+- month: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] 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', 'bin_0', 'target']]
+- fields_requiring_caution: ['target', 'nom_5', 'nom_6', 'nom_7', 'bin_0', 'bin_1', 'bin_2']
+- source_url: https://www.kaggle.com/c/cat-in-the-dat-ii
+
+SQLite schema snapshot:
+{
+  "table_name": "c15",
+  "quoted_table_name": "\"c15\"",
+  "row_count": 600000,
+  "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": "0.0",
+      "bin_1": "0.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Trapezoid",
+      "nom_2": "Hamster",
+      "nom_3": "Russia",
+      "nom_4": "Bassoon",
+      "nom_5": "de4c57ee2",
+      "nom_6": "a64bc7ddf",
+      "nom_7": "598080a91",
+      "nom_8": "0256c7a4b",
+      "nom_9": "02e7c8990",
+      "ord_0": "3.0",
+      "ord_1": "Contributor",
+      "ord_2": "Hot",
+      "ord_3": "c",
+      "ord_4": "U",
+      "ord_5": "Pw",
+      "day": "6.0",
+      "month": "3.0",
+      "target": "0"
+    },
+    {
+      "id": "1",
+      "bin_0": "1.0",
+      "bin_1": "1.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "Y",
+      "nom_0": "Red",
+      "nom_1": "Star",
+      "nom_2": "Axolotl",
+      "nom_3": "",
+      "nom_4": "Theremin",
+      "nom_5": "2bb3c3e5c",
+      "nom_6": "3a3a936e8",
+      "nom_7": "1dddb8473",
+      "nom_8": "52ead350c",
+      "nom_9": "f37df64af",
+      "ord_0": "3.0",
+      "ord_1": "Grandmaster",
+      "ord_2": "Warm",
+      "ord_3": "e",
+      "ord_4": "X",
+      "ord_5": "pE",
+      "day": "7.0",
+      "month": "7.0",
+      "target": "0"
+    },
+    {
+      "id": "2",
+      "bin_0": "0.0",
+      "bin_1": "1.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "",
+      "nom_2": "Hamster",
+      "nom_3": "Canada",
+      "nom_4": "Bassoon",
+      "nom_5": "b574c9841",
+      "nom_6": "708248125",
+      "nom_7": "5ddc9a726",
+      "nom_8": "745b909d1",
+      "nom_9": "",
+      "ord_0": "3.0",
+      "ord_1": "",
+      "ord_2": "Freezing",
+      "ord_3": "n",
+      "ord_4": "P",
+      "ord_5": "eN",
+      "day": "5.0",
+      "month": "9.0",
+      "target": "0"
+    },
+    {
+      "id": "3",
+      "bin_0": "",
+      "bin_1": "0.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Circle",
+      "nom_2": "Hamster",
+      "nom_3": "Finland",
+      "nom_4": "Theremin",
+      "nom_5": "673bdf1f6",
+      "nom_6": "23edb8da3",
+      "nom_7": "3a33ef960",
+      "nom_8": "bdaa56dd1",
+      "nom_9": "f9d456e57",
+      "ord_0": "1.0",
+      "ord_1": "Novice",
+      "ord_2": "Lava Hot",
+      "ord_3": "a",
+      "ord_4": "C",
+      "ord_5": "",
+      "day": "3.0",
+      "month": "3.0",
+      "target": "0"
+    },
+    {
+      "id": "4",
+      "bin_0": "0.0",
+      "bin_1": "",
+      "bin_2": "0.0",
+      "bin_3": "T",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Triangle",
+      "nom_2": "Hamster",
+      "nom_3": "Costa Rica",
+      "nom_4": "",
+      "nom_5": "777d1ac2c",
+      "nom_6": "3a7975e46",
+      "nom_7": "bc9cc2a94",
+      "nom_8": "",
+      "nom_9": "c5361037c",
+      "ord_0": "3.0",
+      "ord_1": "Grandmaster",
+      "ord_2": "Cold",
+      "ord_3": "h",
+      "ord_4": "C",
+      "ord_5": "OZ",
+      "day": "5.0",
+      "month": "12.0",
+      "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": "c15",
+  "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=day, measure_col=bin_2.",
+  "planned_template_id": "tpl_grouped_percentile_point",
+  "bindings": {
+    "group_col": "day",
+    "measure_col": "bin_2",
+    "top_k": 12,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 0.75,
+    "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_b/c15/artifacts/v2q_c15_1344c21725fcec52/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f5-c3f5-7751-97ef-06d8d945a469"}
+{"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_b/c15/artifacts/v2q_c15_1344c21725fcec52/cli/sql_response_attempt_1.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f5-c3f5-7751-97ef-06d8d945a469"}
+{"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_b/c15/artifacts/v2q_c15_1344c21725fcec52/cli/sql_response_attempt_2.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f5-d3ab-72e1-90c7-0bb450fe1e1c"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"base\\\" AS (\\n  SELECT\\n    \\\"day\\\",\\n    CAST(\\\"bin_2\\\" AS REAL) AS \\\"measure_value\\\"\\n  FROM \\\"c15\\\"\\n  WHERE \\\"day\\\" IS NOT NULL\\n    AND \\\"day\\\" <> ''\\n    AND \\\"bin_2\\\" IS NOT NULL\\n    AND \\\"bin_2\\\" <> ''\\n),\\n\\\"ranked\\\" AS (\\n  SELECT\\n    \\\"day\\\",\\n    \\\"measure_value\\\",\\n    ROW_NUMBER() OVER (PARTITION BY \\\"day\\\" ORDER BY \\\"measure_value\\\") AS \\\"rn\\\",\\n    COUNT(*) OVER (PARTITION BY \\\"day\\\") AS \\\"cnt\\\"\\n  FROM \\\"base\\\"\\n)\\nSELECT\\n  \\\"day\\\",\\n  MIN(\\\"measure_value\\\") AS \\\"percentile_measure\\\"\\nFROM \\\"ranked\\\"\\nWHERE 10 * \\\"rn\\\" >= 9 * \\\"cnt\\\"\\nGROUP BY \\\"day\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\",\"notes\":\"SQLite does not support PERCENTILE_CONT, so this uses a nearest-rank 90th percentile approximation per \\\"day\\\" over CAST(\\\"bin_2\\\" AS REAL), excluding blank values.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16094,"cached_input_tokens":12032,"output_tokens":1276,"reasoning_output_tokens":1008}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_1344c21725fcec52/cli/sql_response_attempt_2.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_grouped_percentile_point\nWITH \"base\" AS (\n  SELECT\n    \"day\",\n    CAST(\"bin_2\" AS REAL) AS \"measure_value\"\n  FROM \"c15\"\n  WHERE \"day\" IS NOT NULL\n    AND \"day\" <> ''\n    AND \"bin_2\" IS NOT NULL\n    AND \"bin_2\" <> ''\n),\n\"ranked\" AS (\n  SELECT\n    \"day\",\n    \"measure_value\",\n    ROW_NUMBER() OVER (PARTITION BY \"day\" ORDER BY \"measure_value\") AS \"rn\",\n    COUNT(*) OVER (PARTITION BY \"day\") AS \"cnt\"\n  FROM \"base\"\n)\nSELECT\n  \"day\",\n  MIN(\"measure_value\") AS \"percentile_measure\"\nFROM \"ranked\"\nWHERE 10 * \"rn\" >= 9 * \"cnt\"\nGROUP BY \"day\"\nORDER BY \"percentile_measure\" DESC;","notes":"SQLite does not support PERCENTILE_CONT, so this uses a nearest-rank 90th percentile approximation per \"day\" over CAST(\"bin_2\" AS REAL), excluding blank values."}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_14c04f1e69d9fab0/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 12192, "bytes_utf8": 12192, "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": 261, "bytes_utf8": 261, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16027, "cached_input_tokens": 12032, "output_tokens": 302, "reasoning_output_tokens": 225}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_14c04f1e69d9fab0/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": "c15",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c15_14c04f1e69d9fab0",
+    "api_calls": 0,
+    "input_tokens": 16027,
+    "cached_input_tokens": 12032,
+    "output_tokens": 302,
+    "total_tokens": 16329,
+    "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": 15834.21,
+    "sql_execution_elapsed_ms_total": 323.38,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_14c04f1e69d9fab0/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_14c04f1e69d9fab0/cli/sql_attempt_1.metadata.json

@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:33:25.148856+00:00",
+  "ended_at": "2026-05-19T15:33:40.983093+00:00",
+  "elapsed_ms": 15834.21,
+  "prompt_metrics": {
+    "chars": 12192,
+    "bytes_utf8": 12192,
+    "lines": 394,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 619,
+    "bytes_utf8": 619,
+    "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": 261,
+      "bytes_utf8": 261,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16027,
+      "cached_input_tokens": 12032,
+      "output_tokens": 302,
+      "reasoning_output_tokens": 225
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_14c04f1e69d9fab0/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: c15
+- dataset_name: Cat In The Dat Ii
+- table_name: c15
+- 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: 600000
+- 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=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for bin 0.
+- bin_1: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for bin 1.
+- bin_2: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for bin 2.
+- bin_3: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for bin 3.
+- bin_4: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for bin 4.
+- nom_0: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 0.
+- nom_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 1.
+- nom_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 2.
+- nom_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 3.
+- nom_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 4.
+- nom_5: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 5.
+- nom_6: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 6.
+- nom_7: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 7.
+- nom_8: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 8.
+- nom_9: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 9.
+- ord_0: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for ord 0.
+- ord_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 1.
+- ord_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 2.
+- ord_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 3.
+- ord_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 4.
+- ord_5: role=feature, type=categorical_nominal. tags=['condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 5.
+- day: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for day.
+- month: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] 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', 'bin_0', 'target']]
+- fields_requiring_caution: ['target', 'nom_5', 'nom_6', 'nom_7', 'bin_0', 'bin_1', 'bin_2']
+- source_url: https://www.kaggle.com/c/cat-in-the-dat-ii
+
+SQLite schema snapshot:
+{
+  "table_name": "c15",
+  "quoted_table_name": "\"c15\"",
+  "row_count": 600000,
+  "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": "0.0",
+      "bin_1": "0.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Trapezoid",
+      "nom_2": "Hamster",
+      "nom_3": "Russia",
+      "nom_4": "Bassoon",
+      "nom_5": "de4c57ee2",
+      "nom_6": "a64bc7ddf",
+      "nom_7": "598080a91",
+      "nom_8": "0256c7a4b",
+      "nom_9": "02e7c8990",
+      "ord_0": "3.0",
+      "ord_1": "Contributor",
+      "ord_2": "Hot",
+      "ord_3": "c",
+      "ord_4": "U",
+      "ord_5": "Pw",
+      "day": "6.0",
+      "month": "3.0",
+      "target": "0"
+    },
+    {
+      "id": "1",
+      "bin_0": "1.0",
+      "bin_1": "1.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "Y",
+      "nom_0": "Red",
+      "nom_1": "Star",
+      "nom_2": "Axolotl",
+      "nom_3": "",
+      "nom_4": "Theremin",
+      "nom_5": "2bb3c3e5c",
+      "nom_6": "3a3a936e8",
+      "nom_7": "1dddb8473",
+      "nom_8": "52ead350c",
+      "nom_9": "f37df64af",
+      "ord_0": "3.0",
+      "ord_1": "Grandmaster",
+      "ord_2": "Warm",
+      "ord_3": "e",
+      "ord_4": "X",
+      "ord_5": "pE",
+      "day": "7.0",
+      "month": "7.0",
+      "target": "0"
+    },
+    {
+      "id": "2",
+      "bin_0": "0.0",
+      "bin_1": "1.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "",
+      "nom_2": "Hamster",
+      "nom_3": "Canada",
+      "nom_4": "Bassoon",
+      "nom_5": "b574c9841",
+      "nom_6": "708248125",
+      "nom_7": "5ddc9a726",
+      "nom_8": "745b909d1",
+      "nom_9": "",
+      "ord_0": "3.0",
+      "ord_1": "",
+      "ord_2": "Freezing",
+      "ord_3": "n",
+      "ord_4": "P",
+      "ord_5": "eN",
+      "day": "5.0",
+      "month": "9.0",
+      "target": "0"
+    },
+    {
+      "id": "3",
+      "bin_0": "",
+      "bin_1": "0.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Circle",
+      "nom_2": "Hamster",
+      "nom_3": "Finland",
+      "nom_4": "Theremin",
+      "nom_5": "673bdf1f6",
+      "nom_6": "23edb8da3",
+      "nom_7": "3a33ef960",
+      "nom_8": "bdaa56dd1",
+      "nom_9": "f9d456e57",
+      "ord_0": "1.0",
+      "ord_1": "Novice",
+      "ord_2": "Lava Hot",
+      "ord_3": "a",
+      "ord_4": "C",
+      "ord_5": "",
+      "day": "3.0",
+      "month": "3.0",
+      "target": "0"
+    },
+    {
+      "id": "4",
+      "bin_0": "0.0",
+      "bin_1": "",
+      "bin_2": "0.0",
+      "bin_3": "T",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Triangle",
+      "nom_2": "Hamster",
+      "nom_3": "Costa Rica",
+      "nom_4": "",
+      "nom_5": "777d1ac2c",
+      "nom_6": "3a7975e46",
+      "nom_7": "bc9cc2a94",
+      "nom_8": "",
+      "nom_9": "c5361037c",
+      "ord_0": "3.0",
+      "ord_1": "Grandmaster",
+      "ord_2": "Cold",
+      "ord_3": "h",
+      "ord_4": "C",
+      "ord_5": "OZ",
+      "day": "5.0",
+      "month": "12.0",
+      "target": "0"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_clickbench_group_count",
+    "template_name": "Grouped Count by Category",
+    "primary_family": "subgroup_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;",
+    "required_roles": [
+      "group_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "c15",
+  "question": "Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=day.",
+  "planned_template_id": "tpl_clickbench_group_count",
+  "bindings": {
+    "group_col": "day",
+    "top_k": 10,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 0.75,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_14c04f1e69d9fab0/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40de-d31b-76c0-b5b3-cf9ff4275d10"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"day\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"c15\\\"\\nGROUP BY \\\"day\\\"\\nORDER BY \\\"row_count\\\" DESC;\",\"notes\":\"Applies the provided grouped-count template with group_col bound to \\\"day\\\" on table \\\"c15\\\".\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16027,"cached_input_tokens":12032,"output_tokens":302,"reasoning_output_tokens":225}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_14c04f1e69d9fab0/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_clickbench_group_count\nSELECT \"day\", COUNT(*) AS \"row_count\"\nFROM \"c15\"\nGROUP BY \"day\"\nORDER BY \"row_count\" DESC;","notes":"Applies the provided grouped-count template with group_col bound to \"day\" on table \"c15\"."}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_15b69bb9f5548e5a/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 12686, "bytes_utf8": 12686, "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": 620, "bytes_utf8": 620, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16176, "cached_input_tokens": 14720, "output_tokens": 982, "reasoning_output_tokens": 785}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_15b69bb9f5548e5a/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": "c15",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c15_15b69bb9f5548e5a",
+    "api_calls": 0,
+    "input_tokens": 16176,
+    "cached_input_tokens": 14720,
+    "output_tokens": 982,
+    "total_tokens": 17158,
+    "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": 18785.17,
+    "sql_execution_elapsed_ms_total": 680.38,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_15b69bb9f5548e5a/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_15b69bb9f5548e5a/cli/sql_attempt_1.metadata.json

@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:37:54.759201+00:00",
+  "ended_at": "2026-05-19T15:38:13.544407+00:00",
+  "elapsed_ms": 18785.17,
+  "prompt_metrics": {
+    "chars": 12686,
+    "bytes_utf8": 12686,
+    "lines": 398,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1011,
+    "bytes_utf8": 1011,
+    "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": 620,
+      "bytes_utf8": 620,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16176,
+      "cached_input_tokens": 14720,
+      "output_tokens": 982,
+      "reasoning_output_tokens": 785
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_15b69bb9f5548e5a/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: c15
+- dataset_name: Cat In The Dat Ii
+- table_name: c15
+- 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: 600000
+- 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=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for bin 0.
+- bin_1: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for bin 1.
+- bin_2: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for bin 2.
+- bin_3: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for bin 3.
+- bin_4: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for bin 4.
+- nom_0: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 0.
+- nom_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 1.
+- nom_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 2.
+- nom_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 3.
+- nom_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 4.
+- nom_5: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 5.
+- nom_6: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 6.
+- nom_7: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 7.
+- nom_8: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 8.
+- nom_9: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 9.
+- ord_0: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for ord 0.
+- ord_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 1.
+- ord_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 2.
+- ord_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 3.
+- ord_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 4.
+- ord_5: role=feature, type=categorical_nominal. tags=['condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 5.
+- day: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for day.
+- month: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] 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', 'bin_0', 'target']]
+- fields_requiring_caution: ['target', 'nom_5', 'nom_6', 'nom_7', 'bin_0', 'bin_1', 'bin_2']
+- source_url: https://www.kaggle.com/c/cat-in-the-dat-ii
+
+SQLite schema snapshot:
+{
+  "table_name": "c15",
+  "quoted_table_name": "\"c15\"",
+  "row_count": 600000,
+  "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": "0.0",
+      "bin_1": "0.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Trapezoid",
+      "nom_2": "Hamster",
+      "nom_3": "Russia",
+      "nom_4": "Bassoon",
+      "nom_5": "de4c57ee2",
+      "nom_6": "a64bc7ddf",
+      "nom_7": "598080a91",
+      "nom_8": "0256c7a4b",
+      "nom_9": "02e7c8990",
+      "ord_0": "3.0",
+      "ord_1": "Contributor",
+      "ord_2": "Hot",
+      "ord_3": "c",
+      "ord_4": "U",
+      "ord_5": "Pw",
+      "day": "6.0",
+      "month": "3.0",
+      "target": "0"
+    },
+    {
+      "id": "1",
+      "bin_0": "1.0",
+      "bin_1": "1.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "Y",
+      "nom_0": "Red",
+      "nom_1": "Star",
+      "nom_2": "Axolotl",
+      "nom_3": "",
+      "nom_4": "Theremin",
+      "nom_5": "2bb3c3e5c",
+      "nom_6": "3a3a936e8",
+      "nom_7": "1dddb8473",
+      "nom_8": "52ead350c",
+      "nom_9": "f37df64af",
+      "ord_0": "3.0",
+      "ord_1": "Grandmaster",
+      "ord_2": "Warm",
+      "ord_3": "e",
+      "ord_4": "X",
+      "ord_5": "pE",
+      "day": "7.0",
+      "month": "7.0",
+      "target": "0"
+    },
+    {
+      "id": "2",
+      "bin_0": "0.0",
+      "bin_1": "1.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "",
+      "nom_2": "Hamster",
+      "nom_3": "Canada",
+      "nom_4": "Bassoon",
+      "nom_5": "b574c9841",
+      "nom_6": "708248125",
+      "nom_7": "5ddc9a726",
+      "nom_8": "745b909d1",
+      "nom_9": "",
+      "ord_0": "3.0",
+      "ord_1": "",
+      "ord_2": "Freezing",
+      "ord_3": "n",
+      "ord_4": "P",
+      "ord_5": "eN",
+      "day": "5.0",
+      "month": "9.0",
+      "target": "0"
+    },
+    {
+      "id": "3",
+      "bin_0": "",
+      "bin_1": "0.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Circle",
+      "nom_2": "Hamster",
+      "nom_3": "Finland",
+      "nom_4": "Theremin",
+      "nom_5": "673bdf1f6",
+      "nom_6": "23edb8da3",
+      "nom_7": "3a33ef960",
+      "nom_8": "bdaa56dd1",
+      "nom_9": "f9d456e57",
+      "ord_0": "1.0",
+      "ord_1": "Novice",
+      "ord_2": "Lava Hot",
+      "ord_3": "a",
+      "ord_4": "C",
+      "ord_5": "",
+      "day": "3.0",
+      "month": "3.0",
+      "target": "0"
+    },
+    {
+      "id": "4",
+      "bin_0": "0.0",
+      "bin_1": "",
+      "bin_2": "0.0",
+      "bin_3": "T",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Triangle",
+      "nom_2": "Hamster",
+      "nom_3": "Costa Rica",
+      "nom_4": "",
+      "nom_5": "777d1ac2c",
+      "nom_6": "3a7975e46",
+      "nom_7": "bc9cc2a94",
+      "nom_8": "",
+      "nom_9": "c5361037c",
+      "ord_0": "3.0",
+      "ord_1": "Grandmaster",
+      "ord_2": "Cold",
+      "ord_3": "h",
+      "ord_4": "C",
+      "ord_5": "OZ",
+      "day": "5.0",
+      "month": "12.0",
+      "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": "c15",
+  "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. 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": 13,
+    "top_n": 3,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 509036.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_15b69bb9f5548e5a/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40e2-f059-7fb1-ba85-b34d0fc27b69"}
+{"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 REAL)) AS total_measure,\\n  SUM(CAST(\\\"id\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"id\\\" AS REAL))) OVER (PARTITION BY \\\"ord_0\\\") AS share_within_group\\nFROM \\\"c15\\\"\\nGROUP BY \\\"ord_0\\\", \\\"nom_9\\\"\\nORDER BY share_within_group DESC\\nLIMIT 13;\",\"notes\":\"Applied the Within-Group Share of Total template with group_col=\\\"ord_0\\\", item_col=\\\"nom_9\\\", and measure_col=\\\"id\\\". CAST(\\\"id\\\" AS REAL) is used because the SQLite schema stores \\\"id\\\" as TEXT. The result is limited to the top 13 rows by within-group share.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16176,"cached_input_tokens":14720,"output_tokens":982,"reasoning_output_tokens":785}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_15b69bb9f5548e5a/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 REAL)) AS total_measure,\n  SUM(CAST(\"id\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"id\" AS REAL))) OVER (PARTITION BY \"ord_0\") AS share_within_group\nFROM \"c15\"\nGROUP BY \"ord_0\", \"nom_9\"\nORDER BY share_within_group DESC\nLIMIT 13;","notes":"Applied the Within-Group Share of Total template with group_col=\"ord_0\", item_col=\"nom_9\", and measure_col=\"id\". CAST(\"id\" AS REAL) is used because the SQLite schema stores \"id\" as TEXT. The result is limited to the top 13 rows by within-group share."}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_167252a6e44b53c8/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 13100, "bytes_utf8": 13100, "lines": 399, "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": 610, "bytes_utf8": 610, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16269, "cached_input_tokens": 14720, "output_tokens": 465, "reasoning_output_tokens": 286}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_167252a6e44b53c8/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": "c15",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c15_167252a6e44b53c8",
+    "api_calls": 0,
+    "input_tokens": 16269,
+    "cached_input_tokens": 14720,
+    "output_tokens": 465,
+    "total_tokens": 16734,
+    "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": 12118.85,
+    "sql_execution_elapsed_ms_total": 325.68,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_167252a6e44b53c8/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_167252a6e44b53c8/cli/sql_attempt_1.metadata.json

@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:43:30.447692+00:00",
+  "ended_at": "2026-05-19T15:43:42.566566+00:00",
+  "elapsed_ms": 12118.85,
+  "prompt_metrics": {
+    "chars": 13100,
+    "bytes_utf8": 13100,
+    "lines": 399,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 979,
+    "bytes_utf8": 979,
+    "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": 610,
+      "bytes_utf8": 610,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16269,
+      "cached_input_tokens": 14720,
+      "output_tokens": 465,
+      "reasoning_output_tokens": 286
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_167252a6e44b53c8/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: c15
+- dataset_name: Cat In The Dat Ii
+- table_name: c15
+- 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: 600000
+- 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=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for bin 0.
+- bin_1: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for bin 1.
+- bin_2: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for bin 2.
+- bin_3: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for bin 3.
+- bin_4: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for bin 4.
+- nom_0: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 0.
+- nom_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 1.
+- nom_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 2.
+- nom_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 3.
+- nom_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for nom 4.
+- nom_5: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 5.
+- nom_6: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 6.
+- nom_7: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 7.
+- nom_8: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 8.
+- nom_9: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for nom 9.
+- ord_0: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for ord 0.
+- ord_1: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 1.
+- ord_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 2.
+- ord_3: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 3.
+- ord_4: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 4.
+- ord_5: role=feature, type=categorical_nominal. tags=['condition_candidate', 'missingness_candidate'] desc=Categorical field for ord 5.
+- day: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] desc=Numeric field for day.
+- month: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'missingness_candidate'] 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', 'bin_0', 'target']]
+- fields_requiring_caution: ['target', 'nom_5', 'nom_6', 'nom_7', 'bin_0', 'bin_1', 'bin_2']
+- source_url: https://www.kaggle.com/c/cat-in-the-dat-ii
+
+SQLite schema snapshot:
+{
+  "table_name": "c15",
+  "quoted_table_name": "\"c15\"",
+  "row_count": 600000,
+  "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": "0.0",
+      "bin_1": "0.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Trapezoid",
+      "nom_2": "Hamster",
+      "nom_3": "Russia",
+      "nom_4": "Bassoon",
+      "nom_5": "de4c57ee2",
+      "nom_6": "a64bc7ddf",
+      "nom_7": "598080a91",
+      "nom_8": "0256c7a4b",
+      "nom_9": "02e7c8990",
+      "ord_0": "3.0",
+      "ord_1": "Contributor",
+      "ord_2": "Hot",
+      "ord_3": "c",
+      "ord_4": "U",
+      "ord_5": "Pw",
+      "day": "6.0",
+      "month": "3.0",
+      "target": "0"
+    },
+    {
+      "id": "1",
+      "bin_0": "1.0",
+      "bin_1": "1.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "Y",
+      "nom_0": "Red",
+      "nom_1": "Star",
+      "nom_2": "Axolotl",
+      "nom_3": "",
+      "nom_4": "Theremin",
+      "nom_5": "2bb3c3e5c",
+      "nom_6": "3a3a936e8",
+      "nom_7": "1dddb8473",
+      "nom_8": "52ead350c",
+      "nom_9": "f37df64af",
+      "ord_0": "3.0",
+      "ord_1": "Grandmaster",
+      "ord_2": "Warm",
+      "ord_3": "e",
+      "ord_4": "X",
+      "ord_5": "pE",
+      "day": "7.0",
+      "month": "7.0",
+      "target": "0"
+    },
+    {
+      "id": "2",
+      "bin_0": "0.0",
+      "bin_1": "1.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "",
+      "nom_2": "Hamster",
+      "nom_3": "Canada",
+      "nom_4": "Bassoon",
+      "nom_5": "b574c9841",
+      "nom_6": "708248125",
+      "nom_7": "5ddc9a726",
+      "nom_8": "745b909d1",
+      "nom_9": "",
+      "ord_0": "3.0",
+      "ord_1": "",
+      "ord_2": "Freezing",
+      "ord_3": "n",
+      "ord_4": "P",
+      "ord_5": "eN",
+      "day": "5.0",
+      "month": "9.0",
+      "target": "0"
+    },
+    {
+      "id": "3",
+      "bin_0": "",
+      "bin_1": "0.0",
+      "bin_2": "0.0",
+      "bin_3": "F",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Circle",
+      "nom_2": "Hamster",
+      "nom_3": "Finland",
+      "nom_4": "Theremin",
+      "nom_5": "673bdf1f6",
+      "nom_6": "23edb8da3",
+      "nom_7": "3a33ef960",
+      "nom_8": "bdaa56dd1",
+      "nom_9": "f9d456e57",
+      "ord_0": "1.0",
+      "ord_1": "Novice",
+      "ord_2": "Lava Hot",
+      "ord_3": "a",
+      "ord_4": "C",
+      "ord_5": "",
+      "day": "3.0",
+      "month": "3.0",
+      "target": "0"
+    },
+    {
+      "id": "4",
+      "bin_0": "0.0",
+      "bin_1": "",
+      "bin_2": "0.0",
+      "bin_3": "T",
+      "bin_4": "N",
+      "nom_0": "Red",
+      "nom_1": "Triangle",
+      "nom_2": "Hamster",
+      "nom_3": "Costa Rica",
+      "nom_4": "",
+      "nom_5": "777d1ac2c",
+      "nom_6": "3a7975e46",
+      "nom_7": "bc9cc2a94",
+      "nom_8": "",
+      "nom_9": "c5361037c",
+      "ord_0": "3.0",
+      "ord_1": "Grandmaster",
+      "ord_2": "Cold",
+      "ord_3": "h",
+      "ord_4": "C",
+      "ord_5": "OZ",
+      "day": "5.0",
+      "month": "12.0",
+      "target": "0"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_group_ratio_two_conditions",
+    "template_name": "Grouped Ratio of Two Conditions",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "yes",
+    "sql_skeleton": "WITH grouped AS (\n    SELECT {group_col},\n           SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n           SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n    FROM {table}\n    GROUP BY {group_col}\n)\nSELECT {group_col},\n       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;",
+    "required_roles": [
+      "group_col",
+      "condition_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "c15",
+  "question": "Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=bin_0, condition_col=nom_1.",
+  "planned_template_id": "tpl_m4_group_ratio_two_conditions",
+  "bindings": {
+    "group_col": "bin_0",
+    "condition_col": "nom_1",
+    "condition_value": "Star",
+    "positive_value": "Star",
+    "negative_value": "Triangle",
+    "top_k": 11,
+    "top_n": 3,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 0.75,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "WITH grouped AS (\n    SELECT {group_col},\n           SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n           SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n    FROM {table}\n    GROUP BY {group_col}\n)\nSELECT {group_col},\n       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_167252a6e44b53c8/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40e8-0faa-7691-b153-95521350090c"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n    SELECT \\\"bin_0\\\",\\n           SUM(CASE WHEN \\\"nom_1\\\" = 'Star' THEN 1 ELSE 0 END) AS numerator_count,\\n           SUM(CASE WHEN \\\"nom_1\\\" = 'Triangle' THEN 1 ELSE 0 END) AS denominator_count\\n    FROM \\\"c15\\\"\\n    GROUP BY \\\"bin_0\\\"\\n)\\nSELECT \\\"bin_0\\\",\\n       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\",\"notes\":\"Uses the required grouped ratio template with group_col=\\\"bin_0\\\" and condition_col=\\\"nom_1\\\", comparing 'Star' to 'Triangle'.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16269,"cached_input_tokens":14720,"output_tokens":465,"reasoning_output_tokens":286}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_167252a6e44b53c8/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_m4_group_ratio_two_conditions\nWITH grouped AS (\n    SELECT \"bin_0\",\n           SUM(CASE WHEN \"nom_1\" = 'Star' THEN 1 ELSE 0 END) AS numerator_count,\n           SUM(CASE WHEN \"nom_1\" = 'Triangle' THEN 1 ELSE 0 END) AS denominator_count\n    FROM \"c15\"\n    GROUP BY \"bin_0\"\n)\nSELECT \"bin_0\",\n       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;","notes":"Uses the required grouped ratio template with group_col=\"bin_0\" and condition_col=\"nom_1\", comparing 'Star' to 'Triangle'."}