Add files using upload-large-folder tool

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_00963bbb241f6571/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 12590, "bytes_utf8": 12590, "lines": 400, "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": 486, "bytes_utf8": 486, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16155, "cached_input_tokens": 12032, "output_tokens": 659, "reasoning_output_tokens": 516}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_00963bbb241f6571/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_00963bbb241f6571",
+    "api_calls": 0,
+    "input_tokens": 16155,
+    "cached_input_tokens": 12032,
+    "output_tokens": 659,
+    "total_tokens": 16814,
+    "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": 19101.63,
+    "sql_execution_elapsed_ms_total": 160.39,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_00963bbb241f6571/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_00963bbb241f6571/cli/sql_attempt_1.metadata.json

@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:46:33.968747+00:00",
+  "ended_at": "2026-05-19T15:46:53.070417+00:00",
+  "elapsed_ms": 19101.63,
+  "prompt_metrics": {
+    "chars": 12590,
+    "bytes_utf8": 12590,
+    "lines": 400,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1194,
+    "bytes_utf8": 1194,
+    "lines": 5,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 486,
+      "bytes_utf8": 486,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16155,
+      "cached_input_tokens": 12032,
+      "output_tokens": 659,
+      "reasoning_output_tokens": 516
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_00963bbb241f6571/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,400 @@
+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_c2_filtered_group_count_2d",
+    "template_name": "Filtered Two-Dimensional Group Count",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;",
+    "required_roles": [
+      "group_col",
+      "group_col_2",
+      "predicate_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "c15",
+  "question": "Use template Filtered Two-Dimensional Group Count to probe slice_level_consistency with semantic role count_distribution. Focus on group_col=bin_3, group_col_2=nom_1.",
+  "planned_template_id": "tpl_c2_filtered_group_count_2d",
+  "bindings": {
+    "group_col": "bin_3",
+    "group_col_2": "nom_1",
+    "predicate_col": "id",
+    "predicate_op": ">=",
+    "predicate_value": 509036.0,
+    "top_k": 10,
+    "top_n": 5,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 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}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_00963bbb241f6571/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,5 @@
+{"type":"thread.started","thread_id":"019e40ea-dc94-7f63-a31e-52273d1de45d"}
+{"type":"turn.started"}
+{"type":"error","message":"Reconnecting... 2/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1988333, Requested 16790. Please try again in 153ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_c2_filtered_group_count_2d\\nSELECT \\\"bin_3\\\", \\\"nom_1\\\", COUNT(*) AS row_count\\nFROM \\\"c15\\\"\\nWHERE CAST(\\\"id\\\" AS REAL) >= 509036.0\\nGROUP BY \\\"bin_3\\\", \\\"nom_1\\\"\\nORDER BY row_count DESC;\",\"notes\":\"Instantiated the provided filtered two-dimensional group count template with group_col=\\\"bin_3\\\", group_col_2=\\\"nom_1\\\", and predicate on \\\"id\\\". Used CAST(\\\"id\\\" AS REAL) because the schema stores \\\"id\\\" as TEXT while the bound predicate value is numeric.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16155,"cached_input_tokens":12032,"output_tokens":659,"reasoning_output_tokens":516}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_00963bbb241f6571/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_c2_filtered_group_count_2d\nSELECT \"bin_3\", \"nom_1\", COUNT(*) AS row_count\nFROM \"c15\"\nWHERE CAST(\"id\" AS REAL) >= 509036.0\nGROUP BY \"bin_3\", \"nom_1\"\nORDER BY row_count DESC;","notes":"Instantiated the provided filtered two-dimensional group count template with group_col=\"bin_3\", group_col_2=\"nom_1\", and predicate on \"id\". Used CAST(\"id\" AS REAL) because the schema stores \"id\" as TEXT while the bound predicate value is numeric."}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_047e3a987f760c35/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=ord_0, measure_col=id.
+Result preview: [{"ord_0": "2.0", "nom_9": "717d31bdd", "total_measure": 53336880.0, "share_within_group": 0.11749679612185725}, {"ord_0": "3.0", "nom_9": "c5361037c", "total_measure": 63975937.0, "share_within_group": 0.11123597998336844}, {"ord_0": "2.0", "nom_9": "9d7b3d5d5", "total_measure": 49472166.0, "share_within_group": 0.1089831464121763}, {"ord_0": "1.0", "nom_9": "483535452", "total_measure": 72118952.0, "share_within_group": 0.10880020614191255}, {"ord_0": "3.0", "nom_9": "3bc419b1d", "total_measure": 61012679.0, "share_within_group": 0.10608371613182756}]

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_047e3a987f760c35/generated_sql.sql

@@ -0,0 +1,26 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_b
+-- sql_source_dataset_id: c15
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_tpcds_within_group_share
+-- query_record_id: v2q_c15_047e3a987f760c35
+-- problem_id: v2p_c15_7492c8f3b5d2d05e
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+  "ord_0",
+  "nom_9",
+  SUM(CAST("id" AS REAL)) AS "total_measure",
+  SUM(CAST("id" AS REAL)) * 100.0 / SUM(SUM(CAST("id" AS REAL))) OVER (PARTITION BY "ord_0") AS "share_within_group"
+FROM "c15"
+WHERE "ord_0" IS NOT NULL AND "ord_0" <> ''
+  AND "nom_9" IS NOT NULL AND "nom_9" <> ''
+  AND "id" IS NOT NULL AND "id" <> ''
+GROUP BY "ord_0", "nom_9"
+HAVING COUNT(*) >= 4
+ORDER BY "share_within_group" DESC
+LIMIT 18;

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_047e3a987f760c35/query_results.jsonl

@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT\n  \"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;", "result": "{\"query\": \"-- 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;\", \"columns\": [\"ord_0\", \"nom_9\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"ord_0\": \"2.0\", \"nom_9\": \"717d31bdd\", \"total_measure\": 53336880.0, \"share_within_group\": 0.11749679612185725}, {\"ord_0\": \"3.0\", \"nom_9\": \"c5361037c\", \"total_measure\": 63975937.0, \"share_within_group\": 0.11123597998336844}, {\"ord_0\": \"2.0\", \"nom_9\": \"9d7b3d5d5\", \"total_measure\": 49472166.0, \"share_within_group\": 0.1089831464121763}, {\"ord_0\": \"1.0\", \"nom_9\": \"483535452\", \"total_measure\": 72118952.0, \"share_within_group\": 0.10880020614191255}, {\"ord_0\": \"3.0\", \"nom_9\": \"3bc419b1d\", \"total_measure\": 61012679.0, \"share_within_group\": 0.10608371613182756}, {\"ord_0\": \"1.0\", \"nom_9\": \"9976322be\", \"total_measure\": 70124459.0, \"share_within_group\": 0.10579127099337347}, {\"ord_0\": \"3.0\", \"nom_9\": \"71375ae45\", \"total_measure\": 60838934.0, \"share_within_group\": 0.10578162293478365}, {\"ord_0\": \"1.0\", \"nom_9\": \"203149e41\", \"total_measure\": 68890514.0, \"share_within_group\": 0.10392971495789778}, {\"ord_0\": \"1.0\", \"nom_9\": \"956a98bcb\", \"total_measure\": 68865620.0, \"share_within_group\": 0.1038921593326899}, {\"ord_0\": \"3.0\", \"nom_9\": \"8f3276a6e\", \"total_measure\": 59738630.0, \"share_within_group\": 0.10386850685616145}, {\"ord_0\": \"2.0\", \"nom_9\": \"2fb5641aa\", \"total_measure\": 46809209.0, \"share_within_group\": 0.10311686935003332}, {\"ord_0\": \"3.0\", \"nom_9\": \"5e99ade9b\", \"total_measure\": 59253875.0, \"share_within_group\": 0.10302565562169125}, {\"ord_0\": \"2.0\", \"nom_9\": \"f37df64af\", \"total_measure\": 46538226.0, \"share_within_group\": 0.10251991590424704}, {\"ord_0\": \"1.0\", \"nom_9\": \"91e927321\", \"total_measure\": 67848648.0, \"share_within_group\": 0.10235793344376472}, {\"ord_0\": \"1.0\", \"nom_9\": \"8f3276a6e\", \"total_measure\": 67781649.0, \"share_within_group\": 0.10225685730761534}, {\"ord_0\": \"2.0\", \"nom_9\": \"2ead8fdf5\", \"total_measure\": 46402514.0, \"share_within_group\": 0.10222095343783938}, {\"ord_0\": \"2.0\", \"nom_9\": \"af2a16d75\", \"total_measure\": 46392173.0, \"share_within_group\": 0.10219817305832157}, {\"ord_0\": \"3.0\", \"nom_9\": \"a16717598\", \"total_measure\": 58739139.0, \"share_within_group\": 0.10213067594530575}], \"row_count_returned\": 18, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 715.22}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_047e3a987f760c35/run_manifest.json

@@ -0,0 +1,91 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "c15",
+  "started_at": "2026-05-19T15:38:14.228368+00:00",
+  "ended_at": "2026-05-19T15:38:35.765067+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c15_047e3a987f760c35",
+    "problem_id": "v2p_c15_7492c8f3b5d2d05e",
+    "dataset_id": "c15",
+    "template_id": "tpl_tpcds_within_group_share",
+    "template_name": "Within-Group Share of Total",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "dependency_strength_similarity",
+    "intended_facet_id": "pairwise_conditional_dependency",
+    "variant_semantic_role": "focused_target_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=ord_0, measure_col=id.",
+    "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
+    },
+    "binding_roles": [
+      "group_col",
+      "item_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;",
+    "notes": [
+      "default_facets=pairwise_conditional_dependency",
+      "template_selection_mode=rule",
+      "problem_index_within_template=5",
+      "sql_variant_index=2/2",
+      "binding_index=28"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 3,
+    "problem_index_within_template": 5,
+    "sql_variant_index": 2,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c15/sql/v2q_c15_047e3a987f760c35.sql",
+  "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/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:38:35.047710+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 20788.01, "started_at": "2026-05-19T15:38:14.258880+00:00", "ended_at": "2026-05-19T15:38:35.046918+00:00", "prompt_metrics": {"chars": 12684, "bytes_utf8": 12684, "lines": 398, "estimated_tokens": null}, "response_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}, "stderr_preview": "", "stdout_preview": "{\"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_047e3a987f760c35/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "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_051c2b14bf40526c/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=bin_4, measure_col=ord_0.
+Result preview: [{"bin_4": "N", "total_measure": 590067.0}, {"bin_4": "Y", "total_measure": 509036.0}, {"bin_4": "", "total_measure": 34202.0}]

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_051c2b14bf40526c/generated_sql.sql

@@ -0,0 +1,19 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_b
+-- sql_source_dataset_id: c15
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_rank_order
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_c15_051c2b14bf40526c
+-- problem_id: v2p_c15_54ddee0f6fdca83f
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+  "bin_4",
+  SUM(CAST(NULLIF("ord_0", '') AS REAL)) AS total_measure
+FROM "c15"
+GROUP BY "bin_4"
+ORDER BY total_measure DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_051c2b14bf40526c/query_results.jsonl

@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_h2o_group_sum\nSELECT\n  \"bin_4\",\n  SUM(CAST(NULLIF(\"ord_0\", '') AS REAL)) AS total_measure\nFROM \"c15\"\nGROUP BY \"bin_4\"\nORDER BY total_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT\\n  \\\"bin_4\\\",\\n  SUM(CAST(NULLIF(\\\"ord_0\\\", '') AS REAL)) AS total_measure\\nFROM \\\"c15\\\"\\nGROUP BY \\\"bin_4\\\"\\nORDER BY total_measure DESC;\", \"columns\": [\"bin_4\", \"total_measure\"], \"rows\": [{\"bin_4\": \"N\", \"total_measure\": 590067.0}, {\"bin_4\": \"Y\", \"total_measure\": 509036.0}, {\"bin_4\": \"\", \"total_measure\": 34202.0}], \"row_count_returned\": 3, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 342.74}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_051c2b14bf40526c/run_manifest.json

@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "c15",
+  "started_at": "2026-05-19T15:29:58.260330+00:00",
+  "ended_at": "2026-05-19T15:30:16.732808+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c15_051c2b14bf40526c",
+    "problem_id": "v2p_c15_54ddee0f6fdca83f",
+    "dataset_id": "c15",
+    "template_id": "tpl_h2o_group_sum",
+    "template_name": "Grouped Numeric Sum",
+    "family_id": "subgroup_structure",
+    "canonical_subitem_id": "internal_profile_stability",
+    "intended_facet_id": "subgroup_rank_order",
+    "variant_semantic_role": "collapsed_target_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=bin_4, measure_col=ord_0.",
+    "bindings": {
+      "group_col": "bin_4",
+      "measure_col": "ord_0",
+      "top_k": 14,
+      "top_n": 3,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 2.5,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;",
+    "notes": [
+      "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast",
+      "template_selection_mode=rule",
+      "problem_index_within_template=5",
+      "sql_variant_index=1/2",
+      "binding_index=4"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 1,
+    "problem_index_within_template": 5,
+    "sql_variant_index": 1,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c15/sql/v2q_c15_051c2b14bf40526c.sql",
+  "usage_summary": {
+    "dataset_id": "c15",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c15_051c2b14bf40526c",
+    "api_calls": 0,
+    "input_tokens": 16060,
+    "cached_input_tokens": 12032,
+    "output_tokens": 581,
+    "total_tokens": 16641,
+    "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": 18091.98,
+    "sql_execution_elapsed_ms_total": 342.74,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_051c2b14bf40526c/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_051c2b14bf40526c/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:30:16.388194+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 18091.98, "started_at": "2026-05-19T15:29:58.294300+00:00", "ended_at": "2026-05-19T15:30:16.386319+00:00", "prompt_metrics": {"chars": 12280, "bytes_utf8": 12280, "lines": 396, "estimated_tokens": null}, "response_metrics": {"chars": 451, "bytes_utf8": 451, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16060, "cached_input_tokens": 12032, "output_tokens": 581, "reasoning_output_tokens": 452}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT\\n  \\\"bin_4\\\",\\n  SUM(CAST(NULLIF(\\\"ord_0\\\", '') AS REAL)) AS total_measure\\nFROM \\\"c15\\\"\\nGROUP BY \\\"bin_4\\\"\\nORDER BY total_measure DESC;\",\"notes\":\"Applies the planned grouped-sum template with group_col=\\\"bin_4\\\" and measure_col=\\\"ord_0\\\". Because \\\"ord_0\\\" is stored as TEXT and may contain empty strings, NULLIF plus CAST to REAL keeps the aggregation SQLite-compatible and skips missing values.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_051c2b14bf40526c/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "c15",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_c15_051c2b14bf40526c",
+  "api_calls": 0,
+  "input_tokens": 16060,
+  "cached_input_tokens": 12032,
+  "output_tokens": 581,
+  "total_tokens": 16641,
+  "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": 18091.98,
+  "sql_execution_elapsed_ms_total": 342.74,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_051c2b14bf40526c/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_066dabea71ae6988/cli/sql_attempt_1.metadata.json

@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:09:28.474944+00:00",
+  "ended_at": "2026-05-19T16:09:31.602867+00:00",
+  "elapsed_ms": 3127.9,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 12271,
+    "bytes_utf8": 12271,
+    "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_066dabea71ae6988/cli/sql_attempt_2.metadata.json

@@ -0,0 +1,43 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:09:32.604656+00:00",
+  "ended_at": "2026-05-19T16:09:36.050777+00:00",
+  "elapsed_ms": 3446.08,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 12271,
+    "bytes_utf8": 12271,
+    "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_066dabea71ae6988/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_tail_low_support_group_count_v2",
+    "template_name": "Low-Support Group Count",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT\n    {group_col},\n    COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};",
+    "required_roles": [
+      "group_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "c15",
+  "question": "Use template Low-Support Group Count to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=day.",
+  "planned_template_id": "tpl_tail_low_support_group_count_v2",
+  "bindings": {
+    "group_col": "day",
+    "top_k": 13,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 2.5,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT\n    {group_col},\n    COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_066dabea71ae6988/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_tail_low_support_group_count_v2",
+    "template_name": "Low-Support Group Count",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT\n    {group_col},\n    COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};",
+    "required_roles": [
+      "group_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "c15",
+  "question": "Use template Low-Support Group Count to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=day.",
+  "planned_template_id": "tpl_tail_low_support_group_count_v2",
+  "bindings": {
+    "group_col": "day",
+    "top_k": 13,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 2.5,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT\n    {group_col},\n    COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_066dabea71ae6988/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40ff-d5ae-7ef2-b478-06455afde665"}
+{"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_066dabea71ae6988/cli/sql_response_attempt_1.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40ff-d5ae-7ef2-b478-06455afde665"}
+{"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_066dabea71ae6988/cli/sql_response_attempt_2.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40ff-e5dc-7cc3-a5db-7dca88474d05"}
+{"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_066dabea71ae6988/cli/sql_response_attempt_2.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40ff-e5dc-7cc3-a5db-7dca88474d05"}
+{"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_077cebfa628cef23/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 13107, "bytes_utf8": 13107, "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": 702, "bytes_utf8": 702, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16272, "cached_input_tokens": 12032, "output_tokens": 728, "reasoning_output_tokens": 516}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_077cebfa628cef23/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_077cebfa628cef23",
+    "api_calls": 0,
+    "input_tokens": 16272,
+    "cached_input_tokens": 12032,
+    "output_tokens": 728,
+    "total_tokens": 17000,
+    "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": 21486.64,
+    "sql_execution_elapsed_ms_total": 395.3,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_077cebfa628cef23/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_077cebfa628cef23/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": "2026-05-19T15:44:58.554976+00:00",
+  "ended_at": "2026-05-19T15:45:20.041842+00:00",
+  "elapsed_ms": 21486.64,
+  "prompt_metrics": {
+    "chars": 13107,
+    "bytes_utf8": 13107,
+    "lines": 399,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1430,
+    "bytes_utf8": 1430,
+    "lines": 5,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 702,
+      "bytes_utf8": 702,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16272,
+      "cached_input_tokens": 12032,
+      "output_tokens": 728,
+      "reasoning_output_tokens": 516
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_077cebfa628cef23/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=nom_1, condition_col=ord_2.",
+  "planned_template_id": "tpl_m4_group_ratio_two_conditions",
+  "bindings": {
+    "group_col": "nom_1",
+    "condition_col": "ord_2",
+    "condition_value": "Cold",
+    "positive_value": "Cold",
+    "negative_value": "Boiling Hot",
+    "top_k": 12,
+    "top_n": 5,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 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": "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_077cebfa628cef23/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,5 @@
+{"type":"thread.started","thread_id":"019e40e9-67a9-7ac3-8d69-03395cfca875"}
+{"type":"turn.started"}
+{"type":"error","message":"Reconnecting... 2/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 2000000, Requested 16907. Please try again in 507ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH \\\"grouped\\\" AS (\\n    SELECT\\n        \\\"nom_1\\\",\\n        SUM(CASE WHEN \\\"ord_2\\\" = 'Cold' THEN 1 ELSE 0 END) AS \\\"numerator_count\\\",\\n        SUM(CASE WHEN \\\"ord_2\\\" = 'Boiling Hot' THEN 1 ELSE 0 END) AS \\\"denominator_count\\\"\\n    FROM \\\"c15\\\"\\n    GROUP BY \\\"nom_1\\\"\\n)\\nSELECT\\n    \\\"nom_1\\\",\\n    CAST(\\\"numerator_count\\\" AS FLOAT) / NULLIF(\\\"denominator_count\\\", 0) AS \\\"condition_ratio\\\"\\nFROM \\\"grouped\\\"\\nORDER BY \\\"condition_ratio\\\" DESC;\",\"notes\":\"Grouped ratio template instantiated with group_col=nom_1 and condition_col=ord_2, measuring the Cold-to-Boiling Hot count ratio per nom_1 value. NULLIF prevents division by zero.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16272,"cached_input_tokens":12032,"output_tokens":728,"reasoning_output_tokens":516}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_077cebfa628cef23/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_m4_group_ratio_two_conditions\nWITH \"grouped\" AS (\n    SELECT\n        \"nom_1\",\n        SUM(CASE WHEN \"ord_2\" = 'Cold' THEN 1 ELSE 0 END) AS \"numerator_count\",\n        SUM(CASE WHEN \"ord_2\" = 'Boiling Hot' THEN 1 ELSE 0 END) AS \"denominator_count\"\n    FROM \"c15\"\n    GROUP BY \"nom_1\"\n)\nSELECT\n    \"nom_1\",\n    CAST(\"numerator_count\" AS FLOAT) / NULLIF(\"denominator_count\", 0) AS \"condition_ratio\"\nFROM \"grouped\"\nORDER BY \"condition_ratio\" DESC;","notes":"Grouped ratio template instantiated with group_col=nom_1 and condition_col=ord_2, measuring the Cold-to-Boiling Hot count ratio per nom_1 value. NULLIF prevents division by zero."}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_08a0ff16f243c946/cli/sql_attempt_1.metadata.json

@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:05:04.336014+00:00",
+  "ended_at": "2026-05-19T16:05:07.857519+00:00",
+  "elapsed_ms": 3521.48,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 12557,
+    "bytes_utf8": 12557,
+    "lines": 399,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_08a0ff16f243c946/cli/sql_attempt_2.metadata.json

@@ -0,0 +1,43 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:05:08.859682+00:00",
+  "ended_at": "2026-05-19T16:05:12.108136+00:00",
+  "elapsed_ms": 3248.42,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 12557,
+    "bytes_utf8": 12557,
+    "lines": 399,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_2.txt",
+  "response_path": "cli/sql_response_attempt_2.txt",
+  "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_2.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_08a0ff16f243c946/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_condition_rate",
+    "template_name": "Grouped Condition Rate",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;",
+    "required_roles": [
+      "group_col",
+      "condition_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "c15",
+  "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=nom_3, condition_col=nom_3.",
+  "planned_template_id": "tpl_m4_group_condition_rate",
+  "bindings": {
+    "group_col": "nom_3",
+    "condition_col": "nom_3",
+    "condition_value": "Costa Rica",
+    "positive_value": "Costa Rica",
+    "negative_value": "India",
+    "top_k": 13,
+    "top_n": 5,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 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},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_08a0ff16f243c946/cli/sql_prompt_attempt_2.txt

@@ -0,0 +1,399 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: 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_condition_rate",
+    "template_name": "Grouped Condition Rate",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;",
+    "required_roles": [
+      "group_col",
+      "condition_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "c15",
+  "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=nom_3, condition_col=nom_3.",
+  "planned_template_id": "tpl_m4_group_condition_rate",
+  "bindings": {
+    "group_col": "nom_3",
+    "condition_col": "nom_3",
+    "condition_value": "Costa Rica",
+    "positive_value": "Costa Rica",
+    "negative_value": "India",
+    "top_k": 13,
+    "top_n": 5,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 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},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_08a0ff16f243c946/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fb-cdda-7533-a9e9-80deb427cb33"}
+{"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_08a0ff16f243c946/cli/sql_response_attempt_1.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fb-cdda-7533-a9e9-80deb427cb33"}
+{"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_08a0ff16f243c946/cli/sql_response_attempt_2.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fb-df8c-7701-af54-d0acbe8790ca"}
+{"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_08a0ff16f243c946/cli/sql_response_attempt_2.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fb-df8c-7701-af54-d0acbe8790ca"}
+{"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_0cee3bbc9b500f07/cli/sql_attempt_1.metadata.json

@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:10:12.691135+00:00",
+  "ended_at": "2026-05-19T16:10:17.534306+00:00",
+  "elapsed_ms": 4843.14,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 12280,
+    "bytes_utf8": 12280,
+    "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_0cee3bbc9b500f07/cli/sql_attempt_2.metadata.json

@@ -0,0 +1,43 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:10:18.536740+00:00",
+  "ended_at": "2026-05-19T16:10:21.354159+00:00",
+  "elapsed_ms": 2817.37,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 12280,
+    "bytes_utf8": 12280,
+    "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_0cee3bbc9b500f07/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_tail_low_support_group_count_v2",
+    "template_name": "Low-Support Group Count",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT\n    {group_col},\n    COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};",
+    "required_roles": [
+      "group_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "c15",
+  "question": "Use template Low-Support Group Count to probe tail_set_consistency with semantic role rare_extreme_view. Focus on group_col=bin_0.",
+  "planned_template_id": "tpl_tail_low_support_group_count_v2",
+  "bindings": {
+    "group_col": "bin_0",
+    "top_k": 11,
+    "top_n": 5,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 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\n    {group_col},\n    COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c15/artifacts/v2q_c15_0cee3bbc9b500f07/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_tail_low_support_group_count_v2",
+    "template_name": "Low-Support Group Count",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT\n    {group_col},\n    COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};",
+    "required_roles": [
+      "group_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "c15",
+  "question": "Use template Low-Support Group Count to probe tail_set_consistency with semantic role rare_extreme_view. Focus on group_col=bin_0.",
+  "planned_template_id": "tpl_tail_low_support_group_count_v2",
+  "bindings": {
+    "group_col": "bin_0",
+    "top_k": 11,
+    "top_n": 5,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 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\n    {group_col},\n    COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};"
+}
+
+Repair context:
+{}