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Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_021918a0c8242b2a/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 10159, "bytes_utf8": 10163, "lines": 267, "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": 344, "bytes_utf8": 344, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14909, "cached_input_tokens": 13696, "output_tokens": 457, "reasoning_output_tokens": 357}}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_021918a0c8242b2a/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": "c18",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c18_021918a0c8242b2a",
+    "api_calls": 0,
+    "input_tokens": 14909,
+    "cached_input_tokens": 13696,
+    "output_tokens": 457,
+    "total_tokens": 15366,
+    "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": 10576.79,
+    "sql_execution_elapsed_ms_total": 78.0,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_021918a0c8242b2a/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_021918a0c8242b2a/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": "2026-05-19T16:02:29.958646+00:00",
+  "ended_at": "2026-05-19T16:02:40.535462+00:00",
+  "elapsed_ms": 10576.79,
+  "prompt_metrics": {
+    "chars": 10159,
+    "bytes_utf8": 10163,
+    "lines": 267,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 707,
+    "bytes_utf8": 707,
+    "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": 344,
+      "bytes_utf8": 344,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 14909,
+      "cached_input_tokens": 13696,
+      "output_tokens": 457,
+      "reasoning_output_tokens": 357
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_021918a0c8242b2a/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,267 @@
+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: c18
+- dataset_name: Wine Reviews
+- table_name: c18
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 13 feature columns and target `country`.
+- task_type: classification
+- target_column: country
+- main_row_count: 129971
+- important_fields:
+- row_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for row id.
+- country: role=target, type=categorical_target. tags=['condition_candidate', 'target_candidate', 'missingness_candidate'] desc=Target field for country.
+- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for description.
+- designation: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for designation.
+- points: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for points.
+- price: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate', 'missingness_candidate'] desc=Numeric field for price.
+- province: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for province.
+- region_1: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for region 1.
+- region_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for region 2.
+- taster_name: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for taster name.
+- taster_twitter_handle: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for taster twitter handle.
+- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title.
+- variety: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for variety.
+- winery: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for winery.
+- useful_field_combinations: [['points', 'price', 'country'], ['points', 'points', 'country']]
+- fields_requiring_caution: ['country', 'description', 'designation', 'price']
+- source_url: https://www.kaggle.com/datasets/zynicide/wine-reviews
+
+SQLite schema snapshot:
+{
+  "table_name": "c18",
+  "quoted_table_name": "\"c18\"",
+  "row_count": 129971,
+  "columns": [
+    {
+      "name": "row_id",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "country",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "description",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "designation",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "points",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "price",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "province",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "region_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "region_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "taster_name",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "taster_twitter_handle",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "title",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "variety",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "winery",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "row_id": "0",
+      "country": "Italy",
+      "description": "Aromas include tropical fruit, broom, brimstone and dried herb. The palate isn't overly expressive, offering unripened apple, citrus and dried sage alongside brisk acidity.",
+      "designation": "Vulkà Bianco",
+      "points": "87",
+      "price": "",
+      "province": "Sicily & Sardinia",
+      "region_1": "Etna",
+      "region_2": "",
+      "taster_name": "Kerin O’Keefe",
+      "taster_twitter_handle": "@kerinokeefe",
+      "title": "Nicosia 2013 Vulkà Bianco  (Etna)",
+      "variety": "White Blend",
+      "winery": "Nicosia"
+    },
+    {
+      "row_id": "1",
+      "country": "Portugal",
+      "description": "This is ripe and fruity, a wine that is smooth while still structured. Firm tannins are filled out with juicy red berry fruits and freshened with acidity. It's  already drinkable, although it will certainly be better from 2016.",
+      "designation": "Avidagos",
+      "points": "87",
+      "price": "15.0",
+      "province": "Douro",
+      "region_1": "",
+      "region_2": "",
+      "taster_name": "Roger Voss",
+      "taster_twitter_handle": "@vossroger",
+      "title": "Quinta dos Avidagos 2011 Avidagos Red (Douro)",
+      "variety": "Portuguese Red",
+      "winery": "Quinta dos Avidagos"
+    },
+    {
+      "row_id": "2",
+      "country": "US",
+      "description": "Tart and snappy, the flavors of lime flesh and rind dominate. Some green pineapple pokes through, with crisp acidity underscoring the flavors. The wine was all stainless-steel fermented.",
+      "designation": "",
+      "points": "87",
+      "price": "14.0",
+      "province": "Oregon",
+      "region_1": "Willamette Valley",
+      "region_2": "Willamette Valley",
+      "taster_name": "Paul Gregutt",
+      "taster_twitter_handle": "@paulgwine",
+      "title": "Rainstorm 2013 Pinot Gris (Willamette Valley)",
+      "variety": "Pinot Gris",
+      "winery": "Rainstorm"
+    },
+    {
+      "row_id": "3",
+      "country": "US",
+      "description": "Pineapple rind, lemon pith and orange blossom start off the aromas. The palate is a bit more opulent, with notes of honey-drizzled guava and mango giving way to a slightly astringent, semidry finish.",
+      "designation": "Reserve Late Harvest",
+      "points": "87",
+      "price": "13.0",
+      "province": "Michigan",
+      "region_1": "Lake Michigan Shore",
+      "region_2": "",
+      "taster_name": "Alexander Peartree",
+      "taster_twitter_handle": "",
+      "title": "St. Julian 2013 Reserve Late Harvest Riesling (Lake Michigan Shore)",
+      "variety": "Riesling",
+      "winery": "St. Julian"
+    },
+    {
+      "row_id": "4",
+      "country": "US",
+      "description": "Much like the regular bottling from 2012, this comes across as rather rough and tannic, with rustic, earthy, herbal characteristics. Nonetheless, if you think of it as a pleasantly unfussy country wine, it's a good companion to a hearty winter stew.",
+      "designation": "Vintner's Reserve Wild Child Block",
+      "points": "87",
+      "price": "65.0",
+      "province": "Oregon",
+      "region_1": "Willamette Valley",
+      "region_2": "Willamette Valley",
+      "taster_name": "Paul Gregutt",
+      "taster_twitter_handle": "@paulgwine",
+      "title": "Sweet Cheeks 2012 Vintner's Reserve Wild Child Block Pinot Noir (Willamette Valley)",
+      "variety": "Pinot Noir",
+      "winery": "Sweet Cheeks"
+    }
+  ]
+}
+
+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": "c18",
+  "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=region_2, condition_col=country.",
+  "planned_template_id": "tpl_m4_group_condition_rate",
+  "bindings": {
+    "group_col": "region_2",
+    "condition_col": "country",
+    "condition_value": "Portugal",
+    "positive_value": "US",
+    "negative_value": "Portugal",
+    "top_k": 17,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 56702.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_021918a0c8242b2a/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f9-72e3-7cf1-a039-531595958442"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"region_2\\\",\\n       AVG(CASE WHEN \\\"country\\\" = 'Portugal' THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"c18\\\"\\nGROUP BY \\\"region_2\\\"\\nORDER BY \\\"condition_rate\\\" DESC;\",\"notes\":\"Grouped condition rate by \\\"region_2\\\", measuring the share of rows where \\\"country\\\" is Portugal.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":14909,"cached_input_tokens":13696,"output_tokens":457,"reasoning_output_tokens":357}}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_021918a0c8242b2a/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_m4_group_condition_rate\nSELECT \"region_2\",\n       AVG(CASE WHEN \"country\" = 'Portugal' THEN 1 ELSE 0 END) AS \"condition_rate\"\nFROM \"c18\"\nGROUP BY \"region_2\"\nORDER BY \"condition_rate\" DESC;","notes":"Grouped condition rate by \"region_2\", measuring the share of rows where \"country\" is Portugal."}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_056bac9afcbf36a8/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 10737, "bytes_utf8": 10741, "lines": 267, "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": 715, "bytes_utf8": 715, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15060, "cached_input_tokens": 13696, "output_tokens": 702, "reasoning_output_tokens": 516}}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_056bac9afcbf36a8/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": "c18",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c18_056bac9afcbf36a8",
+    "api_calls": 0,
+    "input_tokens": 15060,
+    "cached_input_tokens": 13696,
+    "output_tokens": 702,
+    "total_tokens": 15762,
+    "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": 25710.0,
+    "sql_execution_elapsed_ms_total": 91.45,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_056bac9afcbf36a8/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_056bac9afcbf36a8/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": "2026-05-19T15:42:22.313433+00:00",
+  "ended_at": "2026-05-19T15:42:48.023462+00:00",
+  "elapsed_ms": 25710.0,
+  "prompt_metrics": {
+    "chars": 10737,
+    "bytes_utf8": 10741,
+    "lines": 267,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 2082,
+    "bytes_utf8": 2082,
+    "lines": 7,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 715,
+      "bytes_utf8": 715,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 15060,
+      "cached_input_tokens": 13696,
+      "output_tokens": 702,
+      "reasoning_output_tokens": 516
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_056bac9afcbf36a8/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,267 @@
+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: c18
+- dataset_name: Wine Reviews
+- table_name: c18
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 13 feature columns and target `country`.
+- task_type: classification
+- target_column: country
+- main_row_count: 129971
+- important_fields:
+- row_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for row id.
+- country: role=target, type=categorical_target. tags=['condition_candidate', 'target_candidate', 'missingness_candidate'] desc=Target field for country.
+- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for description.
+- designation: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for designation.
+- points: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for points.
+- price: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate', 'missingness_candidate'] desc=Numeric field for price.
+- province: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for province.
+- region_1: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for region 1.
+- region_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for region 2.
+- taster_name: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for taster name.
+- taster_twitter_handle: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for taster twitter handle.
+- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title.
+- variety: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for variety.
+- winery: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for winery.
+- useful_field_combinations: [['points', 'price', 'country'], ['points', 'points', 'country']]
+- fields_requiring_caution: ['country', 'description', 'designation', 'price']
+- source_url: https://www.kaggle.com/datasets/zynicide/wine-reviews
+
+SQLite schema snapshot:
+{
+  "table_name": "c18",
+  "quoted_table_name": "\"c18\"",
+  "row_count": 129971,
+  "columns": [
+    {
+      "name": "row_id",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "country",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "description",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "designation",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "points",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "price",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "province",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "region_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "region_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "taster_name",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "taster_twitter_handle",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "title",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "variety",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "winery",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "row_id": "0",
+      "country": "Italy",
+      "description": "Aromas include tropical fruit, broom, brimstone and dried herb. The palate isn't overly expressive, offering unripened apple, citrus and dried sage alongside brisk acidity.",
+      "designation": "Vulkà Bianco",
+      "points": "87",
+      "price": "",
+      "province": "Sicily & Sardinia",
+      "region_1": "Etna",
+      "region_2": "",
+      "taster_name": "Kerin O’Keefe",
+      "taster_twitter_handle": "@kerinokeefe",
+      "title": "Nicosia 2013 Vulkà Bianco  (Etna)",
+      "variety": "White Blend",
+      "winery": "Nicosia"
+    },
+    {
+      "row_id": "1",
+      "country": "Portugal",
+      "description": "This is ripe and fruity, a wine that is smooth while still structured. Firm tannins are filled out with juicy red berry fruits and freshened with acidity. It's  already drinkable, although it will certainly be better from 2016.",
+      "designation": "Avidagos",
+      "points": "87",
+      "price": "15.0",
+      "province": "Douro",
+      "region_1": "",
+      "region_2": "",
+      "taster_name": "Roger Voss",
+      "taster_twitter_handle": "@vossroger",
+      "title": "Quinta dos Avidagos 2011 Avidagos Red (Douro)",
+      "variety": "Portuguese Red",
+      "winery": "Quinta dos Avidagos"
+    },
+    {
+      "row_id": "2",
+      "country": "US",
+      "description": "Tart and snappy, the flavors of lime flesh and rind dominate. Some green pineapple pokes through, with crisp acidity underscoring the flavors. The wine was all stainless-steel fermented.",
+      "designation": "",
+      "points": "87",
+      "price": "14.0",
+      "province": "Oregon",
+      "region_1": "Willamette Valley",
+      "region_2": "Willamette Valley",
+      "taster_name": "Paul Gregutt",
+      "taster_twitter_handle": "@paulgwine",
+      "title": "Rainstorm 2013 Pinot Gris (Willamette Valley)",
+      "variety": "Pinot Gris",
+      "winery": "Rainstorm"
+    },
+    {
+      "row_id": "3",
+      "country": "US",
+      "description": "Pineapple rind, lemon pith and orange blossom start off the aromas. The palate is a bit more opulent, with notes of honey-drizzled guava and mango giving way to a slightly astringent, semidry finish.",
+      "designation": "Reserve Late Harvest",
+      "points": "87",
+      "price": "13.0",
+      "province": "Michigan",
+      "region_1": "Lake Michigan Shore",
+      "region_2": "",
+      "taster_name": "Alexander Peartree",
+      "taster_twitter_handle": "",
+      "title": "St. Julian 2013 Reserve Late Harvest Riesling (Lake Michigan Shore)",
+      "variety": "Riesling",
+      "winery": "St. Julian"
+    },
+    {
+      "row_id": "4",
+      "country": "US",
+      "description": "Much like the regular bottling from 2012, this comes across as rather rough and tannic, with rustic, earthy, herbal characteristics. Nonetheless, if you think of it as a pleasantly unfussy country wine, it's a good companion to a hearty winter stew.",
+      "designation": "Vintner's Reserve Wild Child Block",
+      "points": "87",
+      "price": "65.0",
+      "province": "Oregon",
+      "region_1": "Willamette Valley",
+      "region_2": "Willamette Valley",
+      "taster_name": "Paul Gregutt",
+      "taster_twitter_handle": "@paulgwine",
+      "title": "Sweet Cheeks 2012 Vintner's Reserve Wild Child Block Pinot Noir (Willamette Valley)",
+      "variety": "Pinot Noir",
+      "winery": "Sweet Cheeks"
+    }
+  ]
+}
+
+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": "c18",
+  "question": "Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=taster_twitter_handle, condition_col=country.",
+  "planned_template_id": "tpl_m4_group_ratio_two_conditions",
+  "bindings": {
+    "group_col": "taster_twitter_handle",
+    "condition_col": "country",
+    "condition_value": "US",
+    "positive_value": "US",
+    "negative_value": "Portugal",
+    "top_k": 14,
+    "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": 56702.0,
+    "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_d/c18/artifacts/v2q_c18_056bac9afcbf36a8/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,7 @@
+{"type":"thread.started","thread_id":"019e40e7-056c-71d2-9663-628aa911c1b0"}
+{"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 15695. Please try again in 470ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"error","message":"Reconnecting... 3/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 2000000, Requested 15695. Please try again in 470ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"error","message":"Reconnecting... 4/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1987576, Requested 15695. Please try again in 98ms. 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 \\\"taster_twitter_handle\\\",\\n           SUM(CASE WHEN \\\"country\\\" = 'US' THEN 1 ELSE 0 END) AS numerator_count,\\n           SUM(CASE WHEN \\\"country\\\" = 'Portugal' THEN 1 ELSE 0 END) AS denominator_count\\n    FROM \\\"c18\\\"\\n    GROUP BY \\\"taster_twitter_handle\\\"\\n)\\nSELECT \\\"taster_twitter_handle\\\",\\n       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\",\"notes\":\"Uses the requested grouped ratio template with group_col=\\\"taster_twitter_handle\\\" and condition_col=\\\"country\\\", computing US-to-Portugal row-count ratio per taster Twitter handle.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":15060,"cached_input_tokens":13696,"output_tokens":702,"reasoning_output_tokens":516}}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_056bac9afcbf36a8/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_m4_group_ratio_two_conditions\nWITH grouped AS (\n    SELECT \"taster_twitter_handle\",\n           SUM(CASE WHEN \"country\" = 'US' THEN 1 ELSE 0 END) AS numerator_count,\n           SUM(CASE WHEN \"country\" = 'Portugal' THEN 1 ELSE 0 END) AS denominator_count\n    FROM \"c18\"\n    GROUP BY \"taster_twitter_handle\"\n)\nSELECT \"taster_twitter_handle\",\n       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;","notes":"Uses the requested grouped ratio template with group_col=\"taster_twitter_handle\" and condition_col=\"country\", computing US-to-Portugal row-count ratio per taster Twitter handle."}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_0707b540125b7c00/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 9886, "bytes_utf8": 9890, "lines": 262, "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": 357, "bytes_utf8": 357, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14855, "cached_input_tokens": 12288, "output_tokens": 239, "reasoning_output_tokens": 140}}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_0707b540125b7c00/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": "c18",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c18_0707b540125b7c00",
+    "api_calls": 0,
+    "input_tokens": 14855,
+    "cached_input_tokens": 12288,
+    "output_tokens": 239,
+    "total_tokens": 15094,
+    "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": 7381.63,
+    "sql_execution_elapsed_ms_total": 61.48,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_0707b540125b7c00/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_0707b540125b7c00/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": "2026-05-19T16:04:15.822180+00:00",
+  "ended_at": "2026-05-19T16:04:23.203836+00:00",
+  "elapsed_ms": 7381.63,
+  "prompt_metrics": {
+    "chars": 9886,
+    "bytes_utf8": 9890,
+    "lines": 262,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 714,
+    "bytes_utf8": 714,
+    "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": 357,
+      "bytes_utf8": 357,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 14855,
+      "cached_input_tokens": 12288,
+      "output_tokens": 239,
+      "reasoning_output_tokens": 140
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_0707b540125b7c00/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,262 @@
+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: c18
+- dataset_name: Wine Reviews
+- table_name: c18
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 13 feature columns and target `country`.
+- task_type: classification
+- target_column: country
+- main_row_count: 129971
+- important_fields:
+- row_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for row id.
+- country: role=target, type=categorical_target. tags=['condition_candidate', 'target_candidate', 'missingness_candidate'] desc=Target field for country.
+- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for description.
+- designation: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for designation.
+- points: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for points.
+- price: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate', 'missingness_candidate'] desc=Numeric field for price.
+- province: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for province.
+- region_1: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for region 1.
+- region_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for region 2.
+- taster_name: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for taster name.
+- taster_twitter_handle: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for taster twitter handle.
+- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title.
+- variety: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for variety.
+- winery: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for winery.
+- useful_field_combinations: [['points', 'price', 'country'], ['points', 'points', 'country']]
+- fields_requiring_caution: ['country', 'description', 'designation', 'price']
+- source_url: https://www.kaggle.com/datasets/zynicide/wine-reviews
+
+SQLite schema snapshot:
+{
+  "table_name": "c18",
+  "quoted_table_name": "\"c18\"",
+  "row_count": 129971,
+  "columns": [
+    {
+      "name": "row_id",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "country",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "description",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "designation",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "points",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "price",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "province",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "region_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "region_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "taster_name",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "taster_twitter_handle",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "title",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "variety",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "winery",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "row_id": "0",
+      "country": "Italy",
+      "description": "Aromas include tropical fruit, broom, brimstone and dried herb. The palate isn't overly expressive, offering unripened apple, citrus and dried sage alongside brisk acidity.",
+      "designation": "Vulkà Bianco",
+      "points": "87",
+      "price": "",
+      "province": "Sicily & Sardinia",
+      "region_1": "Etna",
+      "region_2": "",
+      "taster_name": "Kerin O’Keefe",
+      "taster_twitter_handle": "@kerinokeefe",
+      "title": "Nicosia 2013 Vulkà Bianco  (Etna)",
+      "variety": "White Blend",
+      "winery": "Nicosia"
+    },
+    {
+      "row_id": "1",
+      "country": "Portugal",
+      "description": "This is ripe and fruity, a wine that is smooth while still structured. Firm tannins are filled out with juicy red berry fruits and freshened with acidity. It's  already drinkable, although it will certainly be better from 2016.",
+      "designation": "Avidagos",
+      "points": "87",
+      "price": "15.0",
+      "province": "Douro",
+      "region_1": "",
+      "region_2": "",
+      "taster_name": "Roger Voss",
+      "taster_twitter_handle": "@vossroger",
+      "title": "Quinta dos Avidagos 2011 Avidagos Red (Douro)",
+      "variety": "Portuguese Red",
+      "winery": "Quinta dos Avidagos"
+    },
+    {
+      "row_id": "2",
+      "country": "US",
+      "description": "Tart and snappy, the flavors of lime flesh and rind dominate. Some green pineapple pokes through, with crisp acidity underscoring the flavors. The wine was all stainless-steel fermented.",
+      "designation": "",
+      "points": "87",
+      "price": "14.0",
+      "province": "Oregon",
+      "region_1": "Willamette Valley",
+      "region_2": "Willamette Valley",
+      "taster_name": "Paul Gregutt",
+      "taster_twitter_handle": "@paulgwine",
+      "title": "Rainstorm 2013 Pinot Gris (Willamette Valley)",
+      "variety": "Pinot Gris",
+      "winery": "Rainstorm"
+    },
+    {
+      "row_id": "3",
+      "country": "US",
+      "description": "Pineapple rind, lemon pith and orange blossom start off the aromas. The palate is a bit more opulent, with notes of honey-drizzled guava and mango giving way to a slightly astringent, semidry finish.",
+      "designation": "Reserve Late Harvest",
+      "points": "87",
+      "price": "13.0",
+      "province": "Michigan",
+      "region_1": "Lake Michigan Shore",
+      "region_2": "",
+      "taster_name": "Alexander Peartree",
+      "taster_twitter_handle": "",
+      "title": "St. Julian 2013 Reserve Late Harvest Riesling (Lake Michigan Shore)",
+      "variety": "Riesling",
+      "winery": "St. Julian"
+    },
+    {
+      "row_id": "4",
+      "country": "US",
+      "description": "Much like the regular bottling from 2012, this comes across as rather rough and tannic, with rustic, earthy, herbal characteristics. Nonetheless, if you think of it as a pleasantly unfussy country wine, it's a good companion to a hearty winter stew.",
+      "designation": "Vintner's Reserve Wild Child Block",
+      "points": "87",
+      "price": "65.0",
+      "province": "Oregon",
+      "region_1": "Willamette Valley",
+      "region_2": "Willamette Valley",
+      "taster_name": "Paul Gregutt",
+      "taster_twitter_handle": "@paulgwine",
+      "title": "Sweet Cheeks 2012 Vintner's Reserve Wild Child Block Pinot Noir (Willamette Valley)",
+      "variety": "Pinot Noir",
+      "winery": "Sweet Cheeks"
+    }
+  ]
+}
+
+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": "c18",
+  "question": "Use template Low-Support Group Count to probe tail_set_consistency with semantic role count_distribution. Focus on group_col=points.",
+  "planned_template_id": "tpl_tail_low_support_group_count_v2",
+  "bindings": {
+    "group_col": "points",
+    "top_k": 15,
+    "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": 56702.0,
+    "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_d/c18/artifacts/v2q_c18_0707b540125b7c00/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fb-107f-7cd0-8c61-6be84389bf32"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tail_low_support_group_count_v2\\nSELECT\\n    \\\"points\\\",\\n    COUNT(*) AS support\\nFROM \\\"c18\\\"\\nGROUP BY \\\"points\\\"\\nORDER BY support ASC, \\\"points\\\"\\nLIMIT 15;\",\"notes\":\"Instantiated the Low-Support Group Count template with group_col=\\\"points\\\" and top_k=15, using only the single table \\\"c18\\\" and SQLite-compatible syntax.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":14855,"cached_input_tokens":12288,"output_tokens":239,"reasoning_output_tokens":140}}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_0707b540125b7c00/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tail_low_support_group_count_v2\nSELECT\n    \"points\",\n    COUNT(*) AS support\nFROM \"c18\"\nGROUP BY \"points\"\nORDER BY support ASC, \"points\"\nLIMIT 15;","notes":"Instantiated the Low-Support Group Count template with group_col=\"points\" and top_k=15, using only the single table \"c18\" and SQLite-compatible syntax."}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_085778c98281b6b1/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 10065, "bytes_utf8": 10069, "lines": 262, "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": 586, "bytes_utf8": 586, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14900, "cached_input_tokens": 13696, "output_tokens": 554, "reasoning_output_tokens": 382}}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_085778c98281b6b1/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": "c18",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c18_085778c98281b6b1",
+    "api_calls": 0,
+    "input_tokens": 14900,
+    "cached_input_tokens": 13696,
+    "output_tokens": 554,
+    "total_tokens": 15454,
+    "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": 14182.72,
+    "sql_execution_elapsed_ms_total": 212.45,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_085778c98281b6b1/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_085778c98281b6b1/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": "2026-05-19T15:46:26.100771+00:00",
+  "ended_at": "2026-05-19T15:46:40.283533+00:00",
+  "elapsed_ms": 14182.72,
+  "prompt_metrics": {
+    "chars": 10065,
+    "bytes_utf8": 10069,
+    "lines": 262,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 975,
+    "bytes_utf8": 975,
+    "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": 586,
+      "bytes_utf8": 586,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 14900,
+      "cached_input_tokens": 13696,
+      "output_tokens": 554,
+      "reasoning_output_tokens": 382
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_085778c98281b6b1/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,262 @@
+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: c18
+- dataset_name: Wine Reviews
+- table_name: c18
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 13 feature columns and target `country`.
+- task_type: classification
+- target_column: country
+- main_row_count: 129971
+- important_fields:
+- row_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for row id.
+- country: role=target, type=categorical_target. tags=['condition_candidate', 'target_candidate', 'missingness_candidate'] desc=Target field for country.
+- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for description.
+- designation: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for designation.
+- points: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for points.
+- price: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate', 'missingness_candidate'] desc=Numeric field for price.
+- province: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for province.
+- region_1: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for region 1.
+- region_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for region 2.
+- taster_name: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for taster name.
+- taster_twitter_handle: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for taster twitter handle.
+- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title.
+- variety: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for variety.
+- winery: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for winery.
+- useful_field_combinations: [['points', 'price', 'country'], ['points', 'points', 'country']]
+- fields_requiring_caution: ['country', 'description', 'designation', 'price']
+- source_url: https://www.kaggle.com/datasets/zynicide/wine-reviews
+
+SQLite schema snapshot:
+{
+  "table_name": "c18",
+  "quoted_table_name": "\"c18\"",
+  "row_count": 129971,
+  "columns": [
+    {
+      "name": "row_id",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "country",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "description",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "designation",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "points",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "price",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "province",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "region_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "region_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "taster_name",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "taster_twitter_handle",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "title",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "variety",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "winery",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "row_id": "0",
+      "country": "Italy",
+      "description": "Aromas include tropical fruit, broom, brimstone and dried herb. The palate isn't overly expressive, offering unripened apple, citrus and dried sage alongside brisk acidity.",
+      "designation": "Vulkà Bianco",
+      "points": "87",
+      "price": "",
+      "province": "Sicily & Sardinia",
+      "region_1": "Etna",
+      "region_2": "",
+      "taster_name": "Kerin O’Keefe",
+      "taster_twitter_handle": "@kerinokeefe",
+      "title": "Nicosia 2013 Vulkà Bianco  (Etna)",
+      "variety": "White Blend",
+      "winery": "Nicosia"
+    },
+    {
+      "row_id": "1",
+      "country": "Portugal",
+      "description": "This is ripe and fruity, a wine that is smooth while still structured. Firm tannins are filled out with juicy red berry fruits and freshened with acidity. It's  already drinkable, although it will certainly be better from 2016.",
+      "designation": "Avidagos",
+      "points": "87",
+      "price": "15.0",
+      "province": "Douro",
+      "region_1": "",
+      "region_2": "",
+      "taster_name": "Roger Voss",
+      "taster_twitter_handle": "@vossroger",
+      "title": "Quinta dos Avidagos 2011 Avidagos Red (Douro)",
+      "variety": "Portuguese Red",
+      "winery": "Quinta dos Avidagos"
+    },
+    {
+      "row_id": "2",
+      "country": "US",
+      "description": "Tart and snappy, the flavors of lime flesh and rind dominate. Some green pineapple pokes through, with crisp acidity underscoring the flavors. The wine was all stainless-steel fermented.",
+      "designation": "",
+      "points": "87",
+      "price": "14.0",
+      "province": "Oregon",
+      "region_1": "Willamette Valley",
+      "region_2": "Willamette Valley",
+      "taster_name": "Paul Gregutt",
+      "taster_twitter_handle": "@paulgwine",
+      "title": "Rainstorm 2013 Pinot Gris (Willamette Valley)",
+      "variety": "Pinot Gris",
+      "winery": "Rainstorm"
+    },
+    {
+      "row_id": "3",
+      "country": "US",
+      "description": "Pineapple rind, lemon pith and orange blossom start off the aromas. The palate is a bit more opulent, with notes of honey-drizzled guava and mango giving way to a slightly astringent, semidry finish.",
+      "designation": "Reserve Late Harvest",
+      "points": "87",
+      "price": "13.0",
+      "province": "Michigan",
+      "region_1": "Lake Michigan Shore",
+      "region_2": "",
+      "taster_name": "Alexander Peartree",
+      "taster_twitter_handle": "",
+      "title": "St. Julian 2013 Reserve Late Harvest Riesling (Lake Michigan Shore)",
+      "variety": "Riesling",
+      "winery": "St. Julian"
+    },
+    {
+      "row_id": "4",
+      "country": "US",
+      "description": "Much like the regular bottling from 2012, this comes across as rather rough and tannic, with rustic, earthy, herbal characteristics. Nonetheless, if you think of it as a pleasantly unfussy country wine, it's a good companion to a hearty winter stew.",
+      "designation": "Vintner's Reserve Wild Child Block",
+      "points": "87",
+      "price": "65.0",
+      "province": "Oregon",
+      "region_1": "Willamette Valley",
+      "region_2": "Willamette Valley",
+      "taster_name": "Paul Gregutt",
+      "taster_twitter_handle": "@paulgwine",
+      "title": "Sweet Cheeks 2012 Vintner's Reserve Wild Child Block Pinot Noir (Willamette Valley)",
+      "variety": "Pinot Noir",
+      "winery": "Sweet Cheeks"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_quantile_tail_slice",
+    "template_name": "Quantile Tail Slice",
+    "primary_family": "tail_rarity_structure",
+    "portability": "partial",
+    "sql_skeleton": "WITH buckets AS (\n    SELECT {measure_col},\n           NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n    FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;",
+    "required_roles": [
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "c18",
+  "question": "Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=row_id.",
+  "planned_template_id": "tpl_m4_quantile_tail_slice",
+  "bindings": {
+    "measure_col": "row_id",
+    "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": 56702.0,
+    "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 buckets AS (\n    SELECT {measure_col},\n           NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n    FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_085778c98281b6b1/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40ea-bdc1-7140-a07f-3a91085706e7"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_quantile_tail_slice\\nWITH \\\"buckets\\\" AS (\\n    SELECT\\n        \\\"row_id\\\",\\n        NTILE(10) OVER (ORDER BY CAST(\\\"row_id\\\" AS INTEGER) DESC) AS \\\"tail_bucket\\\"\\n    FROM \\\"c18\\\"\\n    WHERE \\\"row_id\\\" IS NOT NULL AND TRIM(\\\"row_id\\\") <> ''\\n)\\nSELECT \\\"row_id\\\"\\nFROM \\\"buckets\\\"\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY CAST(\\\"row_id\\\" AS INTEGER) DESC;\",\"notes\":\"Used the Quantile Tail Slice template with measure_col bound to \\\"row_id\\\" and num_tiles=10. Cast \\\"row_id\\\" to INTEGER for numeric tail ordering because the SQLite schema stores it as TEXT.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":14900,"cached_input_tokens":13696,"output_tokens":554,"reasoning_output_tokens":382}}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_085778c98281b6b1/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_m4_quantile_tail_slice\nWITH \"buckets\" AS (\n    SELECT\n        \"row_id\",\n        NTILE(10) OVER (ORDER BY CAST(\"row_id\" AS INTEGER) DESC) AS \"tail_bucket\"\n    FROM \"c18\"\n    WHERE \"row_id\" IS NOT NULL AND TRIM(\"row_id\") <> ''\n)\nSELECT \"row_id\"\nFROM \"buckets\"\nWHERE \"tail_bucket\" = 1\nORDER BY CAST(\"row_id\" AS INTEGER) DESC;","notes":"Used the Quantile Tail Slice template with measure_col bound to \"row_id\" and num_tiles=10. Cast \"row_id\" to INTEGER for numeric tail ordering because the SQLite schema stores it as TEXT."}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_092c8cc71865a09c/query_results.jsonl

@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_ratio_two_conditions\nWITH grouped AS (\n    SELECT\n        \"region_2\",\n        SUM(CASE WHEN \"country\" = 'US' THEN 1 ELSE 0 END) AS numerator_count,\n        SUM(CASE WHEN \"country\" = 'Portugal' THEN 1 ELSE 0 END) AS denominator_count\n    FROM \"c18\"\n    GROUP BY \"region_2\"\n)\nSELECT\n    \"region_2\",\n    CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC\nLIMIT 12;", "result": "{\"query\": \"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n    SELECT\\n        \\\"region_2\\\",\\n        SUM(CASE WHEN \\\"country\\\" = 'US' THEN 1 ELSE 0 END) AS numerator_count,\\n        SUM(CASE WHEN \\\"country\\\" = 'Portugal' THEN 1 ELSE 0 END) AS denominator_count\\n    FROM \\\"c18\\\"\\n    GROUP BY \\\"region_2\\\"\\n)\\nSELECT\\n    \\\"region_2\\\",\\n    CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC\\nLIMIT 12;\", \"columns\": [\"region_2\", \"condition_ratio\"], \"rows\": [{\"region_2\": \"\", \"condition_ratio\": 0.7016341591987348}, {\"region_2\": \"California Other\", \"condition_ratio\": null}, {\"region_2\": \"Central Coast\", \"condition_ratio\": null}, {\"region_2\": \"Central Valley\", \"condition_ratio\": null}, {\"region_2\": \"Columbia Valley\", \"condition_ratio\": null}, {\"region_2\": \"Finger Lakes\", \"condition_ratio\": null}, {\"region_2\": \"Long Island\", \"condition_ratio\": null}, {\"region_2\": \"Napa\", \"condition_ratio\": null}, {\"region_2\": \"Napa-Sonoma\", \"condition_ratio\": null}, {\"region_2\": \"New York Other\", \"condition_ratio\": null}, {\"region_2\": \"North Coast\", \"condition_ratio\": null}, {\"region_2\": \"Oregon Other\", \"condition_ratio\": null}], \"row_count_returned\": 12, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 89.07}"}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_092c8cc71865a09c/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "c18",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_c18_092c8cc71865a09c",
+  "api_calls": 0,
+  "input_tokens": 15057,
+  "cached_input_tokens": 13696,
+  "output_tokens": 1915,
+  "total_tokens": 16972,
+  "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": 35605.3,
+  "sql_execution_elapsed_ms_total": 89.07,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_092c8cc71865a09c/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_09343ebf8928b7de/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=region_2.
+Result preview: [{"region_2": "", "row_count": 79460}, {"region_2": "Central Coast", "row_count": 11065}, {"region_2": "Sonoma", "row_count": 9028}, {"region_2": "Columbia Valley", "row_count": 8103}, {"region_2": "Napa", "row_count": 6814}]

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_09343ebf8928b7de/generated_sql.sql

@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_d
+-- sql_source_dataset_id: c18
+-- family_id: subgroup_structure
+-- canonical_subitem_id: subgroup_size_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_clickbench_group_count
+-- query_record_id: v2q_c18_09343ebf8928b7de
+-- problem_id: v2p_c18_a5c339c39b45b591
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "region_2", COUNT(*) AS "row_count"
+FROM "c18"
+GROUP BY "region_2"
+ORDER BY "row_count" DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_09343ebf8928b7de/query_results.jsonl

@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_clickbench_group_count\nSELECT \"region_2\", COUNT(*) AS \"row_count\"\nFROM \"c18\"\nGROUP BY \"region_2\"\nORDER BY \"row_count\" DESC;", "result": "{\"query\": \"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"region_2\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"c18\\\"\\nGROUP BY \\\"region_2\\\"\\nORDER BY \\\"row_count\\\" DESC;\", \"columns\": [\"region_2\", \"row_count\"], \"rows\": [{\"region_2\": \"\", \"row_count\": 79460}, {\"region_2\": \"Central Coast\", \"row_count\": 11065}, {\"region_2\": \"Sonoma\", \"row_count\": 9028}, {\"region_2\": \"Columbia Valley\", \"row_count\": 8103}, {\"region_2\": \"Napa\", \"row_count\": 6814}, {\"region_2\": \"Willamette Valley\", \"row_count\": 3423}, {\"region_2\": \"California Other\", \"row_count\": 2663}, {\"region_2\": \"Finger Lakes\", \"row_count\": 1777}, {\"region_2\": \"Sierra Foothills\", \"row_count\": 1462}, {\"region_2\": \"Napa-Sonoma\", \"row_count\": 1169}, {\"region_2\": \"Central Valley\", \"row_count\": 1062}, {\"region_2\": \"Southern Oregon\", \"row_count\": 917}, {\"region_2\": \"Oregon Other\", \"row_count\": 727}, {\"region_2\": \"Long Island\", \"row_count\": 680}, {\"region_2\": \"North Coast\", \"row_count\": 584}, {\"region_2\": \"Washington Other\", \"row_count\": 534}, {\"region_2\": \"South Coast\", \"row_count\": 272}, {\"region_2\": \"New York Other\", \"row_count\": 231}], \"row_count_returned\": 18, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 67.43}"}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_09343ebf8928b7de/run_manifest.json

@@ -0,0 +1,87 @@
+{
+  "run_id": "v2_cli_20260502_081223_d",
+  "dataset_id": "c18",
+  "started_at": "2026-05-19T15:33:47.811167+00:00",
+  "ended_at": "2026-05-19T15:33:59.950737+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c18_09343ebf8928b7de",
+    "problem_id": "v2p_c18_a5c339c39b45b591",
+    "dataset_id": "c18",
+    "template_id": "tpl_clickbench_group_count",
+    "template_name": "Grouped Count by Category",
+    "family_id": "subgroup_structure",
+    "canonical_subitem_id": "subgroup_size_stability",
+    "intended_facet_id": "subgroup_distribution_shift",
+    "variant_semantic_role": "count_distribution",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=region_2.",
+    "bindings": {
+      "group_col": "region_2",
+      "top_k": 12,
+      "top_n": 4,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 25.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;",
+    "notes": [
+      "default_facets=subgroup_distribution_shift",
+      "template_selection_mode=rule",
+      "problem_index_within_template=6",
+      "sql_variant_index=1/1",
+      "binding_index=17"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 2,
+    "problem_index_within_template": 6,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "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_d/c18/sql/v2q_c18_09343ebf8928b7de.sql",
+  "usage_summary": {
+    "dataset_id": "c18",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c18_09343ebf8928b7de",
+    "api_calls": 0,
+    "input_tokens": 14822,
+    "cached_input_tokens": 13696,
+    "output_tokens": 532,
+    "total_tokens": 15354,
+    "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": 12041.21,
+    "sql_execution_elapsed_ms_total": 67.43,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_09343ebf8928b7de/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_09343ebf8928b7de/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:33:59.881516+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": 12041.21, "started_at": "2026-05-19T15:33:47.839422+00:00", "ended_at": "2026-05-19T15:33:59.880669+00:00", "prompt_metrics": {"chars": 9805, "bytes_utf8": 9809, "lines": 262, "estimated_tokens": null}, "response_metrics": {"chars": 327, "bytes_utf8": 327, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14822, "cached_input_tokens": 13696, "output_tokens": 532, "reasoning_output_tokens": 443}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"region_2\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"c18\\\"\\nGROUP BY \\\"region_2\\\"\\nORDER BY \\\"row_count\\\" DESC;\",\"notes\":\"Grouped count distribution over \\\"region_2\\\" using the planned template, with no filters so all values, including empty or NULL entries, are counted.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_09343ebf8928b7de/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "c18",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_c18_09343ebf8928b7de",
+  "api_calls": 0,
+  "input_tokens": 14822,
+  "cached_input_tokens": 13696,
+  "output_tokens": 532,
+  "total_tokens": 15354,
+  "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": 12041.21,
+  "sql_execution_elapsed_ms_total": 67.43,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_09343ebf8928b7de/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_0a33ccd0c47907a7/cli/conversation.jsonl

@@ -0,0 +1,4 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 10064, "bytes_utf8": 10068, "lines": 264, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "status": "failed", "error": "AI CLI command failed with exit code 1: "}
+{"attempt": 2, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_2.txt", "metrics": {"chars": 10064, "bytes_utf8": 10068, "lines": 264, "estimated_tokens": null}}
+{"attempt": 2, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_2.txt", "raw_content_path": "cli/sql_response_attempt_2.raw.txt", "stderr_path": "cli/sql_stderr_attempt_2.txt", "metrics": {"chars": 714, "bytes_utf8": 714, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14881, "cached_input_tokens": 13696, "output_tokens": 2037, "reasoning_output_tokens": 1843}}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_0a33ccd0c47907a7/cli/session_summary.json

@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 2,
+  "usage_summary": {
+    "dataset_id": "c18",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c18_0a33ccd0c47907a7",
+    "api_calls": 0,
+    "input_tokens": 14881,
+    "cached_input_tokens": 13696,
+    "output_tokens": 2037,
+    "total_tokens": 16918,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 2,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 39871.79,
+    "sql_execution_elapsed_ms_total": 93.54,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_0a33ccd0c47907a7/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_0a33ccd0c47907a7/cli/sql_attempt_1.metadata.json

@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:53:44.334845+00:00",
+  "ended_at": "2026-05-19T15:53:47.052915+00:00",
+  "elapsed_ms": 2718.03,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 10064,
+    "bytes_utf8": 10068,
+    "lines": 264,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_0a33ccd0c47907a7/cli/sql_attempt_2.metadata.json

@@ -0,0 +1,45 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:53:48.055606+00:00",
+  "ended_at": "2026-05-19T15:54:25.209415+00:00",
+  "elapsed_ms": 37153.76,
+  "prompt_metrics": {
+    "chars": 10064,
+    "bytes_utf8": 10068,
+    "lines": 264,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1111,
+    "bytes_utf8": 1111,
+    "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": 714,
+      "bytes_utf8": 714,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 14881,
+      "cached_input_tokens": 13696,
+      "output_tokens": 2037,
+      "reasoning_output_tokens": 1843
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_2.txt",
+  "response_path": "cli/sql_response_attempt_2.txt",
+  "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_2.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_0a33ccd0c47907a7/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,264 @@
+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: c18
+- dataset_name: Wine Reviews
+- table_name: c18
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 13 feature columns and target `country`.
+- task_type: classification
+- target_column: country
+- main_row_count: 129971
+- important_fields:
+- row_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for row id.
+- country: role=target, type=categorical_target. tags=['condition_candidate', 'target_candidate', 'missingness_candidate'] desc=Target field for country.
+- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for description.
+- designation: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for designation.
+- points: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for points.
+- price: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate', 'missingness_candidate'] desc=Numeric field for price.
+- province: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for province.
+- region_1: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for region 1.
+- region_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for region 2.
+- taster_name: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for taster name.
+- taster_twitter_handle: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for taster twitter handle.
+- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title.
+- variety: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for variety.
+- winery: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for winery.
+- useful_field_combinations: [['points', 'price', 'country'], ['points', 'points', 'country']]
+- fields_requiring_caution: ['country', 'description', 'designation', 'price']
+- source_url: https://www.kaggle.com/datasets/zynicide/wine-reviews
+
+SQLite schema snapshot:
+{
+  "table_name": "c18",
+  "quoted_table_name": "\"c18\"",
+  "row_count": 129971,
+  "columns": [
+    {
+      "name": "row_id",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "country",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "description",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "designation",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "points",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "price",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "province",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "region_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "region_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "taster_name",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "taster_twitter_handle",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "title",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "variety",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "winery",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "row_id": "0",
+      "country": "Italy",
+      "description": "Aromas include tropical fruit, broom, brimstone and dried herb. The palate isn't overly expressive, offering unripened apple, citrus and dried sage alongside brisk acidity.",
+      "designation": "Vulkà Bianco",
+      "points": "87",
+      "price": "",
+      "province": "Sicily & Sardinia",
+      "region_1": "Etna",
+      "region_2": "",
+      "taster_name": "Kerin O’Keefe",
+      "taster_twitter_handle": "@kerinokeefe",
+      "title": "Nicosia 2013 Vulkà Bianco  (Etna)",
+      "variety": "White Blend",
+      "winery": "Nicosia"
+    },
+    {
+      "row_id": "1",
+      "country": "Portugal",
+      "description": "This is ripe and fruity, a wine that is smooth while still structured. Firm tannins are filled out with juicy red berry fruits and freshened with acidity. It's  already drinkable, although it will certainly be better from 2016.",
+      "designation": "Avidagos",
+      "points": "87",
+      "price": "15.0",
+      "province": "Douro",
+      "region_1": "",
+      "region_2": "",
+      "taster_name": "Roger Voss",
+      "taster_twitter_handle": "@vossroger",
+      "title": "Quinta dos Avidagos 2011 Avidagos Red (Douro)",
+      "variety": "Portuguese Red",
+      "winery": "Quinta dos Avidagos"
+    },
+    {
+      "row_id": "2",
+      "country": "US",
+      "description": "Tart and snappy, the flavors of lime flesh and rind dominate. Some green pineapple pokes through, with crisp acidity underscoring the flavors. The wine was all stainless-steel fermented.",
+      "designation": "",
+      "points": "87",
+      "price": "14.0",
+      "province": "Oregon",
+      "region_1": "Willamette Valley",
+      "region_2": "Willamette Valley",
+      "taster_name": "Paul Gregutt",
+      "taster_twitter_handle": "@paulgwine",
+      "title": "Rainstorm 2013 Pinot Gris (Willamette Valley)",
+      "variety": "Pinot Gris",
+      "winery": "Rainstorm"
+    },
+    {
+      "row_id": "3",
+      "country": "US",
+      "description": "Pineapple rind, lemon pith and orange blossom start off the aromas. The palate is a bit more opulent, with notes of honey-drizzled guava and mango giving way to a slightly astringent, semidry finish.",
+      "designation": "Reserve Late Harvest",
+      "points": "87",
+      "price": "13.0",
+      "province": "Michigan",
+      "region_1": "Lake Michigan Shore",
+      "region_2": "",
+      "taster_name": "Alexander Peartree",
+      "taster_twitter_handle": "",
+      "title": "St. Julian 2013 Reserve Late Harvest Riesling (Lake Michigan Shore)",
+      "variety": "Riesling",
+      "winery": "St. Julian"
+    },
+    {
+      "row_id": "4",
+      "country": "US",
+      "description": "Much like the regular bottling from 2012, this comes across as rather rough and tannic, with rustic, earthy, herbal characteristics. Nonetheless, if you think of it as a pleasantly unfussy country wine, it's a good companion to a hearty winter stew.",
+      "designation": "Vintner's Reserve Wild Child Block",
+      "points": "87",
+      "price": "65.0",
+      "province": "Oregon",
+      "region_1": "Willamette Valley",
+      "region_2": "Willamette Valley",
+      "taster_name": "Paul Gregutt",
+      "taster_twitter_handle": "@paulgwine",
+      "title": "Sweet Cheeks 2012 Vintner's Reserve Wild Child Block Pinot Noir (Willamette Valley)",
+      "variety": "Pinot Noir",
+      "winery": "Sweet Cheeks"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "c18",
+  "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=price, measure_col=price.",
+  "planned_template_id": "tpl_grouped_percentile_point",
+  "bindings": {
+    "group_col": "price",
+    "measure_col": "price",
+    "top_k": 16,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 22.48,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_0a33ccd0c47907a7/cli/sql_prompt_attempt_2.txt

@@ -0,0 +1,264 @@
+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: c18
+- dataset_name: Wine Reviews
+- table_name: c18
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 13 feature columns and target `country`.
+- task_type: classification
+- target_column: country
+- main_row_count: 129971
+- important_fields:
+- row_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for row id.
+- country: role=target, type=categorical_target. tags=['condition_candidate', 'target_candidate', 'missingness_candidate'] desc=Target field for country.
+- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for description.
+- designation: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for designation.
+- points: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for points.
+- price: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate', 'missingness_candidate'] desc=Numeric field for price.
+- province: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate', 'missingness_candidate'] desc=Categorical field for province.
+- region_1: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for region 1.
+- region_2: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for region 2.
+- taster_name: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for taster name.
+- taster_twitter_handle: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for taster twitter handle.
+- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title.
+- variety: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for variety.
+- winery: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for winery.
+- useful_field_combinations: [['points', 'price', 'country'], ['points', 'points', 'country']]
+- fields_requiring_caution: ['country', 'description', 'designation', 'price']
+- source_url: https://www.kaggle.com/datasets/zynicide/wine-reviews
+
+SQLite schema snapshot:
+{
+  "table_name": "c18",
+  "quoted_table_name": "\"c18\"",
+  "row_count": 129971,
+  "columns": [
+    {
+      "name": "row_id",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "country",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "description",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "designation",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "points",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "price",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "province",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "region_1",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "region_2",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "taster_name",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "taster_twitter_handle",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "title",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "variety",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "winery",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "row_id": "0",
+      "country": "Italy",
+      "description": "Aromas include tropical fruit, broom, brimstone and dried herb. The palate isn't overly expressive, offering unripened apple, citrus and dried sage alongside brisk acidity.",
+      "designation": "Vulkà Bianco",
+      "points": "87",
+      "price": "",
+      "province": "Sicily & Sardinia",
+      "region_1": "Etna",
+      "region_2": "",
+      "taster_name": "Kerin O’Keefe",
+      "taster_twitter_handle": "@kerinokeefe",
+      "title": "Nicosia 2013 Vulkà Bianco  (Etna)",
+      "variety": "White Blend",
+      "winery": "Nicosia"
+    },
+    {
+      "row_id": "1",
+      "country": "Portugal",
+      "description": "This is ripe and fruity, a wine that is smooth while still structured. Firm tannins are filled out with juicy red berry fruits and freshened with acidity. It's  already drinkable, although it will certainly be better from 2016.",
+      "designation": "Avidagos",
+      "points": "87",
+      "price": "15.0",
+      "province": "Douro",
+      "region_1": "",
+      "region_2": "",
+      "taster_name": "Roger Voss",
+      "taster_twitter_handle": "@vossroger",
+      "title": "Quinta dos Avidagos 2011 Avidagos Red (Douro)",
+      "variety": "Portuguese Red",
+      "winery": "Quinta dos Avidagos"
+    },
+    {
+      "row_id": "2",
+      "country": "US",
+      "description": "Tart and snappy, the flavors of lime flesh and rind dominate. Some green pineapple pokes through, with crisp acidity underscoring the flavors. The wine was all stainless-steel fermented.",
+      "designation": "",
+      "points": "87",
+      "price": "14.0",
+      "province": "Oregon",
+      "region_1": "Willamette Valley",
+      "region_2": "Willamette Valley",
+      "taster_name": "Paul Gregutt",
+      "taster_twitter_handle": "@paulgwine",
+      "title": "Rainstorm 2013 Pinot Gris (Willamette Valley)",
+      "variety": "Pinot Gris",
+      "winery": "Rainstorm"
+    },
+    {
+      "row_id": "3",
+      "country": "US",
+      "description": "Pineapple rind, lemon pith and orange blossom start off the aromas. The palate is a bit more opulent, with notes of honey-drizzled guava and mango giving way to a slightly astringent, semidry finish.",
+      "designation": "Reserve Late Harvest",
+      "points": "87",
+      "price": "13.0",
+      "province": "Michigan",
+      "region_1": "Lake Michigan Shore",
+      "region_2": "",
+      "taster_name": "Alexander Peartree",
+      "taster_twitter_handle": "",
+      "title": "St. Julian 2013 Reserve Late Harvest Riesling (Lake Michigan Shore)",
+      "variety": "Riesling",
+      "winery": "St. Julian"
+    },
+    {
+      "row_id": "4",
+      "country": "US",
+      "description": "Much like the regular bottling from 2012, this comes across as rather rough and tannic, with rustic, earthy, herbal characteristics. Nonetheless, if you think of it as a pleasantly unfussy country wine, it's a good companion to a hearty winter stew.",
+      "designation": "Vintner's Reserve Wild Child Block",
+      "points": "87",
+      "price": "65.0",
+      "province": "Oregon",
+      "region_1": "Willamette Valley",
+      "region_2": "Willamette Valley",
+      "taster_name": "Paul Gregutt",
+      "taster_twitter_handle": "@paulgwine",
+      "title": "Sweet Cheeks 2012 Vintner's Reserve Wild Child Block Pinot Noir (Willamette Valley)",
+      "variety": "Pinot Noir",
+      "winery": "Sweet Cheeks"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "c18",
+  "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=price, measure_col=price.",
+  "planned_template_id": "tpl_grouped_percentile_point",
+  "bindings": {
+    "group_col": "price",
+    "measure_col": "price",
+    "top_k": 16,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 22.48,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_0a33ccd0c47907a7/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f1-6d9f-7773-9b0d-252d1c506964"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_0a33ccd0c47907a7/cli/sql_response_attempt_1.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f1-6d9f-7773-9b0d-252d1c506964"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_0a33ccd0c47907a7/cli/sql_response_attempt_2.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f1-7c25-7ff2-aa4c-4152719518d2"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"base\\\" AS (\\n  SELECT CAST(\\\"price\\\" AS REAL) AS \\\"price_value\\\"\\n  FROM \\\"c18\\\"\\n  WHERE NULLIF(\\\"price\\\", '') IS NOT NULL\\n)\\nSELECT\\n  \\\"price_value\\\" AS \\\"price\\\",\\n  \\\"price_value\\\" AS \\\"percentile_measure\\\"\\nFROM \\\"base\\\"\\nGROUP BY \\\"price_value\\\"\\nHAVING COUNT(*) >= 5\\nORDER BY \\\"percentile_measure\\\" DESC\\nLIMIT 16;\",\"notes\":\"SQLite does not support PERCENTILE_CONT, and with group_col=\\\"price\\\" and measure_col=\\\"price\\\", the grouped 90th-percentile value is the price itself for each group. The query casts TEXT prices to REAL, excludes blank prices, applies the provided minimum group size of 5, and returns the top 16 ranked price groups.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":14881,"cached_input_tokens":13696,"output_tokens":2037,"reasoning_output_tokens":1843}}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_0a33ccd0c47907a7/cli/sql_response_attempt_2.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_grouped_percentile_point\nWITH \"base\" AS (\n  SELECT CAST(\"price\" AS REAL) AS \"price_value\"\n  FROM \"c18\"\n  WHERE NULLIF(\"price\", '') IS NOT NULL\n)\nSELECT\n  \"price_value\" AS \"price\",\n  \"price_value\" AS \"percentile_measure\"\nFROM \"base\"\nGROUP BY \"price_value\"\nHAVING COUNT(*) >= 5\nORDER BY \"percentile_measure\" DESC\nLIMIT 16;","notes":"SQLite does not support PERCENTILE_CONT, and with group_col=\"price\" and measure_col=\"price\", the grouped 90th-percentile value is the price itself for each group. The query casts TEXT prices to REAL, excludes blank prices, applies the provided minimum group size of 5, and returns the top 16 ranked price groups."}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_0d91f8cc08721aeb/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 10289, "bytes_utf8": 10293, "lines": 266, "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": 772, "bytes_utf8": 772, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14960, "cached_input_tokens": 12032, "output_tokens": 1104, "reasoning_output_tokens": 893}}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_0d91f8cc08721aeb/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": "c18",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c18_0d91f8cc08721aeb",
+    "api_calls": 0,
+    "input_tokens": 14960,
+    "cached_input_tokens": 12032,
+    "output_tokens": 1104,
+    "total_tokens": 16064,
+    "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": 20174.05,
+    "sql_execution_elapsed_ms_total": 106.14,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c18/artifacts/v2q_c18_0d91f8cc08721aeb/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}