Add files using upload-large-folder tool

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_016279e05b0beb15/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Low-Support Group Count to probe tail_set_consistency with semantic role rare_extreme_view. Focus on group_col=persons.
+Result preview: [{"persons": "2", "support": 576}, {"persons": "4", "support": 576}, {"persons": "more", "support": 576}]

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_016279e05b0beb15/generated_sql.sql

@@ -0,0 +1,20 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_f
+-- sql_source_dataset_id: c2
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_set_consistency
+-- intended_facet_id: low_support_extremes
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_tail_low_support_group_count_v2
+-- query_record_id: v2q_c2_016279e05b0beb15
+-- problem_id: v2p_c2_1f52db85db0ce714
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+    "persons",
+    COUNT(*) AS "support"
+FROM "c2"
+GROUP BY "persons"
+ORDER BY "support" ASC, "persons"
+LIMIT 11;

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_016279e05b0beb15/query_results.jsonl

@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tail_low_support_group_count_v2\nSELECT\n    \"persons\",\n    COUNT(*) AS \"support\"\nFROM \"c2\"\nGROUP BY \"persons\"\nORDER BY \"support\" ASC, \"persons\"\nLIMIT 11;", "result": "{\"query\": \"-- template_id: tpl_tail_low_support_group_count_v2\\nSELECT\\n    \\\"persons\\\",\\n    COUNT(*) AS \\\"support\\\"\\nFROM \\\"c2\\\"\\nGROUP BY \\\"persons\\\"\\nORDER BY \\\"support\\\" ASC, \\\"persons\\\"\\nLIMIT 11;\", \"columns\": [\"persons\", \"support\"], \"rows\": [{\"persons\": \"2\", \"support\": 576}, {\"persons\": \"4\", \"support\": 576}, {\"persons\": \"more\", \"support\": 576}], \"row_count_returned\": 3, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 1.72}"}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_016279e05b0beb15/run_manifest.json

@@ -0,0 +1,87 @@
+{
+  "run_id": "v2_cli_20260502_081223_f",
+  "dataset_id": "c2",
+  "started_at": "2026-05-19T15:02:36.695769+00:00",
+  "ended_at": "2026-05-19T15:02:44.654441+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c2_016279e05b0beb15",
+    "problem_id": "v2p_c2_1f52db85db0ce714",
+    "dataset_id": "c2",
+    "template_id": "tpl_tail_low_support_group_count_v2",
+    "template_name": "Low-Support Group Count",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_set_consistency",
+    "intended_facet_id": "low_support_extremes",
+    "variant_semantic_role": "rare_extreme_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Low-Support Group Count to probe tail_set_consistency with semantic role rare_extreme_view. Focus on group_col=persons.",
+    "bindings": {
+      "group_col": "persons",
+      "top_k": 11,
+      "top_n": 5,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 0.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col"
+    ],
+    "coverage_target_min": "5",
+    "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};",
+    "notes": [
+      "default_facets=low_support_extremes",
+      "template_selection_mode=rule",
+      "problem_index_within_template=7",
+      "sql_variant_index=1/2",
+      "binding_index=66"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 6,
+    "problem_index_within_template": 7,
+    "sql_variant_index": 1,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_f/c2/sql/v2q_c2_016279e05b0beb15.sql",
+  "usage_summary": {
+    "dataset_id": "c2",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c2_016279e05b0beb15",
+    "api_calls": 0,
+    "input_tokens": 13699,
+    "cached_input_tokens": 12672,
+    "output_tokens": 270,
+    "total_tokens": 13969,
+    "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": 7952.52,
+    "sql_execution_elapsed_ms_total": 1.72,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_016279e05b0beb15/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_016279e05b0beb15/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:02:44.650552+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": 7952.52, "started_at": "2026-05-19T15:02:36.696628+00:00", "ended_at": "2026-05-19T15:02:44.649182+00:00", "prompt_metrics": {"chars": 5653, "bytes_utf8": 5653, "lines": 178, "estimated_tokens": null}, "response_metrics": {"chars": 355, "bytes_utf8": 355, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13699, "cached_input_tokens": 12672, "output_tokens": 270, "reasoning_output_tokens": 173}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tail_low_support_group_count_v2\\nSELECT\\n    \\\"persons\\\",\\n    COUNT(*) AS \\\"support\\\"\\nFROM \\\"c2\\\"\\nGROUP BY \\\"persons\\\"\\nORDER BY \\\"support\\\" ASC, \\\"persons\\\"\\nLIMIT 11;\",\"notes\":\"Implements the Low-Support Group Count template using \\\"persons\\\" as the grouping column and returns up to 11 groups with the smallest support.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_016279e05b0beb15/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "c2",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_c2_016279e05b0beb15",
+  "api_calls": 0,
+  "input_tokens": 13699,
+  "cached_input_tokens": 12672,
+  "output_tokens": 270,
+  "total_tokens": 13969,
+  "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": 7952.52,
+  "sql_execution_elapsed_ms_total": 1.72,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_016279e05b0beb15/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_02b69913d3879aa5/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Filtered Two-Dimensional Group Count to probe slice_level_consistency with semantic role count_distribution. Focus on group_col=doors, group_col_2=lug_boot.
+Result preview: [{"doors": "2", "lug_boot": "big", "row_count": 48}, {"doors": "2", "lug_boot": "med", "row_count": 48}, {"doors": "2", "lug_boot": "small", "row_count": 48}, {"doors": "3", "lug_boot": "big", "row_count": 48}, {"doors": "3", "lug_boot": "med", "row_count": 48}]

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_02b69913d3879aa5/generated_sql.sql

@@ -0,0 +1,18 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_f
+-- sql_source_dataset_id: c2
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: slice_level_consistency
+-- intended_facet_id: conditional_interaction_hotspots
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_c2_filtered_group_count_2d
+-- query_record_id: v2q_c2_02b69913d3879aa5
+-- problem_id: v2p_c2_b6237a1fb55c3038
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "doors", "lug_boot", COUNT(*) AS "row_count"
+FROM "c2"
+WHERE "safety" = 'high'
+GROUP BY "doors", "lug_boot"
+ORDER BY "row_count" DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_02b69913d3879aa5/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_c2_filtered_group_count_2d\nSELECT \"doors\", \"lug_boot\", COUNT(*) AS \"row_count\"\nFROM \"c2\"\nWHERE \"safety\" = 'high'\nGROUP BY \"doors\", \"lug_boot\"\nORDER BY \"row_count\" DESC;", "result": "{\"query\": \"-- template_id: tpl_c2_filtered_group_count_2d\\nSELECT \\\"doors\\\", \\\"lug_boot\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"c2\\\"\\nWHERE \\\"safety\\\" = 'high'\\nGROUP BY \\\"doors\\\", \\\"lug_boot\\\"\\nORDER BY \\\"row_count\\\" DESC;\", \"columns\": [\"doors\", \"lug_boot\", \"row_count\"], \"rows\": [{\"doors\": \"2\", \"lug_boot\": \"big\", \"row_count\": 48}, {\"doors\": \"2\", \"lug_boot\": \"med\", \"row_count\": 48}, {\"doors\": \"2\", \"lug_boot\": \"small\", \"row_count\": 48}, {\"doors\": \"3\", \"lug_boot\": \"big\", \"row_count\": 48}, {\"doors\": \"3\", \"lug_boot\": \"med\", \"row_count\": 48}, {\"doors\": \"3\", \"lug_boot\": \"small\", \"row_count\": 48}, {\"doors\": \"4\", \"lug_boot\": \"big\", \"row_count\": 48}, {\"doors\": \"4\", \"lug_boot\": \"med\", \"row_count\": 48}, {\"doors\": \"4\", \"lug_boot\": \"small\", \"row_count\": 48}, {\"doors\": \"5more\", \"lug_boot\": \"big\", \"row_count\": 48}, {\"doors\": \"5more\", \"lug_boot\": \"med\", \"row_count\": 48}, {\"doors\": \"5more\", \"lug_boot\": \"small\", \"row_count\": 48}], \"row_count_returned\": 12, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 1.08}"}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_02b69913d3879aa5/run_manifest.json

@@ -0,0 +1,93 @@
+{
+  "run_id": "v2_cli_20260502_081223_f",
+  "dataset_id": "c2",
+  "started_at": "2026-05-19T15:00:25.965855+00:00",
+  "ended_at": "2026-05-19T15:00:35.735765+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c2_02b69913d3879aa5",
+    "problem_id": "v2p_c2_b6237a1fb55c3038",
+    "dataset_id": "c2",
+    "template_id": "tpl_c2_filtered_group_count_2d",
+    "template_name": "Filtered Two-Dimensional Group Count",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "slice_level_consistency",
+    "intended_facet_id": "conditional_interaction_hotspots",
+    "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 Filtered Two-Dimensional Group Count to probe slice_level_consistency with semantic role count_distribution. Focus on group_col=doors, group_col_2=lug_boot.",
+    "bindings": {
+      "group_col": "doors",
+      "group_col_2": "lug_boot",
+      "predicate_col": "safety",
+      "predicate_op": "=",
+      "predicate_value": "high",
+      "top_k": 14,
+      "top_n": 5,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 0.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "group_col_2",
+      "predicate_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;",
+    "notes": [
+      "default_facets=conditional_interaction_hotspots",
+      "template_selection_mode=rule",
+      "problem_index_within_template=7",
+      "sql_variant_index=1/1",
+      "binding_index=54"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 5,
+    "problem_index_within_template": 7,
+    "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_f/c2/sql/v2q_c2_02b69913d3879aa5.sql",
+  "usage_summary": {
+    "dataset_id": "c2",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c2_02b69913d3879aa5",
+    "api_calls": 0,
+    "input_tokens": 13780,
+    "cached_input_tokens": 12672,
+    "output_tokens": 359,
+    "total_tokens": 14139,
+    "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": 9764.14,
+    "sql_execution_elapsed_ms_total": 1.08,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_02b69913d3879aa5/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_02b69913d3879aa5/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:00:35.732935+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": 9764.14, "started_at": "2026-05-19T15:00:25.967757+00:00", "ended_at": "2026-05-19T15:00:35.731932+00:00", "prompt_metrics": {"chars": 5970, "bytes_utf8": 5970, "lines": 184, "estimated_tokens": null}, "response_metrics": {"chars": 352, "bytes_utf8": 352, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13780, "cached_input_tokens": 12672, "output_tokens": 359, "reasoning_output_tokens": 252}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_c2_filtered_group_count_2d\\nSELECT \\\"doors\\\", \\\"lug_boot\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"c2\\\"\\nWHERE \\\"safety\\\" = 'high'\\nGROUP BY \\\"doors\\\", \\\"lug_boot\\\"\\nORDER BY \\\"row_count\\\" DESC;\",\"notes\":\"Uses the planned template with \\\"doors\\\" and \\\"lug_boot\\\" as grouping columns, filtered to rows where \\\"safety\\\" = 'high'.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_02b69913d3879aa5/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "c2",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_c2_02b69913d3879aa5",
+  "api_calls": 0,
+  "input_tokens": 13780,
+  "cached_input_tokens": 12672,
+  "output_tokens": 359,
+  "total_tokens": 14139,
+  "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": 9764.14,
+  "sql_execution_elapsed_ms_total": 1.08,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_02b69913d3879aa5/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_02decc38441289c5/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 5989, "bytes_utf8": 5989, "lines": 184, "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": 475, "bytes_utf8": 475, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13769, "cached_input_tokens": 12672, "output_tokens": 367, "reasoning_output_tokens": 243}}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_02decc38441289c5/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": "c2",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c2_02decc38441289c5",
+    "api_calls": 0,
+    "input_tokens": 13769,
+    "cached_input_tokens": 12672,
+    "output_tokens": 367,
+    "total_tokens": 14136,
+    "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": 9177.2,
+    "sql_execution_elapsed_ms_total": 1.09,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_02decc38441289c5/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_02decc38441289c5/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": "2026-05-19T15:17:53.692588+00:00",
+  "ended_at": "2026-05-19T15:18:02.869823+00:00",
+  "elapsed_ms": 9177.2,
+  "prompt_metrics": {
+    "chars": 5989,
+    "bytes_utf8": 5989,
+    "lines": 184,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 839,
+    "bytes_utf8": 839,
+    "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": 475,
+      "bytes_utf8": 475,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 13769,
+      "cached_input_tokens": 12672,
+      "output_tokens": 367,
+      "reasoning_output_tokens": 243
+    }
+  },
+  "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_f/c2/artifacts/v2q_c2_02decc38441289c5/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,184 @@
+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: c2
+- dataset_name: Car Evaluation
+- table_name: c2
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one car configuration described by six ordinal categorical attributes.
+- task_type: classification
+- target_column: class
+- main_row_count: 1728
+- important_fields:
+- buying: role=feature, type=categorical_ordinal. ordered=['low', 'med', 'high', 'vhigh'] tags=['condition_candidate', 'subgroup_candidate'] desc=Buying price category.
+- maint: role=feature, type=categorical_ordinal. ordered=['low', 'med', 'high', 'vhigh'] tags=['condition_candidate', 'subgroup_candidate'] desc=Maintenance cost category.
+- doors: role=feature, type=categorical_ordinal_count_like. ordered=['2', '3', '4', '5more'] tags=['condition_candidate', 'subgroup_candidate'] desc=Number of doors (count-like ordinal category).
+- persons: role=feature, type=categorical_ordinal_count_like. ordered=['2', '4', 'more'] tags=['condition_candidate', 'subgroup_candidate'] desc=Passenger capacity category (count-like).
+- lug_boot: role=feature, type=categorical_ordinal. ordered=['small', 'med', 'big'] tags=['condition_candidate', 'subgroup_candidate'] desc=Luggage boot size category.
+- safety: role=feature, type=categorical_ordinal. ordered=['low', 'med', 'high'] tags=['condition_candidate', 'subgroup_candidate'] desc=Safety rating category.
+- class: role=target, type=categorical_ordinal_target. ordered=['unacc', 'acc', 'good', 'vgood'] tags=['target_candidate'] desc=Car acceptability class label.
+- useful_field_combinations: [['safety', 'persons', 'class'], ['buying', 'maint', 'class'], ['lug_boot', 'safety', 'class']]
+- fields_requiring_caution: ['class', 'doors', 'persons']
+- source_url: https://archive.ics.uci.edu/dataset/19/car+evaluation
+
+SQLite schema snapshot:
+{
+  "table_name": "c2",
+  "quoted_table_name": "\"c2\"",
+  "row_count": 1728,
+  "columns": [
+    {
+      "name": "buying",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "maint",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "doors",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "persons",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "lug_boot",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "safety",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "class",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "buying": "vhigh",
+      "maint": "vhigh",
+      "doors": "2",
+      "persons": "2",
+      "lug_boot": "small",
+      "safety": "low",
+      "class": "unacc"
+    },
+    {
+      "buying": "vhigh",
+      "maint": "vhigh",
+      "doors": "2",
+      "persons": "2",
+      "lug_boot": "small",
+      "safety": "med",
+      "class": "unacc"
+    },
+    {
+      "buying": "vhigh",
+      "maint": "vhigh",
+      "doors": "2",
+      "persons": "2",
+      "lug_boot": "small",
+      "safety": "high",
+      "class": "unacc"
+    },
+    {
+      "buying": "vhigh",
+      "maint": "vhigh",
+      "doors": "2",
+      "persons": "2",
+      "lug_boot": "med",
+      "safety": "low",
+      "class": "unacc"
+    },
+    {
+      "buying": "vhigh",
+      "maint": "vhigh",
+      "doors": "2",
+      "persons": "2",
+      "lug_boot": "med",
+      "safety": "med",
+      "class": "unacc"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_clickbench_filtered_distinct_topk",
+    "template_name": "Filtered Top-k Distinct Coverage",
+    "primary_family": "subgroup_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT {group_col}, COUNT(DISTINCT {entity_col}) AS distinct_entities\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}\nORDER BY distinct_entities DESC\nLIMIT {top_k};",
+    "required_roles": [
+      "group_col",
+      "entity_col",
+      "predicate_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "c2",
+  "question": "Use template Filtered Top-k Distinct Coverage to probe internal_profile_stability with semantic role ranked_signal_view. Focus on group_col=buying.",
+  "planned_template_id": "tpl_clickbench_filtered_distinct_topk",
+  "bindings": {
+    "group_col": "buying",
+    "predicate_col": "lug_boot",
+    "predicate_op": "=",
+    "predicate_value": "big",
+    "entity_col": "buying",
+    "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": 0.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, COUNT(DISTINCT {entity_col}) AS distinct_entities\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}\nORDER BY distinct_entities DESC\nLIMIT {top_k};"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_02decc38441289c5/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40d0-9c98-7813-8c13-506085c31b5a"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_clickbench_filtered_distinct_topk\\nSELECT \\\"buying\\\", COUNT(DISTINCT \\\"buying\\\") AS \\\"distinct_entities\\\"\\nFROM \\\"c2\\\"\\nWHERE \\\"lug_boot\\\" = 'big'\\nGROUP BY \\\"buying\\\"\\nORDER BY \\\"distinct_entities\\\" DESC\\nLIMIT 15;\",\"notes\":\"Used the provided template and bindings exactly. Because both group_col and entity_col are bound to \\\"buying\\\", each returned group's distinct count will be 1 whenever that buying category appears with lug_boot = 'big'.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":13769,"cached_input_tokens":12672,"output_tokens":367,"reasoning_output_tokens":243}}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_02decc38441289c5/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_clickbench_filtered_distinct_topk\nSELECT \"buying\", COUNT(DISTINCT \"buying\") AS \"distinct_entities\"\nFROM \"c2\"\nWHERE \"lug_boot\" = 'big'\nGROUP BY \"buying\"\nORDER BY \"distinct_entities\" DESC\nLIMIT 15;","notes":"Used the provided template and bindings exactly. Because both group_col and entity_col are bound to \"buying\", each returned group's distinct count will be 1 whenever that buying category appears with lug_boot = 'big'."}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_034415e85fd9f3c3/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 5845, "bytes_utf8": 5845, "lines": 182, "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": 442, "bytes_utf8": 442, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13736, "cached_input_tokens": 0, "output_tokens": 293, "reasoning_output_tokens": 175}}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_034415e85fd9f3c3/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": "c2",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c2_034415e85fd9f3c3",
+    "api_calls": 0,
+    "input_tokens": 13736,
+    "cached_input_tokens": 0,
+    "output_tokens": 293,
+    "total_tokens": 14029,
+    "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": 9296.46,
+    "sql_execution_elapsed_ms_total": 0.71,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_034415e85fd9f3c3/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_034415e85fd9f3c3/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": "2026-05-19T15:12:34.913688+00:00",
+  "ended_at": "2026-05-19T15:12:44.210176+00:00",
+  "elapsed_ms": 9296.46,
+  "prompt_metrics": {
+    "chars": 5845,
+    "bytes_utf8": 5845,
+    "lines": 182,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 794,
+    "bytes_utf8": 794,
+    "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": 442,
+      "bytes_utf8": 442,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 13736,
+      "cached_input_tokens": 0,
+      "output_tokens": 293,
+      "reasoning_output_tokens": 175
+    }
+  },
+  "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_f/c2/artifacts/v2q_c2_034415e85fd9f3c3/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,182 @@
+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: c2
+- dataset_name: Car Evaluation
+- table_name: c2
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one car configuration described by six ordinal categorical attributes.
+- task_type: classification
+- target_column: class
+- main_row_count: 1728
+- important_fields:
+- buying: role=feature, type=categorical_ordinal. ordered=['low', 'med', 'high', 'vhigh'] tags=['condition_candidate', 'subgroup_candidate'] desc=Buying price category.
+- maint: role=feature, type=categorical_ordinal. ordered=['low', 'med', 'high', 'vhigh'] tags=['condition_candidate', 'subgroup_candidate'] desc=Maintenance cost category.
+- doors: role=feature, type=categorical_ordinal_count_like. ordered=['2', '3', '4', '5more'] tags=['condition_candidate', 'subgroup_candidate'] desc=Number of doors (count-like ordinal category).
+- persons: role=feature, type=categorical_ordinal_count_like. ordered=['2', '4', 'more'] tags=['condition_candidate', 'subgroup_candidate'] desc=Passenger capacity category (count-like).
+- lug_boot: role=feature, type=categorical_ordinal. ordered=['small', 'med', 'big'] tags=['condition_candidate', 'subgroup_candidate'] desc=Luggage boot size category.
+- safety: role=feature, type=categorical_ordinal. ordered=['low', 'med', 'high'] tags=['condition_candidate', 'subgroup_candidate'] desc=Safety rating category.
+- class: role=target, type=categorical_ordinal_target. ordered=['unacc', 'acc', 'good', 'vgood'] tags=['target_candidate'] desc=Car acceptability class label.
+- useful_field_combinations: [['safety', 'persons', 'class'], ['buying', 'maint', 'class'], ['lug_boot', 'safety', 'class']]
+- fields_requiring_caution: ['class', 'doors', 'persons']
+- source_url: https://archive.ics.uci.edu/dataset/19/car+evaluation
+
+SQLite schema snapshot:
+{
+  "table_name": "c2",
+  "quoted_table_name": "\"c2\"",
+  "row_count": 1728,
+  "columns": [
+    {
+      "name": "buying",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "maint",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "doors",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "persons",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "lug_boot",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "safety",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "class",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "buying": "vhigh",
+      "maint": "vhigh",
+      "doors": "2",
+      "persons": "2",
+      "lug_boot": "small",
+      "safety": "low",
+      "class": "unacc"
+    },
+    {
+      "buying": "vhigh",
+      "maint": "vhigh",
+      "doors": "2",
+      "persons": "2",
+      "lug_boot": "small",
+      "safety": "med",
+      "class": "unacc"
+    },
+    {
+      "buying": "vhigh",
+      "maint": "vhigh",
+      "doors": "2",
+      "persons": "2",
+      "lug_boot": "small",
+      "safety": "high",
+      "class": "unacc"
+    },
+    {
+      "buying": "vhigh",
+      "maint": "vhigh",
+      "doors": "2",
+      "persons": "2",
+      "lug_boot": "med",
+      "safety": "low",
+      "class": "unacc"
+    },
+    {
+      "buying": "vhigh",
+      "maint": "vhigh",
+      "doors": "2",
+      "persons": "2",
+      "lug_boot": "med",
+      "safety": "med",
+      "class": "unacc"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_clickbench_filtered_topk_group_count",
+    "template_name": "Filtered Top-k Group Count",
+    "primary_family": "subgroup_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col}, COUNT(*) AS support\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}\nORDER BY support DESC\nLIMIT {top_k};",
+    "required_roles": [
+      "group_col",
+      "predicate_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "c2",
+  "question": "Use template Filtered Top-k Group Count to probe subgroup_size_stability with semantic role filtered_stable_view. Focus on group_col=class.",
+  "planned_template_id": "tpl_clickbench_filtered_topk_group_count",
+  "bindings": {
+    "group_col": "class",
+    "predicate_col": "class",
+    "predicate_op": "=",
+    "predicate_value": "vgood",
+    "top_k": 11,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 0.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, COUNT(*) AS support\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}\nORDER BY support DESC\nLIMIT {top_k};"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_034415e85fd9f3c3/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40cb-bf68-7763-af48-0ecdf0e2c450"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_clickbench_filtered_topk_group_count\\nSELECT \\\"class\\\", COUNT(*) AS support\\nFROM \\\"c2\\\"\\nWHERE \\\"class\\\" = 'vgood'\\nGROUP BY \\\"class\\\"\\nORDER BY support DESC\\nLIMIT 11;\",\"notes\":\"Applied the provided Filtered Top-k Group Count template with group_col=\\\"class\\\" and predicate_col=\\\"class\\\" fixed to 'vgood'. Because the filter and grouping use the same column, the result will contain at most one group: 'vgood'.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":13736,"cached_input_tokens":0,"output_tokens":293,"reasoning_output_tokens":175}}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_034415e85fd9f3c3/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_clickbench_filtered_topk_group_count\nSELECT \"class\", COUNT(*) AS support\nFROM \"c2\"\nWHERE \"class\" = 'vgood'\nGROUP BY \"class\"\nORDER BY support DESC\nLIMIT 11;","notes":"Applied the provided Filtered Top-k Group Count template with group_col=\"class\" and predicate_col=\"class\" fixed to 'vgood'. Because the filter and grouping use the same column, the result will contain at most one group: 'vgood'."}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_040cd7db47ae0614/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 5962, "bytes_utf8": 5962, "lines": 183, "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": 382, "bytes_utf8": 382, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13789, "cached_input_tokens": 12672, "output_tokens": 433, "reasoning_output_tokens": 319}}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_040cd7db47ae0614/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": "c2",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c2_040cd7db47ae0614",
+    "api_calls": 0,
+    "input_tokens": 13789,
+    "cached_input_tokens": 12672,
+    "output_tokens": 433,
+    "total_tokens": 14222,
+    "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": 13061.09,
+    "sql_execution_elapsed_ms_total": 1.47,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_040cd7db47ae0614/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_040cd7db47ae0614/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": "2026-05-19T15:08:18.986142+00:00",
+  "ended_at": "2026-05-19T15:08:32.047271+00:00",
+  "elapsed_ms": 13061.09,
+  "prompt_metrics": {
+    "chars": 5962,
+    "bytes_utf8": 5962,
+    "lines": 183,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 745,
+    "bytes_utf8": 745,
+    "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": 382,
+      "bytes_utf8": 382,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 13789,
+      "cached_input_tokens": 12672,
+      "output_tokens": 433,
+      "reasoning_output_tokens": 319
+    }
+  },
+  "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_f/c2/artifacts/v2q_c2_040cd7db47ae0614/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,183 @@
+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: c2
+- dataset_name: Car Evaluation
+- table_name: c2
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one car configuration described by six ordinal categorical attributes.
+- task_type: classification
+- target_column: class
+- main_row_count: 1728
+- important_fields:
+- buying: role=feature, type=categorical_ordinal. ordered=['low', 'med', 'high', 'vhigh'] tags=['condition_candidate', 'subgroup_candidate'] desc=Buying price category.
+- maint: role=feature, type=categorical_ordinal. ordered=['low', 'med', 'high', 'vhigh'] tags=['condition_candidate', 'subgroup_candidate'] desc=Maintenance cost category.
+- doors: role=feature, type=categorical_ordinal_count_like. ordered=['2', '3', '4', '5more'] tags=['condition_candidate', 'subgroup_candidate'] desc=Number of doors (count-like ordinal category).
+- persons: role=feature, type=categorical_ordinal_count_like. ordered=['2', '4', 'more'] tags=['condition_candidate', 'subgroup_candidate'] desc=Passenger capacity category (count-like).
+- lug_boot: role=feature, type=categorical_ordinal. ordered=['small', 'med', 'big'] tags=['condition_candidate', 'subgroup_candidate'] desc=Luggage boot size category.
+- safety: role=feature, type=categorical_ordinal. ordered=['low', 'med', 'high'] tags=['condition_candidate', 'subgroup_candidate'] desc=Safety rating category.
+- class: role=target, type=categorical_ordinal_target. ordered=['unacc', 'acc', 'good', 'vgood'] tags=['target_candidate'] desc=Car acceptability class label.
+- useful_field_combinations: [['safety', 'persons', 'class'], ['buying', 'maint', 'class'], ['lug_boot', 'safety', 'class']]
+- fields_requiring_caution: ['class', 'doors', 'persons']
+- source_url: https://archive.ics.uci.edu/dataset/19/car+evaluation
+
+SQLite schema snapshot:
+{
+  "table_name": "c2",
+  "quoted_table_name": "\"c2\"",
+  "row_count": 1728,
+  "columns": [
+    {
+      "name": "buying",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "maint",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "doors",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "persons",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "lug_boot",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "safety",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "class",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "buying": "vhigh",
+      "maint": "vhigh",
+      "doors": "2",
+      "persons": "2",
+      "lug_boot": "small",
+      "safety": "low",
+      "class": "unacc"
+    },
+    {
+      "buying": "vhigh",
+      "maint": "vhigh",
+      "doors": "2",
+      "persons": "2",
+      "lug_boot": "small",
+      "safety": "med",
+      "class": "unacc"
+    },
+    {
+      "buying": "vhigh",
+      "maint": "vhigh",
+      "doors": "2",
+      "persons": "2",
+      "lug_boot": "small",
+      "safety": "high",
+      "class": "unacc"
+    },
+    {
+      "buying": "vhigh",
+      "maint": "vhigh",
+      "doors": "2",
+      "persons": "2",
+      "lug_boot": "med",
+      "safety": "low",
+      "class": "unacc"
+    },
+    {
+      "buying": "vhigh",
+      "maint": "vhigh",
+      "doors": "2",
+      "persons": "2",
+      "lug_boot": "med",
+      "safety": "med",
+      "class": "unacc"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_c2_two_dim_target_rate",
+    "template_name": "Two-Axis Target Rate Surface",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT {group_col}, {group_col_2},\n       AVG(CASE WHEN {target_col} = {target_value} THEN 1 ELSE 0 END) AS target_rate\nFROM {table}\nGROUP BY {group_col}, {group_col_2}\nORDER BY target_rate DESC;",
+    "required_roles": [
+      "group_col",
+      "group_col_2",
+      "target_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "c2",
+  "question": "Use template Two-Axis Target Rate Surface to probe dependency_strength_similarity with semantic role ranked_signal_view. Focus on group_col=doors, group_col_2=lug_boot, target_col=class.",
+  "planned_template_id": "tpl_c2_two_dim_target_rate",
+  "bindings": {
+    "group_col": "doors",
+    "group_col_2": "lug_boot",
+    "target_col": "class",
+    "target_value": "unacc",
+    "top_k": 16,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 0.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, {group_col_2},\n       AVG(CASE WHEN {target_col} = {target_value} THEN 1 ELSE 0 END) AS target_rate\nFROM {table}\nGROUP BY {group_col}, {group_col_2}\nORDER BY target_rate DESC;"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_040cd7db47ae0614/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40c7-d7ad-73f2-a7df-67614c3fd456"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_c2_two_dim_target_rate\\nSELECT \\\"doors\\\", \\\"lug_boot\\\",\\n       AVG(CASE WHEN \\\"class\\\" = 'unacc' THEN 1 ELSE 0 END) AS \\\"target_rate\\\"\\nFROM \\\"c2\\\"\\nGROUP BY \\\"doors\\\", \\\"lug_boot\\\"\\nORDER BY \\\"target_rate\\\" DESC;\",\"notes\":\"Computes the rate of rows with class='unacc' for each (doors, lug_boot) combination and ranks combinations by that target rate.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":13789,"cached_input_tokens":12672,"output_tokens":433,"reasoning_output_tokens":319}}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_040cd7db47ae0614/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_c2_two_dim_target_rate\nSELECT \"doors\", \"lug_boot\",\n       AVG(CASE WHEN \"class\" = 'unacc' THEN 1 ELSE 0 END) AS \"target_rate\"\nFROM \"c2\"\nGROUP BY \"doors\", \"lug_boot\"\nORDER BY \"target_rate\" DESC;","notes":"Computes the rate of rows with class='unacc' for each (doors, lug_boot) combination and ranks combinations by that target rate."}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_050bb8c9612638aa/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 6001, "bytes_utf8": 6001, "lines": 181, "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": 464, "bytes_utf8": 464, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13804, "cached_input_tokens": 0, "output_tokens": 453, "reasoning_output_tokens": 312}}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_050bb8c9612638aa/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": "c2",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c2_050bb8c9612638aa",
+    "api_calls": 0,
+    "input_tokens": 13804,
+    "cached_input_tokens": 0,
+    "output_tokens": 453,
+    "total_tokens": 14257,
+    "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": 10672.6,
+    "sql_execution_elapsed_ms_total": 1.74,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_050bb8c9612638aa/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_050bb8c9612638aa/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": "2026-05-19T15:06:18.037040+00:00",
+  "ended_at": "2026-05-19T15:06:28.709675+00:00",
+  "elapsed_ms": 10672.6,
+  "prompt_metrics": {
+    "chars": 6001,
+    "bytes_utf8": 6001,
+    "lines": 181,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 819,
+    "bytes_utf8": 819,
+    "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": 464,
+      "bytes_utf8": 464,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 13804,
+      "cached_input_tokens": 0,
+      "output_tokens": 453,
+      "reasoning_output_tokens": 312
+    }
+  },
+  "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_f/c2/artifacts/v2q_c2_050bb8c9612638aa/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,181 @@
+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: c2
+- dataset_name: Car Evaluation
+- table_name: c2
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one car configuration described by six ordinal categorical attributes.
+- task_type: classification
+- target_column: class
+- main_row_count: 1728
+- important_fields:
+- buying: role=feature, type=categorical_ordinal. ordered=['low', 'med', 'high', 'vhigh'] tags=['condition_candidate', 'subgroup_candidate'] desc=Buying price category.
+- maint: role=feature, type=categorical_ordinal. ordered=['low', 'med', 'high', 'vhigh'] tags=['condition_candidate', 'subgroup_candidate'] desc=Maintenance cost category.
+- doors: role=feature, type=categorical_ordinal_count_like. ordered=['2', '3', '4', '5more'] tags=['condition_candidate', 'subgroup_candidate'] desc=Number of doors (count-like ordinal category).
+- persons: role=feature, type=categorical_ordinal_count_like. ordered=['2', '4', 'more'] tags=['condition_candidate', 'subgroup_candidate'] desc=Passenger capacity category (count-like).
+- lug_boot: role=feature, type=categorical_ordinal. ordered=['small', 'med', 'big'] tags=['condition_candidate', 'subgroup_candidate'] desc=Luggage boot size category.
+- safety: role=feature, type=categorical_ordinal. ordered=['low', 'med', 'high'] tags=['condition_candidate', 'subgroup_candidate'] desc=Safety rating category.
+- class: role=target, type=categorical_ordinal_target. ordered=['unacc', 'acc', 'good', 'vgood'] tags=['target_candidate'] desc=Car acceptability class label.
+- useful_field_combinations: [['safety', 'persons', 'class'], ['buying', 'maint', 'class'], ['lug_boot', 'safety', 'class']]
+- fields_requiring_caution: ['class', 'doors', 'persons']
+- source_url: https://archive.ics.uci.edu/dataset/19/car+evaluation
+
+SQLite schema snapshot:
+{
+  "table_name": "c2",
+  "quoted_table_name": "\"c2\"",
+  "row_count": 1728,
+  "columns": [
+    {
+      "name": "buying",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "maint",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "doors",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "persons",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "lug_boot",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "safety",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "class",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "buying": "vhigh",
+      "maint": "vhigh",
+      "doors": "2",
+      "persons": "2",
+      "lug_boot": "small",
+      "safety": "low",
+      "class": "unacc"
+    },
+    {
+      "buying": "vhigh",
+      "maint": "vhigh",
+      "doors": "2",
+      "persons": "2",
+      "lug_boot": "small",
+      "safety": "med",
+      "class": "unacc"
+    },
+    {
+      "buying": "vhigh",
+      "maint": "vhigh",
+      "doors": "2",
+      "persons": "2",
+      "lug_boot": "small",
+      "safety": "high",
+      "class": "unacc"
+    },
+    {
+      "buying": "vhigh",
+      "maint": "vhigh",
+      "doors": "2",
+      "persons": "2",
+      "lug_boot": "med",
+      "safety": "low",
+      "class": "unacc"
+    },
+    {
+      "buying": "vhigh",
+      "maint": "vhigh",
+      "doors": "2",
+      "persons": "2",
+      "lug_boot": "med",
+      "safety": "med",
+      "class": "unacc"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_tail_target_rate_extremes_v2",
+    "template_name": "Tail Target-Rate Extremes",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT\n    {group_col},\n    COUNT(*) AS support,\n    AVG(CASE WHEN {target_col} = {target_value} THEN 1 ELSE 0 END) AS focus_rate\nFROM {table}\nGROUP BY {group_col}\nHAVING COUNT(*) >= {min_support}\nORDER BY focus_rate DESC, support ASC\nLIMIT {top_k};",
+    "required_roles": [
+      "group_col",
+      "target_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "c2",
+  "question": "Use template Tail Target-Rate Extremes to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=lug_boot, target_col=class.",
+  "planned_template_id": "tpl_tail_target_rate_extremes_v2",
+  "bindings": {
+    "group_col": "lug_boot",
+    "target_col": "class",
+    "target_value": "unacc",
+    "top_k": 18,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 0.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT\n    {group_col},\n    COUNT(*) AS support,\n    AVG(CASE WHEN {target_col} = {target_value} THEN 1 ELSE 0 END) AS focus_rate\nFROM {table}\nGROUP BY {group_col}\nHAVING COUNT(*) >= {min_support}\nORDER BY focus_rate DESC, support ASC\nLIMIT {top_k};"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_050bb8c9612638aa/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40c5-ff3d-7653-b1dc-99def89cc0ff"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tail_target_rate_extremes_v2\\nSELECT\\n    \\\"lug_boot\\\",\\n    COUNT(*) AS support,\\n    AVG(CASE WHEN \\\"class\\\" = 'unacc' THEN 1 ELSE 0 END) AS focus_rate\\nFROM \\\"c2\\\"\\nGROUP BY \\\"lug_boot\\\"\\nHAVING COUNT(*) >= 4\\nORDER BY focus_rate DESC, support ASC\\nLIMIT 18;\",\"notes\":\"Instantiated the provided Tail Target-Rate Extremes template with group_col=\\\"lug_boot\\\", target_col=\\\"class\\\", target_value='unacc', min_support=4, and top_k=18.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":13804,"cached_input_tokens":0,"output_tokens":453,"reasoning_output_tokens":312}}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_050bb8c9612638aa/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tail_target_rate_extremes_v2\nSELECT\n    \"lug_boot\",\n    COUNT(*) AS support,\n    AVG(CASE WHEN \"class\" = 'unacc' THEN 1 ELSE 0 END) AS focus_rate\nFROM \"c2\"\nGROUP BY \"lug_boot\"\nHAVING COUNT(*) >= 4\nORDER BY focus_rate DESC, support ASC\nLIMIT 18;","notes":"Instantiated the provided Tail Target-Rate Extremes template with group_col=\"lug_boot\", target_col=\"class\", target_value='unacc', min_support=4, and top_k=18."}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_0584255cfe12d3f4/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 5958, "bytes_utf8": 5958, "lines": 183, "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": 539, "bytes_utf8": 539, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13788, "cached_input_tokens": 12672, "output_tokens": 648, "reasoning_output_tokens": 494}}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_0584255cfe12d3f4/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": "c2",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c2_0584255cfe12d3f4",
+    "api_calls": 0,
+    "input_tokens": 13788,
+    "cached_input_tokens": 12672,
+    "output_tokens": 648,
+    "total_tokens": 14436,
+    "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": 12610.63,
+    "sql_execution_elapsed_ms_total": 1.86,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_0584255cfe12d3f4/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_0584255cfe12d3f4/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": "2026-05-19T15:11:08.473020+00:00",
+  "ended_at": "2026-05-19T15:11:21.083686+00:00",
+  "elapsed_ms": 12610.63,
+  "prompt_metrics": {
+    "chars": 5958,
+    "bytes_utf8": 5958,
+    "lines": 183,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 918,
+    "bytes_utf8": 918,
+    "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": 539,
+      "bytes_utf8": 539,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 13788,
+      "cached_input_tokens": 12672,
+      "output_tokens": 648,
+      "reasoning_output_tokens": 494
+    }
+  },
+  "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_f/c2/artifacts/v2q_c2_0584255cfe12d3f4/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,183 @@
+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: c2
+- dataset_name: Car Evaluation
+- table_name: c2
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one car configuration described by six ordinal categorical attributes.
+- task_type: classification
+- target_column: class
+- main_row_count: 1728
+- important_fields:
+- buying: role=feature, type=categorical_ordinal. ordered=['low', 'med', 'high', 'vhigh'] tags=['condition_candidate', 'subgroup_candidate'] desc=Buying price category.
+- maint: role=feature, type=categorical_ordinal. ordered=['low', 'med', 'high', 'vhigh'] tags=['condition_candidate', 'subgroup_candidate'] desc=Maintenance cost category.
+- doors: role=feature, type=categorical_ordinal_count_like. ordered=['2', '3', '4', '5more'] tags=['condition_candidate', 'subgroup_candidate'] desc=Number of doors (count-like ordinal category).
+- persons: role=feature, type=categorical_ordinal_count_like. ordered=['2', '4', 'more'] tags=['condition_candidate', 'subgroup_candidate'] desc=Passenger capacity category (count-like).
+- lug_boot: role=feature, type=categorical_ordinal. ordered=['small', 'med', 'big'] tags=['condition_candidate', 'subgroup_candidate'] desc=Luggage boot size category.
+- safety: role=feature, type=categorical_ordinal. ordered=['low', 'med', 'high'] tags=['condition_candidate', 'subgroup_candidate'] desc=Safety rating category.
+- class: role=target, type=categorical_ordinal_target. ordered=['unacc', 'acc', 'good', 'vgood'] tags=['target_candidate'] desc=Car acceptability class label.
+- useful_field_combinations: [['safety', 'persons', 'class'], ['buying', 'maint', 'class'], ['lug_boot', 'safety', 'class']]
+- fields_requiring_caution: ['class', 'doors', 'persons']
+- source_url: https://archive.ics.uci.edu/dataset/19/car+evaluation
+
+SQLite schema snapshot:
+{
+  "table_name": "c2",
+  "quoted_table_name": "\"c2\"",
+  "row_count": 1728,
+  "columns": [
+    {
+      "name": "buying",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "maint",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "doors",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "persons",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "lug_boot",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "safety",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "class",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "buying": "vhigh",
+      "maint": "vhigh",
+      "doors": "2",
+      "persons": "2",
+      "lug_boot": "small",
+      "safety": "low",
+      "class": "unacc"
+    },
+    {
+      "buying": "vhigh",
+      "maint": "vhigh",
+      "doors": "2",
+      "persons": "2",
+      "lug_boot": "small",
+      "safety": "med",
+      "class": "unacc"
+    },
+    {
+      "buying": "vhigh",
+      "maint": "vhigh",
+      "doors": "2",
+      "persons": "2",
+      "lug_boot": "small",
+      "safety": "high",
+      "class": "unacc"
+    },
+    {
+      "buying": "vhigh",
+      "maint": "vhigh",
+      "doors": "2",
+      "persons": "2",
+      "lug_boot": "med",
+      "safety": "low",
+      "class": "unacc"
+    },
+    {
+      "buying": "vhigh",
+      "maint": "vhigh",
+      "doors": "2",
+      "persons": "2",
+      "lug_boot": "med",
+      "safety": "med",
+      "class": "unacc"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_c2_two_dim_target_rate",
+    "template_name": "Two-Axis Target Rate Surface",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT {group_col}, {group_col_2},\n       AVG(CASE WHEN {target_col} = {target_value} THEN 1 ELSE 0 END) AS target_rate\nFROM {table}\nGROUP BY {group_col}, {group_col_2}\nORDER BY target_rate DESC;",
+    "required_roles": [
+      "group_col",
+      "group_col_2",
+      "target_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "c2",
+  "question": "Use template Two-Axis Target Rate Surface to probe dependency_strength_similarity with semantic role ranked_signal_view. Focus on group_col=safety, group_col_2=class, target_col=class.",
+  "planned_template_id": "tpl_c2_two_dim_target_rate",
+  "bindings": {
+    "group_col": "safety",
+    "group_col_2": "class",
+    "target_col": "class",
+    "target_value": "unacc",
+    "top_k": 19,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 0.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, {group_col_2},\n       AVG(CASE WHEN {target_col} = {target_value} THEN 1 ELSE 0 END) AS target_rate\nFROM {table}\nGROUP BY {group_col}, {group_col_2}\nORDER BY target_rate DESC;"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_0584255cfe12d3f4/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40ca-6dcf-7f63-b374-d33f137f4fc4"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_c2_two_dim_target_rate.\\nSELECT \\\"safety\\\", \\\"class\\\",\\n       AVG(CASE WHEN \\\"class\\\" = 'unacc' THEN 1 ELSE 0 END) AS \\\"target_rate\\\"\\nFROM \\\"c2\\\"\\nGROUP BY \\\"safety\\\", \\\"class\\\"\\nORDER BY \\\"target_rate\\\" DESC;\",\"notes\":\"Uses the required Two-Axis Target Rate Surface template with group_col=\\\"safety\\\", group_col_2=\\\"class\\\", and target_col=\\\"class\\\". Because the grouping includes the target column itself, the computed rate is deterministic within each group: 1.0 when \\\"class\\\"='unacc' and 0.0 otherwise.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":13788,"cached_input_tokens":12672,"output_tokens":648,"reasoning_output_tokens":494}}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_0584255cfe12d3f4/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_c2_two_dim_target_rate.\nSELECT \"safety\", \"class\",\n       AVG(CASE WHEN \"class\" = 'unacc' THEN 1 ELSE 0 END) AS \"target_rate\"\nFROM \"c2\"\nGROUP BY \"safety\", \"class\"\nORDER BY \"target_rate\" DESC;","notes":"Uses the required Two-Axis Target Rate Surface template with group_col=\"safety\", group_col_2=\"class\", and target_col=\"class\". Because the grouping includes the target column itself, the computed rate is deterministic within each group: 1.0 when \"class\"='unacc' and 0.0 otherwise."}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_06a19f9d880447a9/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 5991, "bytes_utf8": 5991, "lines": 181, "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": 458, "bytes_utf8": 458, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13801, "cached_input_tokens": 12672, "output_tokens": 363, "reasoning_output_tokens": 221}}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_06a19f9d880447a9/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": "c2",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c2_06a19f9d880447a9",
+    "api_calls": 0,
+    "input_tokens": 13801,
+    "cached_input_tokens": 12672,
+    "output_tokens": 363,
+    "total_tokens": 14164,
+    "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": 10899.9,
+    "sql_execution_elapsed_ms_total": 0.96,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_06a19f9d880447a9/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_f/c2/artifacts/v2q_c2_06a19f9d880447a9/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": "2026-05-19T15:05:10.195975+00:00",
+  "ended_at": "2026-05-19T15:05:21.095895+00:00",
+  "elapsed_ms": 10899.9,
+  "prompt_metrics": {
+    "chars": 5991,
+    "bytes_utf8": 5991,
+    "lines": 181,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 833,
+    "bytes_utf8": 833,
+    "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": 458,
+      "bytes_utf8": 458,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 13801,
+      "cached_input_tokens": 12672,
+      "output_tokens": 363,
+      "reasoning_output_tokens": 221
+    }
+  },
+  "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"
+}