Add files using upload-large-folder tool

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_023ee72a13638b07/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Window Partition Average to probe direction_consistency with semantic role ranked_signal_view. Focus on group_col=duration, measure_col=release_year.
+Result preview: [{"duration": "273 min", "avg_measure": 2021.0}, {"duration": "39 min", "avg_measure": 2021.0}, {"duration": "36 min", "avg_measure": 2020.6}, {"duration": "21 min", "avg_measure": 2020.3333333333333}, {"duration": "13 min", "avg_measure": 2020.0}] Results were truncated.

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_023ee72a13638b07/generated_sql.sql

@@ -0,0 +1,20 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_b
+-- sql_source_dataset_id: c17
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: direction_consistency
+-- intended_facet_id: conditional_rate_shift
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_m4_window_partition_avg
+-- query_record_id: v2q_c17_023ee72a13638b07
+-- problem_id: v2p_c17_4bbe8e94c2d33afe
+-- realization_mode: agent
+-- source_kind: agent
+SELECT DISTINCT "duration",
+       AVG(CAST("release_year" AS REAL)) OVER (PARTITION BY "duration") AS avg_measure
+FROM "c17"
+WHERE "duration" IS NOT NULL
+  AND "duration" <> ''
+  AND "release_year" GLOB '[0-9][0-9][0-9][0-9]'
+ORDER BY avg_measure DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_023ee72a13638b07/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_window_partition_avg\nSELECT DISTINCT \"duration\",\n       AVG(CAST(\"release_year\" AS REAL)) OVER (PARTITION BY \"duration\") AS avg_measure\nFROM \"c17\"\nWHERE \"duration\" IS NOT NULL\n  AND \"duration\" <> ''\n  AND \"release_year\" GLOB '[0-9][0-9][0-9][0-9]'\nORDER BY avg_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"duration\\\",\\n       AVG(CAST(\\\"release_year\\\" AS REAL)) OVER (PARTITION BY \\\"duration\\\") AS avg_measure\\nFROM \\\"c17\\\"\\nWHERE \\\"duration\\\" IS NOT NULL\\n  AND \\\"duration\\\" <> ''\\n  AND \\\"release_year\\\" GLOB '[0-9][0-9][0-9][0-9]'\\nORDER BY avg_measure DESC;\", \"columns\": [\"duration\", \"avg_measure\"], \"rows\": [{\"duration\": \"273 min\", \"avg_measure\": 2021.0}, {\"duration\": \"39 min\", \"avg_measure\": 2021.0}, {\"duration\": \"36 min\", \"avg_measure\": 2020.6}, {\"duration\": \"21 min\", \"avg_measure\": 2020.3333333333333}, {\"duration\": \"13 min\", \"avg_measure\": 2020.0}, {\"duration\": \"16 min\", \"avg_measure\": 2020.0}, {\"duration\": \"17 Seasons\", \"avg_measure\": 2020.0}, {\"duration\": \"17 min\", \"avg_measure\": 2020.0}, {\"duration\": \"5 min\", \"avg_measure\": 2020.0}, {\"duration\": \"8 min\", \"avg_measure\": 2020.0}, {\"duration\": \"9 min\", \"avg_measure\": 2020.0}, {\"duration\": \"15 min\", \"avg_measure\": 2019.6666666666667}, {\"duration\": \"10 min\", \"avg_measure\": 2019.0}, {\"duration\": \"14 min\", \"avg_measure\": 2019.0}, {\"duration\": \"20 min\", \"avg_measure\": 2019.0}, {\"duration\": \"34 min\", \"avg_measure\": 2018.3333333333333}, {\"duration\": \"11 min\", \"avg_measure\": 2018.0}, {\"duration\": \"15 Seasons\", \"avg_measure\": 2018.0}, {\"duration\": \"312 min\", \"avg_measure\": 2018.0}, {\"duration\": \"33 min\", \"avg_measure\": 2017.8333333333333}, {\"duration\": \"38 min\", \"avg_measure\": 2017.8}, {\"duration\": \"3 Seasons\", \"avg_measure\": 2017.7085427135678}, {\"duration\": \"13 Seasons\", \"avg_measure\": 2017.6666666666667}, {\"duration\": \"41 min\", \"avg_measure\": 2017.6666666666667}, {\"duration\": \"23 min\", \"avg_measure\": 2017.5384615384614}, {\"duration\": \"12 Seasons\", \"avg_measure\": 2017.5}, {\"duration\": \"51 min\", \"avg_measure\": 2017.3636363636363}, {\"duration\": \"2 Seasons\", \"avg_measure\": 2017.270588235294}, {\"duration\": \"65 min\", \"avg_measure\": 2017.16}, {\"duration\": \"57 min\", \"avg_measure\": 2017.0714285714287}, {\"duration\": \"67 min\", \"avg_measure\": 2017.047619047619}, {\"duration\": \"190 min\", \"avg_measure\": 2017.0}, {\"duration\": \"212 min\", \"avg_measure\": 2017.0}, {\"duration\": \"24 min\", \"avg_measure\": 2017.0}, {\"duration\": \"27 min\", \"avg_measure\": 2017.0}, {\"duration\": \"64 min\", \"avg_measure\": 2016.9565217391305}, {\"duration\": \"54 min\", \"avg_measure\": 2016.9166666666667}, {\"duration\": \"44 min\", \"avg_measure\": 2016.842105263158}, {\"duration\": \"35 min\", \"avg_measure\": 2016.8}, {\"duration\": \"53 min\", \"avg_measure\": 2016.7083333333333}, {\"duration\": \"60 min\", \"avg_measure\": 2016.655172413793}, {\"duration\": \"1 Season\", \"avg_measure\": 2016.58561070831}, {\"duration\": \"22 min\", \"avg_measure\": 2016.375}, {\"duration\": \"70 min\", \"avg_measure\": 2016.3214285714287}, {\"duration\": \"28 min\", \"avg_measure\": 2016.2}, {\"duration\": \"5 Seasons\", \"avg_measure\": 2016.2}, {\"duration\": \"12 min\", \"avg_measure\": 2016.0}, {\"duration\": \"180 min\", \"avg_measure\": 2016.0}, {\"duration\": \"19 min\", \"avg_measure\": 2016.0}, {\"duration\": \"66 min\", \"avg_measure\": 2015.9285714285713}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 33.32}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_023ee72a13638b07/run_manifest.json

@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "c17",
+  "started_at": "2026-05-19T16:01:36.361729+00:00",
+  "ended_at": "2026-05-19T16:01:47.979626+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c17_023ee72a13638b07",
+    "problem_id": "v2p_c17_4bbe8e94c2d33afe",
+    "dataset_id": "c17",
+    "template_id": "tpl_m4_window_partition_avg",
+    "template_name": "Window Partition Average",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "direction_consistency",
+    "intended_facet_id": "conditional_rate_shift",
+    "variant_semantic_role": "ranked_signal_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Window Partition Average to probe direction_consistency with semantic role ranked_signal_view. Focus on group_col=duration, measure_col=release_year.",
+    "bindings": {
+      "group_col": "duration",
+      "measure_col": "release_year",
+      "top_k": 10,
+      "top_n": 6,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 2019.0,
+      "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",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;",
+    "notes": [
+      "default_facets=conditional_rate_shift",
+      "template_selection_mode=rule",
+      "problem_index_within_template=4",
+      "sql_variant_index=1/2",
+      "binding_index=135"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 12,
+    "problem_index_within_template": 4,
+    "sql_variant_index": 1,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/sql/v2q_c17_023ee72a13638b07.sql",
+  "usage_summary": {
+    "dataset_id": "c17",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c17_023ee72a13638b07",
+    "api_calls": 0,
+    "input_tokens": 14655,
+    "cached_input_tokens": 12032,
+    "output_tokens": 528,
+    "total_tokens": 15183,
+    "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": 11577.72,
+    "sql_execution_elapsed_ms_total": 33.32,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_023ee72a13638b07/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_023ee72a13638b07/trace.jsonl

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+{"timestamp": "2026-05-19T16:01:47.943971+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": 11577.72, "started_at": "2026-05-19T16:01:36.364739+00:00", "ended_at": "2026-05-19T16:01:47.942494+00:00", "prompt_metrics": {"chars": 9259, "bytes_utf8": 9261, "lines": 240, "estimated_tokens": null}, "response_metrics": {"chars": 585, "bytes_utf8": 585, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14655, "cached_input_tokens": 12032, "output_tokens": 528, "reasoning_output_tokens": 369}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"duration\\\",\\n       AVG(CAST(\\\"release_year\\\" AS REAL)) OVER (PARTITION BY \\\"duration\\\") AS avg_measure\\nFROM \\\"c17\\\"\\nWHERE \\\"duration\\\" IS NOT NULL\\n  AND \\\"duration\\\" <> ''\\n  AND \\\"release_year\\\" GLOB '[0-9][0-9][0-9][0-9]'\\nORDER BY avg_measure DESC;\",\"notes\":\"Applied the Window Partition Average template with group_col=\\\"duration\\\" and measure_col=\\\"release_year\\\". Cast \\\"release_year\\\" to REAL because it is stored as TEXT in the schema, and filtered to 4-digit numeric years for SQLite-safe averaging.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_023ee72a13638b07/usage_summary.json

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+{
+  "dataset_id": "c17",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_c17_023ee72a13638b07",
+  "api_calls": 0,
+  "input_tokens": 14655,
+  "cached_input_tokens": 12032,
+  "output_tokens": 528,
+  "total_tokens": 15183,
+  "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": 11577.72,
+  "sql_execution_elapsed_ms_total": 33.32,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_023ee72a13638b07/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_0fdb2bad4974287c/run_manifest.json

@@ -0,0 +1,72 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "c17",
+  "started_at": "2026-05-19T15:55:21.406433+00:00",
+  "ended_at": "2026-05-19T15:55:29.431127+00:00",
+  "status": "failed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c17_0fdb2bad4974287c",
+    "problem_id": "v2p_c17_03a0cffb6eb8afaa",
+    "dataset_id": "c17",
+    "template_id": "tpl_m4_group_condition_rate",
+    "template_name": "Grouped Condition Rate",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "direction_consistency",
+    "intended_facet_id": "conditional_rate_shift",
+    "variant_semantic_role": "within_group_proportion",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Condition Rate to probe direction_consistency with semantic role within_group_proportion. Focus on group_col=duration, condition_col=type.",
+    "bindings": {
+      "group_col": "duration",
+      "condition_col": "type",
+      "condition_value": "TV Show",
+      "positive_value": "Movie",
+      "negative_value": "TV Show",
+      "top_k": 19,
+      "top_n": 7,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.05,
+      "baseline_multiplier": 1.75,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 4,
+      "measure_threshold": 2019.0,
+      "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",
+      "condition_col"
+    ],
+    "coverage_target_min": "5",
+    "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;",
+    "notes": [
+      "default_facets=conditional_rate_shift",
+      "template_selection_mode=rule",
+      "problem_index_within_template=4",
+      "sql_variant_index=2/2",
+      "binding_index=99"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 9,
+    "problem_index_within_template": 4,
+    "sql_variant_index": 2,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "error": "AI CLI command failed with exit code 1: "
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_0fdb2bad4974287c/trace.jsonl

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+{"timestamp": "2026-05-19T15:55:29.431044+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3136.02, "started_at": "2026-05-19T15:55:26.294279+00:00", "ended_at": "2026-05-19T15:55:29.430323+00:00", "prompt_metrics": {"chars": 9421, "bytes_utf8": 9423, "lines": 243, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f2-fbf3-7bb1-a7dc-7e960f00e2e9\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_1680b99102f41f4e/run_manifest.json

@@ -0,0 +1,72 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "c17",
+  "started_at": "2026-05-19T15:54:31.026441+00:00",
+  "ended_at": "2026-05-19T15:54:38.327259+00:00",
+  "status": "failed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c17_1680b99102f41f4e",
+    "problem_id": "v2p_c17_32232684335c43bb",
+    "dataset_id": "c17",
+    "template_id": "tpl_m4_group_condition_rate",
+    "template_name": "Grouped Condition Rate",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "direction_consistency",
+    "intended_facet_id": "conditional_rate_shift",
+    "variant_semantic_role": "focused_target_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Condition Rate to probe direction_consistency with semantic role focused_target_view. Focus on group_col=release_year, condition_col=type.",
+    "bindings": {
+      "group_col": "release_year",
+      "condition_col": "type",
+      "condition_value": "Movie",
+      "positive_value": "Movie",
+      "negative_value": "TV Show",
+      "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": 2019.0,
+      "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",
+      "condition_col"
+    ],
+    "coverage_target_min": "5",
+    "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;",
+    "notes": [
+      "default_facets=conditional_rate_shift",
+      "template_selection_mode=rule",
+      "problem_index_within_template=2",
+      "sql_variant_index=1/2",
+      "binding_index=97"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 9,
+    "problem_index_within_template": 2,
+    "sql_variant_index": 1,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "error": "AI CLI command failed with exit code 1: "
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_1680b99102f41f4e/trace.jsonl

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+{"timestamp": "2026-05-19T15:54:34.190196+00:00", "event_type": "ai_cli_sql_generation_error", "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": 1, "elapsed_ms": 3158.68, "started_at": "2026-05-19T15:54:31.030723+00:00", "ended_at": "2026-05-19T15:54:34.189431+00:00", "prompt_metrics": {"chars": 9420, "bytes_utf8": 9422, "lines": 243, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f2-23f3-7f23-a35a-5b975e388cd0\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}
+{"timestamp": "2026-05-19T15:54:38.327053+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3134.43, "started_at": "2026-05-19T15:54:35.191046+00:00", "ended_at": "2026-05-19T15:54:38.325508+00:00", "prompt_metrics": {"chars": 9420, "bytes_utf8": 9422, "lines": 243, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f2-3437-7e83-9c46-714aa9cc119c\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_2160283566237046/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=release_year.
+Result preview: [{"empirical_cdf_at_threshold": 0.8245713636879755}]

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_2160283566237046/generated_sql.sql

@@ -0,0 +1,15 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_b
+-- sql_source_dataset_id: c17
+-- 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_threshold_rarity_cdf
+-- query_record_id: v2q_c17_2160283566237046
+-- problem_id: v2p_c17_f4f07927e929c16f
+-- realization_mode: agent
+-- source_kind: agent
+SELECT AVG(CASE WHEN CAST("release_year" AS REAL) <= 2019.0 THEN 1 ELSE 0 END) AS "empirical_cdf_at_threshold"
+FROM "c17";

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_2160283566237046/query_results.jsonl

@@ -0,0 +1 @@
+{"step_index": 2, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_threshold_rarity_cdf\nSELECT AVG(CASE WHEN CAST(\"release_year\" AS REAL) <= 2019.0 THEN 1 ELSE 0 END) AS \"empirical_cdf_at_threshold\"\nFROM \"c17\";", "result": "{\"query\": \"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(\\\"release_year\\\" AS REAL) <= 2019.0 THEN 1 ELSE 0 END) AS \\\"empirical_cdf_at_threshold\\\"\\nFROM \\\"c17\\\";\", \"columns\": [\"empirical_cdf_at_threshold\"], \"rows\": [{\"empirical_cdf_at_threshold\": 0.8245713636879755}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 5.95}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_2160283566237046/run_manifest.json

@@ -0,0 +1,87 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "c17",
+  "started_at": "2026-05-19T15:57:12.506958+00:00",
+  "ended_at": "2026-05-19T15:57:24.999505+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c17_2160283566237046",
+    "problem_id": "v2p_c17_f4f07927e929c16f",
+    "dataset_id": "c17",
+    "template_id": "tpl_threshold_rarity_cdf",
+    "template_name": "Threshold Rarity CDF",
+    "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 Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=release_year.",
+    "bindings": {
+      "measure_col": "release_year",
+      "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": 2019.0,
+      "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": [
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};",
+    "notes": [
+      "default_facets=low_support_extremes",
+      "template_selection_mode=rule",
+      "problem_index_within_template=4",
+      "sql_variant_index=1/1",
+      "binding_index=111"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 10,
+    "problem_index_within_template": 4,
+    "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_b/c17/sql/v2q_c17_2160283566237046.sql",
+  "usage_summary": {
+    "dataset_id": "c17",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c17_2160283566237046",
+    "api_calls": 0,
+    "input_tokens": 14636,
+    "cached_input_tokens": 13696,
+    "output_tokens": 300,
+    "total_tokens": 14936,
+    "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": 11476.58,
+    "sql_execution_elapsed_ms_total": 5.95,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_2160283566237046/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_2160283566237046/trace.jsonl

@@ -0,0 +1,2 @@
+{"timestamp": "2026-05-19T15:57:15.364719+00:00", "event_type": "ai_cli_sql_generation_error", "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": 1, "elapsed_ms": 2853.73, "started_at": "2026-05-19T15:57:12.510170+00:00", "ended_at": "2026-05-19T15:57:15.363924+00:00", "prompt_metrics": {"chars": 9114, "bytes_utf8": 9116, "lines": 238, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f4-9ace-75b0-a5eb-0adf1d016317\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}
+{"timestamp": "2026-05-19T15:57:24.990729+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 2, "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": 8622.85, "started_at": "2026-05-19T15:57:16.366233+00:00", "ended_at": "2026-05-19T15:57:24.989131+00:00", "prompt_metrics": {"chars": 9114, "bytes_utf8": 9116, "lines": 238, "estimated_tokens": null}, "response_metrics": {"chars": 376, "bytes_utf8": 376, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14636, "cached_input_tokens": 13696, "output_tokens": 300, "reasoning_output_tokens": 191}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(\\\"release_year\\\" AS REAL) <= 2019.0 THEN 1 ELSE 0 END) AS \\\"empirical_cdf_at_threshold\\\"\\nFROM \\\"c17\\\";\",\"notes\":\"Used the planned Threshold Rarity CDF template with measure_col bound to \\\"release_year\\\" and threshold 2019.0. CAST was added because \\\"release_year\\\" is stored as TEXT in the schema.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_2160283566237046/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "c17",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_c17_2160283566237046",
+  "api_calls": 0,
+  "input_tokens": 14636,
+  "cached_input_tokens": 13696,
+  "output_tokens": 300,
+  "total_tokens": 14936,
+  "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": 11476.58,
+  "sql_execution_elapsed_ms_total": 5.95,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_2160283566237046/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_25f04d7a3f001d53/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=rating, measure_col=release_year.
+Result preview: [{"rating": "TV-14", "percentile_measure": 2020}, {"rating": "TV-G", "percentile_measure": 2020}, {"rating": "TV-MA", "percentile_measure": 2020}, {"rating": "TV-PG", "percentile_measure": 2020}, {"rating": "TV-Y", "percentile_measure": 2020}]

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_25f04d7a3f001d53/generated_sql.sql

@@ -0,0 +1,49 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_b
+-- sql_source_dataset_id: c17
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_c17_25f04d7a3f001d53
+-- problem_id: v2p_c17_785161151a7147a7
+-- realization_mode: agent
+-- source_kind: agent
+WITH "ordered" AS (
+  SELECT
+    "rating",
+    CAST("release_year" AS INTEGER) AS "release_year_int",
+    ROW_NUMBER() OVER (
+      PARTITION BY "rating"
+      ORDER BY CAST("release_year" AS INTEGER)
+    ) AS "rn",
+    COUNT(*) OVER (
+      PARTITION BY "rating"
+    ) AS "cnt"
+  FROM "c17"
+  WHERE "rating" IS NOT NULL
+    AND "rating" <> ''
+    AND "release_year" IS NOT NULL
+    AND "release_year" <> ''
+),
+"percentiles" AS (
+  SELECT
+    "rating",
+    "release_year_int" AS "percentile_measure",
+    "cnt",
+    ROW_NUMBER() OVER (
+      PARTITION BY "rating"
+      ORDER BY "rn"
+    ) AS "pick_rank"
+  FROM "ordered"
+  WHERE "rn" >= CAST((0.9 * "cnt") + 0.999999 AS INTEGER)
+)
+SELECT
+  "rating",
+  "percentile_measure"
+FROM "percentiles"
+WHERE "pick_rank" = 1
+  AND "cnt" >= 5
+ORDER BY "percentile_measure" DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_25f04d7a3f001d53/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_grouped_percentile_point\nWITH \"ordered\" AS (\n  SELECT\n    \"rating\",\n    CAST(\"release_year\" AS INTEGER) AS \"release_year_int\",\n    ROW_NUMBER() OVER (\n      PARTITION BY \"rating\"\n      ORDER BY CAST(\"release_year\" AS INTEGER)\n    ) AS \"rn\",\n    COUNT(*) OVER (\n      PARTITION BY \"rating\"\n    ) AS \"cnt\"\n  FROM \"c17\"\n  WHERE \"rating\" IS NOT NULL\n    AND \"rating\" <> ''\n    AND \"release_year\" IS NOT NULL\n    AND \"release_year\" <> ''\n),\n\"percentiles\" AS (\n  SELECT\n    \"rating\",\n    \"release_year_int\" AS \"percentile_measure\",\n    \"cnt\",\n    ROW_NUMBER() OVER (\n      PARTITION BY \"rating\"\n      ORDER BY \"rn\"\n    ) AS \"pick_rank\"\n  FROM \"ordered\"\n  WHERE \"rn\" >= CAST((0.9 * \"cnt\") + 0.999999 AS INTEGER)\n)\nSELECT\n  \"rating\",\n  \"percentile_measure\"\nFROM \"percentiles\"\nWHERE \"pick_rank\" = 1\n  AND \"cnt\" >= 5\nORDER BY \"percentile_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ordered\\\" AS (\\n  SELECT\\n    \\\"rating\\\",\\n    CAST(\\\"release_year\\\" AS INTEGER) AS \\\"release_year_int\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"rating\\\"\\n      ORDER BY CAST(\\\"release_year\\\" AS INTEGER)\\n    ) AS \\\"rn\\\",\\n    COUNT(*) OVER (\\n      PARTITION BY \\\"rating\\\"\\n    ) AS \\\"cnt\\\"\\n  FROM \\\"c17\\\"\\n  WHERE \\\"rating\\\" IS NOT NULL\\n    AND \\\"rating\\\" <> ''\\n    AND \\\"release_year\\\" IS NOT NULL\\n    AND \\\"release_year\\\" <> ''\\n),\\n\\\"percentiles\\\" AS (\\n  SELECT\\n    \\\"rating\\\",\\n    \\\"release_year_int\\\" AS \\\"percentile_measure\\\",\\n    \\\"cnt\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"rating\\\"\\n      ORDER BY \\\"rn\\\"\\n    ) AS \\\"pick_rank\\\"\\n  FROM \\\"ordered\\\"\\n  WHERE \\\"rn\\\" >= CAST((0.9 * \\\"cnt\\\") + 0.999999 AS INTEGER)\\n)\\nSELECT\\n  \\\"rating\\\",\\n  \\\"percentile_measure\\\"\\nFROM \\\"percentiles\\\"\\nWHERE \\\"pick_rank\\\" = 1\\n  AND \\\"cnt\\\" >= 5\\nORDER BY \\\"percentile_measure\\\" DESC;\", \"columns\": [\"rating\", \"percentile_measure\"], \"rows\": [{\"rating\": \"TV-14\", \"percentile_measure\": 2020}, {\"rating\": \"TV-G\", \"percentile_measure\": 2020}, {\"rating\": \"TV-MA\", \"percentile_measure\": 2020}, {\"rating\": \"TV-PG\", \"percentile_measure\": 2020}, {\"rating\": \"TV-Y\", \"percentile_measure\": 2020}, {\"rating\": \"TV-Y7\", \"percentile_measure\": 2020}, {\"rating\": \"PG\", \"percentile_measure\": 2019}, {\"rating\": \"PG-13\", \"percentile_measure\": 2019}, {\"rating\": \"R\", \"percentile_measure\": 2019}, {\"rating\": \"TV-Y7-FV\", \"percentile_measure\": 2018}, {\"rating\": \"G\", \"percentile_measure\": 2017}, {\"rating\": \"NR\", \"percentile_measure\": 2016}], \"row_count_returned\": 12, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 49.24}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_25f04d7a3f001d53/run_manifest.json

@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "c17",
+  "started_at": "2026-05-19T15:52:34.244099+00:00",
+  "ended_at": "2026-05-19T15:52:49.956540+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c17_25f04d7a3f001d53",
+    "problem_id": "v2p_c17_785161151a7147a7",
+    "dataset_id": "c17",
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_concentration_consistency",
+    "intended_facet_id": "rare_target_concentration",
+    "variant_semantic_role": "ranked_signal_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=rating, measure_col=release_year.",
+    "bindings": {
+      "group_col": "rating",
+      "measure_col": "release_year",
+      "top_k": 15,
+      "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": 2018.0,
+      "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",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "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;",
+    "notes": [
+      "default_facets=rare_target_concentration",
+      "template_selection_mode=rule",
+      "problem_index_within_template=7",
+      "sql_variant_index=2/2",
+      "binding_index=90"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 8,
+    "problem_index_within_template": 7,
+    "sql_variant_index": 2,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/sql/v2q_c17_25f04d7a3f001d53.sql",
+  "usage_summary": {
+    "dataset_id": "c17",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c17_25f04d7a3f001d53",
+    "api_calls": 0,
+    "input_tokens": 14683,
+    "cached_input_tokens": 13696,
+    "output_tokens": 877,
+    "total_tokens": 15560,
+    "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": 15656.18,
+    "sql_execution_elapsed_ms_total": 49.24,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_25f04d7a3f001d53/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_25f04d7a3f001d53/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:52:49.904895+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": 15656.18, "started_at": "2026-05-19T15:52:34.246874+00:00", "ended_at": "2026-05-19T15:52:49.903085+00:00", "prompt_metrics": {"chars": 9353, "bytes_utf8": 9355, "lines": 240, "estimated_tokens": null}, "response_metrics": {"chars": 1258, "bytes_utf8": 1258, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14683, "cached_input_tokens": 13696, "output_tokens": 877, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ordered\\\" AS (\\n  SELECT\\n    \\\"rating\\\",\\n    CAST(\\\"release_year\\\" AS INTEGER) AS \\\"release_year_int\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"rating\\\"\\n      ORDER BY CAST(\\\"release_year\\\" AS INTEGER)\\n    ) AS \\\"rn\\\",\\n    COUNT(*) OVER (\\n      PARTITION BY \\\"rating\\\"\\n    ) AS \\\"cnt\\\"\\n  FROM \\\"c17\\\"\\n  WHERE \\\"rating\\\" IS NOT NULL\\n    AND \\\"rating\\\" <> ''\\n    AND \\\"release_year\\\" IS NOT NULL\\n    AND \\\"release_year\\\" <> ''\\n),\\n\\\"percentiles\\\" AS (\\n  SELECT\\n    \\\"rating\\\",\\n    \\\"release_year_int\\\" AS \\\"percentile_measure\\\",\\n    \\\"cnt\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"rating\\\"\\n      ORDER BY \\\"rn\\\"\\n    ) AS \\\"pick_rank\\\"\\n  FROM \\\"ordered\\\"\\n  WHERE \\\"rn\\\" >= CAST((0.9 * \\\"cnt\\\") + 0.999999 AS INTEGER)\\n)\\nSELECT\\n  \\\"rating\\\",\\n  \\\"percentile_measure\\\"\\nFROM \\\"percentiles\\\"\\nWHERE \\\"pick_rank\\\" = 1\\n  AND \\\"cnt\\\" >= 5\\nORDER BY \\\"percentile_measure\\\" DESC;\",\"notes\":\"SQLite has no PERCENT"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_25f04d7a3f001d53/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "c17",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_c17_25f04d7a3f001d53",
+  "api_calls": 0,
+  "input_tokens": 14683,
+  "cached_input_tokens": 13696,
+  "output_tokens": 877,
+  "total_tokens": 15560,
+  "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": 15656.18,
+  "sql_execution_elapsed_ms_total": 49.24,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_25f04d7a3f001d53/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_2a26c1bc75524d73/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Low-Support Group Count to probe tail_mass_similarity with semantic role rare_extreme_view. Focus on group_col=duration.
+Result preview: [{"duration": "10 min", "support": 1}, {"duration": "16 min", "support": 1}, {"duration": "167 min", "support": 1}, {"duration": "17 Seasons", "support": 1}, {"duration": "178 min", "support": 1}]

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_2a26c1bc75524d73/generated_sql.sql

@@ -0,0 +1,20 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_b
+-- sql_source_dataset_id: c17
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_tail_low_support_group_count_v2
+-- query_record_id: v2q_c17_2a26c1bc75524d73
+-- problem_id: v2p_c17_a6844072f31a1af6
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+    "duration",
+    COUNT(*) AS "support"
+FROM "c17"
+GROUP BY "duration"
+ORDER BY "support" ASC, "duration"
+LIMIT 18;

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_2a26c1bc75524d73/query_results.jsonl

@@ -0,0 +1 @@
+{"step_index": 2, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tail_low_support_group_count_v2\nSELECT\n    \"duration\",\n    COUNT(*) AS \"support\"\nFROM \"c17\"\nGROUP BY \"duration\"\nORDER BY \"support\" ASC, \"duration\"\nLIMIT 18;", "result": "{\"query\": \"-- template_id: tpl_tail_low_support_group_count_v2\\nSELECT\\n    \\\"duration\\\",\\n    COUNT(*) AS \\\"support\\\"\\nFROM \\\"c17\\\"\\nGROUP BY \\\"duration\\\"\\nORDER BY \\\"support\\\" ASC, \\\"duration\\\"\\nLIMIT 18;\", \"columns\": [\"duration\", \"support\"], \"rows\": [{\"duration\": \"10 min\", \"support\": 1}, {\"duration\": \"16 min\", \"support\": 1}, {\"duration\": \"167 min\", \"support\": 1}, {\"duration\": \"17 Seasons\", \"support\": 1}, {\"duration\": \"178 min\", \"support\": 1}, {\"duration\": \"18 min\", \"support\": 1}, {\"duration\": \"186 min\", \"support\": 1}, {\"duration\": \"189 min\", \"support\": 1}, {\"duration\": \"191 min\", \"support\": 1}, {\"duration\": \"193 min\", \"support\": 1}, {\"duration\": \"194 min\", \"support\": 1}, {\"duration\": \"196 min\", \"support\": 1}, {\"duration\": \"200 min\", \"support\": 1}, {\"duration\": \"201 min\", \"support\": 1}, {\"duration\": \"203 min\", \"support\": 1}, {\"duration\": \"205 min\", \"support\": 1}, {\"duration\": \"208 min\", \"support\": 1}, {\"duration\": \"212 min\", \"support\": 1}], \"row_count_returned\": 18, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 7.71}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_2a26c1bc75524d73/run_manifest.json

@@ -0,0 +1,87 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "c17",
+  "started_at": "2026-05-19T15:59:13.068405+00:00",
+  "ended_at": "2026-05-19T15:59:25.454532+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c17_2a26c1bc75524d73",
+    "problem_id": "v2p_c17_a6844072f31a1af6",
+    "dataset_id": "c17",
+    "template_id": "tpl_tail_low_support_group_count_v2",
+    "template_name": "Low-Support Group Count",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_mass_similarity",
+    "intended_facet_id": "tail_ranked_signal",
+    "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_mass_similarity with semantic role rare_extreme_view. Focus on group_col=duration.",
+    "bindings": {
+      "group_col": "duration",
+      "top_k": 18,
+      "top_n": 7,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.05,
+      "baseline_multiplier": 1.75,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 4,
+      "measure_threshold": 2019.0,
+      "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=tail_ranked_signal",
+      "template_selection_mode=rule",
+      "problem_index_within_template=4",
+      "sql_variant_index=2/2",
+      "binding_index=123"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 11,
+    "problem_index_within_template": 4,
+    "sql_variant_index": 2,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/sql/v2q_c17_2a26c1bc75524d73.sql",
+  "usage_summary": {
+    "dataset_id": "c17",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c17_2a26c1bc75524d73",
+    "api_calls": 0,
+    "input_tokens": 14655,
+    "cached_input_tokens": 13696,
+    "output_tokens": 250,
+    "total_tokens": 14905,
+    "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": 11371.12,
+    "sql_execution_elapsed_ms_total": 7.71,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_2a26c1bc75524d73/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_2a26c1bc75524d73/trace.jsonl

@@ -0,0 +1,2 @@
+{"timestamp": "2026-05-19T15:59:16.417939+00:00", "event_type": "ai_cli_sql_generation_error", "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": 1, "elapsed_ms": 3346.13, "started_at": "2026-05-19T15:59:13.071071+00:00", "ended_at": "2026-05-19T15:59:16.417224+00:00", "prompt_metrics": {"chars": 9161, "bytes_utf8": 9163, "lines": 238, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f6-71b3-74e3-984d-64683626fe74\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}
+{"timestamp": "2026-05-19T15:59:25.445387+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 2, "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": 8024.99, "started_at": "2026-05-19T15:59:17.419542+00:00", "ended_at": "2026-05-19T15:59:25.444582+00:00", "prompt_metrics": {"chars": 9161, "bytes_utf8": 9163, "lines": 238, "estimated_tokens": null}, "response_metrics": {"chars": 349, "bytes_utf8": 349, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14655, "cached_input_tokens": 13696, "output_tokens": 250, "reasoning_output_tokens": 154}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tail_low_support_group_count_v2\\nSELECT\\n    \\\"duration\\\",\\n    COUNT(*) AS \\\"support\\\"\\nFROM \\\"c17\\\"\\nGROUP BY \\\"duration\\\"\\nORDER BY \\\"support\\\" ASC, \\\"duration\\\"\\nLIMIT 18;\",\"notes\":\"Uses the Low-Support Group Count template with group_col bound to \\\"duration\\\", returning the 18 rarest duration groups by row count.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_2a26c1bc75524d73/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "c17",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_c17_2a26c1bc75524d73",
+  "api_calls": 0,
+  "input_tokens": 14655,
+  "cached_input_tokens": 13696,
+  "output_tokens": 250,
+  "total_tokens": 14905,
+  "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": 11371.12,
+  "sql_execution_elapsed_ms_total": 7.71,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_2a26c1bc75524d73/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_32b454616a5f99a9/run_manifest.json

@@ -0,0 +1,72 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "c17",
+  "started_at": "2026-05-19T15:55:13.924161+00:00",
+  "ended_at": "2026-05-19T15:55:21.406080+00:00",
+  "status": "failed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c17_32b454616a5f99a9",
+    "problem_id": "v2p_c17_d4897c1b5bbead31",
+    "dataset_id": "c17",
+    "template_id": "tpl_m4_group_condition_rate",
+    "template_name": "Grouped Condition Rate",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "direction_consistency",
+    "intended_facet_id": "conditional_rate_shift",
+    "variant_semantic_role": "focused_target_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Condition Rate to probe direction_consistency with semantic role focused_target_view. Focus on group_col=duration, condition_col=type.",
+    "bindings": {
+      "group_col": "duration",
+      "condition_col": "type",
+      "condition_value": "Movie",
+      "positive_value": "Movie",
+      "negative_value": "TV Show",
+      "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": 2019.0,
+      "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",
+      "condition_col"
+    ],
+    "coverage_target_min": "5",
+    "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;",
+    "notes": [
+      "default_facets=conditional_rate_shift",
+      "template_selection_mode=rule",
+      "problem_index_within_template=4",
+      "sql_variant_index=1/2",
+      "binding_index=99"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 9,
+    "problem_index_within_template": 4,
+    "sql_variant_index": 1,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "error": "AI CLI command failed with exit code 1: "
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_32b454616a5f99a9/trace.jsonl

@@ -0,0 +1,2 @@
+{"timestamp": "2026-05-19T15:55:17.055815+00:00", "event_type": "ai_cli_sql_generation_error", "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": 1, "elapsed_ms": 3128.11, "started_at": "2026-05-19T15:55:13.927020+00:00", "ended_at": "2026-05-19T15:55:17.055148+00:00", "prompt_metrics": {"chars": 9412, "bytes_utf8": 9414, "lines": 243, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f2-cb80-7e62-ad08-eb94e9dbbf06\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}
+{"timestamp": "2026-05-19T15:55:21.405980+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3348.51, "started_at": "2026-05-19T15:55:18.056624+00:00", "ended_at": "2026-05-19T15:55:21.405170+00:00", "prompt_metrics": {"chars": 9412, "bytes_utf8": 9414, "lines": 243, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f2-dba5-7893-a2fb-a1a5a19a5ca2\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_32f25932f5557732/final_answer.txt

@@ -0,0 +1 @@
+{"row_count": null, "preview_rows": [{"type": "Movie", "total_rows": 6131, "missing_rows": 0, "missing_rate": 0.0}, {"type": "TV Show", "total_rows": 2676, "missing_rows": 0, "missing_rate": 0.0}]}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_32f25932f5557732/generated_sql.sql

@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_b
+-- sql_source_dataset_id: c17
+-- family_id: missingness_structure
+-- canonical_subitem_id: co_missingness_pattern_consistency
+-- intended_facet_id: missing_rate_by_subgroup
+-- variant_semantic_role: missing_rate_by_subgroup
+-- template_id: tpl_missing_rate_by_subgroup
+-- query_record_id: v2q_c17_32f25932f5557732
+-- problem_id: v2p_c17_c057067152a33e29
+-- realization_mode: deterministic
+-- source_kind: deterministic
+SELECT
+    "type",
+    COUNT(*) AS total_rows,
+    SUM(CASE WHEN "director" IS NULL THEN 1 ELSE 0 END) AS missing_rows,
+    AVG(CASE WHEN "director" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate
+FROM "c17"
+GROUP BY "type"
+ORDER BY missing_rate DESC, total_rows DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_32f25932f5557732/query_results.jsonl

@@ -0,0 +1 @@
+{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_b\n-- sql_source_dataset_id: c17\n-- family_id: missingness_structure\n-- canonical_subitem_id: co_missingness_pattern_consistency\n-- intended_facet_id: missing_rate_by_subgroup\n-- variant_semantic_role: missing_rate_by_subgroup\n-- template_id: tpl_missing_rate_by_subgroup\n-- query_record_id: v2q_c17_32f25932f5557732\n-- problem_id: v2p_c17_c057067152a33e29\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n    \"type\",\n    COUNT(*) AS total_rows,\n    SUM(CASE WHEN \"director\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n    AVG(CASE WHEN \"director\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM \"c17\"\nGROUP BY \"type\"\nORDER BY missing_rate DESC, total_rows DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_b\\n-- sql_source_dataset_id: c17\\n-- family_id: missingness_structure\\n-- canonical_subitem_id: co_missingness_pattern_consistency\\n-- intended_facet_id: missing_rate_by_subgroup\\n-- variant_semantic_role: missing_rate_by_subgroup\\n-- template_id: tpl_missing_rate_by_subgroup\\n-- query_record_id: v2q_c17_32f25932f5557732\\n-- problem_id: v2p_c17_c057067152a33e29\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n    \\\"type\\\",\\n    COUNT(*) AS total_rows,\\n    SUM(CASE WHEN \\\"director\\\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\\n    AVG(CASE WHEN \\\"director\\\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\\nFROM \\\"c17\\\"\\nGROUP BY \\\"type\\\"\\nORDER BY missing_rate DESC, total_rows DESC;\", \"columns\": [\"type\", \"total_rows\", \"missing_rows\", \"missing_rate\"], \"rows\": [{\"type\": \"Movie\", \"total_rows\": 6131, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"type\": \"TV Show\", \"total_rows\": 2676, \"missing_rows\": 0, \"missing_rate\": 0.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 4.52}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_32f25932f5557732/run_manifest.json

@@ -0,0 +1,59 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "c17",
+  "started_at": "2026-05-19T16:03:15.317476+00:00",
+  "ended_at": "2026-05-19T16:03:15.322685+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c17_32f25932f5557732",
+    "problem_id": "v2p_c17_c057067152a33e29",
+    "dataset_id": "c17",
+    "template_id": "tpl_missing_rate_by_subgroup",
+    "template_name": "Missing Rate by Subgroup",
+    "family_id": "missingness_structure",
+    "canonical_subitem_id": "co_missingness_pattern_consistency",
+    "intended_facet_id": "missing_rate_by_subgroup",
+    "variant_semantic_role": "missing_rate_by_subgroup",
+    "subitem_assignment_source": "template_fixed",
+    "source_kind": "deterministic",
+    "realization_mode": "deterministic",
+    "gate_priority": "deterministic",
+    "extended_family": false,
+    "question": "Use template Missing Rate by Subgroup to probe co_missingness_pattern_consistency with semantic role missing_rate_by_subgroup. Focus on group_col=type, missing_col=director.",
+    "bindings": {
+      "missing_col": "director",
+      "group_col": "type"
+    },
+    "binding_roles": [
+      "missing_col",
+      "group_col"
+    ],
+    "coverage_target_min": "enumerate_all_applicable",
+    "runtime_sql_skeleton": "SELECT\n    {group_col},\n    COUNT(*) AS total_rows,\n    SUM(CASE WHEN {missing_col} IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n    AVG(CASE WHEN {missing_col} IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY missing_rate DESC, total_rows DESC;",
+    "notes": [
+      "default_facets=missing_rate_by_subgroup,missing_target_interaction",
+      "template_selection_mode=deterministic",
+      "problem_index_within_template=1",
+      "sql_variant_index=1/1"
+    ],
+    "template_selection_mode": "deterministic",
+    "selected_template_rank": 0,
+    "problem_index_within_template": 1,
+    "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_b/c17/sql/v2q_c17_32f25932f5557732.sql",
+  "usage_summary": {
+    "engine": "template",
+    "input_tokens": 0,
+    "cached_input_tokens": 0,
+    "output_tokens": 0,
+    "total_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "none"
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_32f25932f5557732/usage_summary.json

@@ -0,0 +1,9 @@
+{
+  "engine": "template",
+  "input_tokens": 0,
+  "cached_input_tokens": 0,
+  "output_tokens": 0,
+  "total_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "none"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_3e0379dd71f9e74b/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Condition Rate to probe direction_consistency with semantic role within_group_proportion. Focus on group_col=release_year, condition_col=type.
+Result preview: [{"release_year": "1925", "condition_rate": 1.0}, {"release_year": "2021", "condition_rate": 0.5320945945945946}, {"release_year": "1963", "condition_rate": 0.5}, {"release_year": "1946", "condition_rate": 0.5}, {"release_year": "2020", "condition_rate": 0.45750262329485836}] Results were truncated.

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_3e0379dd71f9e74b/generated_sql.sql

@@ -0,0 +1,18 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_b
+-- sql_source_dataset_id: c17
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: direction_consistency
+-- intended_facet_id: conditional_rate_shift
+-- variant_semantic_role: within_group_proportion
+-- template_id: tpl_m4_group_condition_rate
+-- query_record_id: v2q_c17_3e0379dd71f9e74b
+-- problem_id: v2p_c17_00afd17e5ca8ef68
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "release_year",
+       AVG(CASE WHEN "type" = 'TV Show' THEN 1 ELSE 0 END) AS condition_rate
+FROM "c17"
+GROUP BY "release_year"
+ORDER BY condition_rate DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_3e0379dd71f9e74b/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_condition_rate\nSELECT \"release_year\",\n       AVG(CASE WHEN \"type\" = 'TV Show' THEN 1 ELSE 0 END) AS condition_rate\nFROM \"c17\"\nGROUP BY \"release_year\"\nORDER BY condition_rate DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"release_year\\\",\\n       AVG(CASE WHEN \\\"type\\\" = 'TV Show' THEN 1 ELSE 0 END) AS condition_rate\\nFROM \\\"c17\\\"\\nGROUP BY \\\"release_year\\\"\\nORDER BY condition_rate DESC;\", \"columns\": [\"release_year\", \"condition_rate\"], \"rows\": [{\"release_year\": \"1925\", \"condition_rate\": 1.0}, {\"release_year\": \"2021\", \"condition_rate\": 0.5320945945945946}, {\"release_year\": \"1963\", \"condition_rate\": 0.5}, {\"release_year\": \"1946\", \"condition_rate\": 0.5}, {\"release_year\": \"2020\", \"condition_rate\": 0.45750262329485836}, {\"release_year\": \"2019\", \"condition_rate\": 0.38543689320388347}, {\"release_year\": \"2018\", \"condition_rate\": 0.33129904097646035}, {\"release_year\": \"2015\", \"condition_rate\": 0.2892857142857143}, {\"release_year\": \"2016\", \"condition_rate\": 0.270509977827051}, {\"release_year\": \"2012\", \"condition_rate\": 0.270042194092827}, {\"release_year\": \"2017\", \"condition_rate\": 0.2567829457364341}, {\"release_year\": \"2014\", \"condition_rate\": 0.25}, {\"release_year\": \"1945\", \"condition_rate\": 0.25}, {\"release_year\": \"2009\", \"condition_rate\": 0.2236842105263158}, {\"release_year\": \"2013\", \"condition_rate\": 0.21875}, {\"release_year\": \"2011\", \"condition_rate\": 0.21621621621621623}, {\"release_year\": \"2010\", \"condition_rate\": 0.20618556701030927}, {\"release_year\": \"1972\", \"condition_rate\": 0.2}, {\"release_year\": \"1967\", \"condition_rate\": 0.2}, {\"release_year\": \"1999\", \"condition_rate\": 0.1794871794871795}, {\"release_year\": \"2008\", \"condition_rate\": 0.16911764705882354}, {\"release_year\": \"2003\", \"condition_rate\": 0.16393442622950818}, {\"release_year\": \"2005\", \"condition_rate\": 0.1625}, {\"release_year\": \"2007\", \"condition_rate\": 0.1590909090909091}, {\"release_year\": \"1986\", \"condition_rate\": 0.15384615384615385}, {\"release_year\": \"2006\", \"condition_rate\": 0.14583333333333334}, {\"release_year\": \"1993\", \"condition_rate\": 0.14285714285714285}, {\"release_year\": \"1977\", \"condition_rate\": 0.14285714285714285}, {\"release_year\": \"1974\", \"condition_rate\": 0.14285714285714285}, {\"release_year\": \"2004\", \"condition_rate\": 0.140625}, {\"release_year\": \"2002\", \"condition_rate\": 0.13725490196078433}, {\"release_year\": \"1990\", \"condition_rate\": 0.13636363636363635}, {\"release_year\": \"1992\", \"condition_rate\": 0.13043478260869565}, {\"release_year\": \"1996\", \"condition_rate\": 0.125}, {\"release_year\": \"2001\", \"condition_rate\": 0.1111111111111111}, {\"release_year\": \"1998\", \"condition_rate\": 0.1111111111111111}, {\"release_year\": \"1988\", \"condition_rate\": 0.1111111111111111}, {\"release_year\": \"2000\", \"condition_rate\": 0.10810810810810811}, {\"release_year\": \"1997\", \"condition_rate\": 0.10526315789473684}, {\"release_year\": \"1985\", \"condition_rate\": 0.1}, {\"release_year\": \"1994\", \"condition_rate\": 0.09090909090909091}, {\"release_year\": \"1979\", \"condition_rate\": 0.09090909090909091}, {\"release_year\": \"1995\", \"condition_rate\": 0.08}, {\"release_year\": \"1981\", \"condition_rate\": 0.07692307692307693}, {\"release_year\": \"1989\", \"condition_rate\": 0.0625}, {\"release_year\": \"1991\", \"condition_rate\": 0.058823529411764705}, {\"release_year\": \"1987\", \"condition_rate\": 0.0}, {\"release_year\": \"1984\", \"condition_rate\": 0.0}, {\"release_year\": \"1983\", \"condition_rate\": 0.0}, {\"release_year\": \"1982\", \"condition_rate\": 0.0}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 6.32}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_3e0379dd71f9e74b/run_manifest.json

@@ -0,0 +1,92 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "c17",
+  "started_at": "2026-05-19T15:56:05.034700+00:00",
+  "ended_at": "2026-05-19T15:56:14.460242+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c17_3e0379dd71f9e74b",
+    "problem_id": "v2p_c17_00afd17e5ca8ef68",
+    "dataset_id": "c17",
+    "template_id": "tpl_m4_group_condition_rate",
+    "template_name": "Grouped Condition Rate",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "direction_consistency",
+    "intended_facet_id": "conditional_rate_shift",
+    "variant_semantic_role": "within_group_proportion",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Condition Rate to probe direction_consistency with semantic role within_group_proportion. Focus on group_col=release_year, condition_col=type.",
+    "bindings": {
+      "group_col": "release_year",
+      "condition_col": "type",
+      "condition_value": "TV Show",
+      "positive_value": "Movie",
+      "negative_value": "TV Show",
+      "top_k": 16,
+      "top_n": 5,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.05,
+      "baseline_multiplier": 1.75,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 4,
+      "measure_threshold": 2019.0,
+      "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",
+      "condition_col"
+    ],
+    "coverage_target_min": "5",
+    "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;",
+    "notes": [
+      "default_facets=conditional_rate_shift",
+      "template_selection_mode=rule",
+      "problem_index_within_template=6",
+      "sql_variant_index=2/2",
+      "binding_index=101"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 9,
+    "problem_index_within_template": 6,
+    "sql_variant_index": 2,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/sql/v2q_c17_3e0379dd71f9e74b.sql",
+  "usage_summary": {
+    "dataset_id": "c17",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c17_3e0379dd71f9e74b",
+    "api_calls": 0,
+    "input_tokens": 14709,
+    "cached_input_tokens": 13696,
+    "output_tokens": 366,
+    "total_tokens": 15075,
+    "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": 9414.86,
+    "sql_execution_elapsed_ms_total": 6.32,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_3e0379dd71f9e74b/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_3e0379dd71f9e74b/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:56:14.452392+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": 9414.86, "started_at": "2026-05-19T15:56:05.036663+00:00", "ended_at": "2026-05-19T15:56:14.451556+00:00", "prompt_metrics": {"chars": 9429, "bytes_utf8": 9431, "lines": 243, "estimated_tokens": null}, "response_metrics": {"chars": 364, "bytes_utf8": 364, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14709, "cached_input_tokens": 13696, "output_tokens": 366, "reasoning_output_tokens": 267}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"release_year\\\",\\n       AVG(CASE WHEN \\\"type\\\" = 'TV Show' THEN 1 ELSE 0 END) AS condition_rate\\nFROM \\\"c17\\\"\\nGROUP BY \\\"release_year\\\"\\nORDER BY condition_rate DESC;\",\"notes\":\"Computes the within-release_year proportion of rows where \\\"type\\\" is 'TV Show' using the grouped condition rate template.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_3e0379dd71f9e74b/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "c17",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_c17_3e0379dd71f9e74b",
+  "api_calls": 0,
+  "input_tokens": 14709,
+  "cached_input_tokens": 13696,
+  "output_tokens": 366,
+  "total_tokens": 15075,
+  "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": 9414.86,
+  "sql_execution_elapsed_ms_total": 6.32,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_3e0379dd71f9e74b/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_43f3e0b05589c349/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=duration, measure_col=release_year.
+Result preview: [{"duration": "1 Season", "total_measure": 3615738}, {"duration": "2 Seasons", "total_measure": 857340}, {"duration": "3 Seasons", "total_measure": 401524}, {"duration": "90 min", "total_measure": 306278}, {"duration": "97 min", "total_measure": 294045}] Results were truncated.

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_43f3e0b05589c349/generated_sql.sql

@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_b
+-- sql_source_dataset_id: c17
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_c17_43f3e0b05589c349
+-- problem_id: v2p_c17_46819be5f5134667
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "duration", SUM(CAST("release_year" AS INTEGER)) AS total_measure
+FROM "c17"
+GROUP BY "duration"
+ORDER BY total_measure DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_43f3e0b05589c349/query_results.jsonl

@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_h2o_group_sum\nSELECT \"duration\", SUM(CAST(\"release_year\" AS INTEGER)) AS total_measure\nFROM \"c17\"\nGROUP BY \"duration\"\nORDER BY total_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"duration\\\", SUM(CAST(\\\"release_year\\\" AS INTEGER)) AS total_measure\\nFROM \\\"c17\\\"\\nGROUP BY \\\"duration\\\"\\nORDER BY total_measure DESC;\", \"columns\": [\"duration\", \"total_measure\"], \"rows\": [{\"duration\": \"1 Season\", \"total_measure\": 3615738}, {\"duration\": \"2 Seasons\", \"total_measure\": 857340}, {\"duration\": \"3 Seasons\", \"total_measure\": 401524}, {\"duration\": \"90 min\", \"total_measure\": 306278}, {\"duration\": \"97 min\", \"total_measure\": 294045}, {\"duration\": \"93 min\", \"total_measure\": 293871}, {\"duration\": \"94 min\", \"total_measure\": 293826}, {\"duration\": \"91 min\", \"total_measure\": 290100}, {\"duration\": \"95 min\", \"total_measure\": 275915}, {\"duration\": \"96 min\", \"total_measure\": 261790}, {\"duration\": \"92 min\", \"total_measure\": 259953}, {\"duration\": \"102 min\", \"total_measure\": 245767}, {\"duration\": \"98 min\", \"total_measure\": 241676}, {\"duration\": \"99 min\", \"total_measure\": 237647}, {\"duration\": \"88 min\", \"total_measure\": 233624}, {\"duration\": \"101 min\", \"total_measure\": 233430}, {\"duration\": \"103 min\", \"total_measure\": 229449}, {\"duration\": \"106 min\", \"total_measure\": 223504}, {\"duration\": \"100 min\", \"total_measure\": 217541}, {\"duration\": \"89 min\", \"total_measure\": 213407}, {\"duration\": \"104 min\", \"total_measure\": 209265}, {\"duration\": \"86 min\", \"total_measure\": 207557}, {\"duration\": \"87 min\", \"total_measure\": 203583}, {\"duration\": \"105 min\", \"total_measure\": 203416}, {\"duration\": \"107 min\", \"total_measure\": 197496}, {\"duration\": \"110 min\", \"total_measure\": 195405}, {\"duration\": \"4 Seasons\", \"total_measure\": 191511}, {\"duration\": \"108 min\", \"total_measure\": 175019}, {\"duration\": \"116 min\", \"total_measure\": 160897}, {\"duration\": \"112 min\", \"total_measure\": 148867}, {\"duration\": \"85 min\", \"total_measure\": 146935}, {\"duration\": \"113 min\", \"total_measure\": 138992}, {\"duration\": \"109 min\", \"total_measure\": 138925}, {\"duration\": \"111 min\", \"total_measure\": 136893}, {\"duration\": \"84 min\", \"total_measure\": 134936}, {\"duration\": \"5 Seasons\", \"total_measure\": 131053}, {\"duration\": \"83 min\", \"total_measure\": 130953}, {\"duration\": \"118 min\", \"total_measure\": 130838}, {\"duration\": \"119 min\", \"total_measure\": 126817}, {\"duration\": \"81 min\", \"total_measure\": 124879}, {\"duration\": \"115 min\", \"total_measure\": 122832}, {\"duration\": \"117 min\", \"total_measure\": 122789}, {\"duration\": \"114 min\", \"total_measure\": 112730}, {\"duration\": \"120 min\", \"total_measure\": 112627}, {\"duration\": \"121 min\", \"total_measure\": 108615}, {\"duration\": \"82 min\", \"total_measure\": 104657}, {\"duration\": \"124 min\", \"total_measure\": 104608}, {\"duration\": \"127 min\", \"total_measure\": 96477}, {\"duration\": \"78 min\", \"total_measure\": 90693}, {\"duration\": \"122 min\", \"total_measure\": 90616}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 8.85}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_43f3e0b05589c349/run_manifest.json

@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "c17",
+  "started_at": "2026-05-19T15:29:15.222889+00:00",
+  "ended_at": "2026-05-19T15:29:27.152275+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c17_43f3e0b05589c349",
+    "problem_id": "v2p_c17_46819be5f5134667",
+    "dataset_id": "c17",
+    "template_id": "tpl_h2o_group_sum",
+    "template_name": "Grouped Numeric Sum",
+    "family_id": "subgroup_structure",
+    "canonical_subitem_id": "internal_profile_stability",
+    "intended_facet_id": "subgroup_distribution_shift",
+    "variant_semantic_role": "collapsed_target_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=duration, measure_col=release_year.",
+    "bindings": {
+      "group_col": "duration",
+      "measure_col": "release_year",
+      "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": 2019.0,
+      "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",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;",
+    "notes": [
+      "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast",
+      "template_selection_mode=rule",
+      "problem_index_within_template=4",
+      "sql_variant_index=1/2",
+      "binding_index=3"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 1,
+    "problem_index_within_template": 4,
+    "sql_variant_index": 1,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/sql/v2q_c17_43f3e0b05589c349.sql",
+  "usage_summary": {
+    "dataset_id": "c17",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c17_43f3e0b05589c349",
+    "api_calls": 0,
+    "input_tokens": 14645,
+    "cached_input_tokens": 12032,
+    "output_tokens": 508,
+    "total_tokens": 15153,
+    "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": 11914.3,
+    "sql_execution_elapsed_ms_total": 8.85,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_43f3e0b05589c349/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_43f3e0b05589c349/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:29:27.141409+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": 11914.3, "started_at": "2026-05-19T15:29:15.225969+00:00", "ended_at": "2026-05-19T15:29:27.140292+00:00", "prompt_metrics": {"chars": 9177, "bytes_utf8": 9179, "lines": 240, "estimated_tokens": null}, "response_metrics": {"chars": 363, "bytes_utf8": 363, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14645, "cached_input_tokens": 12032, "output_tokens": 508, "reasoning_output_tokens": 416}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"duration\\\", SUM(CAST(\\\"release_year\\\" AS INTEGER)) AS total_measure\\nFROM \\\"c17\\\"\\nGROUP BY \\\"duration\\\"\\nORDER BY total_measure DESC;\",\"notes\":\"Uses the provided grouped numeric sum template with \\\"duration\\\" as the grouping column and casts TEXT \\\"release_year\\\" to INTEGER so SQLite can sum it numerically.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_43f3e0b05589c349/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "c17",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_c17_43f3e0b05589c349",
+  "api_calls": 0,
+  "input_tokens": 14645,
+  "cached_input_tokens": 12032,
+  "output_tokens": 508,
+  "total_tokens": 15153,
+  "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": 11914.3,
+  "sql_execution_elapsed_ms_total": 8.85,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_43f3e0b05589c349/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_459b53933ba802db/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=type, condition_col=type.
+Result preview: [{"type": "TV Show", "condition_ratio": 0.0}, {"type": "Movie", "condition_ratio": null}]

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_459b53933ba802db/generated_sql.sql

@@ -0,0 +1,26 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_b
+-- sql_source_dataset_id: c17
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: direction_consistency
+-- intended_facet_id: conditional_rate_shift
+-- variant_semantic_role: contrastive_conditional_view
+-- template_id: tpl_m4_group_ratio_two_conditions
+-- query_record_id: v2q_c17_459b53933ba802db
+-- problem_id: v2p_c17_9b1b6ba3ad09a2b9
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+    SELECT
+        "type",
+        SUM(CASE WHEN "type" = 'Movie' THEN 1 ELSE 0 END) AS numerator_count,
+        SUM(CASE WHEN "type" = 'TV Show' THEN 1 ELSE 0 END) AS denominator_count
+    FROM "c17"
+    GROUP BY "type"
+)
+SELECT
+    "type",
+    CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio
+FROM grouped
+ORDER BY condition_ratio DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_459b53933ba802db/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        \"type\",\n        SUM(CASE WHEN \"type\" = 'Movie' THEN 1 ELSE 0 END) AS numerator_count,\n        SUM(CASE WHEN \"type\" = 'TV Show' THEN 1 ELSE 0 END) AS denominator_count\n    FROM \"c17\"\n    GROUP BY \"type\"\n)\nSELECT\n    \"type\",\n    CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n    SELECT\\n        \\\"type\\\",\\n        SUM(CASE WHEN \\\"type\\\" = 'Movie' THEN 1 ELSE 0 END) AS numerator_count,\\n        SUM(CASE WHEN \\\"type\\\" = 'TV Show' THEN 1 ELSE 0 END) AS denominator_count\\n    FROM \\\"c17\\\"\\n    GROUP BY \\\"type\\\"\\n)\\nSELECT\\n    \\\"type\\\",\\n    CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\", \"columns\": [\"type\", \"condition_ratio\"], \"rows\": [{\"type\": \"TV Show\", \"condition_ratio\": 0.0}, {\"type\": \"Movie\", \"condition_ratio\": null}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 10.81}"}