Gemini 3.8 Flash (effort medium · thinking on) on Catch log checked against a made-up fishing regulations table
GGemini 3.8 Flashmedium · thinking on · Antigravity CLI 1.4.5 (agy -p) · cloud · 2026-10-22 · by @bobsiopener
- Estimated cost
- $0.32
- Wall time
- 3m
- Human step-ins
- 0
- Outcome
- Pass
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Summary
Exact prompt
# Catch log checked against a made-up regulations table `input.json` names `regulations.json` and `catch_log.csv`. All rules, species codes and data are **fictional** (not real fishing regulations). Write `solve.py` (Python 3 standard library only); `python solve.py input.json answer.json`. Fresh files are used too. ## Data - `regulations.json`: `species` maps a code to `aliases`, `season` ["MM-DD", "MM-DD"] inclusive (if start > end the season wraps over New Year), `min_in`, `max_in` (null = no maximum), `bag` (legal kept fish per angler per day for that species); `aggregate_daily` = legal kept fish per angler per day, all species. - `catch_log.csv`: `date` (YYYY-MM-DD), `angler`, `species`, `length`, `unit` (`in` or `cm`, any case), `action` (`kept` or `released`, any case). Process rows in file order; row numbers start at 1 for the first data row. ## Rules (first match wins) 1. Species: trim, case-insensitive match to a code or alias; no match -> `unknown_species` (species null). 2. `released` -> status `released` (never a violation, never counted). 3. Kept fish: length in inches (cm / 2.54 rounded to 2 decimals). Then: not in season -> `out_of_season`; below min -> `undersize`; above max -> `oversize`; angler already has `bag` legal fish of that species that date -> `over_bag`; angler already has `aggregate_daily` legal fish that date -> `over_aggregate`; else `legal` (and it counts toward the limits). Boundaries are legal (equal to min or max, first/last season day). 4. Every status except `legal` and `released` is a violation for that angler. ## answer.json `{"rows": [{"row", "species", "status"}, ...], "violations_by_angler": {angler: n} (only anglers with >0, sorted by name), "legal_kept_by_species": {code: n} (only >0, sorted)}` ## Scoring Hidden checks (partial credit; all must pass): `species_and_release` (species codes and which rows are released), `row_statuses` (every row exact), `summaries`, `fresh_run_1`, `fresh_run_2`. 60-second limit per run.
Aliases with odd spacing and case, cm conversion near limits, a season that wraps New Year with boundary dates, slot maximum, and bag/aggregate limits that only count legal fish in log order. Original benchmark task written for usecaserank.com. Headless, offline run on a reproducible fixture. Cost shown is a list-price API-equivalent estimate (run on a Google account via Antigravity CLI, not billed per token).
Benchmark code for comparing AI models, not navigation or safety software.
Success criteria: 1. species_and_release 2. row_statuses 3. summaries 4. fresh_run_1 5. fresh_run_2
Setup notes: Use Case Scout batch10 case k04-catch-log-regulations (offline fixture). Prepared with batch10/prepare.sh on the shared box; only TASK.md + starting files went to the agent machine, hidden keys stayed on the box. Prompt = TASK.md verbatim. Flags: -p --model gemini-3.8-flash-medium --sandbox --dangerously-skip-permissions --disable-slash-commands --output-format stream-json, cwd=workdir. Scored on the box with `python score.py WORKDIR KEYDIR`. Single run, no retries, no human input. Requested model gemini-3.8-flash-medium (effort medium); priced at the base model row gemini-3.8-flash (pricing.json, https://ai.google.dev/gemini-api/docs/pricing). Score: 5/5. Cost is an ESTIMATE: measured tokens x pricing.json list price (Google account, nothing billed per token); output_tokens include thinking tokens. Tool calls 21 (0 failed). Single run.
Estimated cost List-price estimate; not actually billed.
Metrics
- Estimated cost
- $0.32
- Wall time
- 3m
- Human step-ins
- 0
- Turns
- 22
| Model | Input tok | Output tok | Cost |
|---|---|---|---|
| GGemini 3.8 Flashgoogle/gemini-3.8-flasheffort medium · thinking on | 783,257 | 40,021 | $0.32 |
Reproduce this run
- Use the use case prompt on the use case page.
- Same setup: Gemini 3.8 Flash (google/gemini-3.8-flash, effort medium · thinking on) via
Antigravity CLI 1.4.5 (agy -p), cloud. - It counts as a success only if it meets every success criterion: 1. species_and_release 2. row_statuses 3. summaries 4. fresh_run_1 5. fresh_run_2
- Log model, tokens, wall time, human step-ins and the evidence log, then submit it as a reproduction. A different model? Submit a head-to-head rerun.
How runs are scored: Methodology.
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Automated checks
Trust 80% comes from these checks (how Trust % works).
- Run date is not in the future : passed
- Model is in the dated pricing table : passed
- Cost recomputed from tokens matches : passed
- Cached tokens are consistent : passed
- Output throughput is plausible : passed
- Autonomy matches step-ins : passed
- Step-ins do not exceed turns : passed
- Retries agree with first-try result : passed
- Evidence log SHA-256 matches : passed
- Evidence log is substantial : passed
Evidence log
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{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 0, "state": "DONE", "step_type": "user_input"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 1, "state": "DONE", "step_type": "agent_response", "duration_seconds": 2.958037697, "usage": {"input_tokens": 8382, "output_tokens": 106, "thinking_tokens": 69, "cache_read_tokens": 0, "total_tokens": 8488}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 2, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "ls -la"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 2, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.289131547, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "ls -la"}, "output": "Command exited with code 0.\n\nCommand output:\ntotal 24\r\ndrwxr-xr-x 2 bob bob 4096 Oct 22 10:56 .\r\ndrwxrwxr-x 3 bob bob 4096 Oct 22 11:04 ..\r\n-rw-r--r-- 1 bob bob 2000 Oct 22 10:56 TASK.md\r\n-rw-r--r-- 1 bob bob 2020 Oct 22 10:56 catch_log.csv\r\n-rw-r--r-- 1 bob bob 59 Oct 22 10:56 input.json\r\n-rw-r--r-- 1 bob bob 720 Oct 22 10:56 regulations.json\r\n"}}}
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{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 4, "state": "ACTIVE", "step_type": "tool", "tool_name": "read_file", "tool_info": {"name": "read_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k04/work/TASK.md"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 4, "state": "DONE", "step_type": "tool", "tool_name": "read_file", "duration_seconds": 0.049390829, "tool_info": {"name": "read_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k04/work/TASK.md"}, "output": "19 lines, 2000 bytes"}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 5, "state": "DONE", "step_type": "agent_response", "duration_seconds": 2.948509814, "usage": {"input_tokens": 5500, "output_tokens": 75, "thinking_tokens": 24, "cache_read_tokens": 4051, "total_tokens": 5575}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 6, "state": "ACTIVE", "step_type": "tool", "tool_name": "read_file", "tool_info": {"name": "read_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k04/work/input.json"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 6, "state": "DONE", "step_type": "tool", "tool_name": "read_file", "duration_seconds": 0.360224445, "tool_info": {"name": "read_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k04/work/input.json"}, "output": "1 lines, 59 bytes"}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 7, "state": "DONE", "step_type": "agent_response", "duration_seconds": 2.413276996, "usage": {"input_tokens": 9740, "output_tokens": 62, "thinking_tokens": 10, "cache_read_tokens": 0, "total_tokens": 9802}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 8, "state": "ACTIVE", "step_type": "tool", "tool_name": "read_file", "tool_info": {"name": "read_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k04/work/regulations.json"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 8, "state": "DONE", "step_type": "tool", "tool_name": "read_file", "duration_seconds": 0.099670892, "tool_info": {"name": "read_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k04/work/regulations.json"}, "output": "58 lines, 720 bytes"}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 9, "state": "DONE", "step_type": "agent_response", "duration_seconds": 3.5023444550000002, "usage": {"input_tokens": 10432, "output_tokens": 64, "thinking_tokens": 11, "cache_read_tokens": 0, "total_tokens": 10496}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 10, "state": "ACTIVE", "step_type": "tool", "tool_name": "read_file", "tool_info": {"name": "read_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k04/work/catch_log.csv"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 10, "state": "DONE", "step_type": "tool", "tool_name": "read_file", "duration_seconds": 0.035348574, "tool_info": {"name": "read_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k04/work/catch_log.csv"}, "output": "56 lines, 2020 bytes"}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 11, "state": "DONE", "step_type": "agent_response", "duration_seconds": 8.109674077, "usage": {"input_tokens": 12163, "output_tokens": 2068, "thinking_tokens": 1957, "cache_read_tokens": 0, "total_tokens": 14231}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 12, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport csv\nwith open('catch_log.csv') as f:\n r = csv.DictReader(f)\n for i, row in enumerate(r, 1):\n if row['action'].strip().lower() == 'released':\n print(i, row)\n\""}}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 12, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.299793036, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport csv\nwith open('catch_log.csv') as f:\n r = csv.DictReader(f)\n for i, row in enumerate(r, 1):\n if row['action'].strip().lower() == 'released':\n print(i, row)\n\""}, "output": "Command exited with code 0.\n\nCommand output:\n11 {'date': '2026-09-30', 'angler': 'ben', 'species': 'STB', 'length': '32', 'unit': 'in', 'action': 'released'}\r\n16 {'date': '2026-09-30', 'angler': 'ben', 'species': 'BSB', 'length': '14.5', 'unit': 'in', 'action': 'released'}\r\n29 {'date': '2026-10-20', 'angler': 'ben', 'species': 'BSB', 'length': '14.5', 'unit': 'in', 'action': 'released'}\r\n38 {'date': '2026-10-20', 'angler': 'ana', 'species': 'fluke', 'length': '19.5', 'unit': 'in', 'action': 'released'}\r\n41 {'date': '2026-10-14', 'angler': 'ben', 'species': 'fluke', 'length': '18', 'unit': 'in', 'action': 'released'}\r\n42 {'date': '2026-10-14', 'angler': 'ben', 'species': 'sea bass', 'length': '43.2', 'unit': 'cm', 'action': 'released'}\r\n44 {'date': '2026-10-14', 'angler': 'ben', 'species': 'fluke', 'length': '19.5', 'unit': 'in', 'action': 'released'}\r\n50 {'date': '2026-11-03', 'angler': 'ben', 'species': 'sea bass', 'length': '13', 'unit': 'in', 'action': 'released'}\r\n53 {'date': '2026-11-03', 'angler': 'ben', 'species': 'Tautog', 'length': '49.5', 'unit': 'cm', 'action': 'released'}\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 13, "state": "DONE", "step_type": "agent_response", "duration_seconds": 29.410325842, "usage": {"input_tokens": 14778, "output_tokens": 10331, "thinking_tokens": 10191, "cache_read_tokens": 0, "total_tokens": 25109}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 14, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport json, csv\n\nwith open('regulations.json') as f:\n regs = json.load(f)\n\nspecies_lookup = {}\nfor code, info in regs['species'].items():\n species_lookup[code.strip().lower()] = code\n for alias in info.get('aliases', []):\n species_lookup[alias.strip().lower()] = code\n\nprint('Lookup keys:', species_lookup.keys())\n\""}}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 14, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.293915136, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport json, csv\n\nwith open('regulations.json') as f:\n regs = json.load(f)\n\nspecies_lookup = {}\nfor code, info in regs['species'].items():\n species_lookup[code.strip().lower()] = code\n for alias in info.get('aliases', []):\n species_lookup[alias.strip().lower()] = code\n\nprint('Lookup keys:', species_lookup.keys())\n\""}, "output": "Command exited with code 0.\n\nCommand output:\nLookup keys: dict_keys(['stb', 'striper', 'striped bass', 'rockfish', 'flk', 'fluke', 'summer flounder', 'bsb', 'black sea bass', 'sea bass', 'tog', 'tautog', 'blackfish'])\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 15, "state": "DONE", "step_type": "agent_response", "duration_seconds": 8.111631222, "usage": {"input_tokens": 25254, "output_tokens": 871, "thinking_tokens": 42, "cache_read_tokens": 0, "total_tokens": 26125}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 16, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport json, csv\n\nwith open('regulations.json') as f:\n regs = json.load(f)\n\nspecies_lookup = {}\nfor code, info in regs['species'].items():\n species_lookup[code.strip().lower()] = code\n for alias in info.get('aliases', []):\n species_lookup[alias.strip().lower()] = code\n\naggregate_daily = regs.get('aggregate_daily', float('inf'))\n\ndef in_season(date_str, season):\n # date_str: YYYY-MM-DD\n mm_dd = date_str[5:]\n start, end = season\n if start <= end:\n return start <\u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 16, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.290229058, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport json, csv\n\nwith open('regulations.json') as f:\n regs = json.load(f)\n\nspecies_lookup = {}\nfor code, info in regs['species'].items():\n species_lookup[code.strip().lower()] = code\n for alias in info.get('aliases', []):\n species_lookup[alias.strip().lower()] = code\n\naggregate_daily = regs.get('aggregate_daily', float('inf'))\n\ndef in_season(date_str, season):\n # date_str: YYYY-MM-DD\n mm_dd = date_str[5:]\n start, end = season\n if start <= end:\n return start <\u2026"}, "output": "Command exited with code 0.\n\nCommand output:\n 1: 2026-12-31 ben raw=blackfish sp=TOG act=kept -> legal\r\n 2: 2026-12-31 ana raw=Striped Bass sp=STB act=kept -> out_of_season\r\n 3: 2026-12-31 ana raw=BSB sp=BSB act=kept -> legal\r\n 4: 2026-12-31 ben raw=fluke sp=FLK act=kept -> out_of_season\r\n 5: 2026-12-31 ben raw=Summer Flounder sp=FLK act=kept -> out_of_season\r\n 6: 2026-12-31 ana raw=STB sp=STB act=kept -> out_of_season\r\n 7: 2026-12-31 ben raw=Striped Bass sp=STB act=kept -> out_of_season\r\n 8: 2026-12-31 ana raw=blackfish sp=TOG act=kept -> legal\r\n 9: 2026-12-31 ben raw=Tautog sp=TOG act=kept -> legal\r\n10: 2026-12-31 ana raw=BSB sp=BSB act=kept -> undersize\r\n11: 2026-09-30 ben raw=STB sp=STB act=released -> released\r\n12: 2026-09-30 ana raw=Summer Flounder sp=FLK act=kept -> legal\r\n13: 2026-09-30 ana raw=bluegill sp=None act=kept -> unknown_species\r\n14: 2026-09-30 ben raw=fluke sp=FLK act=kept -> legal\r\n15: 2026-09-30 ben raw=blackfish sp=TOG act=kept -> out_of_season\r\n16: 2026-09-30 ben raw=BSB sp=BSB act=released -> released\r\n17: 2026-09-30 ben raw=fluke sp=FLK act=kept -> legal\r\n18: 2026-09-30 ben raw=blackfish sp=TOG act=kept -> out_of_season\r\n19: 2026-09-30 ben raw=BSB sp=BSB act=kept -> legal\r\n20: 2026-01-20 ana raw=sea bass sp=BSB act=kept -> out_of_season\r\n21: 2026-01-20 ana raw=Summer Flounder sp=FLK act=kept -> out_of_season\r\n22: 2026-01-20 ben raw=blackfish sp=TOG act=kept -> legal\r\n23: 2026-01-20 ana raw=sea bass sp=BSB act=kept -> out_of_season\r\n24: 2026-01-20 ana raw=bluegill sp=None act=kept -> unknown_species\r\n25: 2026-01-20 ana raw=sea bass sp=BSB act=kept -> out_of_season\r\n26: 2026-01-20 ana raw=blackfish sp=TOG act=kept -> legal\r\n27: 2026-01-20 ben raw=striper sp=STB act=kept -> out_of_season\r\n28: 2026-10-20 ben raw=Tautog sp=TOG act=kept -> undersize\r\n29: 2026-10-20 ben raw=BSB sp=BSB act=released -> released\r\n30: 2026-10-20 ben raw=fluke sp=FLK act=kept -> out_of_season\r\n31: 2026-10-20 ana raw=sea bass sp=BSB act=kept -> legal\r\n32: 2026-10-20 ana raw=rockfish sp=STB act=kept -> legal\r\n33: 2026-10-20 ana raw=STB sp=STB act=kept -> legal\r\n34: 2026-10-20 ana raw=blackfish sp=TOG act=kept -> over_aggregate\r\n35: 2026-10-20 ben raw=Striped Bass sp=STB act=kept -> legal\r\n36: 2026-10-20 ben raw=bluegill sp=None act=kept -> unknown_species\r\n37: 2026-10-20 ana raw=STB sp=STB act=kept -> over_bag\r\n38: 2026-10-20 ana raw=fluke sp=FLK act=released -> released\r\n39: 2026-10-14 ben raw=STB sp=STB act=kept -> legal\r\n40: 2026-10-14 ben raw=Striped Bass sp=STB act=kept -> oversize\r\n41: 2026-10-14 ben raw=fluke sp=FLK act=released -> released\r\n42: 2026-10-14 ben raw=sea bass sp=BSB act=released -> released\r\n43: 2026-10-14 ana raw=Summer Flounder sp=FLK act=kept -> out_of_season\r\n44: 2026-10-14 ben raw=fluke sp=FLK act=released -> released\r\n45: 2026-10-14 ben raw=fluke sp=FLK act=kept -> out_of_season\r\n46: 2026-11-03 ben raw=fluke sp=FLK act=kept -> out_of_season\r\n47: 2026-11-03 ana raw=fluke sp=FLK act=kept -> out_of_season\r\n48: 2026-11-03 ana raw=sea bass sp=BSB act=kept -> undersize\r\n49: 2026-11-03 ana raw=rockfish sp=STB act=kept -> legal\r\n50: 2026-11-03 ben raw=sea bass sp=BSB act=released -> released\r\n51: 2026-11-03 ben raw=Tautog sp=TOG act=kept -> legal\r\n52: 2026-11-03 ben raw=BSB sp=BSB act=kept -> legal\r\n53: 2026-11-03 ben raw=Tautog sp=TOG act=released -> released\r\n54: 2026-11-03 ana raw=Summer Flounder sp=FLK act=kept -> out_of_season\r\n55: 2026-11-03 ana raw=BSB sp=BSB act=kept -> legal\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 17, "state": "DONE", "step_type": "agent_response", "duration_seconds": 20.321217108, "usage": {"input_tokens": 3660, "output_tokens": 5217, "thinking_tokens": 5064, "cache_read_tokens": 24433, "total_tokens": 8877}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 18, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nfor i in range(1, 1000):\n val = i / 10.0\n res = val / 2.54\n # check if res * 100 is close to an integer + 0.5\n rem = (res * 100) % 1\n if abs(rem - 0.5) < 1e-4:\n print(f'{val}: {res}')\n\""}}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 18, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.889070951, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nfor i in range(1, 1000):\n val = i / 10.0\n res = val / 2.54\n # check if res * 100 is close to an integer + 0.5\n rem = (res * 100) % 1\n if abs(rem - 0.5) < 1e-4:\n print(f'{val}: {res}')\n\""}, "output": "Command exited with code 0.\n\nNo output from the command."}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 19, "state": "DONE", "step_type": "agent_response", "duration_seconds": 9.504302831, "usage": {"input_tokens": 8949, "output_tokens": 2483, "thinking_tokens": 1406, "cache_read_tokens": 24448, "total_tokens": 11432}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 20, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport json, csv\n\nwith open('regulations.json') as f:\n regs = json.load(f)\n\nspecies_lookup = {}\nfor code, info in regs['species'].items():\n species_lookup[code.strip().lower()] = code\n for alias in info.get('aliases', []):\n species_lookup[alias.strip().lower()] = code\n\naggregate_daily = regs.get('aggregate_daily', float('inf'))\n\ndef in_season(date_str, season):\n mm_dd = date_str[5:]\n start, end = season\n if start <= end:\n return start <= mm_dd <= end\n else:\n \u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 20, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.310754624, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport json, csv\n\nwith open('regulations.json') as f:\n regs = json.load(f)\n\nspecies_lookup = {}\nfor code, info in regs['species'].items():\n species_lookup[code.strip().lower()] = code\n for alias in info.get('aliases', []):\n species_lookup[alias.strip().lower()] = code\n\naggregate_daily = regs.get('aggregate_daily', float('inf'))\n\ndef in_season(date_str, season):\n mm_dd = date_str[5:]\n start, end = season\n if start <= end:\n return start <= mm_dd <= end\n else:\n \u2026"}, "output": "Command exited with code 0.\n\nCommand output:\nViolations by angler: {'ana': 15, 'ben': 12}\r\nLegal kept by species: {'BSB': 5, 'FLK': 3, 'STB': 5, 'TOG': 6}\r\nTotal rows: 55\r\nStatus counts:\r\n legal: 19\r\n out_of_season: 18\r\n over_aggregate: 1\r\n over_bag: 1\r\n oversize: 1\r\n released: 9\r\n undersize: 3\r\n unknown_species: 3\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 21, "state": "DONE", "step_type": "agent_response", "duration_seconds": 30.918113514, "usage": {"input_tokens": 3490, "output_tokens": 9767, "thinking_tokens": 8041, "cache_read_tokens": 32601, "total_tokens": 13257}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 22, "state": "ACTIVE", "step_type": "tool", "tool_name": "write_file", "tool_info": {"name": "write_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k04/work/solve.py"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 22, "state": "DONE", "step_type": "tool", "tool_name": "write_file", "duration_seconds": 0.099956094, "tool_info": {"name": "write_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k04/work/solve.py"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 23, "state": "DONE", "step_type": "agent_response", "duration_seconds": 2.779861075, "usage": {"input_tokens": 13304, "output_tokens": 69, "thinking_tokens": 19, "cache_read_tokens": 32630, "total_tokens": 13373}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 24, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 solve.py input.json answer.json"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 24, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.506165096, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 solve.py input.json answer.json"}, "output": "Command exited with code 1.\n\nThere were sandbox errors that may or may not be related to the failure. If you think the failure is because of running in the sandbox, you can run the command again with `BypassSandbox` set to true to request explicit user permission.\n\nCommand output:\nTraceback (most recent call last):\r\n File \"/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k04/work/solve.py\", line 159, in <module>\r\n main()\r\n ~~~~^^\r\n File \"/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k04/work/solve.py\", line 154, in main\r\n with open(output_path, \"w\", encoding=\"utf-8\") as f:\r\n ~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\r\nOSError: [Errno 30] Read-only file system: 'answer.json'\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 25, "state": "DONE", "step_type": "agent_response", "duration_seconds": 2.942498484, "usage": {"input_tokens": 5528, "output_tokens": 123, "thinking_tokens": 65, "cache_read_tokens": 40780, "total_tokens": 5651}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 26, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"import os; print(os.access('.', os.W_OK))\""}}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 26, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.305296498, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"import os; print(os.access('.', os.W_OK))\""}, "output": "Command exited with code 0.\n\nCommand output:\nFalse\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 27, "state": "DONE", "step_type": "agent_response", "duration_seconds": 2.349083419, "usage": {"input_tokens": 5746, "output_tokens": 116, "thinking_tokens": 52, "cache_read_tokens": 40772, "total_tokens": 5862}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 28, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 solve.py input.json /tmp/answer.json && cat /tmp/answer.json"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 28, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.398203402, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 solve.py input.json /tmp/answer.json && cat /tmp/answer.json"}, "output": "Command exited with code 0.\n\nCommand output:\n{\r\n \"rows\": [\r\n {\r\n \"row\": 1,\r\n \"species\": \"TOG\",\r\n \"status\": \"legal\"\r\n },\r\n {\r\n \"row\": 2,\r\n \"species\": \"STB\",\r\n \"status\": \"out_of_season\"\r\n },\r\n {\r\n \"row\": 3,\r\n \"species\": \"BSB\",\r\n \"status\": \"legal\"\r\n },\r\n {\r\n \"row\": 4,\r\n \"species\": \"FLK\",\r\n \"status\": \"out_of_season\"\r\n },\r\n {\r\n \"row\": 5,\r\n \"species\": \"FLK\",\r\n \"status\": \"out_of_season\"\r\n },\r\n {\r\n \"row\": 6,\r\n \"species\": \"STB\",\r\n \"status\": \"out_of_season\"\r\n },\r\n {\r\n \"row\": 7,\r\n \"species\": \"STB\",\r\n \"status\": \"out_of_season\"\r\n },\r\n {\r\n \"row\": 8,\r\n \"species\": \"TOG\",\r\n \"status\": \"legal\"\r\n },\r\n {\r\n \"row\": 9,\r\n \"species\": \"TOG\",\r\n \"status\": \"legal\"\r\n },\r\n {\r\n \"row\": 10,\r\n \"species\": \"BSB\",\r\n \"status\": \"undersize\"\r\n },\r\n {\r\n \"row\": 11,\r\n \"species\": \"STB\",\r\n \"status\": \"released\"\r\n },\r\n {\r\n \"row\": 12,\r\n \"species\": \"FLK\",\r\n \"status\": \"legal\"\r\n },\r\n {\r\n \"row\": 13,\r\n \"species\": null,\r\n \"status\": \"unknown_species\"\r\n },\r\n {\r\n \"row\": 14,\r\n \"species\": \"FLK\",\r\n \"status\": \"legal\"\r\n },\r\n {\r\n \"row\": 15,\r\n \"species\": \"TOG\",\r\n \"status\": \"out_of_season\"\r\n },\r\n {\r\n \"row\": 16,\r\n \"species\": \"BSB\",\r\n \"status\": \"released\"\r\n },\r\n {\r\n \"row\": 17,\r\n \"species\": \"FLK\",\r\n \"status\": \"legal\"\r\n },\r\n {\r\n \"row\": 18,\r\n \"species\": \"TOG\",\r\n \"status\": \"out_of_season\"\r\n },\r\n {\r\n \"row\": 19,\r\n \"species\": \"BSB\",\r\n \"status\": \"legal\"\r\n },\r\n {\r\n \"row\": 20,\r\n \"species\": \"BSB\",\r\n \"status\": \"out_of_season\"\r\n },\r\n {\r\n \"row\": 21,\r\n \"species\": \"FLK\",\r\n \"status\": \"out_of_season\"\r\n },\r\n {\r\n \"row\": 22,\r\n \"species\": \"TOG\",\r\n \"status\": \"legal\"\r\n },\r\n {\r\n \"row\": 23,\r\n \"species\": \"BSB\",\r\n \"status\": \"out_of_season\"\r\n },\r\n {\r\n \"row\": 24,\r\n \"species\": null,\r\n \"status\": \"unknown_species\"\r\n },\r\n {\r\n \"row\": 25,\r\n \"species\": \"BSB\",\r\n \"status\": \"out_of_season\"\r\n },\r\n {\r\n \"row\": 26,\r\n \"species\": \"TOG\",\r\n \"status\": \"legal\"\r\n },\r\n {\r\n \"row\": 27,\r\n \"species\": \"STB\",\r\n \"status\": \"out_of_season\"\r\n },\r\n {\r\n \"row\": 28,\r\n \"species\": \"TOG\",\r\n \"status\": \"undersize\"\r\n },\r\n {\r\n \"row\": 29,\r\n \"species\": \"BSB\",\r\n \"status\": \"released\"\r\n },\r\n {\r\n \"row\": 30,\r\n \"species\": \"FLK\",\r\n \"status\": \"out_of_season\"\r\n },\r\n {\r\n \"row\": 31,\r\n \"species\": \"BSB\",\r\n \"status\": \"legal\"\r\n },\r\n {\r\n \"row\": 32,\r\n \"species\": \"STB\",\r\n \"status\": \"legal\"\r\n },\r\n {\r\n \"row\": 33,\r\n \"species\": \"STB\",\r\n \"status\": \"legal\"\r\n },\r\n {\r\n \"row\": 34,\r\n \"species\": \"TOG\",\r\n \"status\": \"over_aggregate\"\r\n },\r\n {\r\n \"row\": 35,\r\n \"species\": \"STB\",\r\n \"status\": \"legal\"\r\n },\r\n {\r\n \"row\": 36,\r\n \"species\": null,\r\n \"status\": \"unknown_species\"\r\n },\r\n {\r\n \"row\": 37,\r\n \"species\": \"STB\",\r\n \"status\": \"over_bag\"\r\n },\r\n {\r\n \"row\": 38,\r\n \"species\": \"FLK\",\r\n \"status\": \"released\"\r\n },\r\n {\r\n \"row\": 39,\r\n \"species\": \"STB\",\r\n \"status\": \"legal\"\r\n },\r\n {\r\n \"row\": 40,\r\n \"species\": \"STB\",\r\n \"status\": \"oversize\"\r\n },\r\n {\r\n \"row\": 41,\r\n \"species\": \"FLK\",\r\n \"status\": \"released\"\r\n },\r\n {\r\n \"row\": 42,\r\n \"species\": \"BSB\",\r\n \"status\": \"released\"\r\n },\r\n {\r\n \"row\": 43,\r\n \"species\": \"FLK\",\r\n \"status\": \"out_of_season\"\r\n },\r\n {\r\n \"row\": 44,\r\n \"species\": \"FLK\",\r\n \"status\": \"released\"\r\n },\r\n {\r\n \"row\": 45,\r\n \"species\": \"FLK\",\r\n \"status\": \"out_of_season\"\r\n },\r\n {\r\n \"row\": 46,\r\n \"species\": \"FLK\",\r\n \"status\": \"out_of_season\"\r\n },\r\n {\r\n \"row\": 47,\r\n \"species\": \"FLK\",\r\n \"status\": \"out_of_season\"\r\n },\r\n {\r\n \"row\": 48,\r\n \"species\": \"BSB\",\r\n \"status\": \"undersize\"\r\n },\r\n {\r\n \"row\": 49,\r\n \"species\": \"STB\",\r\n \"status\": \"legal\"\r\n },\r\n {\r\n \"row\": 50,\r\n \"species\": \"BSB\",\r\n \"status\": \"released\"\r\n },\r\n {\r\n \"row\": 51,\r\n \"species\": \"TOG\",\r\n \"status\": \"legal\"\r\n },\r\n {\r\n \"row\": 52,\r\n \"species\": \"BSB\",\r\n \"status\": \"legal\"\r\n },\r\n {\r\n \"row\": 53,\r\n \"species\": \"TOG\",\r\n \"status\": \"released\"\r\n },\r\n {\r\n \"row\": 54,\r\n \"species\": \"FLK\",\r\n \"status\": \"out_of_season\"\r\n },\r\n {\r\n \"row\": 55,\r\n \"species\": \"BSB\",\r\n \"status\": \"legal\"\r\n }\r\n ],\r\n \"violations_by_angler\": {\r\n \"ana\": 15,\r\n \"ben\": 12\r\n },\r\n \"legal_kept_by_species\": {\r\n \"BSB\": 5,\r\n \"FLK\": 3,\r\n \"STB\": 5,\r\n \"TOG\": 6\r\n }\r\n}"}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 29, "state": "DONE", "step_type": "agent_response", "duration_seconds": 2.37097505, "usage": {"input_tokens": 3781, "output_tokens": 90, "thinking_tokens": 69, "cache_read_tokens": 44849, "total_tokens": 3871}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 30, "state": "ACTIVE", "step_type": "tool", "tool_name": "read_file", "tool_info": {"name": "read_file", "parameters": {"Path": "/tmp/answer.json"}}}}
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{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 35, "state": "DONE", "step_type": "agent_response", "duration_seconds": 2.266690322, "usage": {"input_tokens": 4498, "output_tokens": 77, "thinking_tokens": 27, "cache_read_tokens": 53013, "total_tokens": 4575}}}
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{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 36, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.304733254, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 solve.py input.json /tmp/answer.json"}, "output": "Command exited with code 0.\n\nNo output from the command."}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 37, "state": "DONE", "step_type": "agent_response", "duration_seconds": 1.8441992539999998, "usage": {"input_tokens": 4670, "output_tokens": 75, "thinking_tokens": 21, "cache_read_tokens": 53005, "total_tokens": 4745}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 38, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "diff -u /tmp/answer.json answer.json"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 38, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.303751115, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "diff -u /tmp/answer.json answer.json"}, "output": "Command exited with code 1.\n\nCommand output:\n--- /tmp/answer.json\t2026-10-22 11:07:02.763869389 -0400\r\n+++ answer.json\t2026-10-22 11:06:50.966714262 -0400\r\n@@ -286,4 +286,4 @@\r\n \"STB\": 5,\r\n \"TOG\": 6\r\n }\r\n-}\r\n\\ No newline at end of file\r\n+}\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 39, "state": "DONE", "step_type": "agent_response", "duration_seconds": 6.041216453, "usage": {"input_tokens": 4967, "output_tokens": 2006, "thinking_tokens": 34, "cache_read_tokens": 52997, "total_tokens": 6973}}}
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{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 40, "state": "DONE", "step_type": "tool", "tool_name": "write_file", "duration_seconds": 0.046777779, "tool_info": {"name": "write_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k04/work/answer.json"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 41, "state": "DONE", "step_type": "agent_response", "duration_seconds": 1.9290053569999999, "usage": {"input_tokens": 2972, "output_tokens": 55, "thinking_tokens": 18, "cache_read_tokens": 57074, "total_tokens": 3027}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 42, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "ls -la"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 42, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.281709623, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "ls -la"}, "output": "Command exited with code 0.\n\nCommand output:\ntotal 40\r\ndrwxr-xr-x 2 bob bob 4096 Oct 22 11:06 .\r\ndrwxrwxr-x 3 bob bob 4096 Oct 22 11:04 ..\r\n-rw-r--r-- 1 bob bob 2000 Oct 22 10:56 TASK.md\r\n-rw-r--r-- 1 bob bob 4676 Oct 22 11:07 answer.json\r\n-rw-r--r-- 1 bob bob 2020 Oct 22 10:56 catch_log.csv\r\n-rw-r--r-- 1 bob bob 59 Oct 22 10:56 input.json\r\n-rw-r--r-- 1 bob bob 720 Oct 22 10:56 regulations.json\r\n-rw-r--r-- 1 bob bob 5830 Oct 22 11:07 solve.py\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "The solution has been im"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "plemented in [`solve.py`"}}
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{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "-medium/k04/"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "work/solve.py) and verified against "}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "the provided datasets.\n\n"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "### Implemen"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "tation Summary\n- **Input"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " Parsing & Path Resolution**: Dynamically resolv"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "es `regulati"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ons` and `log` paths rel"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ative to `in"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "put.json` or current wor"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "king directory.\n- **Spec"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ies Resolution**: Matches species st"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "rings against codes and "}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "aliases (trimmed, case-insensitive)."}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " Unmatched entries recei"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ve status `u"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "nknown_species` with `species: null`.\n- **Action"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " Handling**: Rows marked"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " `released` "}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "receive status `released"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "` without co"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "unting toward catch limits or violations.\n- **Le"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ngth Conversion & Bounda"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ry Rules**: "}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "Lengths in `cm` are conv"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "erted to inc"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "hes via `round(cm / 2.54, 2)`. Boundary values e"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "qual to minimum or maxim"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "um lengths a"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "nd season start/end days"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " are treated as legal.\n- **Season Va"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "lidation**: Compares `MM"}}
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{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " wrapping across New Yea"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "r.\n- **Quota Tracking**: Tracks lega"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "l kept fish counts per angler and date for both "}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "individual species (`bag`) and across all species (`aggregate_daily`). O"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "nly legal ke"}}
{"event": "step_update", "step_update": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "step_index": 43, "state": "DONE", "step_type": "agent_response", "text_delta": "pt catches increment quotas.\n- **Output Generation**: Produces the formatted result matching [`answer.json`](file:///home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k04/work/answer.json) with sorted `violations_by_angler` and `legal_kept_by_species` summaries.\n", "duration_seconds": 5.236334688, "usage": {"input_tokens": 3357, "output_tokens": 703, "thinking_tokens": 356, "cache_read_tokens": 57066, "total_tokens": 4060}}}
{"event": "result", "result": {"conversation_id": "fb8329c4-0566-4a58-afb1-eaa7c0b444ee", "status": "SUCCESS", "response": "The solution has been implemented in [`solve.py`](file:///home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k04/work/solve.py) and verified against the provided datasets.\n\n### Implementation Summary\n- **Input Parsing & Path Resolution**: Dynamically resolves `regulations` and `log` paths relative to `input.json` or current working directory.\n- **Species Resolution**: Matches species strings against codes and aliases (trimmed, case-insensitive). Unmatched entries receive status `unknown_species` with `species: null`.\n- **Action Handling**: Rows marked `released` receive status `released` without counting toward catch limits or violations.\n- **Length Conversion & Boundary Rules**: Lengths in `cm` are converted to inches via `round(cm / 2.54, 2)`. Boundary values equal to minimum or maximum lengths and season start/end days are treated as legal.\n- **Season Validation**: Compares `MM-DD` against species season dates, properly handling seasons wrapping across New Year.\n- **Quota Tracking**: Tracks legal kept fish counts per angler and date for both individual species (`bag`) and across all species (`aggregate_daily`). Only legal kept catches increment quotas.\n- **Output Generation**: Produces the formatted result matching [`answer.json`](file:///home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k04/work/answer.json) with sorted `violations_by_angler` and `legal_kept_by_species` summaries.\n", "duration_seconds": 167.458598583, "num_turns": 1, "usage": {"input_tokens": 171755, "output_tokens": 40021, "thinking_tokens": 29302, "cache_read_tokens": 611502, "total_tokens": 211776}}}