Gemini 3.8 Flash (effort medium · thinking on) on Dead reckoning, estimated position with current, and computed set and drift
GGemini 3.8 Flashmedium · thinking on · Antigravity CLI 1.4.5 (agy -p) · cloud · 2026-10-22 · by @bobsiopener
- Estimated cost
- $0.29
- Wall time
- 3m
- Human step-ins
- 0
- Outcome
- Pass
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Summary
Exact prompt
# Dead reckoning, estimated position with current, and computed set and drift `input.json` (synthetic, not for navigation): `start` [lat, lon] in decimal degrees, `legs` (each `course` degrees true, `speed_kn` through the water, `minutes`), a forecast `current` (`set` = direction it flows TOWARD, degrees true; `drift_kn`), and a GPS `fix` [lat, lon] at the end of the last leg. Write `solve.py` (Python 3 standard library only); `python solve.py input.json answer.json` writes `answer.json` and `track.svg`. Fresh inputs are used too. ## Rules (plane sailing, 1 minute of latitude = 1 nm) 1. A move of n nm north and e nm east from (lat, lon): dlat = n / 60; mid = lat + dlat / 2; new lat = lat + dlat; new lon = lon + e / (60 * cos(mid)). 2. **DR**: per leg, distance = speed * hours along the course. **EP**: per leg, add the current vector (drift * hours toward set) to the leg's water vector, then move once. 3. Difference from point A to point B: north = (latB - latA) * 60, east = (lonB - lonA) * 60 * cos((latA + latB) / 2). 4. **Set/drift**: vector from the final DR position to the fix; set = atan2(east, north) in degrees mod 360; drift = length / total hours. `ep_error_nm` = distance from the final EP to the fix. **CMG/SMG**: same from `start` to the fix. 5. Round positions to 5 decimals, hours to 4, angles to 1, speeds and distances to 3. `dr` and `ep` list the start and the position after every leg. ## Visual output: track.svg Static, self-contained SVG (root `<svg>`, no scripts, images, links or external assets; renders headless) with `<polyline id="dr-track">`, `<polyline id="ep-track">` and `<circle id="fix">`. The drawing itself is not graded. ## answer.json `{"dr": [[lat, lon], ...], "ep": [...], "hours", "set_deg", "drift_kn", "ep_error_nm", "cmg_deg", "smg_kn"}` ## Scoring Hidden checks (partial credit; all must pass): `dr_positions`, `ep_positions`, `set_and_drift`, `course_speed_made_good`, `track_svg_static` (track.svg exists, follows the static rules, has the ids/tags above), `fresh_run_1`, `fresh_run_2`. Positions within 2e-5 degrees, angles within 0.11, speeds and distances within 0.002. 60-second limit per run.
Mid-latitude longitude scaling per leg, current applied per leg as a vector, 'set' as the direction the current flows toward, angle wrap, and positions checked at five decimals at high latitudes. 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. dr_positions 2. ep_positions 3. set_and_drift 4. course_speed_made_good 5. track_svg_static 6. fresh_run_1 7. fresh_run_2
Setup notes: Use Case Scout batch10 case k06-dead-reckoning-set-drift (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. Visual output (track.svg) rendered offline to PNG with google-chrome headless, network blocked, 1280x800 at ~3 s after load. 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: 7/7. Cost is an ESTIMATE: measured tokens x pricing.json list price (Google account, nothing billed per token); output_tokens include thinking tokens. Tool calls 27 (0 failed). Single run.
Estimated cost List-price estimate; not actually billed.
Output
Metrics
- Estimated cost
- $0.29
- Wall time
- 3m
- Human step-ins
- 0
- Turns
- 26
| Model | Input tok | Output tok | Cost |
|---|---|---|---|
| GGemini 3.8 Flashgoogle/gemini-3.8-flasheffort medium · thinking on | 803,903 | 32,801 | $0.29 |
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. dr_positions 2. ep_positions 3. set_and_drift 4. course_speed_made_good 5. track_svg_static 6. fresh_run_1 7. 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
{"event": "init", "conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "init": {"model": "gemini-3.8-flash-medium", "cwd": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k06/work", "tools": ["ask_custom_permission", "ask_permission", "ask_question", "browser_click_element", "browser_drag_pixel_to_pixel", "browser_get_dom", "browser_get_network_request", "browser_input", "browser_list_network_requests", "browser_mouse_down", "browser_mouse_up", "browser_move_mouse", "browser_press_key", "browser_refresh_page", "browser_resize_window", "browser_scroll", "browser_scroll_dom", "browser_select_option", "browser_subagent", "call_mcp_tool", "capture_browser_console_logs", "capture_browser_screenshot", "click_browser_pixel", "command_status", "define_subagent", "delete_knowledge", "execute_browser_javascript", "find_by_name", "finish", "generate_image", "grep_search", "invoke_subagent", "list_browser_pages", "list_dir", "list_permissions", "list_plugin_accounts", "list_resources", "manage_inbox", "manage_subagents", "manage_task", "multi_replace_file_content", "notebook_edit", "notebook_execution", "open_browser_url", "read_browser_page", "read_resource", "read_url_content", "replace_file_content", "run_command", "run_workflow", "schedule", "search_marketplace", "search_web", "sed_file", "send_command_input", "send_message", "view_file", "wait", "wait_5_seconds", "write_to_file"], "permission_mode": "always-proceed"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 0, "state": "DONE", "step_type": "user_input"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 1, "state": "DONE", "step_type": "agent_response", "duration_seconds": 1.5873695639999998, "usage": {"input_tokens": 8486, "output_tokens": 76, "thinking_tokens": 39, "cache_read_tokens": 0, "total_tokens": 8562}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "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": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 2, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.258102308, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "ls -la"}, "output": "Command exited with code 0.\n\nCommand output:\ntotal 16\r\ndrwxr-xr-x 2 bob bob 4096 Oct 22 10:28 .\r\ndrwxrwxr-x 3 bob bob 4096 Oct 22 10:37 ..\r\n-rw-r--r-- 1 bob bob 2165 Oct 22 10:28 TASK.md\r\n-rw-r--r-- 1 bob bob 521 Oct 22 10:28 input.json\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 3, "state": "DONE", "step_type": "agent_response", "duration_seconds": 4.607462009, "usage": {"input_tokens": 8764, "output_tokens": 117, "thinking_tokens": 15, "cache_read_tokens": 0, "total_tokens": 8881}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "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/k06/work/TASK.md"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 4, "state": "DONE", "step_type": "tool", "tool_name": "read_file", "duration_seconds": 0.04817062, "tool_info": {"name": "read_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k06/work/TASK.md"}, "output": "19 lines, 2165 bytes"}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 5, "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/k06/work/input.json"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 5, "state": "DONE", "step_type": "tool", "tool_name": "read_file", "duration_seconds": 0.040476876, "tool_info": {"name": "read_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k06/work/input.json"}, "output": "46 lines, 521 bytes"}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 6, "state": "DONE", "step_type": "agent_response", "duration_seconds": 10.388197948, "usage": {"input_tokens": 10244, "output_tokens": 2582, "thinking_tokens": 2533, "cache_read_tokens": 0, "total_tokens": 12826}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 7, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"import json; print('Python 3 available')\""}}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 7, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.2826878, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"import json; print('Python 3 available')\""}, "output": "Command exited with code 0.\n\nCommand output:\nPython 3 available\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 8, "state": "DONE", "step_type": "agent_response", "duration_seconds": 6.881907339, "usage": {"input_tokens": 12916, "output_tokens": 2021, "thinking_tokens": 1948, "cache_read_tokens": 0, "total_tokens": 14937}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 9, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport json, math\n\nwith open('input.json') as f:\n data = json.load(f)\n\nprint(data)\n\""}}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 9, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.588155499, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport json, math\n\nwith open('input.json') as f:\n data = json.load(f)\n\nprint(data)\n\""}, "output": "Command exited with code 0.\n\nCommand output:\n{'start': [-16.7478, 90.7095], 'legs': [{'course': 98, 'speed_kn': 3.4, 'minutes': 90}, {'course': 31, 'speed_kn': 7.1, 'minutes': 30}, {'course': 258, 'speed_kn': 3.5, 'minutes': 30}, {'course': 157, 'speed_kn': 6.5, 'minutes': 45}, {'course': 197, 'speed_kn': 3.1, 'minutes': 60}, {'course': 68, 'speed_kn': 7.3, 'minutes': 60}], 'current': {'set': 239, 'drift_kn': 1.1}, 'fix': [-16.8217, 90.8589]}\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 10, "state": "DONE", "step_type": "agent_response", "duration_seconds": 3.556990292, "usage": {"input_tokens": 15236, "output_tokens": 1001, "thinking_tokens": 19, "cache_read_tokens": 0, "total_tokens": 16237}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 11, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport json, math\n\nwith open('input.json') as f:\n data = json.load(f)\n\ndef move(lat, lon, n, e):\n dlat = n / 60.0\n mid = lat + dlat / 2.0\n new_lat = lat + dlat\n new_lon = lon + e / (60.0 * math.cos(math.radians(mid)))\n return new_lat, new_lon\n\ndef diff(latA, lonA, latB, lonB):\n north = (latB - latA) * 60.0\n east = (lonB - lonA) * 60.0 * math.cos(math.radians((latA + latB) / 2.0))\n return north, east\n\n# Method 1: unrounded intermediate\nstart = data['start']\nlegs = data\u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 11, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.270588448, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport json, math\n\nwith open('input.json') as f:\n data = json.load(f)\n\ndef move(lat, lon, n, e):\n dlat = n / 60.0\n mid = lat + dlat / 2.0\n new_lat = lat + dlat\n new_lon = lon + e / (60.0 * math.cos(math.radians(mid)))\n return new_lat, new_lon\n\ndef diff(latA, lonA, latB, lonB):\n north = (latB - latA) * 60.0\n east = (lonB - lonA) * 60.0 * math.cos(math.radians((latA + latB) / 2.0))\n return north, east\n\n# Method 1: unrounded intermediate\nstart = data['start']\nlegs = data\u2026"}, "output": "Command exited with code 0.\n\nCommand output:\nDR unrounded final: [-16.793601035474413, 90.93465761983002]\r\nEP unrounded final: [-16.843173450184505, 90.84851124028921]\r\nSet: 248.8207, Drift: 0.8889\r\nEP error: 1.4198\r\nCMG: 117.3234, SMG: 1.8400\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 12, "state": "DONE", "step_type": "agent_response", "duration_seconds": 7.317018186, "usage": {"input_tokens": 16469, "output_tokens": 372, "thinking_tokens": 32, "cache_read_tokens": 0, "total_tokens": 16841}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 13, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport json, math\n\nwith open('input.json') as f:\n data = json.load(f)\n\ndef move(lat, lon, n, e):\n dlat = n / 60.0\n mid = lat + dlat / 2.0\n new_lat = lat + dlat\n new_lon = lon + e / (60.0 * math.cos(math.radians(mid)))\n return new_lat, new_lon\n\nstart = data['start']\nlegs = data['legs']\ncurrent = data['current']\n\n# rounded vs unrounded\ncur_lat, cur_lon = start[0], start[1]\nfor leg in legs:\n hrs = leg['minutes'] / 60.0\n dist = leg['speed_kn'] * hrs\n crs = math.radians(le\u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 13, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 1.211920288, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport json, math\n\nwith open('input.json') as f:\n data = json.load(f)\n\ndef move(lat, lon, n, e):\n dlat = n / 60.0\n mid = lat + dlat / 2.0\n new_lat = lat + dlat\n new_lon = lon + e / (60.0 * math.cos(math.radians(mid)))\n return new_lat, new_lon\n\nstart = data['start']\nlegs = data['legs']\ncurrent = data['current']\n\n# rounded vs unrounded\ncur_lat, cur_lon = start[0], start[1]\nfor leg in legs:\n hrs = leg['minutes'] / 60.0\n dist = leg['speed_kn'] * hrs\n crs = math.radians(le\u2026"}, "output": "Command exited with code 0.\n\nCommand output:\nDR rounded-at-each-step: -16.79359 90.93465\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 14, "state": "DONE", "step_type": "agent_response", "duration_seconds": 12.275102943, "usage": {"input_tokens": 4776, "output_tokens": 710, "thinking_tokens": 245, "cache_read_tokens": 12178, "total_tokens": 5486}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 15, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport json, math\n\nwith open('input.json') as f:\n data = json.load(f)\n\ndef diff(latA, lonA, latB, lonB):\n north = (latB - latA) * 60.0\n east = (lonB - lonA) * 60.0 * math.cos(math.radians((latA + latB) / 2.0))\n return north, east\n\ntot_hrs = sum(leg['minutes'] for leg in data['legs']) / 60.0\nfix = data['fix']\n\n# unrounded:\ndr_u = [-16.793601035474413, 90.93465761983002]\nn, e = diff(dr_u[0], dr_u[1], fix[0], fix[1])\nset_u = math.degrees(math.atan2(e, n)) % 360\ndrift_u = math.hypot(e, \u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 15, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.293079276, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport json, math\n\nwith open('input.json') as f:\n data = json.load(f)\n\ndef diff(latA, lonA, latB, lonB):\n north = (latB - latA) * 60.0\n east = (lonB - lonA) * 60.0 * math.cos(math.radians((latA + latB) / 2.0))\n return north, east\n\ntot_hrs = sum(leg['minutes'] for leg in data['legs']) / 60.0\nfix = data['fix']\n\n# unrounded:\ndr_u = [-16.793601035474413, 90.93465761983002]\nn, e = diff(dr_u[0], dr_u[1], fix[0], fix[1])\nset_u = math.degrees(math.atan2(e, n)) % 360\ndrift_u = math.hypot(e, \u2026"}, "output": "Command exited with code 0.\n\nCommand output:\nUnrounded -> set: 248.82074410106355 drift: 0.8888529806121956\r\nRounded -> set: 248.82063929397458 drift: 0.8888815392173159\r\nDiff set: 0.00010480708897375735 Diff drift: 2.8558605120299063e-05\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 16, "state": "DONE", "step_type": "agent_response", "duration_seconds": 6.25784705, "usage": {"input_tokens": 5717, "output_tokens": 847, "thinking_tokens": 148, "cache_read_tokens": 12177, "total_tokens": 6564}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 17, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport json, math\n\nwith open('input.json') as f:\n data = json.load(f)\n\ndef move(lat, lon, n, e):\n dlat = n / 60.0\n mid = lat + dlat / 2.0\n new_lat = lat + dlat\n new_lon = lon + e / (60.0 * math.cos(math.radians(mid)))\n return new_lat, new_lon\n\nstart = data['start']\nlegs = data['legs']\ncurrent = data['current']\n\n# Method A: per leg combined\nep_a = [start]\ncur = list(start)\nfor leg in legs:\n hrs = leg['minutes'] / 60.0\n dist = leg['speed_kn'] * hrs\n crs = math.radians(l\u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 17, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.297379704, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport json, math\n\nwith open('input.json') as f:\n data = json.load(f)\n\ndef move(lat, lon, n, e):\n dlat = n / 60.0\n mid = lat + dlat / 2.0\n new_lat = lat + dlat\n new_lon = lon + e / (60.0 * math.cos(math.radians(mid)))\n return new_lat, new_lon\n\nstart = data['start']\nlegs = data['legs']\ncurrent = data['current']\n\n# Method A: per leg combined\nep_a = [start]\ncur = list(start)\nfor leg in legs:\n hrs = leg['minutes'] / 60.0\n dist = leg['speed_kn'] * hrs\n crs = math.radians(l\u2026"}, "output": "Command exited with code 0.\n\nCommand output:\nMethod A final EP: (-16.843173450184505, 90.84851124028921)\r\nMethod B final EP: (-16.843173450184505, 90.84846868118332)\r\nDiff lat: 0.0\r\nDiff lon: 4.2559105892792104e-05\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 18, "state": "DONE", "step_type": "agent_response", "duration_seconds": 13.890315494, "usage": {"input_tokens": 2715, "output_tokens": 776, "thinking_tokens": 357, "cache_read_tokens": 16236, "total_tokens": 3491}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 19, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport json, math\n\nwith open('input.json') as f:\n data = json.load(f)\n\ndef move(lat, lon, n, e):\n dlat = n / 60.0\n mid = lat + dlat / 2.0\n new_lat = lat + dlat\n new_lon = lon + e / (60.0 * math.cos(math.radians(mid)))\n return new_lat, new_lon\n\nlegs = data['legs']\nstart = data['start']\n\ncur_unrounded = list(start)\ncur_rounded = list(start)\n\nfor i, leg in enumerate(legs):\n hrs = leg['minutes'] / 60.0\n dist = leg['speed_kn'] * hrs\n crs = math.radians(leg['course'])\n n\u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 19, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.303623052, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport json, math\n\nwith open('input.json') as f:\n data = json.load(f)\n\ndef move(lat, lon, n, e):\n dlat = n / 60.0\n mid = lat + dlat / 2.0\n new_lat = lat + dlat\n new_lon = lon + e / (60.0 * math.cos(math.radians(mid)))\n return new_lat, new_lon\n\nlegs = data['legs']\nstart = data['start']\n\ncur_unrounded = list(start)\ncur_rounded = list(start)\n\nfor i, leg in enumerate(legs):\n hrs = leg['minutes'] / 60.0\n dist = leg['speed_kn'] * hrs\n crs = math.radians(leg['course'])\n n\u2026"}, "output": "Command exited with code 0.\n\nCommand output:\nLeg 0: diff lat=0.0000003, diff lon=0.0000041\r\nLeg 1: diff lat=0.0000040, diff lon=0.0000048\r\nLeg 2: diff lat=0.0000081, diff lon=0.0000073\r\nLeg 3: diff lat=0.0000091, diff lon=0.0000113\r\nLeg 4: diff lat=0.0000082, diff lon=0.0000107\r\nLeg 5: diff lat=0.0000110, diff lon=0.0000076\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 20, "state": "DONE", "step_type": "agent_response", "duration_seconds": 10.208983361, "usage": {"input_tokens": 3756, "output_tokens": 779, "thinking_tokens": 448, "cache_read_tokens": 16236, "total_tokens": 4535}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 21, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport math\n\nfix = [-16.8217, 90.8589]\nep_u = [-16.843173450184505, 90.84851124028921]\nep_r = [round(ep_u[0], 5), round(ep_u[1], 5)]\n\ndef diff(latA, lonA, latB, lonB):\n north = (latB - latA) * 60.0\n east = (lonB - lonA) * 60.0 * math.cos(math.radians((latA + latB) / 2.0))\n return north, east\n\nn_u, e_u = diff(ep_u[0], ep_u[1], fix[0], fix[1])\nn_r, e_r = diff(ep_r[0], ep_r[1], fix[0], fix[1])\n\nprint('Unrounded EP error:', round(math.hypot(e_u, n_u), 3))\nprint('Rounded EP error:', round(m\u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 21, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 1.190081495, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport math\n\nfix = [-16.8217, 90.8589]\nep_u = [-16.843173450184505, 90.84851124028921]\nep_r = [round(ep_u[0], 5), round(ep_u[1], 5)]\n\ndef diff(latA, lonA, latB, lonB):\n north = (latB - latA) * 60.0\n east = (lonB - lonA) * 60.0 * math.cos(math.radians((latA + latB) / 2.0))\n return north, east\n\nn_u, e_u = diff(ep_u[0], ep_u[1], fix[0], fix[1])\nn_r, e_r = diff(ep_r[0], ep_r[1], fix[0], fix[1])\n\nprint('Unrounded EP error:', round(math.hypot(e_u, n_u), 3))\nprint('Rounded EP error:', round(m\u2026"}, "output": "Command exited with code 0.\n\nCommand output:\nUnrounded EP error: 1.42\r\nRounded EP error: 1.42\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 22, "state": "DONE", "step_type": "agent_response", "duration_seconds": 19.424351848, "usage": {"input_tokens": 4643, "output_tokens": 6586, "thinking_tokens": 6330, "cache_read_tokens": 16234, "total_tokens": 11229}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 23, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport xml.etree.ElementTree as ET\n\nsvg_sample = '''<svg xmlns=\\\"http://www.w3.org/2000/svg\\\" viewBox=\\\"0 0 800 600\\\" width=\\\"800\\\" height=\\\"600\\\">\n <polyline id=\\\"dr-track\\\" points=\\\"10,10 20,20\\\" fill=\\\"none\\\" stroke=\\\"blue\\\" stroke-width=\\\"2\\\" />\n <polyline id=\\\"ep-track\\\" points=\\\"10,10 25,25\\\" fill=\\\"none\\\" stroke=\\\"green\\\" stroke-width=\\\"2\\\" />\n <circle id=\\\"fix\\\" cx=\\\"30\\\" cy=\\\"30\\\" r=\\\"5\\\" fill=\\\"red\\\" />\n</svg>'''\n\nroot = ET.fromstring(svg_sample)\nprint('Tag:', root.tag)\nfor elem in\u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 23, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.297401509, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport xml.etree.ElementTree as ET\n\nsvg_sample = '''<svg xmlns=\\\"http://www.w3.org/2000/svg\\\" viewBox=\\\"0 0 800 600\\\" width=\\\"800\\\" height=\\\"600\\\">\n <polyline id=\\\"dr-track\\\" points=\\\"10,10 20,20\\\" fill=\\\"none\\\" stroke=\\\"blue\\\" stroke-width=\\\"2\\\" />\n <polyline id=\\\"ep-track\\\" points=\\\"10,10 25,25\\\" fill=\\\"none\\\" stroke=\\\"green\\\" stroke-width=\\\"2\\\" />\n <circle id=\\\"fix\\\" cx=\\\"30\\\" cy=\\\"30\\\" r=\\\"5\\\" fill=\\\"red\\\" />\n</svg>'''\n\nroot = ET.fromstring(svg_sample)\nprint('Tag:', root.tag)\nfor elem in\u2026"}, "output": "Command exited with code 0.\n\nCommand output:\nTag: {http://www.w3.org/2000/svg}svg\r\n{http://www.w3.org/2000/svg}svg {'viewBox': '0 0 800 600', 'width': '800', 'height': '600'}\r\n{http://www.w3.org/2000/svg}polyline {'id': 'dr-track', 'points': '10,10 20,20', 'fill': 'none', 'stroke': 'blue', 'stroke-width': '2'}\r\n{http://www.w3.org/2000/svg}polyline {'id': 'ep-track', 'points': '10,10 25,25', 'fill': 'none', 'stroke': 'green', 'stroke-width': '2'}\r\n{http://www.w3.org/2000/svg}circle {'id': 'fix', 'cx': '30', 'cy': '30', 'r': '5', 'fill': 'red'}\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 24, "state": "DONE", "step_type": "agent_response", "duration_seconds": 11.630186887, "usage": {"input_tokens": 7466, "output_tokens": 3439, "thinking_tokens": 2806, "cache_read_tokens": 20332, "total_tokens": 10905}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 25, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport json, math\n\nwith open('input.json') as f:\n data = json.load(f)\n\ndef move(lat, lon, n, e):\n dlat = n / 60.0\n mid = lat + dlat / 2.0\n new_lat = lat + dlat\n new_lon = lon + e / (60.0 * math.cos(math.radians(mid)))\n return new_lat, new_lon\n\nstart = data['start']\nlegs = data['legs']\ncurrent = data['current']\nfix = data['fix']\n\ndr = [list(start)]\ncur_lat, cur_lon = start[0], start[1]\nfor leg in legs:\n hrs = leg['minutes'] / 60.0\n dist = leg['speed_kn'] * hrs\n crs = m\u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 25, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.448763342, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport json, math\n\nwith open('input.json') as f:\n data = json.load(f)\n\ndef move(lat, lon, n, e):\n dlat = n / 60.0\n mid = lat + dlat / 2.0\n new_lat = lat + dlat\n new_lon = lon + e / (60.0 * math.cos(math.radians(mid)))\n return new_lat, new_lon\n\nstart = data['start']\nlegs = data['legs']\ncurrent = data['current']\nfix = data['fix']\n\ndr = [list(start)]\ncur_lat, cur_lon = start[0], start[1]\nfor leg in legs:\n hrs = leg['minutes'] / 60.0\n dist = leg['speed_kn'] * hrs\n crs = m\u2026"}, "output": "Command exited with code 0.\n\nCommand output:\nLat range: -16.87930822101009 -16.708913981623397\r\nLon range: 90.7095 90.93465761983002\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 26, "state": "DONE", "step_type": "agent_response", "duration_seconds": 8.834742306999999, "usage": {"input_tokens": 6982, "output_tokens": 2329, "thinking_tokens": 1012, "cache_read_tokens": 24411, "total_tokens": 9311}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 27, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport json, math\n\ndef solve(input_path, answer_path):\n with open(input_path, 'r', encoding='utf-8') as f:\n data = json.load(f)\n\n start = data['start']\n legs = data.get('legs', [])\n current = data.get('current', {'set': 0.0, 'drift_kn': 0.0})\n fix = data['fix']\n\n def move(lat, lon, n, e):\n dlat = n / 60.0\n mid = lat + dlat / 2.0\n new_lat = lat + dlat\n new_lon = lon + e / (60.0 * math.cos(math.radians(mid)))\n return new_lat, new_lon\n\n \u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 27, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 1.442336262, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport json, math\n\ndef solve(input_path, answer_path):\n with open(input_path, 'r', encoding='utf-8') as f:\n data = json.load(f)\n\n start = data['start']\n legs = data.get('legs', [])\n current = data.get('current', {'set': 0.0, 'drift_kn': 0.0})\n fix = data['fix']\n\n def move(lat, lon, n, e):\n dlat = n / 60.0\n mid = lat + dlat / 2.0\n new_lat = lat + dlat\n new_lon = lon + e / (60.0 * math.cos(math.radians(mid)))\n return new_lat, new_lon\n\n \u2026"}, "output": "Command exited with code 0.\n\nCommand output:\n{\r\n \"dr\": [\r\n [\r\n -16.7478,\r\n 90.7095\r\n ],\r\n [\r\n -16.75963,\r\n 90.7974\r\n ],\r\n [\r\n -16.70891,\r\n 90.82922\r\n ],\r\n [\r\n -16.71498,\r\n 90.79944\r\n ],\r\n [\r\n -16.78977,\r\n 90.83259\r\n ],\r\n [\r\n -16.83918,\r\n 90.81681\r\n ],\r\n [\r\n -16.7936,\r\n 90.93466\r\n ]\r\n ],\r\n \"ep\": [\r\n [\r\n -16.7478,\r\n 90.7095\r\n ],\r\n [\r\n -16.77379,\r\n 90.77279\r\n ],\r\n [\r\n -16.7278,\r\n 90.79641\r\n ],\r\n [\r\n -16.73858,\r\n 90.75841\r\n ],\r\n [\r\n -16.82046,\r\n 90.77926\r\n ],\r\n [\r\n -16.87931,\r\n 90.74706\r\n ],\r\n [\r\n -16.84317,\r\n 90.84851\r\n ]\r\n ],\r\n \"hours\": 5.25,\r\n \"set_deg\": 248.8,\r\n \"drift_kn\": 0.889,\r\n \"ep_error_nm\": 1.42,\r\n \"cmg_deg\": 117.3,\r\n \"smg_kn\": 1.84\r\n}\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 28, "state": "DONE", "step_type": "agent_response", "duration_seconds": 11.21885878, "usage": {"input_tokens": 5809, "output_tokens": 4124, "thinking_tokens": 3286, "cache_read_tokens": 28487, "total_tokens": 9933}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 29, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport json, math\n\nwith open('input.json') as f:\n data = json.load(f)\n\n# Using our earlier solved coordinates\n# Let's verify mapping\nfix = data['fix']\ndr = [[-16.7478, 90.7095], [-16.75963, 90.7974], [-16.70891, 90.82922], [-16.71498, 90.79944], [-16.78977, 90.83259], [-16.83918, 90.81681], [-16.7936, 90.93466]]\nep = [[-16.7478, 90.7095], [-16.77379, 90.77279], [-16.7278, 90.79641], [-16.73858, 90.75841], [-16.82046, 90.77926], [-16.87931, 90.74706], [-16.84317, 90.84851]]\n\nall_pts = dr + ep\u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 29, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.312902083, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport json, math\n\nwith open('input.json') as f:\n data = json.load(f)\n\n# Using our earlier solved coordinates\n# Let's verify mapping\nfix = data['fix']\ndr = [[-16.7478, 90.7095], [-16.75963, 90.7974], [-16.70891, 90.82922], [-16.71498, 90.79944], [-16.78977, 90.83259], [-16.83918, 90.81681], [-16.7936, 90.93466]]\nep = [[-16.7478, 90.7095], [-16.77379, 90.77279], [-16.7278, 90.79641], [-16.73858, 90.75841], [-16.82046, 90.77926], [-16.87931, 90.74706], [-16.84317, 90.84851]]\n\nall_pts = dr + ep\u2026"}, "output": "Command exited with code 0.\n\nCommand output:\ndr_pts: [(83.75, 164.11), (330.67, 198.83), (420.06, 50.0), (336.4, 67.81), (429.52, 287.27), (385.2, 432.25), (716.25, 298.5)]\r\nfix_pt: (503.43, 380.96)\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 30, "state": "DONE", "step_type": "agent_response", "duration_seconds": 10.645898655, "usage": {"input_tokens": 6064, "output_tokens": 4434, "thinking_tokens": 1776, "cache_read_tokens": 32572, "total_tokens": 10498}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 31, "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/k06/work/solve.py"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 31, "state": "DONE", "step_type": "tool", "tool_name": "write_file", "duration_seconds": 0.058551956, "tool_info": {"name": "write_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k06/work/solve.py"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 32, "state": "DONE", "step_type": "agent_response", "duration_seconds": 1.801810912, "usage": {"input_tokens": 6488, "output_tokens": 63, "thinking_tokens": 17, "cache_read_tokens": 36658, "total_tokens": 6551}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 33, "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": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 33, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.363619872, "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/k06/work/solve.py\", line 204, in <module>\r\n main()\r\n ~~~~^^\r\n File \"/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k06/work/solve.py\", line 187, in main\r\n with open(answer_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": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 34, "state": "DONE", "step_type": "agent_response", "duration_seconds": 1.937475563, "usage": {"input_tokens": 2790, "output_tokens": 262, "thinking_tokens": 210, "cache_read_tokens": 40724, "total_tokens": 3052}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 35, "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": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 35, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.068886753, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 solve.py input.json answer.json"}, "output": "Command exited with code 0.\n\nNo output from the command."}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 36, "state": "DONE", "step_type": "agent_response", "duration_seconds": 1.8337534309999999, "usage": {"input_tokens": 3147, "output_tokens": 121, "thinking_tokens": 19, "cache_read_tokens": 40716, "total_tokens": 3268}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 37, "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/k06/work/answer.json"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 37, "state": "DONE", "step_type": "tool", "tool_name": "read_file", "duration_seconds": 0.078923671, "tool_info": {"name": "read_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k06/work/answer.json"}, "output": "68 lines, 623 bytes"}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 38, "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/k06/work/track.svg"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 38, "state": "DONE", "step_type": "tool", "tool_name": "read_file", "duration_seconds": 0.052200309, "tool_info": {"name": "read_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k06/work/track.svg"}, "output": "5 lines, 545 bytes"}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 39, "state": "DONE", "step_type": "agent_response", "duration_seconds": 6.09264089, "usage": {"input_tokens": 4489, "output_tokens": 1057, "thinking_tokens": 536, "cache_read_tokens": 40707, "total_tokens": 5546}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 40, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport subprocess, json, tempfile, os\n\n# Create a fresh synthetic input\nsynth_input = {\n 'start': [34.0522, -118.2437],\n 'legs': [\n {'course': 0, 'speed_kn': 10.0, 'minutes': 60},\n {'course': 90, 'speed_kn': 12.0, 'minutes': 30},\n {'course': 180, 'speed_kn': 8.0, 'minutes': 45},\n {'course': 270, 'speed_kn': 5.0, 'minutes': 15}\n ],\n 'current': {\n 'set': 45,\n 'drift_kn': 2.0\n },\n 'fix': [34.15, -118.15]\n}\n\nwith tempfile.TemporaryDirector\u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 40, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.101734252, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c \"\nimport subprocess, json, tempfile, os\n\n# Create a fresh synthetic input\nsynth_input = {\n 'start': [34.0522, -118.2437],\n 'legs': [\n {'course': 0, 'speed_kn': 10.0, 'minutes': 60},\n {'course': 90, 'speed_kn': 12.0, 'minutes': 30},\n {'course': 180, 'speed_kn': 8.0, 'minutes': 45},\n {'course': 270, 'speed_kn': 5.0, 'minutes': 15}\n ],\n 'current': {\n 'set': 45,\n 'drift_kn': 2.0\n },\n 'fix': [34.15, -118.15]\n}\n\nwith tempfile.TemporaryDirector\u2026"}, "output": "Command exited with code 0.\n\nCommand output:\nReturn code: 0\r\nStderr: \r\nAnswer keys: ['dr', 'ep', 'hours', 'set_deg', 'drift_kn', 'ep_error_nm', 'cmg_deg', 'smg_kn']\r\nHours: 2.5\r\nSet deg: 356.9\r\nDrift kn: 0.748\r\nSVG in dir exists: True\r\nSVG in cwd exists: True\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 41, "state": "DONE", "step_type": "agent_response", "duration_seconds": 3.310850068, "usage": {"input_tokens": 5727, "output_tokens": 100, "thinking_tokens": 44, "cache_read_tokens": 40705, "total_tokens": 5827}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 42, "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": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 42, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.075324979, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 solve.py input.json answer.json"}, "output": "Command exited with code 0.\n\nNo output from the command."}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 43, "state": "DONE", "step_type": "agent_response", "duration_seconds": 2.050972739, "usage": {"input_tokens": 5921, "output_tokens": 62, "thinking_tokens": 20, "cache_read_tokens": 40698, "total_tokens": 5983}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 44, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "git status"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 44, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.117959118, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "git status"}, "output": "Command exited with code 128.\n\nCommand output:\nfatal: not a git repository (or any of the parent directories): .git\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 45, "state": "DONE", "step_type": "agent_response", "duration_seconds": 6.2921961809999996, "usage": {"input_tokens": 6095, "output_tokens": 51, "thinking_tokens": 9, "cache_read_tokens": 40690, "total_tokens": 6146}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 46, "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": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 46, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.798696429, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "ls -la"}, "output": "Command exited with code 0.\n\nCommand output:\ntotal 32\r\ndrwxr-xr-x 2 bob bob 4096 Oct 22 10:39 .\r\ndrwxrwxr-x 3 bob bob 4096 Oct 22 10:37 ..\r\n-rw-r--r-- 1 bob bob 2165 Oct 22 10:28 TASK.md\r\n-rw-rw-r-- 1 bob bob 623 Oct 22 10:39 answer.json\r\n-rw-r--r-- 1 bob bob 521 Oct 22 10:28 input.json\r\n-rw-r--r-- 1 bob bob 6372 Oct 22 10:39 solve.py\r\n-rw-rw-r-- 1 bob bob 545 Oct 22 10:39 track.svg\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 47, "state": "DONE", "step_type": "agent_response", "duration_seconds": 3.004957066, "usage": {"input_tokens": 2374, "output_tokens": 74, "thinking_tokens": 26, "cache_read_tokens": 44752, "total_tokens": 2448}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 48, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "chmod +x solve.py"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 48, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.05449843, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "chmod +x solve.py"}, "output": "Command exited with code 0.\n\nNo output from the command."}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 49, "state": "DONE", "step_type": "agent_response", "duration_seconds": 4.732936564, "usage": {"input_tokens": 2544, "output_tokens": 65, "thinking_tokens": 14, "cache_read_tokens": 44743, "total_tokens": 2609}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 50, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -m py_compile solve.py"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 50, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.116060176, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -m py_compile solve.py"}, "output": "Command exited with code 0.\n\nNo output from the command."}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 51, "state": "DONE", "step_type": "agent_response", "duration_seconds": 2.09961913, "usage": {"input_tokens": 2704, "output_tokens": 64, "thinking_tokens": 17, "cache_read_tokens": 44735, "total_tokens": 2768}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 52, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "rm -rf __pycache__"}}}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 52, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.040523796, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "rm -rf __pycache__"}, "output": "Command exited with code 0.\n\nNo output from the command."}}}
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{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " reckoning, estimated position, and "}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "set/drift solver has bee"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "n implemented in [`solve.py`](file:///home/bob/u"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "secase-runs/agy-batch/ou"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "t/gemini-3.8"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "-flash-medium/k06/"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "work/solve.py).\n\n### Summary of Impl"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ementation\n- **Plane Sai"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ling Rules**:\n - Implemented `move("}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "lat, lon, n, e)` using $"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "\\text{dlat} = n / 60$, $"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "\\text{mid} ="}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " \\text{lat} + \\text{dlat} / 2$, and $\\text{dlon} = e / (60 \\cdot \\cos(\\t"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ext{mid}))$."}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "\n - Implemented differe"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "nce calculation `diff(la"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "tA, lonA, latB, lonB)` using mid-lat"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "itude cosine correction."}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "\n - Calcula"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ted Dead Reckoning (**DR"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "**) track and Estimated Position (**"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "EP**) track combining wa"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ter and current vectors per leg.\n - Calculated "}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "**Set and Dr"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ift** from final DR to GPS fix, **EP error**, an"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "d Course/Spe"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ed Made Good (**CMG/SMG*"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "*) from start to fix.\n - Rounded coordinates to"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " 5 decimal p"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "laces, hours to 4, angles to 1, and distances/sp"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "eeds to 3 de"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "cimal places.\n- **Visual"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " Output**:\n - Generates"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " self-contai"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ned, static SVG [`track.svg`](file:///home/bob/u"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "secase-runs/agy-batch/out/gemini-3.8"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "-flash-medium/k06/work/t"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "rack.svg) containing `<polyline id=\"dr-track\">`,"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " `<polyline "}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "id=\"ep-track\">`, and `<c"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ircle id=\"fix\">`.\n- **Outputs Tested"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "**:\n - Ran `python solv"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "e.py input.json answer.json` producing [`answer."}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "json`](file:///home/bob/usecase-runs"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "/agy-batch/out/gemini-3.8-flash-medium/k06/work/"}}
{"event": "step_update", "step_update": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "step_index": 53, "state": "DONE", "step_type": "agent_response", "text_delta": "answer.json) and [`track.svg`](file:///home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k06/work/track.svg). Verified against fresh synthetic scenarios as well.\n", "duration_seconds": 4.737984543, "usage": {"input_tokens": 2863, "output_tokens": 689, "thinking_tokens": 214, "cache_read_tokens": 44727, "total_tokens": 3552}}}
{"event": "result", "result": {"conversation_id": "fdf78aa2-ef45-4264-bd17-97d63019ddfe", "status": "SUCCESS", "response": "The dead reckoning, estimated position, and set/drift solver has been implemented in [`solve.py`](file:///home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k06/work/solve.py).\n\n### Summary of Implementation\n- **Plane Sailing Rules**:\n - Implemented `move(lat, lon, n, e)` using $\\text{dlat} = n / 60$, $\\text{mid} = \\text{lat} + \\text{dlat} / 2$, and $\\text{dlon} = e / (60 \\cdot \\cos(\\text{mid}))$.\n - Implemented difference calculation `diff(latA, lonA, latB, lonB)` using mid-latitude cosine correction.\n - Calculated Dead Reckoning (**DR**) track and Estimated Position (**EP**) track combining water and current vectors per leg.\n - Calculated **Set and Drift** from final DR to GPS fix, **EP error**, and Course/Speed Made Good (**CMG/SMG**) from start to fix.\n - Rounded coordinates to 5 decimal places, hours to 4, angles to 1, and distances/speeds to 3 decimal places.\n- **Visual Output**:\n - Generates self-contained, static SVG [`track.svg`](file:///home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k06/work/track.svg) containing `<polyline id=\"dr-track\">`, `<polyline id=\"ep-track\">`, and `<circle id=\"fix\">`.\n- **Outputs Tested**:\n - Ran `python solve.py input.json answer.json` producing [`answer.json`](file:///home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k06/work/answer.json) and [`track.svg`](file:///home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k06/work/track.svg). Verified against fresh synthetic scenarios as well.\n", "duration_seconds": 180.652000455, "num_turns": 1, "usage": {"input_tokens": 165185, "output_tokens": 32801, "thinking_tokens": 22120, "cache_read_tokens": 638718, "total_tokens": 197986}}}