Gemini 4 Argon (effort medium · thinking on) on Dead reckoning, estimated position with current, and computed set and drift
GGemini 4 Argonmedium · thinking on · Antigravity CLI 1.4.5 (agy -p) · cloud · 2026-10-22 · by @bobsiopener
- Estimated cost
- $0.14
- Wall time
- 2m
- 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-4-argon-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-4-argon-medium (effort medium); priced at the base model row gemini-4-argon (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 8 (0 failed). Single run.
Estimated cost List-price estimate; not actually billed.
Output
Metrics
- Estimated cost
- $0.14
- Wall time
- 2m
- Human step-ins
- 0
- Turns
- 8
| Model | Input tok | Output tok | Cost |
|---|---|---|---|
| GGemini 4 Argongoogle/gemini-4-argoneffort medium · thinking on | 111,794 | 7,591 | $0.14 |
Reproduce this run
- Use the use case prompt on the use case page.
- Same setup: Gemini 4 Argon (google/gemini-4-argon, 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
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{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 2, "state": "DONE", "step_type": "tool", "tool_name": "read_file", "duration_seconds": 0.022578391, "tool_info": {"name": "read_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k06/work/input.json"}, "output": "46 lines, 521 bytes"}}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 3, "state": "DONE", "step_type": "agent_response", "duration_seconds": 36.981573524, "usage": {"input_tokens": 2691, "output_tokens": 3962, "thinking_tokens": 1120, "cache_read_tokens": 6407, "total_tokens": 6653}}}
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{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 5, "state": "DONE", "step_type": "agent_response", "duration_seconds": 5.526588473, "usage": {"input_tokens": 4046, "output_tokens": 85, "thinking_tokens": 22, "cache_read_tokens": 9099, "total_tokens": 4131}}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 6, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 solve.py input.json answer.json && cat answer.json"}}}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 6, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 2.312523682, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 solve.py input.json answer.json && cat 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-4-argon-medium/k06/work/solve.py\", line 178, in <module>\r\n solve(in_file, out_file)\r\n ~~~~~^^^^^^^^^^^^^^^^^^^\r\n File \"/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k06/work/solve.py\", line 163, in solve\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"}}}
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{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 8, "state": "DONE", "step_type": "tool", "tool_name": "edit_file", "duration_seconds": 1.451913768, "tool_info": {"name": "edit_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k06/work/solve.py"}}}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 9, "state": "DONE", "step_type": "agent_response", "duration_seconds": 6.527227789, "usage": {"input_tokens": 2783, "output_tokens": 139, "thinking_tokens": 61, "cache_read_tokens": 11484, "total_tokens": 2922}}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 10, "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 && cat /tmp/track.svg"}}}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 10, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 2.634885339, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 solve.py input.json /tmp/answer.json && cat /tmp/answer.json && cat /tmp/track.svg"}, "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}<svg xmlns=\"http://www.w3.org/2000/svg\" viewBox=\"0 0 800 600\" width=\"800\" height=\"600\">\r\n <rect width=\"100%\" height=\"100%\" fill=\"#f8fafc\" />\r\n <rect x=\"70\" y=\"70\" width=\"660\" height=\"460\" fill=\"#ffffff\" stroke=\"#cbd5e1\" stroke-width=\"1\" />\r\n <text x=\"400.0\" y=\"35\" text-anchor=\"middle\" font-family=\"sans-serif\" font-size=\"18\" font-weight=\"bold\" fill=\"#0f172a\">Dead Reckoning (DR), Estimated Position (EP), and GPS Fix</text>\r\n <line x1=\"647.31\" y1=\"298.83\" x2=\"480.88\" y2=\"363.31\" stroke=\"#dc2626\" stroke-width=\"1.5\" stroke-dasharray=\"4,4\" />\r\n <polyline id=\"dr-track\" points=\"152.69,193.74 345.78,220.88 415.68,104.5 350.27,118.43 423.09,290.04 388.42,403.42 647.31,298.83\" fill=\"none\" stroke=\"#1d4ed8\" stroke-width=\"2.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\" />\r\n <polyline id=\"ep-track\" points=\"152.69,193.74 291.72,253.37 343.61,147.85 260.13,172.58 305.94,360.46 235.2,495.5 458.06,412.57\" fill=\"none\" stroke=\"#059669\" stroke-width=\"2.5\" stroke-dasharray=\"6,3\" stroke-linecap=\"round\" stroke-linejoin=\"round\" />\r\n <circle cx=\"345.78\" cy=\"220.88\" r=\"3.5\" fill=\"#1d4ed8\" />\r\n <circle cx=\"415.68\" cy=\"104.5\" r=\"3.5\" fill=\"#1d4ed8\" />\r\n <circle cx=\"350.27\" cy=\"118.43\" r=\"3.5\" fill=\"#1d4ed8\" />\r\n <circle cx=\"423.09\" cy=\"290.04\" r=\"3.5\" fill=\"#1d4ed8\" />\r\n <circle cx=\"388.42\" cy=\"403.42\" r=\"3.5\" fill=\"#1d4ed8\" />\r\n <circle cx=\"647.31\" cy=\"298.83\" r=\"3.5\" fill=\"#1d4ed8\" />\r\n <circle cx=\"291.72\" cy=\"253.37\" r=\"3.5\" fill=\"#059669\" />\r\n <circle cx=\"343.61\" cy=\"147.85\" r=\"3.5\" fill=\"#059669\" />\r\n <circle cx=\"260.13\" cy=\"172.58\" r=\"3.5\" fill=\"#059669\" />\r\n <circle cx=\"305.94\" cy=\"360.46\" r=\"3.5\" fill=\"#059669\" />\r\n <circle cx=\"235.2\" cy=\"495.5\" r=\"3.5\" fill=\"#059669\" />\r\n <circle cx=\"458.06\" cy=\"412.57\" r=\"3.5\" fill=\"#059669\" />\r\n <circle id=\"start\" cx=\"152.69\" cy=\"193.74\" r=\"5\" fill=\"#0f172a\" />\r\n <circle id=\"fix\" cx=\"480.88\" cy=\"363.31\" r=\"6\" fill=\"#dc2626\" stroke=\"#ffffff\" stroke-width=\"1.5\" />\r\n <g font-family=\"sans-serif\" font-size=\"12\" fill=\"#334155\">\r\n <text x=\"85\" y=\"560\">DR Track (solid blue) | EP Track (dashed green) | Fix (red circle)</text>\r\n <text x=\"85\" y=\"580\">Set: 248.8 deg | Drift: 0.889 kn | EP Error: 1.42 nm | CMG: 117.3 deg | SMG: 1.84 kn</text>\r\n </g>\r\n</svg>\r\n"}}}
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{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 12, "state": "DONE", "step_type": "tool", "tool_name": "write_file", "duration_seconds": 1.789168077, "tool_info": {"name": "write_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k06/work/answer.json"}}}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 13, "state": "ACTIVE", "step_type": "tool", "tool_name": "write_file", "tool_info": {"name": "write_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k06/work/track.svg"}}}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 13, "state": "DONE", "step_type": "tool", "tool_name": "write_file", "duration_seconds": 3.920155587, "tool_info": {"name": "write_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k06/work/track.svg"}}}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 14, "state": "DONE", "step_type": "agent_response", "duration_seconds": 4.430402489, "usage": {"input_tokens": 2173, "output_tokens": 158, "thinking_tokens": 32, "cache_read_tokens": 16208, "total_tokens": 2331}}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 15, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c 'import xml.etree.ElementTree as ET, json; root = ET.parse(\"track.svg\").getroot(); print(root.tag, [el.attrib.get(\"id\") for el in root.iter() if \"id\" in el.attrib]); print(list(json.load(open(\"answer.json\")).keys()))'"}}}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 15, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 1.32664267, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c 'import xml.etree.ElementTree as ET, json; root = ET.parse(\"track.svg\").getroot(); print(root.tag, [el.attrib.get(\"id\") for el in root.iter() if \"id\" in el.attrib]); print(list(json.load(open(\"answer.json\")).keys()))'"}, "output": "Command exited with code 0.\n\nCommand output:\n{http://www.w3.org/2000/svg}svg ['dr-track', 'ep-track', 'start', 'fix']\r\n['dr', 'ep', 'hours', 'set_deg', 'drift_kn', 'ep_error_nm', 'cmg_deg', 'smg_kn']\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "Created [solve.py](file"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": ":///home/bob/usecase-run"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "s/agy-batch/"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "out/gemini-4-argon-mediu"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "m/"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "k06/work/solve.py), [answer.json](file:///home/b"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ob/usecase-"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "runs/agy-batch/out/gemini-4-argon-me"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "dium/k06/work/answer."}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "json), and [track.svg](file:///home/bob/usecase-"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "runs/agy-bat"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ch/out"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "/gemini-4-argon-medium/k"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "06/work/trac"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "k.svg).\n\n### Summary of "}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "Implementation\n- **"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "Plane Sailing & Tracks ([`move_point"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "`](file:///home/bob/usec"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ase-runs/agy"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "-batch/out"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "/gemini-4-argon-medium/k06/work/solve.py#L7-L12"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "), [`solve`](file:///home/bob/usecas"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "e-runs/agy-b"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "atch/out/gemini-4-"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "argon-medium/k06/work/so"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "lve.py#L96-L173))**: Com"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "putes"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " dead reckoning (`dr`) a"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "nd estimated position (`"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ep`) per leg"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " using mid-latitude plan"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "e sailing, a"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "dding the forecast curre"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "nt vector per"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " leg for `ep`.\n- **Vectors & Metrics"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " ([`diff_nm`](file:///ho"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "me/bob/usecase-runs"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "/agy-batch/out/gemini-4-"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "argon-medium/k06/work/so"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "lve.py"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "#L15-L19), [`vector_angle_and_len`](file:///home"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "/bob/usecase"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "-runs/agy-"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "batch/out/gemini-4-argon"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "-medium/k06/work/solve.p"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "y#L2"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "2-L25))**: Computes `set_deg` and `drift_kn` fro"}}
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{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "o fix, `ep_error"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "_nm` from final EP to fi"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "x, and `cmg_deg` and `sm"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "g_kn` from"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " start to fi"}}
{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "x.\n- **Static Visualization ([`gener"}}
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{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "e.py#L28-L"}}
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{"event": "step_update", "step_update": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "step_index": 16, "state": "DONE", "step_type": "agent_response", "text_delta": "\n", "duration_seconds": 12.959295628, "usage": {"input_tokens": 2370, "output_tokens": 530, "thinking_tokens": 16, "cache_read_tokens": 16332, "total_tokens": 2900}}}
{"event": "result", "result": {"conversation_id": "12e723c6-0647-400b-9150-e23dcf04d215", "status": "SUCCESS", "response": "Created [solve.py](file:///home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k06/work/solve.py), [answer.json](file:///home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k06/work/answer.json), and [track.svg](file:///home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k06/work/track.svg).\n\n### Summary of Implementation\n- **Plane Sailing & Tracks ([`move_point`](file:///home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k06/work/solve.py#L7-L12), [`solve`](file:///home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k06/work/solve.py#L96-L173))**: Computes dead reckoning (`dr`) and estimated position (`ep`) per leg using mid-latitude plane sailing, adding the forecast current vector per leg for `ep`.\n- **Vectors & Metrics ([`diff_nm`](file:///home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k06/work/solve.py#L15-L19), [`vector_angle_and_len`](file:///home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k06/work/solve.py#L22-L25))**: Computes `set_deg` and `drift_kn` from final DR to fix, `ep_error_nm` from final EP to fix, and `cmg_deg` and `smg_kn` from start to fix.\n- **Static Visualization ([`generate_svg`](file:///home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k06/work/solve.py#L28-L93))**: Renders a self-contained `<svg>` with `<polyline id=\"dr-track\">`, `<polyline id=\"ep-track\">`, and `<circle id=\"fix\">`.\n", "duration_seconds": 134.971722336, "num_turns": 1, "usage": {"input_tokens": 27427, "output_tokens": 7591, "thinking_tokens": 1765, "cache_read_tokens": 84367, "total_tokens": 35018}}}