Gemini 4 Argon (effort medium · thinking on) on Tide height by rule of twelfths and cosine, with under-keel clearance windows
GGemini 4 Argonmedium · thinking on · Antigravity CLI 1.4.5 (agy -p) · cloud · 2026-10-22 · by @bobsiopener
- Estimated cost
- $0.27
- Wall time
- 5m
- Human step-ins
- 0
- Outcome
- Pass
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Summary
Exact prompt
# Tide height by rule of twelfths and cosine, and under-keel clearance `input.json` (synthetic, not for navigation) gives two consecutive tide events `event1` and `event2` (`time_min` minutes, `height_m`; either rising or falling), `chart_depth_m`, the boat's `draft_m`, required `min_ukc_m`, `need_minutes`, and `queries` (minutes). Write `solve.py` (Python 3 standard library only); `python solve.py input.json answer.json` writes `answer.json` and `tide.svg`. Fresh inputs are used too. ## Rules Let T = event2 time - event1 time and f = (t - event1 time) / T clamped to [0, 1]. Height = h1 + (h2 - h1) * F(f). - **Twelfths**: split [0, 1] into 6 equal parts; cumulative fractions at the part boundaries are 0, 1, 3, 6, 9, 11, 12 twelfths; interpolate linearly inside a part. - **Cosine**: F(f) = (1 - cos(pi * f)) / 2. - Under-keel clearance UKC = chart_depth + height(twelfths) - draft. A query is `safe` if UKC >= min_ukc. `required_height_m` = draft + min_ukc - chart_depth. - Safe window (per method): scan whole minutes t from event1 to event2 inclusive; a run is consecutive minutes with height >= required height. Report the first run whose length end - start (minutes) is >= `need_minutes` as `{"start", "end"}` (first and last safe minute), or null. - `max_method_diff_m`: the largest |twelfths - cosine| over those whole minutes. Use a 1e-9 tolerance on the >= comparisons. Round heights and UKC to 3 decimals. ## Visual output: tide.svg Static, self-contained SVG (root `<svg>`, no scripts, images, links or external assets; renders headless) with `<polyline id="tide-twelfths">`, `<polyline id="tide-cosine">` and `<line id="min-depth-line">` at the required height. The drawing itself is not graded. ## answer.json `{"required_height_m", "queries": [{"t", "twelfths", "cosine", "ukc", "safe"}, ...], "window_twelfths", "window_cosine", "max_method_diff_m"}` ## Scoring Hidden checks (partial credit; all must pass): `query_heights`, `safe_windows` (exact), `method_difference`, `tide_svg_static` (tide.svg exists, follows the static rules, has the ids/tags above), `fresh_run_1`, `fresh_run_2`. Numbers within 0.0015. 60-second limit per run.
Piecewise twelfths interpolation vs the cosine curve on rising and falling tides, a clamped fraction, a minute-by-minute run search with a length rule, and exact window endpoints. 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. query_heights 2. safe_windows 3. method_difference 4. tide_svg_static 5. fresh_run_1 6. fresh_run_2
Setup notes: Use Case Scout batch10 case k05-tide-underkeel-clearance (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 (tide.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: 6/6. Cost is an ESTIMATE: measured tokens x pricing.json list price (Google account, nothing billed per token); output_tokens include thinking tokens. Tool calls 10 (0 failed). Single run.
Estimated cost List-price estimate; not actually billed.
Output
Metrics
- Estimated cost
- $0.27
- Wall time
- 5m
- Human step-ins
- 0
- Turns
- 10
| Model | Input tok | Output tok | Cost |
|---|---|---|---|
| GGemini 4 Argongoogle/gemini-4-argoneffort medium · thinking on | 171,344 | 15,608 | $0.27 |
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. query_heights 2. safe_windows 3. method_difference 4. tide_svg_static 5. fresh_run_1 6. 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": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "init": {"model": "gemini-4-argon-medium", "cwd": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k05/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"}}
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{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 1, "state": "DONE", "step_type": "agent_response", "duration_seconds": 7.498478146, "usage": {"input_tokens": 8460, "output_tokens": 68, "thinking_tokens": 14, "cache_read_tokens": 0, "total_tokens": 8528}}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 2, "state": "ACTIVE", "step_type": "tool", "tool_name": "read_file", "tool_info": {"name": "read_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k05/work/input.json"}}}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 2, "state": "DONE", "step_type": "tool", "tool_name": "read_file", "duration_seconds": 0.050419628, "tool_info": {"name": "read_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k05/work/input.json"}, "output": "26 lines, 281 bytes"}}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 3, "state": "DONE", "step_type": "agent_response", "duration_seconds": 55.09576242, "usage": {"input_tokens": 2482, "output_tokens": 3343, "thinking_tokens": 1097, "cache_read_tokens": 6406, "total_tokens": 5825}}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 4, "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/k05/work/solve.py"}}}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 4, "state": "DONE", "step_type": "tool", "tool_name": "write_file", "duration_seconds": 3.224795064, "tool_info": {"name": "write_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k05/work/solve.py"}}}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 5, "state": "DONE", "step_type": "agent_response", "duration_seconds": 5.296350159, "usage": {"input_tokens": 3423, "output_tokens": 85, "thinking_tokens": 22, "cache_read_tokens": 8889, "total_tokens": 3508}}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "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": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 6, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 1.905435254, "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/k05/work/solve.py\", line 168, in <module>\r\n main()\r\n ~~~~^^\r\n File \"/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k05/work/solve.py\", line 155, in main\r\n with open(out_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": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 7, "state": "DONE", "step_type": "agent_response", "duration_seconds": 14.124170739, "usage": {"input_tokens": 2428, "output_tokens": 173, "thinking_tokens": 101, "cache_read_tokens": 10263, "total_tokens": 2601}}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 8, "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": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 8, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 3.359008991, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 solve.py input.json /tmp/answer.json && cat /tmp/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/k05/work/solve.py\", line 168, in <module>\r\n main()\r\n ~~~~^^\r\n File \"/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k05/work/solve.py\", line 163, in main\r\n with open(sp, \"w\", encoding=\"utf-8\") as f:\r\n ~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^\r\nOSError: [Errno 30] Read-only file system: 'tide.svg'\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 9, "state": "DONE", "step_type": "agent_response", "duration_seconds": 10.674627442, "usage": {"input_tokens": 2515, "output_tokens": 603, "thinking_tokens": 249, "cache_read_tokens": 10642, "total_tokens": 3118}}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 10, "state": "ACTIVE", "step_type": "tool", "tool_name": "edit_file", "tool_info": {"name": "edit_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k05/work/solve.py"}}}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 10, "state": "DONE", "step_type": "tool", "tool_name": "edit_file", "duration_seconds": 1.13342649, "tool_info": {"name": "edit_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k05/work/solve.py"}}}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 11, "state": "DONE", "step_type": "agent_response", "duration_seconds": 12.328082748, "usage": {"input_tokens": 2782, "output_tokens": 110, "thinking_tokens": 38, "cache_read_tokens": 11108, "total_tokens": 2892}}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 12, "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": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 12, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 1.845823635, "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 \"required_height_m\": 1.54,\r\n \"queries\": [\r\n {\r\n \"t\": 597,\r\n \"twelfths\": 0.96,\r\n \"cosine\": 0.96,\r\n \"ukc\": 0.02,\r\n \"safe\": false\r\n },\r\n {\r\n \"t\": 628,\r\n \"twelfths\": 1.049,\r\n \"cosine\": 1.0,\r\n \"ukc\": 0.109,\r\n \"safe\": false\r\n },\r\n {\r\n \"t\": 648,\r\n \"twelfths\": 1.106,\r\n \"cosine\": 1.066,\r\n \"ukc\": 0.166,\r\n \"safe\": false\r\n },\r\n {\r\n \"t\": 653,\r\n \"twelfths\": 1.121,\r\n \"cosine\": 1.088,\r\n \"ukc\": 0.181,\r\n \"safe\": false\r\n },\r\n {\r\n \"t\": 656,\r\n \"twelfths\": 1.136,\r\n \"cosine\": 1.101,\r\n \"ukc\": 0.196,\r\n \"safe\": false\r\n },\r\n {\r\n \"t\": 767,\r\n \"twelfths\": 1.935,\r\n \"cosine\": 1.935,\r\n \"ukc\": 0.995,\r\n \"safe\": true\r\n },\r\n {\r\n \"t\": 867,\r\n \"twelfths\": 2.671,\r\n \"cosine\": 2.713,\r\n \"ukc\": 1.731,\r\n \"safe\": true\r\n },\r\n {\r\n \"t\": 880,\r\n \"twelfths\": 2.746,\r\n \"cosine\": 2.778,\r\n \"ukc\": 1.806,\r\n \"safe\": true\r\n },\r\n {\r\n \"t\": 902,\r\n \"twelfths\": 2.81,\r\n \"cosine\": 2.859,\r\n \"ukc\": 1.87,\r\n \"safe\": true\r\n },\r\n {\r\n \"t\": 937,\r\n \"twelfths\": 2.91,\r\n \"cosine\": 2.91,\r\n \"ukc\": 1.97,\r\n \"safe\": true\r\n }\r\n ],\r\n \"window_twelfths\": {\r\n \"start\": 722,\r\n \"end\": 937\r\n },\r\n \"window_cosine\": {\r\n \"start\": 722,\r\n \"end\": 937\r\n },\r\n \"max_method_diff_m\": 0.05\r\n}"}}}
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{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 18, "state": "DONE", "step_type": "tool", "tool_name": "write_file", "duration_seconds": 1.7150760840000001, "tool_info": {"name": "write_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k05/work/answer.json"}}}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 19, "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/k05/work/tide.svg"}}}}
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{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "-argon-medium/"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "k05/work/answer.json) an"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "d [tide.svg](file:///hom"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "e/bob/usecas"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "e"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "-runs/agy-batch/out/gemi"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ni-4-argon-medium/k05/wo"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "rk/tide"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": ".svg):\n\n- Implemented [`"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "f_twelfths`](file:///hom"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "e/bob/usecase-runs/"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "agy-batch/out/gemini-4-a"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "rgon-medium/k05/work/sol"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ve.py#"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "L14-L23) and [`f_cosine`](file:///ho"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "me/bob/usecase-runs/agy-"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "batch/out/"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "gemini-4-argon-medium/k0"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "5/work/solve.py#L26-L2"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "8) for tide height interpolation acr"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "oss `[event1, event2]`.\n"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "- Computed `"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "required_height_m`, per-"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "query `twelfths`, `cosine`, `ukc`, a"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "nd `safe` fl"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ags, safe windows via"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " [`find_safe_window`](file:///home/b"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ob/usecase-runs/agy-batc"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "h/out/gemini"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "-4-argon"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "-medium/k05/work/solve.p"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "y#L38-L59) with `1"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "e-9` tolerance, and `max_method_diff"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "_m`.\n- Rendered self-con"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "tained static SVG"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " output via [`make_svg`](file:///home/bob/usecas"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "e-runs/agy-b"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "atch/out/"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "gemini-4-argon-medium/k05/work/solve"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": ".py#L62-L1"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "02) containing `#tide-twelfths`, `#t"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ide-cosine`, and `#min-d"}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "epth-line`."}}
{"event": "step_update", "step_update": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "step_index": 20, "state": "DONE", "step_type": "agent_response", "text_delta": "\n", "duration_seconds": 17.257433494, "usage": {"input_tokens": 10695, "output_tokens": 444, "thinking_tokens": 18, "cache_read_tokens": 25874, "total_tokens": 11139}}}
{"event": "result", "result": {"conversation_id": "20101b6e-78c8-4b96-8965-8cf8c0a60433", "status": "SUCCESS", "response": "Created [solve.py](file:///home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k05/work/solve.py) and generated [answer.json](file:///home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k05/work/answer.json) and [tide.svg](file:///home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k05/work/tide.svg):\n\n- Implemented [`f_twelfths`](file:///home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k05/work/solve.py#L14-L23) and [`f_cosine`](file:///home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k05/work/solve.py#L26-L28) for tide height interpolation across `[event1, event2]`.\n- Computed `required_height_m`, per-query `twelfths`, `cosine`, `ukc`, and `safe` flags, safe windows via [`find_safe_window`](file:///home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k05/work/solve.py#L38-L59) with `1e-9` tolerance, and `max_method_diff_m`.\n- Rendered self-contained static SVG output via [`make_svg`](file:///home/bob/usecase-runs/agy-batch/out/gemini-4-argon-medium/k05/work/solve.py#L62-L102) containing `#tide-twelfths`, `#tide-cosine`, and `#min-depth-line`.\n", "duration_seconds": 272.976577685, "num_turns": 1, "usage": {"input_tokens": 48865, "output_tokens": 15608, "thinking_tokens": 1755, "cache_read_tokens": 122479, "total_tokens": 64473}}}