Gemini 3.8 Flash (effort medium · thinking on) on Anchor drag alarm from a GPS track

GGemini 3.8 Flashmedium · thinking on · Antigravity CLI 1.4.5 (agy -p) · cloud · 2026-10-22 · by @bobsiopener
Trust 80%Fully autonomoussuccess · first tryCompare
Estimated cost: $0.46
Wall time: 4m
Human step-ins: 0
Outcome: Pass
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Exact prompt

# Anchor drag alarm from a GPS track `input.json` (synthetic, not for real anchor watch): `anchor` [lat, lon], `rode_m`, `depth_m`, `bow_height_m`, `gps_offset_m`, `margin_m`, `consecutive` N, and `track` (CSV `t,lat,lon`, t in seconds). Write `solve.py` (Python 3 standard library only); `python solve.py input.json answer.json` writes `answer.json` and `anchor.svg`. Fresh inputs are used too. ## Rules 1. Alarm radius = sqrt(rode^2 - (depth + bow_height)^2) (0 if rode <= depth + bow_height) + gps_offset + margin. 2. Track rows: skip the header. A row is **bad** (counted, skipped) if it has fewer than 3 fields, t is not an integer, lat/lon is not a finite number in range [-90, 90] / [-180, 180], or t is not greater than the last *valid* row's t. 3. Distance from the anchor (metres): R = 6371000; m = mean of the anchor and point latitudes; x = radians(dlon) * cos(m) * R (east), y = radians(dlat) * R (north); distance = hypot(x, y). A point is **outside** if distance > radius. 4. An **event** is a maximal run of consecutive valid points that are outside, with length >= N. Report `start_t` (first point), `trigger_t` (Nth point), `end_t` (last point), `max_dist_m`, and `bearing_deg` = atan2(x, y) mod 360 from the anchor to the run's last point. 5. Round the radius to 2 decimals and distances and bearings to 1. ## Visual output: anchor.svg Static, self-contained SVG (root `<svg>`, no scripts, images, links or external assets; renders headless) with `<circle id="swing-circle">`, `<polyline id="track">` and an element `id="anchor"`. The drawing itself is not graded. ## answer.json `{"radius_m", "valid_points", "bad_rows", "events": [...], "max_dist_m", "outside_points"}` ## Scoring Hidden checks (partial credit; all must pass): `swing_radius` (within 0.011), `track_cleaning` (exact), `distances`, `alarm_events` (times exact, values within 0.11), `anchor_svg_static` (anchor.svg exists, follows the static rules, has the ids/tags above), `fresh_run_1`, `fresh_run_2`. 60-second limit per run.
Catenary-free swing radius with offsets, rejecting bad and out-of-order rows against the last valid time, short excursions that must not trigger, and a real drag run with trigger time and bearing. 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. swing_radius 2. track_cleaning 3. distances 4. alarm_events 5. anchor_svg_static 6. fresh_run_1 7. fresh_run_2
Setup notes: Use Case Scout batch10 case k07-anchor-drag-alarm (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 (anchor.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 39 (0 failed). Single run.
Estimated cost List-price estimate; not actually billed.
Output

Gemini 3.8 Flash (effort medium · thinking on) on Anchor drag alarm from a GPS trackSuccess
Metrics

Estimated cost: $0.46
Wall time: 4m
Human step-ins: 0
Turns: 40
Model usage
Model	Input tok	Output tok	Cost
GGemini 3.8 Flashgoogle/gemini-3.8-flasheffort medium · thinking on	1,583,952	46,722	$0.46
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. swing_radius 2. track_cleaning 3. distances 4. alarm_events 5. anchor_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": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "init": {"model": "gemini-3.8-flash-medium", "cwd": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k07/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": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 0, "state": "DONE", "step_type": "user_input"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 1, "state": "DONE", "step_type": "agent_response", "duration_seconds": 3.287336934, "usage": {"input_tokens": 8455, "output_tokens": 114, "thinking_tokens": 77, "cache_read_tokens": 0, "total_tokens": 8569}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "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": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 2, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.295602519, "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 10:56 .\r\ndrwxrwxr-x 3 bob bob 4096 Oct 22 12:11 ..\r\n-rw-r--r-- 1 bob bob 2020 Oct 22 10:56 TASK.md\r\n-rw-r--r-- 1 bob bob 3849 Oct 22 10:56 anchor.svg\r\n-rw-r--r-- 1 bob bob  183 Oct 22 10:56 input.json\r\n-rw-r--r-- 1 bob bob 8517 Oct 22 10:56 track.csv\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 3, "state": "DONE", "step_type": "agent_response", "duration_seconds": 2.638107524, "usage": {"input_tokens": 8831, "output_tokens": 78, "thinking_tokens": 27, "cache_read_tokens": 0, "total_tokens": 8909}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "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/k07/work/TASK.md"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 4, "state": "DONE", "step_type": "tool", "tool_name": "read_file", "duration_seconds": 0.02676807, "tool_info": {"name": "read_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k07/work/TASK.md"}, "output": "19 lines, 2020 bytes"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 5, "state": "DONE", "step_type": "agent_response", "duration_seconds": 4.226512107, "usage": {"input_tokens": 9705, "output_tokens": 74, "thinking_tokens": 23, "cache_read_tokens": 0, "total_tokens": 9779}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 6, "state": "ACTIVE", "step_type": "tool", "tool_name": "read_file", "tool_info": {"name": "read_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k07/work/input.json"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 6, "state": "DONE", "step_type": "tool", "tool_name": "read_file", "duration_seconds": 0.032818838, "tool_info": {"name": "read_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k07/work/input.json"}, "output": "13 lines, 183 bytes"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 7, "state": "DONE", "step_type": "agent_response", "duration_seconds": 3.088895412, "usage": {"input_tokens": 10023, "output_tokens": 83, "thinking_tokens": 21, "cache_read_tokens": 0, "total_tokens": 10106}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 8, "state": "ACTIVE", "step_type": "tool", "tool_name": "read_file", "tool_info": {"name": "read_file", "parameters": {"EndLine": 50, "Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k07/work/track.csv", "StartLine": 1}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 8, "state": "DONE", "step_type": "tool", "tool_name": "read_file", "duration_seconds": 0.022267592, "tool_info": {"name": "read_file", "parameters": {"EndLine": 50, "Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k07/work/track.csv", "StartLine": 1}, "output": "301 lines, 8517 bytes"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 9, "state": "DONE", "step_type": "agent_response", "duration_seconds": 5.179035362, "usage": {"input_tokens": 11701, "output_tokens": 79, "thinking_tokens": 11, "cache_read_tokens": 0, "total_tokens": 11780}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 10, "state": "ACTIVE", "step_type": "tool", "tool_name": "read_file", "tool_info": {"name": "read_file", "parameters": {"ByteOffset": 0, "EndLine": 100, "Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k07/work/anchor.svg", "StartLine": 1}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 10, "state": "DONE", "step_type": "tool", "tool_name": "read_file", "duration_seconds": 0.029292171, "tool_info": {"name": "read_file", "parameters": {"ByteOffset": 0, "EndLine": 100, "Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k07/work/anchor.svg", "StartLine": 1}, "output": "1 lines, 3849 bytes"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 11, "state": "DONE", "step_type": "agent_response", "duration_seconds": 2.085272965, "usage": {"input_tokens": 15536, "output_tokens": 82, "thinking_tokens": 46, "cache_read_tokens": 0, "total_tokens": 15618}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 12, "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": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 12, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.285024402, "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 parent up to mount point /)\r\nStopping at filesystem boundary (GIT_DISCOVERY_ACROSS_FILESYSTEM not set).\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 13, "state": "DONE", "step_type": "agent_response", "duration_seconds": 8.589052342, "usage": {"input_tokens": 15742, "output_tokens": 1499, "thinking_tokens": 1422, "cache_read_tokens": 0, "total_tokens": 17241}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 14, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport json, math, csv\n\nwith open(\"input.json\") as f:\n    inp = json.load(f)\n\nprint(inp)\n'"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 14, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 1.572276089, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport json, math, csv\n\nwith open(\"input.json\") as f:\n    inp = json.load(f)\n\nprint(inp)\n'"}, "output": "Command exited with code 0.\n\nCommand output:\n{'anchor': [-23.4155114, 143.598916], 'rode_m': 30, 'depth_m': 5.9, 'bow_height_m': 1.2, 'gps_offset_m': 4.0, 'margin_m': 5.0, 'consecutive': 3, 'track': 'track.csv'}\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 15, "state": "DONE", "step_type": "agent_response", "duration_seconds": 3.041983813, "usage": {"input_tokens": 17422, "output_tokens": 507, "thinking_tokens": 380, "cache_read_tokens": 0, "total_tokens": 17929}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 16, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport re\n\nwith open(\"anchor.svg\") as f:\n    s = f.read()\n\npts = re.findall(r\"([0-9.]+),([0-9.]+)\", s)\nprint(f\"Number of points in polyline: {len(pts)}\")\nprint(\"First 5:\", pts[:5])\nprint(\"Last 5:\", pts[-5:])\n'"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 16, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.273198633, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport re\n\nwith open(\"anchor.svg\") as f:\n    s = f.read()\n\npts = re.findall(r\"([0-9.]+),([0-9.]+)\", s)\nprint(f\"Number of points in polyline: {len(pts)}\")\nprint(\"First 5:\", pts[:5])\nprint(\"Last 5:\", pts[-5:])\n'"}, "output": "Command exited with code 0.\n\nCommand output:\nNumber of points in polyline: 295\r\nFirst 5: [('372.6', '264.8'), ('365.7', '245.7'), ('363.8', '233.3'), ('352.9', '223.9'), ('335.3', '240.1')]\r\nLast 5: [('363.8', '199.9'), ('338.0', '189.4'), ('360.1', '204.4'), ('353.5', '211.1'), ('357.5', '207.9')]\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 17, "state": "DONE", "step_type": "agent_response", "duration_seconds": 3.616949178, "usage": {"input_tokens": 6000, "output_tokens": 684, "thinking_tokens": 158, "cache_read_tokens": 12178, "total_tokens": 6684}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 18, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport csv, math\n\nwith open(\"track.csv\") as f:\n    reader = csv.reader(f)\n    header = next(reader)\n    print(\"Header:\", header)\n    \n    valid = []\n    bad = []\n    last_t = None\n    \n    for row_idx, row in enumerate(reader, start=2):\n        if len(row) < 3:\n            bad.append((row_idx, row, \"fewer than 3 fields\"))\n            continue\n        try:\n            t_val = int(row[0])\n            # Check if t is an integer string (or does int() handle it? what if float string like 12.3?)\n    \u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 18, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.27746847, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport csv, math\n\nwith open(\"track.csv\") as f:\n    reader = csv.reader(f)\n    header = next(reader)\n    print(\"Header:\", header)\n    \n    valid = []\n    bad = []\n    last_t = None\n    \n    for row_idx, row in enumerate(reader, start=2):\n        if len(row) < 3:\n            bad.append((row_idx, row, \"fewer than 3 fields\"))\n            continue\n        try:\n            t_val = int(row[0])\n            # Check if t is an integer string (or does int() handle it? what if float string like 12.3?)\n    \u2026"}, "output": "Command exited with code 0.\n\nCommand output:\nHeader: ['t', 'lat', 'lon']\r\nValid count: 290, Bad count: 10\r\n(83, ['842', '-23.4153660', 'NaNx'], 'lat/lon not float')\r\n(88, ['892', '', '143.5992776'], 'lat/lon not float')\r\n(106, ['1075', '-23.4154449', 'NaNx'], 'lat/lon not float')\r\n(109, ['1106', '', '143.5989548'], 'lat/lon not float')\r\n(111, ['1126', '-23.4154351', 'NaNx'], 'lat/lon not float')\r\n(136, ['1379', '', '143.5988188'], 'lat/lon not float')\r\n(195, ['1986', '', '143.5989700'], 'lat/lon not float')\r\n(239, ['2433', '', '143.5987847'], 'lat/lon not float')\r\n(268, ['2718', '-23.4152097', '143.5986662'], 't 2718 <= last_t 2722')\r\n(281, ['2866', '', '143.5986846'], 'lat/lon not float')\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 19, "state": "DONE", "step_type": "agent_response", "duration_seconds": 2.899628188, "usage": {"input_tokens": 3090, "output_tokens": 256, "thinking_tokens": 130, "cache_read_tokens": 16237, "total_tokens": 3346}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 20, "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\ntree = ET.parse(\"anchor.svg\")\nroot = tree.getroot()\nfor elem in root.iter():\n    if elem.get(\"id\") == \"track\":\n        pts = elem.get(\"points\").strip().split()\n        print(\"Count in polyline track:\", len(pts))\n'"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 20, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.294139914, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport xml.etree.ElementTree as ET\n\ntree = ET.parse(\"anchor.svg\")\nroot = tree.getroot()\nfor elem in root.iter():\n    if elem.get(\"id\") == \"track\":\n        pts = elem.get(\"points\").strip().split()\n        print(\"Count in polyline track:\", len(pts))\n'"}, "output": "Command exited with code 0.\n\nCommand output:\nCount in polyline track: 295\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 21, "state": "DONE", "step_type": "agent_response", "duration_seconds": 9.500298424, "usage": {"input_tokens": 3447, "output_tokens": 239, "thinking_tokens": 67, "cache_read_tokens": 16232, "total_tokens": 3686}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 22, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport xml.etree.ElementTree as ET\nimport csv\n\ntree = ET.parse(\"anchor.svg\")\npts = None\nfor elem in tree.getroot().iter():\n    if elem.get(\"id\") == \"track\":\n        pts = [list(map(float, p.split(\",\"))) for p in elem.get(\"points\").strip().split()]\n\nwith open(\"track.csv\") as f:\n    rows = list(csv.reader(f))[1:]\n\nprint(\"len pts:\", len(pts), \"len rows:\", len(rows))\n'"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 22, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.309410259, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport xml.etree.ElementTree as ET\nimport csv\n\ntree = ET.parse(\"anchor.svg\")\npts = None\nfor elem in tree.getroot().iter():\n    if elem.get(\"id\") == \"track\":\n        pts = [list(map(float, p.split(\",\"))) for p in elem.get(\"points\").strip().split()]\n\nwith open(\"track.csv\") as f:\n    rows = list(csv.reader(f))[1:]\n\nprint(\"len pts:\", len(pts), \"len rows:\", len(rows))\n'"}, "output": "Command exited with code 0.\n\nCommand output:\nlen pts: 295 len rows: 300\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 23, "state": "DONE", "step_type": "agent_response", "duration_seconds": 3.216794501, "usage": {"input_tokens": 3792, "output_tokens": 457, "thinking_tokens": 44, "cache_read_tokens": 16226, "total_tokens": 4249}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 24, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport xml.etree.ElementTree as ET\nimport csv, math\n\ntree = ET.parse(\"anchor.svg\")\nsvg_pts = None\nfor elem in tree.getroot().iter():\n    if elem.get(\"id\") == \"track\":\n        svg_pts = [list(map(float, p.split(\",\"))) for p in elem.get(\"points\").strip().split()]\n\nwith open(\"track.csv\") as f:\n    rows = list(csv.reader(f))[1:]\n\n# Let us check which rows in track.csv correspond to svg_pts\n# Look at first point in svg_pts: (372.6, 264.8)\n# Let anchor = [-23.4155114, 143.598916]\n# Let us compute x, \u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 24, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.275004532, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport xml.etree.ElementTree as ET\nimport csv, math\n\ntree = ET.parse(\"anchor.svg\")\nsvg_pts = None\nfor elem in tree.getroot().iter():\n    if elem.get(\"id\") == \"track\":\n        svg_pts = [list(map(float, p.split(\",\"))) for p in elem.get(\"points\").strip().split()]\n\nwith open(\"track.csv\") as f:\n    rows = list(csv.reader(f))[1:]\n\n# Let us check which rows in track.csv correspond to svg_pts\n# Look at first point in svg_pts: (372.6, 264.8)\n# Let anchor = [-23.4155114, 143.598916]\n# Let us compute x, \u2026"}, "output": "Command exited with code 0.\n\nCommand output:\nRow 0: t=10, x=21.41, y=1.43, svg=[372.6, 264.8]\r\nRow 1: t=20, x=21.76, y=7.59, svg=[365.7, 245.7]\r\nRow 2: t=30, x=19.47, y=9.13, svg=[363.8, 233.3]\r\nRow 3: t=40, x=17.11, y=5.39, svg=[352.9, 223.9]\r\nRow 4: t=50, x=17.54, y=8.85, svg=[335.3, 240.1]\r\nRow 5: t=60, x=16.10, y=11.11, svg=[341.9, 223.8]\r\nRow 6: t=70, x=16.53, y=13.93, svg=[337.1, 211.8]\r\nRow 7: t=80, x=10.55, y=15.40, svg=[343.2, 197.8]\r\nRow 8: t=90, x=9.39, y=14.42, svg=[314.0, 186.7]\r\nRow 9: t=100, x=9.85, y=15.06, svg=[306.6, 191.2]\r\nRow 10: t=110, x=9.56, y=13.51, svg=[309.9, 188.2]\r\nRow 11: t=120, x=9.64, y=12.79, svg=[306.2, 196.1]\r\nRow 12: t=130, x=9.13, y=13.25, svg=[305.5, 199.9]\r\nRow 13: t=140, x=6.42, y=13.87, svg=[303.7, 197.2]\r\nRow 14: t=151, x=6.22, y=14.20, svg=[291.2, 192.7]\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 25, "state": "DONE", "step_type": "agent_response", "duration_seconds": 8.053155811, "usage": {"input_tokens": 4947, "output_tokens": 587, "thinking_tokens": 475, "cache_read_tokens": 16227, "total_tokens": 5534}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 26, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport csv\n\nwith open(\"track.csv\") as f:\n    rows = list(csv.reader(f))[1:]\n\nfor i, r in enumerate(rows):\n    if \"\" in r or \"NaNx\" in r:\n        print(\"Missing/NaN row:\", i, r)\n'"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 26, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.280615237, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport csv\n\nwith open(\"track.csv\") as f:\n    rows = list(csv.reader(f))[1:]\n\nfor i, r in enumerate(rows):\n    if \"\" in r or \"NaNx\" in r:\n        print(\"Missing/NaN row:\", i, r)\n'"}, "output": "Command exited with code 0.\n\nCommand output:\nMissing/NaN row: 81 ['842', '-23.4153660', 'NaNx']\r\nMissing/NaN row: 86 ['892', '', '143.5992776']\r\nMissing/NaN row: 104 ['1075', '-23.4154449', 'NaNx']\r\nMissing/NaN row: 107 ['1106', '', '143.5989548']\r\nMissing/NaN row: 109 ['1126', '-23.4154351', 'NaNx']\r\nMissing/NaN row: 134 ['1379', '', '143.5988188']\r\nMissing/NaN row: 193 ['1986', '', '143.5989700']\r\nMissing/NaN row: 237 ['2433', '', '143.5987847']\r\nMissing/NaN row: 279 ['2866', '', '143.5986846']\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 27, "state": "DONE", "step_type": "agent_response", "duration_seconds": 12.361872879, "usage": {"input_tokens": 5892, "output_tokens": 4279, "thinking_tokens": 4238, "cache_read_tokens": 16226, "total_tokens": 10171}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 28, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "find . -type f"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 28, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.293262975, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "find . -type f"}, "output": "Command exited with code 0.\n\nCommand output:\n./anchor.svg\r\n./TASK.md\r\n./track.csv\r\n./input.json\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 29, "state": "DONE", "step_type": "agent_response", "duration_seconds": 13.740016187, "usage": {"input_tokens": 6194, "output_tokens": 1131, "thinking_tokens": 65, "cache_read_tokens": 20308, "total_tokens": 7325}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 30, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport json, csv, math\n\nwith open(\"input.json\") as f:\n    inp = json.load(f)\n\nanchor_lat, anchor_lon = inp[\"anchor\"]\nrode = inp[\"rode_m\"]\ndepth = inp[\"depth_m\"]\nbow = inp[\"bow_height_m\"]\ngps_offset = inp[\"gps_offset_m\"]\nmargin = inp[\"margin_m\"]\nN = inp[\"consecutive\"]\n\nh = depth + bow\nif rode <= h:\n    radius = gps_offset + margin\nelse:\n    radius = math.sqrt(rode**2 - h**2) + gps_offset + margin\n\nprint(f\"Calculated radius: {radius:.4f}, rounded: {round(radius, 2)}\")\n\ntrack_file = inp[\"track\"]\nw\u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 30, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.308946652, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport json, csv, math\n\nwith open(\"input.json\") as f:\n    inp = json.load(f)\n\nanchor_lat, anchor_lon = inp[\"anchor\"]\nrode = inp[\"rode_m\"]\ndepth = inp[\"depth_m\"]\nbow = inp[\"bow_height_m\"]\ngps_offset = inp[\"gps_offset_m\"]\nmargin = inp[\"margin_m\"]\nN = inp[\"consecutive\"]\n\nh = depth + bow\nif rode <= h:\n    radius = gps_offset + margin\nelse:\n    radius = math.sqrt(rode**2 - h**2) + gps_offset + margin\n\nprint(f\"Calculated radius: {radius:.4f}, rounded: {round(radius, 2)}\")\n\ntrack_file = inp[\"track\"]\nw\u2026"}, "output": "Command exited with code 0.\n\nCommand output:\nCalculated radius: 38.1477, rounded: 38.15\r\nValid points: 290, Bad rows: 10\r\nOutside points: 49\r\nAll valid points max dist: 50.4557, rounded: 50.5\r\nNumber of events: 3\r\nEvent 0: start_t=822, trigger_t=852, end_t=902, len=7, max_dist=42.9, bearing=68.2\r\nEvent 1: start_t=2640, trigger_t=2660, end_t=2967, len=31, max_dist=50.5, bearing=314.9\r\nEvent 2: start_t=2988, trigger_t=3009, end_t=3071, len=9, max_dist=43.6, bearing=301.8\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 31, "state": "DONE", "step_type": "agent_response", "duration_seconds": 3.529879884, "usage": {"input_tokens": 3574, "output_tokens": 623, "thinking_tokens": 180, "cache_read_tokens": 24371, "total_tokens": 4197}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 32, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport json, csv, math\n\nwith open(\"input.json\") as f:\n    inp = json.load(f)\n\nanchor_lat, anchor_lon = inp[\"anchor\"]\nradius = math.sqrt(inp[\"rode_m\"]**2 - (inp[\"depth_m\"] + inp[\"bow_height_m\"])**2) + inp[\"gps_offset_m\"] + inp[\"margin_m\"]\n\ntrack_file = inp[\"track\"]\nwith open(track_file) as f:\n    reader = csv.reader(f)\n    next(reader)\n    valid_points = []\n    last_t = None\n    for row in reader:\n        try:\n            t = int(row[0])\n            lat, lon = float(row[1]), float(row[2])\n      \u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 32, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.295726074, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport json, csv, math\n\nwith open(\"input.json\") as f:\n    inp = json.load(f)\n\nanchor_lat, anchor_lon = inp[\"anchor\"]\nradius = math.sqrt(inp[\"rode_m\"]**2 - (inp[\"depth_m\"] + inp[\"bow_height_m\"])**2) + inp[\"gps_offset_m\"] + inp[\"margin_m\"]\n\ntrack_file = inp[\"track\"]\nwith open(track_file) as f:\n    reader = csv.reader(f)\n    next(reader)\n    valid_points = []\n    last_t = None\n    for row in reader:\n        try:\n            t = int(row[0])\n            lat, lon = float(row[1]), float(row[2])\n      \u2026"}, "output": "Command exited with code 0.\n\nCommand output:\n(801, 10.829880589854403, False)\r\n(811, 10.606633305086943, False)\r\n(822, 39.799243083499, True)\r\n(832, 42.2805933159846, True)\r\n(852, 42.06005527680969, True)\r\n(862, 42.54297064573093, True)\r\n(872, 42.42769002812203, True)\r\n(882, 42.944873520315284, True)\r\n(902, 42.29227801261507, True)\r\n(912, 13.05162077183685, False)\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 33, "state": "DONE", "step_type": "agent_response", "duration_seconds": 4.662663098, "usage": {"input_tokens": 4553, "output_tokens": 555, "thinking_tokens": 268, "cache_read_tokens": 24370, "total_tokens": 5108}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 34, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport json, csv, math\n\nwith open(\"input.json\") as f:\n    inp = json.load(f)\n\nanchor_lat, anchor_lon = inp[\"anchor\"]\n# t=902\n# find row with t=902\nwith open(\"track.csv\") as f:\n    for row in csv.reader(f):\n        if row and row[0] == \"902\":\n            lat, lon = float(row[1]), float(row[2])\n            R = 6371000\n            m = math.radians((anchor_lat + lat) / 2.0)\n            x = math.radians(lon - anchor_lon) * math.cos(m) * R\n            y = math.radians(lat - anchor_lat) * R\n          \u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 34, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.29261247, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport json, csv, math\n\nwith open(\"input.json\") as f:\n    inp = json.load(f)\n\nanchor_lat, anchor_lon = inp[\"anchor\"]\n# t=902\n# find row with t=902\nwith open(\"track.csv\") as f:\n    for row in csv.reader(f):\n        if row and row[0] == \"902\":\n            lat, lon = float(row[1]), float(row[2])\n            R = 6371000\n            m = math.radians((anchor_lat + lat) / 2.0)\n            x = math.radians(lon - anchor_lon) * math.cos(m) * R\n            y = math.radians(lat - anchor_lat) * R\n          \u2026"}, "output": "Command exited with code 0.\n\nCommand output:\nx: 39.27433132626534 y: 15.689604149597185 dist: 42.29227801261507 bearing: 68.2239092144092 rounded: 68.2\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 35, "state": "DONE", "step_type": "agent_response", "duration_seconds": 10.371660938, "usage": {"input_tokens": 5284, "output_tokens": 3602, "thinking_tokens": 3231, "cache_read_tokens": 24367, "total_tokens": 8886}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 36, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport json, csv, math\n\nwith open(\"input.json\") as f:\n    inp = json.load(f)\n\nanchor_lat, anchor_lon = inp[\"anchor\"]\nradius = math.sqrt(inp[\"rode_m\"]**2 - (inp[\"depth_m\"] + inp[\"bow_height_m\"])**2) + inp[\"gps_offset_m\"] + inp[\"margin_m\"]\nradius_rounded = round(radius, 2)\n\nprint(\"radius:\", radius, \"radius_rounded:\", radius_rounded)\n\nwith open(inp[\"track\"]) as f:\n    reader = csv.reader(f)\n    next(reader)\n    for row in reader:\n        try:\n            t = int(row[0])\n            lat, lon = floa\u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 36, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.30390848, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport json, csv, math\n\nwith open(\"input.json\") as f:\n    inp = json.load(f)\n\nanchor_lat, anchor_lon = inp[\"anchor\"]\nradius = math.sqrt(inp[\"rode_m\"]**2 - (inp[\"depth_m\"] + inp[\"bow_height_m\"])**2) + inp[\"gps_offset_m\"] + inp[\"margin_m\"]\nradius_rounded = round(radius, 2)\n\nprint(\"radius:\", radius, \"radius_rounded:\", radius_rounded)\n\nwith open(inp[\"track\"]) as f:\n    reader = csv.reader(f)\n    next(reader)\n    for row in reader:\n        try:\n            t = int(row[0])\n            lat, lon = floa\u2026"}, "output": "Command exited with code 0.\n\nCommand output:\nradius: 38.14772718412192 radius_rounded: 38.15\r\nNear border: t=2640, dist=38.55033488623928\r\nNear border: t=2977, dist=37.84966439922902\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 37, "state": "DONE", "step_type": "agent_response", "duration_seconds": 7.809332939, "usage": {"input_tokens": 4982, "output_tokens": 2515, "thinking_tokens": 1849, "cache_read_tokens": 28447, "total_tokens": 7497}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 38, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport xml.etree.ElementTree as ET\nimport csv, math\n\nwith open(\"input.json\") as f:\n    import json\n    inp = json.load(f)\n\ntree = ET.parse(\"anchor.svg\")\nsvg_pts = None\nfor elem in tree.getroot().iter():\n    if elem.get(\"id\") == \"track\":\n        svg_pts = [list(map(float, p.split(\",\"))) for p in elem.get(\"points\").strip().split()]\n\nanchor_lat, anchor_lon = inp[\"anchor\"]\nR = 6371000\n\n# Compute valid points\nvalid_pts = []\nwith open(\"track.csv\") as f:\n    reader = csv.reader(f)\n    next(reader)\n   \u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 38, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.294479513, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport xml.etree.ElementTree as ET\nimport csv, math\n\nwith open(\"input.json\") as f:\n    import json\n    inp = json.load(f)\n\ntree = ET.parse(\"anchor.svg\")\nsvg_pts = None\nfor elem in tree.getroot().iter():\n    if elem.get(\"id\") == \"track\":\n        svg_pts = [list(map(float, p.split(\",\"))) for p in elem.get(\"points\").strip().split()]\n\nanchor_lat, anchor_lon = inp[\"anchor\"]\nR = 6371000\n\n# Compute valid points\nvalid_pts = []\nwith open(\"track.csv\") as f:\n    reader = csv.reader(f)\n    next(reader)\n   \u2026"}, "output": "Command exited with code 0.\n\nCommand output:\nValid pts: 290 svg pts: 295\r\nv0: (21.40751031416416, 1.4344145534906352) s0: [372.6, 264.8]\r\nv1: (21.764646834286864, 7.594613489689914) s1: [365.7, 245.7]\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 39, "state": "DONE", "step_type": "agent_response", "duration_seconds": 3.11728137, "usage": {"input_tokens": 3643, "output_tokens": 482, "thinking_tokens": 242, "cache_read_tokens": 32521, "total_tokens": 4125}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 40, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport xml.etree.ElementTree as ET\nimport csv, math\n\nwith open(\"input.json\") as f:\n    import json\n    inp = json.load(f)\n\ntree = ET.parse(\"anchor.svg\")\nsvg_pts = None\nfor elem in tree.getroot().iter():\n    if elem.get(\"id\") == \"track\":\n        svg_pts = [list(map(float, p.split(\",\"))) for p in elem.get(\"points\").strip().split()]\n\nwith open(\"track.csv\") as f:\n    rows = list(csv.reader(f))[1:]\n\n# Is there a linear fit between valid_pts or all rows and svg_pts?\n# Notice svg_pts has 295 points.\n#\u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 40, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.295844386, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport xml.etree.ElementTree as ET\nimport csv, math\n\nwith open(\"input.json\") as f:\n    import json\n    inp = json.load(f)\n\ntree = ET.parse(\"anchor.svg\")\nsvg_pts = None\nfor elem in tree.getroot().iter():\n    if elem.get(\"id\") == \"track\":\n        svg_pts = [list(map(float, p.split(\",\"))) for p in elem.get(\"points\").strip().split()]\n\nwith open(\"track.csv\") as f:\n    rows = list(csv.reader(f))[1:]\n\n# Is there a linear fit between valid_pts or all rows and svg_pts?\n# Notice svg_pts has 295 points.\n#\u2026"}, "output": "Command exited with code 0.\n\nNo output from the command."}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 41, "state": "DONE", "step_type": "agent_response", "duration_seconds": 11.8423234, "usage": {"input_tokens": 4217, "output_tokens": 3695, "thinking_tokens": 3526, "cache_read_tokens": 32516, "total_tokens": 7912}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 42, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport math\n\n# North is x=0, y=1 -> atan2(0, 1) = 0.0\nprint(\"Due North:\", math.degrees(math.atan2(0, 1)) % 360)\n# Slightly West of North: x = -0.0001, y = 1.0\na = math.degrees(math.atan2(-0.0001, 1.0)) % 360\nprint(\"Slightly West:\", a, \"rounded:\", round(a, 1))\n'"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 42, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.291808307, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport math\n\n# North is x=0, y=1 -> atan2(0, 1) = 0.0\nprint(\"Due North:\", math.degrees(math.atan2(0, 1)) % 360)\n# Slightly West of North: x = -0.0001, y = 1.0\na = math.degrees(math.atan2(-0.0001, 1.0)) % 360\nprint(\"Slightly West:\", a, \"rounded:\", round(a, 1))\n'"}, "output": "Command exited with code 0.\n\nCommand output:\nDue North: 0.0\r\nSlightly West: 359.9942704220678 rounded: 360.0\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 43, "state": "DONE", "step_type": "agent_response", "duration_seconds": 14.207806527, "usage": {"input_tokens": 3954, "output_tokens": 4630, "thinking_tokens": 4273, "cache_read_tokens": 36598, "total_tokens": 8584}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 44, "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_content = \"\"\"<svg xmlns=\"http://www.w3.org/2000/svg\" width=\"500\" height=\"500\" viewBox=\"0 0 500 500\">\n  <rect width=\"500\" height=\"500\" fill=\"white\"/>\n  <circle id=\"swing-circle\" cx=\"250\" cy=\"250\" r=\"173.8\" fill=\"none\" stroke=\"green\" stroke-width=\"2\"/>\n  <circle id=\"anchor\" cx=\"250\" cy=\"250\" r=\"4\" fill=\"black\"/>\n  <polyline id=\"track\" fill=\"none\" stroke=\"blue\" stroke-width=\"1.5\" points=\"250.0,250.0 260.0,240.0\"/>\n</svg>\"\"\"\n\nroot = ET.fromstring(svg_content)\u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 44, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.319195796, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport xml.etree.ElementTree as ET\n\nsvg_content = \"\"\"<svg xmlns=\"http://www.w3.org/2000/svg\" width=\"500\" height=\"500\" viewBox=\"0 0 500 500\">\n  <rect width=\"500\" height=\"500\" fill=\"white\"/>\n  <circle id=\"swing-circle\" cx=\"250\" cy=\"250\" r=\"173.8\" fill=\"none\" stroke=\"green\" stroke-width=\"2\"/>\n  <circle id=\"anchor\" cx=\"250\" cy=\"250\" r=\"4\" fill=\"black\"/>\n  <polyline id=\"track\" fill=\"none\" stroke=\"blue\" stroke-width=\"1.5\" points=\"250.0,250.0 260.0,240.0\"/>\n</svg>\"\"\"\n\nroot = ET.fromstring(svg_content)\u2026"}, "output": "Command exited with code 0.\n\nCommand output:\nTag: {http://www.w3.org/2000/svg}svg\r\nswing-circle: {http://www.w3.org/2000/svg}circle {'id': 'swing-circle', 'cx': '250', 'cy': '250', 'r': '173.8', 'fill': 'none', 'stroke': 'green', 'stroke-width': '2'}\r\ntrack: {http://www.w3.org/2000/svg}polyline {'id': 'track', 'fill': 'none', 'stroke': 'blue', 'stroke-width': '1.5', 'points': '250.0,250.0 260.0,240.0'}\r\nanchor: {http://www.w3.org/2000/svg}circle {'id': 'anchor', 'cx': '250', 'cy': '250', 'r': '4', 'fill': 'black'}\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 45, "state": "DONE", "step_type": "agent_response", "duration_seconds": 13.469773074999999, "usage": {"input_tokens": 8878, "output_tokens": 4850, "thinking_tokens": 3720, "cache_read_tokens": 36619, "total_tokens": 13728}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 46, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport json, math, csv\n\nwith open(\"input.json\") as f:\n    inp = json.load(f)\n\nanchor_lat, anchor_lon = inp[\"anchor\"]\nrode = inp[\"rode_m\"]\ndepth = inp[\"depth_m\"]\nbow = inp[\"bow_height_m\"]\ngps_offset = inp[\"gps_offset_m\"]\nmargin = inp[\"margin_m\"]\nN = inp[\"consecutive\"]\n\nh = depth + bow\nif rode <= h:\n    radius = gps_offset + margin\nelse:\n    radius = math.sqrt(rode**2 - h**2) + gps_offset + margin\n\nwith open(inp[\"track\"]) as f:\n    reader = csv.reader(f)\n    next(reader, None)\n    \n    valid_poin\u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 46, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.306818725, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport json, math, csv\n\nwith open(\"input.json\") as f:\n    inp = json.load(f)\n\nanchor_lat, anchor_lon = inp[\"anchor\"]\nrode = inp[\"rode_m\"]\ndepth = inp[\"depth_m\"]\nbow = inp[\"bow_height_m\"]\ngps_offset = inp[\"gps_offset_m\"]\nmargin = inp[\"margin_m\"]\nN = inp[\"consecutive\"]\n\nh = depth + bow\nif rode <= h:\n    radius = gps_offset + margin\nelse:\n    radius = math.sqrt(rode**2 - h**2) + gps_offset + margin\n\nwith open(inp[\"track\"]) as f:\n    reader = csv.reader(f)\n    next(reader, None)\n    \n    valid_poin\u2026"}, "output": "Command exited with code 0.\n\nCommand output:\n{\r\n  \"radius_m\": 38.15,\r\n  \"valid_points\": 290,\r\n  \"bad_rows\": 10,\r\n  \"events\": [\r\n    {\r\n      \"start_t\": 822,\r\n      \"trigger_t\": 852,\r\n      \"end_t\": 902,\r\n      \"max_dist_m\": 42.9,\r\n      \"bearing_deg\": 68.2\r\n    },\r\n    {\r\n      \"start_t\": 2640,\r\n      \"trigger_t\": 2660,\r\n      \"end_t\": 2967,\r\n      \"max_dist_m\": 50.5,\r\n      \"bearing_deg\": 314.9\r\n    },\r\n    {\r\n      \"start_t\": 2988,\r\n      \"trigger_t\": 3009,\r\n      \"end_t\": 3071,\r\n      \"max_dist_m\": 43.6,\r\n      \"bearing_deg\": 301.8\r\n    }\r\n  ],\r\n  \"max_dist_m\": 50.5,\r\n  \"outside_points\": 49\r\n}\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 47, "state": "DONE", "step_type": "agent_response", "duration_seconds": 8.087938176, "usage": {"input_tokens": 5944, "output_tokens": 2593, "thinking_tokens": 1799, "cache_read_tokens": 44778, "total_tokens": 8537}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 48, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport json, csv, math\n\nwith open(\"input.json\") as f:\n    inp = json.load(f)\n\nanchor_lat, anchor_lon = inp[\"anchor\"]\nrode = inp[\"rode_m\"]\ndepth = inp[\"depth_m\"]\nbow = inp[\"bow_height_m\"]\ngps_offset = inp[\"gps_offset_m\"]\nmargin = inp[\"margin_m\"]\nN = inp[\"consecutive\"]\n\nh = depth + bow\nradius = (0.0 if rode <= h else math.sqrt(rode**2 - h**2)) + gps_offset + margin\n\nvalid_points = []\nwith open(inp[\"track\"]) as f:\n    reader = csv.reader(f)\n    next(reader, None)\n    last_t = None\n    for row in r\u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 48, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.489240924, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport json, csv, math\n\nwith open(\"input.json\") as f:\n    inp = json.load(f)\n\nanchor_lat, anchor_lon = inp[\"anchor\"]\nrode = inp[\"rode_m\"]\ndepth = inp[\"depth_m\"]\nbow = inp[\"bow_height_m\"]\ngps_offset = inp[\"gps_offset_m\"]\nmargin = inp[\"margin_m\"]\nN = inp[\"consecutive\"]\n\nh = depth + bow\nradius = (0.0 if rode <= h else math.sqrt(rode**2 - h**2)) + gps_offset + margin\n\nvalid_points = []\nwith open(inp[\"track\"]) as f:\n    reader = csv.reader(f)\n    next(reader, None)\n    last_t = None\n    for row in r\u2026"}, "output": "Command exited with code 1.\n\nCommand output:\n  File \"<string>\", line 47\r\n    pts = [f\"{250 + p[\\\"x\\\"] * scale:.1f},{250 - p[\\\"y\\\"] * scale:.1f}\" for p in valid_points]\r\n                       ^\r\nSyntaxError: unexpected character after line continuation character\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 49, "state": "DONE", "step_type": "agent_response", "duration_seconds": 6.029608359, "usage": {"input_tokens": 4612, "output_tokens": 829, "thinking_tokens": 20, "cache_read_tokens": 48855, "total_tokens": 5441}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 50, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport json, csv, math\n\nwith open(\"input.json\") as f:\n    inp = json.load(f)\n\nanchor_lat, anchor_lon = inp[\"anchor\"]\nrode = inp[\"rode_m\"]\ndepth = inp[\"depth_m\"]\nbow = inp[\"bow_height_m\"]\ngps_offset = inp[\"gps_offset_m\"]\nmargin = inp[\"margin_m\"]\nN = inp[\"consecutive\"]\n\nh = depth + bow\nradius = (0.0 if rode <= h else math.sqrt(rode**2 - h**2)) + gps_offset + margin\n\nvalid_points = []\nwith open(inp[\"track\"]) as f:\n    reader = csv.reader(f)\n    next(reader, None)\n    last_t = None\n    for row in r\u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 50, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.443544637, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport json, csv, math\n\nwith open(\"input.json\") as f:\n    inp = json.load(f)\n\nanchor_lat, anchor_lon = inp[\"anchor\"]\nrode = inp[\"rode_m\"]\ndepth = inp[\"depth_m\"]\nbow = inp[\"bow_height_m\"]\ngps_offset = inp[\"gps_offset_m\"]\nmargin = inp[\"margin_m\"]\nN = inp[\"consecutive\"]\n\nh = depth + bow\nradius = (0.0 if rode <= h else math.sqrt(rode**2 - h**2)) + gps_offset + margin\n\nvalid_points = []\nwith open(inp[\"track\"]) as f:\n    reader = csv.reader(f)\n    next(reader, None)\n    last_t = None\n    for row in r\u2026"}, "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 \"<string>\", line 61, in <module>\r\n    with open(\"test_anchor.svg\", \"w\") as f:\r\n         ~~~~^^^^^^^^^^^^^^^^^^^^^^^^\r\nOSError: [Errno 30] Read-only file system: 'test_anchor.svg'\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 51, "state": "DONE", "step_type": "agent_response", "duration_seconds": 2.093553041, "usage": {"input_tokens": 5653, "output_tokens": 139, "thinking_tokens": 99, "cache_read_tokens": 48852, "total_tokens": 5792}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 52, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "pwd && ls -ld ."}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 52, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.45522713, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "pwd && ls -ld ."}, "output": "Command exited with code 0.\n\nCommand output:\n/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k07/work\r\ndrwxr-xr-x 2 bob bob 4096 Oct 22 10:56 .\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 53, "state": "DONE", "step_type": "agent_response", "duration_seconds": 7.031173873, "usage": {"input_tokens": 5944, "output_tokens": 2216, "thinking_tokens": 104, "cache_read_tokens": 48845, "total_tokens": 8160}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 54, "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/k07/work/solve.py"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 54, "state": "DONE", "step_type": "tool", "tool_name": "write_file", "duration_seconds": 0.053193531, "tool_info": {"name": "write_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k07/work/solve.py"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 55, "state": "DONE", "step_type": "agent_response", "duration_seconds": 2.20493095, "usage": {"input_tokens": 4162, "output_tokens": 151, "thinking_tokens": 105, "cache_read_tokens": 52919, "total_tokens": 4313}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 56, "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": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 56, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.413626575, "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/k07/work/solve.py\", line 193, in <module>\r\n    solve(sys.argv[1], sys.argv[2])\r\n    ~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^\r\n  File \"/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k07/work/solve.py\", line 147, in solve\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": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 57, "state": "DONE", "step_type": "agent_response", "duration_seconds": 2.597572623, "usage": {"input_tokens": 4643, "output_tokens": 230, "thinking_tokens": 178, "cache_read_tokens": 52913, "total_tokens": 4873}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 58, "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": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 58, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.072653121, "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": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 59, "state": "DONE", "step_type": "agent_response", "duration_seconds": 7.335571983, "usage": {"input_tokens": 4967, "output_tokens": 82, "thinking_tokens": 31, "cache_read_tokens": 52906, "total_tokens": 5049}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 60, "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/k07/work/answer.json"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 60, "state": "DONE", "step_type": "tool", "tool_name": "read_file", "duration_seconds": 0.033029092, "tool_info": {"name": "read_file", "parameters": {"Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k07/work/answer.json"}, "output": "30 lines, 529 bytes"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 61, "state": "DONE", "step_type": "agent_response", "duration_seconds": 5.16896992, "usage": {"input_tokens": 5519, "output_tokens": 73, "thinking_tokens": 11, "cache_read_tokens": 52900, "total_tokens": 5592}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 62, "state": "ACTIVE", "step_type": "tool", "tool_name": "read_file", "tool_info": {"name": "read_file", "parameters": {"EndLine": 10, "Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k07/work/anchor.svg", "StartLine": 1}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 62, "state": "DONE", "step_type": "tool", "tool_name": "read_file", "duration_seconds": 0.058499325, "tool_info": {"name": "read_file", "parameters": {"EndLine": 10, "Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k07/work/anchor.svg", "StartLine": 1}, "output": "6 lines, 3848 bytes"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 63, "state": "DONE", "step_type": "agent_response", "duration_seconds": 4.121214142, "usage": {"input_tokens": 5245, "output_tokens": 543, "thinking_tokens": 162, "cache_read_tokens": 56983, "total_tokens": 5788}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 64, "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\ntree = ET.parse(\"anchor.svg\")\nroot = tree.getroot()\nassert root.tag.endswith(\"svg\"), f\"Root tag is not svg: {root.tag}\"\n\n# Check required elements\nswing = root.find(\".//*[@id=\\\"swing-circle\\\"]\")\nassert swing is not None, \"Missing #swing-circle\"\nassert swing.tag.endswith(\"circle\"), f\"#swing-circle is not <circle>: {swing.tag}\"\n\ntrack = root.find(\".//*[@id=\\\"track\\\"]\")\nassert track is not None, \"Missing #track\"\nassert track.tag.endswith(\"polyline\"), f\"#track is\u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 64, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.122193358, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport xml.etree.ElementTree as ET\n\ntree = ET.parse(\"anchor.svg\")\nroot = tree.getroot()\nassert root.tag.endswith(\"svg\"), f\"Root tag is not svg: {root.tag}\"\n\n# Check required elements\nswing = root.find(\".//*[@id=\\\"swing-circle\\\"]\")\nassert swing is not None, \"Missing #swing-circle\"\nassert swing.tag.endswith(\"circle\"), f\"#swing-circle is not <circle>: {swing.tag}\"\n\ntrack = root.find(\".//*[@id=\\\"track\\\"]\")\nassert track is not None, \"Missing #track\"\nassert track.tag.endswith(\"polyline\"), f\"#track is\u2026"}, "output": "Command exited with code 0.\n\nCommand output:\nSVG validation PASSED!\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 65, "state": "DONE", "step_type": "agent_response", "duration_seconds": 7.441400845, "usage": {"input_tokens": 5885, "output_tokens": 1891, "thinking_tokens": 1769, "cache_read_tokens": 56977, "total_tokens": 7776}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 66, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nwith open(\"track.csv\", \"rb\") as f:\n    content = f.read()\nprint(\"Ends with newline?\", content.endswith(b\"\\n\"))\nlines = content.split(b\"\\n\")\nprint(\"Total split lines:\", len(lines))\nprint(\"Last 3 lines:\", lines[-3:])\n'"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 66, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.074086522, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nwith open(\"track.csv\", \"rb\") as f:\n    content = f.read()\nprint(\"Ends with newline?\", content.endswith(b\"\\n\"))\nlines = content.split(b\"\\n\")\nprint(\"Total split lines:\", len(lines))\nprint(\"Last 3 lines:\", lines[-3:])\n'"}, "output": "Command exited with code 0.\n\nCommand output:\nEnds with newline? True\r\nTotal split lines: 302\r\nLast 3 lines: [b'3061,-23.4153205,143.5985484', b'3071,-23.4153068,143.5985558', b'']\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 67, "state": "DONE", "step_type": "agent_response", "duration_seconds": 1.968000298, "usage": {"input_tokens": 3873, "output_tokens": 129, "thinking_tokens": 37, "cache_read_tokens": 61050, "total_tokens": 4002}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 68, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport csv\nwith open(\"track.csv\", newline=\"\") as f:\n    r = list(csv.reader(f))\nprint(\"Total rows from csv.reader:\", len(r))\n'"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 68, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.084865144, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport csv\nwith open(\"track.csv\", newline=\"\") as f:\n    r = list(csv.reader(f))\nprint(\"Total rows from csv.reader:\", len(r))\n'"}, "output": "Command exited with code 0.\n\nCommand output:\nTotal rows from csv.reader: 301\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 69, "state": "DONE", "step_type": "agent_response", "duration_seconds": 15.271521831, "usage": {"input_tokens": 4107, "output_tokens": 5191, "thinking_tokens": 3565, "cache_read_tokens": 61042, "total_tokens": 9298}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 70, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport subprocess, json, os, tempfile, shutil\n\ntemp_dir = tempfile.mkdtemp()\ntry:\n    # Test Case 1: Empty track (header only)\n    inp1 = {\n        \"anchor\": [0.0, 0.0],\n        \"rode_m\": 20.0,\n        \"depth_m\": 5.0,\n        \"bow_height_m\": 1.0,\n        \"gps_offset_m\": 2.0,\n        \"margin_m\": 3.0,\n        \"consecutive\": 2,\n        \"track\": os.path.join(temp_dir, \"t1.csv\")\n    }\n    with open(os.path.join(temp_dir, \"t1.csv\"), \"w\") as f:\n        f.write(\"t,lat,lon\\n\")\n    with open(os.path.join\u2026"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 70, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.301752452, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport subprocess, json, os, tempfile, shutil\n\ntemp_dir = tempfile.mkdtemp()\ntry:\n    # Test Case 1: Empty track (header only)\n    inp1 = {\n        \"anchor\": [0.0, 0.0],\n        \"rode_m\": 20.0,\n        \"depth_m\": 5.0,\n        \"bow_height_m\": 1.0,\n        \"gps_offset_m\": 2.0,\n        \"margin_m\": 3.0,\n        \"consecutive\": 2,\n        \"track\": os.path.join(temp_dir, \"t1.csv\")\n    }\n    with open(os.path.join(temp_dir, \"t1.csv\"), \"w\") as f:\n        f.write(\"t,lat,lon\\n\")\n    with open(os.path.join\u2026"}, "output": "Command exited with code 1.\n\nCommand output:\nTest 1 (empty track): {'radius_m': 24.08, 'valid_points': 0, 'bad_rows': 0, 'events': [], 'max_dist_m': 0.0, 'outside_points': 0}\r\nTest 2 (rode <= depth+bow): radius = 5.0\r\nTest 3 answer: {'radius_m': 5.0, 'valid_points': 6, 'bad_rows': 8, 'events': [{'start_t': 10, 'trigger_t': 12, 'end_t': 12, 'max_dist_m': 11.1, 'bearing_deg': 0.0}], 'max_dist_m': 11.1, 'outside_points': 3}\r\nTraceback (most recent call last):\r\n  File \"<string>\", line 72, in <module>\r\n    assert ans3[\"valid_points\"] == 5 # rows: t=1, 10, 12, 15, 20, 25 -> 6 points!\r\n           ^^^^^^^^^^^^^^^^^^^^^^^^^\r\nAssertionError\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 71, "state": "DONE", "step_type": "agent_response", "duration_seconds": 6.859522717, "usage": {"input_tokens": 5552, "output_tokens": 680, "thinking_tokens": 387, "cache_read_tokens": 65136, "total_tokens": 6232}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 72, "state": "ACTIVE", "step_type": "tool", "tool_name": "run_command", "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport math\n\nR = 6371000\nfor name, dlat, dlon, expected in [\n    (\"North\", 0.0001, 0.0, 0.0),\n    (\"East\", 0.0, 0.0001, 90.0),\n    (\"South\", -0.0001, 0.0, 180.0),\n    (\"West\", 0.0, -0.0001, 270.0),\n]:\n    m = math.radians(dlat / 2.0)\n    x = math.radians(dlon) * math.cos(m) * R\n    y = math.radians(dlat) * R\n    b = round(math.degrees(math.atan2(x, y)) % 360, 1) % 360\n    print(f\"{name}: computed={b}, expected={expected}\")\n    assert abs(b - expected) < 1e-4\nprint(\"All bearings match!\")\n'"}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 72, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.191749146, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "python3 -c '\nimport math\n\nR = 6371000\nfor name, dlat, dlon, expected in [\n    (\"North\", 0.0001, 0.0, 0.0),\n    (\"East\", 0.0, 0.0001, 90.0),\n    (\"South\", -0.0001, 0.0, 180.0),\n    (\"West\", 0.0, -0.0001, 270.0),\n]:\n    m = math.radians(dlat / 2.0)\n    x = math.radians(dlon) * math.cos(m) * R\n    y = math.radians(dlat) * R\n    b = round(math.degrees(math.atan2(x, y)) % 360, 1) % 360\n    print(f\"{name}: computed={b}, expected={expected}\")\n    assert abs(b - expected) < 1e-4\nprint(\"All bearings match!\")\n'"}, "output": "Command exited with code 0.\n\nCommand output:\nNorth: computed=0.0, expected=0.0\r\nEast: computed=90.0, expected=90.0\r\nSouth: computed=180.0, expected=180.0\r\nWest: computed=270.0, expected=270.0\r\nAll bearings match!\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 73, "state": "DONE", "step_type": "agent_response", "duration_seconds": 3.985409701, "usage": {"input_tokens": 2322, "output_tokens": 107, "thinking_tokens": 51, "cache_read_tokens": 69202, "total_tokens": 2429}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 74, "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": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 74, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.076653925, "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": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 75, "state": "DONE", "step_type": "agent_response", "duration_seconds": 4.234058022, "usage": {"input_tokens": 2525, "output_tokens": 59, "thinking_tokens": 16, "cache_read_tokens": 69193, "total_tokens": 2584}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 76, "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": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 76, "state": "DONE", "step_type": "tool", "tool_name": "run_command", "duration_seconds": 0.063456018, "tool_info": {"name": "run_command", "parameters": {"CommandLine": "ls -la"}, "output": "Command exited with code 0.\n\nCommand output:\ntotal 44\r\ndrwxr-xr-x 2 bob bob 4096 Oct 22 12:14 .\r\ndrwxrwxr-x 3 bob bob 4096 Oct 22 12:11 ..\r\n-rw-r--r-- 1 bob bob 2020 Oct 22 10:56 TASK.md\r\n-rw-r--r-- 1 bob bob 3848 Oct 22 12:15 anchor.svg\r\n-rw-rw-r-- 1 bob bob  529 Oct 22 12:15 answer.json\r\n-rw-r--r-- 1 bob bob  183 Oct 22 10:56 input.json\r\n-rw-r--r-- 1 bob bob 6467 Oct 22 12:14 solve.py\r\n-rw-r--r-- 1 bob bob 8517 Oct 22 10:56 track.csv\r\n"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 77, "state": "DONE", "step_type": "agent_response", "duration_seconds": 1.939215823, "usage": {"input_tokens": 2912, "output_tokens": 89, "thinking_tokens": 26, "cache_read_tokens": 69186, "total_tokens": 3001}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 78, "state": "ACTIVE", "step_type": "tool", "tool_name": "read_file", "tool_info": {"name": "read_file", "parameters": {"EndLine": 250, "Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k07/work/solve.py", "StartLine": 1}}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 78, "state": "DONE", "step_type": "tool", "tool_name": "read_file", "duration_seconds": 0.047220949, "tool_info": {"name": "read_file", "parameters": {"EndLine": 250, "Path": "/home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k07/work/solve.py", "StartLine": 1}, "output": "193 lines, 6467 bytes"}}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "The anchor drag alarm processor has been implemented in [`so"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "lve.py`](file:///home/bo"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "b/usecase-ru"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ns/agy-batch/out/gemini-"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "3.8-flash-medium/k07/work/solve.py) using the Py"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "thon 3 standard library."}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "\n\n### Key"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " Implementation Details\n- **Alarm Radius**: Computed using $\\sqrt{\\text{rode}^2 - (\\"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "text{depth} + \\text{bow\\"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "_height})^2} + \\text{gps"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "\\_offset} + \\text{margin}$ (evaluating the squar"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "e root term as $0$ if $\\"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "text{rode} \\le \\text{depth} + \\text{bow\\_height}"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "$), rounded to 2 decimal"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " places.\n- *"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "*Track Cleaning**: Skips"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " header, filters rows with fewer than 3 fields, non-integer "}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "timestamps, "}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "non-finite or out-of-range latitudes/longitudes,"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " and non-mon"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "otonically increasing ti"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "mestamps relative to the last valid row.\n- **Distance & Bear"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ing**: Equir"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ectangular projection co"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ordinates $("}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "x, y)$ computed with $R "}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "= 6371000\\,\\text{m}$ and mean latitude $\\cos(m)$. Bearings are calculated as $\\text{"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "atan2}(x, y)"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " \\pmod{360}$ from anchor to the run's final poin"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "t, rounded t"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "o 1 decimal place.\n- **Alarm Events**: Maximal c"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ontiguous ru"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ns of valid outside poin"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ts of length $\\ge N$ are"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " reported with `start_t`, `trigger_t` ($N$-th po"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "int), `end_t`, `max_dist_m`, and `be"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "aring_deg`.\n- **Outputs**:\n  - [`answer.json`](f"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ile:///home/"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "bob/usecase-runs/agy-bat"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ch/out/gemin"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "i-3.8-flash-medium/k07/work/answer.json): Contai"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ns `radius_m`, `valid_po"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ints`, `bad_rows`, `events`, `max_di"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "st_m`, and `outside_poin"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ts`.\n  - [`a"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "nchor.svg`](file:///home/bob/usecase-runs/agy-ba"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "tch/out/gemini-3.8-flash"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "-medium/k07/"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "work/anchor.svg): Static, self-contained SVG fea"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "turing `<cir"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "cle id=\"swing-circle\">`, `<polyline id=\"track\">`"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": ", and `<circle id=\"anchor\">`.\n\n### V"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "erification\n- Tested aga"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "inst `input.json` and `t"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "rack.csv` as"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " well as edge-case suite"}}
{"event": "step_update", "step_update": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "step_index": 79, "state": "DONE", "step_type": "agent_response", "text_delta": "s (empty track, non-increasing timestamps, NaN/infinite coordinates, $N=1$, runs $< N$, and $\\text{rode} \\le \\text{depth} + \\text{bow\\_height}$).\n- Validated SVG structure and elements headless using `xml.etree.ElementTree`.\n", "duration_seconds": 4.56682995, "usage": {"input_tokens": 5851, "output_tokens": 619, "thinking_tokens": 29, "cache_read_tokens": 69194, "total_tokens": 6470}}}
{"event": "result", "result": {"conversation_id": "b6cace64-61b0-4a78-9eaa-06d1ec645703", "status": "SUCCESS", "response": "The anchor drag alarm processor has been implemented in [`solve.py`](file:///home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k07/work/solve.py) using the Python 3 standard library.\n\n### Key Implementation Details\n- **Alarm Radius**: Computed using $\\sqrt{\\text{rode}^2 - (\\text{depth} + \\text{bow\\_height})^2} + \\text{gps\\_offset} + \\text{margin}$ (evaluating the square root term as $0$ if $\\text{rode} \\le \\text{depth} + \\text{bow\\_height}$), rounded to 2 decimal places.\n- **Track Cleaning**: Skips header, filters rows with fewer than 3 fields, non-integer timestamps, non-finite or out-of-range latitudes/longitudes, and non-monotonically increasing timestamps relative to the last valid row.\n- **Distance & Bearing**: Equirectangular projection coordinates $(x, y)$ computed with $R = 6371000\\,\\text{m}$ and mean latitude $\\cos(m)$. Bearings are calculated as $\\text{atan2}(x, y) \\pmod{360}$ from anchor to the run's final point, rounded to 1 decimal place.\n- **Alarm Events**: Maximal contiguous runs of valid outside points of length $\\ge N$ are reported with `start_t`, `trigger_t` ($N$-th point), `end_t`, `max_dist_m`, and `bearing_deg`.\n- **Outputs**:\n  - [`answer.json`](file:///home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k07/work/answer.json): Contains `radius_m`, `valid_points`, `bad_rows`, `events`, `max_dist_m`, and `outside_points`.\n  - [`anchor.svg`](file:///home/bob/usecase-runs/agy-batch/out/gemini-3.8-flash-medium/k07/work/anchor.svg): Static, self-contained SVG featuring `<circle id=\"swing-circle\">`, `<polyline id=\"track\">`, and `<circle id=\"anchor\">`.\n\n### Verification\n- Tested against `input.json` and `track.csv` as well as edge-case suites (empty track, non-increasing timestamps, NaN/infinite coordinates, $N=1$, runs $< N$, and $\\text{rode} \\le \\text{depth} + \\text{bow\\_height}$).\n- Validated SVG structure and elements headless using `xml.etree.ElementTree`.\n", "duration_seconds": 252.442063377, "num_turns": 1, "usage": {"input_tokens": 249578, "output_tokens": 46722, "thinking_tokens": 32862, "cache_read_tokens": 1334374, "total_tokens": 296300}}}