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Gemini 4 Argon (effort medium · thinking on) on Animate a junction where cars obey a traffic light's timed sequence in one self-contained HTML file

GGemini 4 Argonmedium · thinking on · Antigravity CLI 1.4.6 (agy -p) · cloud · 2026-10-23 · by @bobsiopener

Trust 80%Fully autonomoussuccess · first try
Estimated cost
$0.22
Wall time
3m
Human step-ins
0
Outcome
Pass

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Summary

Exact prompt

# Animate a junction where cars obey a traffic light's timed sequence in one self-contained HTML file Make a small animated scene: a road junction with a traffic light. Write one file, `out/scene.html`, that works opened straight from disk with no network access. `spec.json` gives the page title, the stage size and the scene parameters. **Looks are not scored**: the page is opened in a headless browser (800x600 window, UTC time zone, network blocked) and checked by objective tests only. ## Scene contract - Draw the scene on one `<canvas>` or `<svg>` stage of `width` x `height` CSS pixels (spec.json), visible on load, with `<title>` containing spec.json `title`. - Animate continuously from load (`requestAnimationFrame` or timers); no click is needed unless stated below. - Expose `window.sceneState()`, returning the scene's current state in stage pixel coordinates (origin top-left of the stage): `{light: <the light showing now, one of the spec.json phase names>, cars: [{x}, ...]}`. Extra fields are fine. It must describe what is actually drawn. - Cars drive left to right along one lane; `x` is the front of the car in stage pixels and may wrap back to the left edge after a car leaves the stage. The light runs through `phases` in the order given, starting at the first phase on load, each for its `s` seconds, then repeats. Cars may only cross `stop_line_x` on green; on any other phase they stop at the line or queue behind the car ahead. Keep the traffic dense enough that a car is waiting at the line during the non-green phases. - The page must log no errors and throw no exceptions. Keep the file at most 200,000 bytes; no external scripts, fonts, images or URLs (inline everything). ## Checks (partial credit = share passed) 1. `self_contained`: `out/scene.html` exists, is at most 200,000 bytes, references no http(s) or protocol-relative URL, and requests nothing from the network when opened. 2. `has_canvas_or_svg`: a visible `<canvas>` or `<svg>` of at least 300x200 CSS pixels is on the page. 3. `frames_change`: over 3 s, some later screenshot differs from the first in at least 0.1% of pixels, and at least 3 of 30 screenshots differ. 4. `light_sequence`: over 3 s `sceneState().light` only takes spec.json phase names, changes only to the next phase in spec.json order (wrapping round), changes at least 3 times, and every phase seen from its start to its end lasts its `s` seconds within 0.25 s. 5. `cars_obey_lights`: `cars` has exactly spec.json `cars` entries; between two samples a car's x only goes from below `stop_line_x` to at or above it when the light is green in one of the two samples; some car moves while the light stays green, and some car waits (moves under 0.5 px) within 60 px before the stop line while the light stays on a phase other than green. 6. `no_console_errors`: no uncaught exception, `console.error` or browser error is logged during the run. ## How this run works - Work on your own: nobody will answer questions in this task, and writing to `ask/` counts against the run. - Write only under `out/`. Create `out/` if it is missing. Inputs are synthetic; don't fetch anything from the network. - Scoring is partial credit: each listed check is pass/fail, and the score is the share passed. Numbers are compared to within 0.005 unless the task says otherwise.

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).

Success criteria: self_contained has_canvas_or_svg frames_change light_sequence cars_obey_lights no_console_errors

Setup notes: batch29 case h08-traffic-light-junction (offline fixture). Prepared with batch29/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 `MEDIA_DIR=<dir> python3 score.py WORKDIR KEYDIR`. Single run, no retries, no human input. Gallery media (3 s headless-Chrome capture: poster.png + clip.mp4, network blocked) written to a fresh MEDIA_DIR by the scorer; SHA-256 in evidence.media. Autonomous case (seed 399810934): no stand-in user; any ask/ file counts as an intervention and blocks a pass. 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 6 (0 failed). Single run.

Estimated cost List-price estimate; not actually billed.

Output

Metrics

Estimated cost
$0.22
Wall time
3m
Human step-ins
0
Turns
6
Model usage
ModelInput tokOutput tokCost
GGemini 4 Argongoogle/gemini-4-argoneffort medium · thinking on106,14114,908$0.22

Reproduce this run

  1. Use the use case prompt on the use case page.
  2. Same setup: Gemini 4 Argon (google/gemini-4-argon, effort medium · thinking on) via Antigravity CLI 1.4.6 (agy -p), cloud.
  3. It counts as a success only if it meets every success criterion: self_contained has_canvas_or_svg frames_change light_sequence cars_obey_lights no_console_errors
  4. 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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Evidence log
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{"event": "step_update", "step_update": {"conversation_id": "ae25ef92-8bcc-4a08-b0f5-c2c669771242", "step_index": 12, "state": "ACTIVE", "step_type": "agent_response", "text_delta": " timing.\n- *"}}
{"event": "step_update", "step_update": {"conversation_id": "ae25ef92-8bcc-4a08-b0f5-c2c669771242", "step_index": 12, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "*"}}
{"event": "step_update", "step_update": {"conversation_id": "ae25ef92-8bcc-4a08-b0f5-c2c669771242", "step_index": 12, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "Traffic Behavior & State**: Exposes `window.scen"}}
{"event": "step_update", "step_update": {"conversation_id": "ae25ef92-8bcc-4a08-b0f5-c2c669771242", "step_index": 12, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "eState()` re"}}
{"event": "step_update", "step_update": {"conversation_id": "ae25ef92-8bcc-4a08-b0f5-c2c669771242", "step_index": 12, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "turning `{ light, cars: "}}
{"event": "step_update", "step_update": {"conversation_id": "ae25ef92-8bcc-4a08-b0f5-c2c669771242", "step_index": 12, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "[{ x }, ...] }` for the "}}
{"event": "step_update", "step_update": {"conversation_id": "ae25ef92-8bcc-4a08-b0f5-c2c669771242", "step_index": 12, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "3 cars driving left-to-right, queuei"}}
{"event": "step_update", "step_update": {"conversation_id": "ae25ef92-8bcc-4a08-b0f5-c2c669771242", "step_index": 12, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "ng behind `stop_line_x` (`325`) during non-green phases and proceeding a"}}
{"event": "step_update", "step_update": {"conversation_id": "ae25ef92-8bcc-4a08-b0f5-c2c669771242", "step_index": 12, "state": "ACTIVE", "step_type": "agent_response", "text_delta": "cross the ju"}}
{"event": "step_update", "step_update": {"conversation_id": "ae25ef92-8bcc-4a08-b0f5-c2c669771242", "step_index": 12, "state": "DONE", "step_type": "agent_response", "text_delta": "nction on `green`.\n", "duration_seconds": 5.718681043, "usage": {"input_tokens": 2868, "output_tokens": 303, "thinking_tokens": 16, "cache_read_tokens": 21422, "total_tokens": 3171}}}
{"event": "result", "result": {"conversation_id": "ae25ef92-8bcc-4a08-b0f5-c2c669771242", "status": "SUCCESS", "response": "Created the self-contained animated traffic junction scene in [out/scene.html](file:///home/bob/usecase-runs/b2930/out/agy/gemini-4-argon-medium/b29h08/work/out/scene.html) matching all parameters in [spec.json](file:///home/bob/usecase-runs/b2930/out/agy/gemini-4-argon-medium/b29h08/work/spec.json):\n\n- **Stage & Metadata**: `<title>Junction 511</title>` and a visible `720x480` `<canvas id=\"stage\">` rendered immediately on load with zero external network dependencies.\n- **Traffic Light Sequence**: Cycles through `red` (`0.8s`), `red_amber` (`0.4s`), `green` (`0.8s`), and `amber` (`0.4s`) continuously using high-precision wall-clock timing.\n- **Traffic Behavior & State**: Exposes `window.sceneState()` returning `{ light, cars: [{ x }, ...] }` for the 3 cars driving left-to-right, queueing behind `stop_line_x` (`325`) during non-green phases and proceeding across the junction on `green`.\n", "duration_seconds": 177.735872032, "num_turns": 1, "usage": {"input_tokens": 30440, "output_tokens": 14908, "thinking_tokens": 8724, "cache_read_tokens": 75701, "total_tokens": 45348}}}

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