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Animate a row of pendulums, each swinging at its own true period, in one self-contained HTML file

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# Animate a row of pendulums, each swinging at its own true period, in one self-contained HTML file Make a small animated scene: a pendulum wave. 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): `{pendulums: [{name, angle_deg, pivot: {x, y}, bob: {x, y}}, ...]}`. Extra fields are fine. It must describe what is actually drawn. - Each pendulum in spec.json has a `length_m`. Its period T is the time for one full back-and-forth swing of an ideal small-angle pendulum of that length under `gravity` (m/s²); every pendulum swings with the same amplitude `amplitude_deg`. `sceneState()` must return the state at the moment it is called (work it out from `performance.now()`, don't return the last frame's numbers). - 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. `swing_periods`: `sceneState().pendulums` names exactly the pendulums in spec.json, and over 3 s each pendulum's `angle_deg` stays within 2.5° of `amplitude_deg` × cos(2π t / T + φ) for some fixed φ, where t is `performance.now()` in seconds and T is the pendulum's period. 5. `bobs_on_strings`: in every sample, each bob is within 3 px of pivot + `length_m` × `px_per_m` × (sin θ, cos θ), θ = `angle_deg` (positive swings the bob to the right of the pivot, y grows downwards). 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.

Make a pendulum wave animation as one self-contained HTML file. A headless browser checks objective facts only: the file is offline and small, a canvas or SVG stage is drawn, frames change, the scene follows a timed specification (swing periods; bobs on strings) and nothing errors. A poster PNG and a short MP4 are captured for the gallery. Looks are not scored. Original benchmark task written for usecaserank.com (not based on a specific public post). Headless, offline run on a reproducible fixture. Each run's notes say how its cost was measured (estimates are marked).

Success criteria: self_contained has_canvas_or_svg frames_change swing_periods bobs_on_strings no_console_errors

Best model for this task so far: Claude Haiku 5.5 (effort default (no --effort flag) · thinking on) (success, $0.0072, 34s). Best AI model for Creative / Animated Scene (one HTML File) →

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All runs (6)

100% pass rate across 6 eligible runs: 6 pass, 0 partial, 0 fail. Partial and failed runs are listed below with everything else.ⓘ

Runs for this use case
ModelCostTimeStep-insⓘAutonomyOutcomeTrustⓘDateCompare
GGemini 4 Argonmedium · thinking on$0.0853s0Fully autonomouspassTrust 80%2026-10-23
GGemini 3.8 Flashmedium · thinking on$0.353m0Fully autonomouspassTrust 80%2026-10-23
OGPT-6.1 Soldefault · thinking off$0.0328s0Fully autonomouspassTrust 80%2026-10-23
AClaude Opus 5.5default · thinking on$0.1323s0Fully autonomouspassTrust 80%2026-10-23
AClaude Haiku 5.5default · thinking on$0.007234s0Fully autonomouspassTrust 80%2026-10-23
AClaude Sonnet 5.5default · thinking on$0.0511s0Fully autonomouspassTrust 80%2026-10-23

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