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GPT-6 Astra in Codex CLI 0.156.1

skills off

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Poster frame of GPT-6 Astra's page
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The model's own page, run in a sandboxed frame only when you ask (a page that needs its own origin opens in a new tab on a separate demo site). Phones get a full-screen player capped at 1.5x pixel density (2x on larger screens) so it stays smooth; the original page runs uncapped. Tap inside for sound.

OKFourier epicyclesmax effortNeutral harness

Wall time 16m 24sCost $4.12 estimated

Review

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The full review

OK. Finished on its own after 16.4 min.

Scores

AI judge

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Visitor votes and reviewer grades are not available yet.

AI judge
AI judge: the test runner (model claude-opus-5-5), scoring by visual review of the 1600 px render against the pre-registered rubric. No AI-judge score exists for this result: there is no rubric for this prompt, so no score is shown and none is made up.
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The reviewer's own grade appears here once it is added.

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Downloads

Files actually published for this run. Original output, site-made previews and post-run conversions are labelled separately.

The exact prompt

as run, 1,953 characters. Every result for this prompt

Build a Fourier epicycles visualizer that shows how the discrete Fourier transform rebuilds a drawing from rotating circles. Start from a closed path (presets: a heart, a treble clef, a five-pointed star, a cat silhouette and the outline of a guitar, each defined as point lists in code), resample it to 256 evenly spaced points, compute the DFT yourself in JavaScript, and draw the epicycles: a chain of circles sorted from largest to smallest, each rotating at its frequency, with the tip tracing the reconstructed path as a glowing trail that fades over time. Show the original path faintly underneath so viewers can compare. A slider sets how many terms are used (1 to 256), and the reconstruction updates live so people can watch the shape sharpen as terms are added; a small bar chart shows the magnitude spectrum with the active terms highlighted. Let the user draw their own closed shape with the mouse or a finger and then watch it transformed. Controls: preset picker, term slider, speed slider, play, pause, show or hide circles, clear and draw. So the page is alive without input, on load it plays the heart while slowly sweeping the term count from 1 up to 128, then moves to the next preset after one full drawing, forever, until the user touches a control. Make it mesmerizing, dark background, crisp thin lines and luminous trails.

Save it as index.html in the current directory: one self-contained file with inline CSS and JavaScript only, no libraries or frameworks, and no external requests of any kind (no CDNs, web fonts, images or audio files). It must work when opened directly from disk, fit any window from a 390 px wide phone to a desktop, and run without console errors. You may serve it locally and open it in headless chromium (/usr/bin/chromium, software WebGL, no GPU) to screenshot and inspect your own output, and iterate on your own before finishing. Close any browser you open as soon as you've taken your screenshot.

How it was made

Wall time 16m 24sFirst artifact at 6m 44s3 saved versions

Versions saved during the run

3 intermediate outputs, in the order the model wrote them.

Version 3 of 3
  1. Version 1 at 6m 47s thumbnailv1 6:47
  2. Version 2 at 7m 43s thumbnailv2 7:43
  3. Version 3 at 12m 30s thumbnailv3 12:30

No transcript was delivered with this result.

Cost breakdown

Headline cost $4.12, estimated from the token counts at list price.

Tokens by typeTokens$ per 1MCost
Input (uncached)66$10.00$0.0007
Cache write87,797$10.00$0.8780
Cache read870,851$1.00$0.8709
Output47,365$50.00$2.3683
of which reasoning22,243billed as output
Total computed from tokens
$4.1177
Total reported by the harness
none

Computed from harness-reported token counts x list prices. Cache writes priced at the input rate (the price table has no separate cache-write price).

Prices: Project price table (vendor list prices), 2026-09-22.

Run notes

one prompt, agentic harness (self-review allowed)

  • frozen prompt (written): written 2026-10-05 for the MR category expansion (owner request: 500 finished runs in every category); category algorithm_visualizers; zero results
  • plain CODEX_HOME copy (config.toml only, run work/ trusted; no AGENTS.md/skills/state)
  • Mode: interactive TUI in tmux (160x48), inside bubblewrap sandbox
  • Isolation audit: outside paths seen
  • Renderer: Canvas 2D (getContext('2d') at index.html line 99); single self-contained index.html, no CDN and no external assets.
  • Card video: the run's own 8 s session capture (headless Chromium, no GPU), re-encoded as H.264. Poster: the run's own render.png.