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GPT-6 Astra in OpenCode 1.18.32

skills on · OpenCode 1.18.32 + default skills kitKit: default (46 web/Three.js/QA + 33 video) · 79 skills installed; skill use not recorded

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Poster frame of GPT-6 Astra's page
Open the original page

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.

OKWorld weather stationsmax effortNeutral harness

Wall time 37m 21sCost $4.73 reported

Review

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The full review

OK. Finished on its own after 37.4 min.

Scores

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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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Downloads

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

The exact prompt

as run, 3,863 characters. Every result for this prompt

Build an interactive climate dashboard comparing six weather stations from the exact dataset below (CSV: one row per city and month with the average daily high temperature in Celsius, total rainfall in millimetres and sunshine hours). Embed the data in the page verbatim and compute every number from it; do not invent or alter any value.

city,month,avg_high_c,rain_mm,sun_hours
Reykjavik,Jan,0.4,77,54
Reykjavik,Feb,0.9,76,81
Reykjavik,Mar,3.8,67,116
Reykjavik,Apr,6.3,48,147
Reykjavik,May,10.1,32,221
Reykjavik,Jun,12.9,24,247
Reykjavik,Jul,13.2,24,274
Reykjavik,Aug,12.2,29,233
Reykjavik,Sep,9.9,37,214
Reykjavik,Oct,6.2,51,160
Reykjavik,Nov,3.1,59,103
Reykjavik,Dec,2.6,74,77
Lisbon,Jan,13.3,100,52
Lisbon,Feb,14.1,99,77
Lisbon,Mar,18.5,69,113
Lisbon,Apr,20.3,47,168
Lisbon,May,25.3,31,222
Lisbon,Jun,27.9,15,245
Lisbon,Jul,28.5,1,259
Lisbon,Aug,27.6,5,259
Lisbon,Sep,24.3,21,212
Lisbon,Oct,21.1,51,146
Lisbon,Nov,18.0,83,100
Lisbon,Dec,15.4,89,84
Singapore,Jan,29.6,254,152
Singapore,Feb,30.6,249,136
Singapore,Mar,30.4,223,151
Singapore,Apr,31.4,201,174
Singapore,May,31.6,183,132
Singapore,Jun,30.9,158,155
Singapore,Jul,31.8,164,167
Singapore,Aug,31.0,163,160
Singapore,Sep,30.8,182,130
Singapore,Oct,31.9,203,172
Singapore,Nov,30.7,235,129
Singapore,Dec,29.9,237,146
Denver,Jan,5.9,47,63
Denver,Feb,7.5,42,76
Denver,Mar,11.6,41,101
Denver,Apr,18.0,40,160
Denver,May,24.9,27,219
Denver,Jun,30.0,23,251
Denver,Jul,30.7,22,253
Denver,Aug,29.4,25,241
Denver,Sep,24.9,38,201
Denver,Oct,17.6,29,153
Denver,Nov,12.2,33,106
Denver,Dec,7.4,35,64
Cape Town,Jan,27.6,9,269
Cape Town,Feb,25.9,16,279
Cape Town,Mar,24.9,30,236
Cape Town,Apr,23.3,60,192
Cape Town,May,21.0,68,142
Cape Town,Jun,18.1,87,111
Cape Town,Jul,17.8,94,111
Cape Town,Aug,18.8,79,131
Cape Town,Sep,20.3,69,163
Cape Town,Oct,22.7,46,187
Cape Town,Nov,24.4,35,227
Cape Town,Dec,25.9,16,280
Mumbai,Jan,30.2,7,62
Mumbai,Feb,30.0,6,68
Mumbai,Mar,29.9,11,121
Mumbai,Apr,32.1,79,166
Mumbai,May,33.0,247,205
Mumbai,Jun,33.0,481,245
Mumbai,Jul,33.2,601,273
Mumbai,Aug,32.3,494,241
Mumbai,Sep,32.5,252,225
Mumbai,Oct,31.5,67,166
Mumbai,Nov,29.8,3,115
Mumbai,Dec,30.1,7,81

The dashboard needs: small-multiple climate charts, one per city, each with monthly temperature as a line over rainfall as bars and the two axes clearly labelled; a radial (polar) chart of the selected city's year with temperature as radius and rainfall as colour; a heatmap of temperature by city and month; KPI cards per city for annual rainfall, hottest and coldest month, temperature range and total sunshine; a 'best month to visit' calculator with sliders for preferred temperature range, maximum rain and minimum sunshine that scores every city-month and lists the top five; a Celsius and Fahrenheit toggle; hover or tap tooltips with exact values; and a short auto-written comparison panel computed from the data. Make it beautiful, editorial and calm, like a data feature in a great magazine. So the page is alive without input, on load the charts draw in and a tour cycles forever: it rotates the radial chart through each city, sweeps a highlight across the heatmap month by month, adjusts the visit calculator sliders to show the ranking change, and toggles units once per loop, until the user touches a control.

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 37m 21sFirst artifact at 23m 50s4 saved versions

Versions saved during the run

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

Version 4 of 4
  1. Version 1 at 23m 58s thumbnailv1 23:58
  2. Version 2 at 31m 18s thumbnailv2 31:18
  3. Version 3 at 34m 46s thumbnailv3 34:46
  4. Version 4 at 35m 31s thumbnailv4 35:31

No transcript was delivered with this result.

Cost breakdown

Headline cost $4.73, as reported by OpenCode (its own bill for the run). The list-price estimate from the token counts is $4.52.

Tokens by typeTokens$ per 1MCost
Input (uncached)84$10.00$0.0008
Cache write83,928$10.00$0.8393
Cache read1,565,054$1.00$1.5651
Output42,339$50.00$2.1170
of which reasoning12,037billed as output
Total computed from tokens
$4.5221
Total reported by the harness
$4.7319
Difference
Harness-reported $4.7319 vs list-price estimate $4.5221 (-4.4%); the harness figure is the headline.

OpenCode 1.18.32 reported its own total; token counts x list prices shown beside it. Cache writes priced at the input rate (the price table has no separate cache-write price). The harness reports reasoning tokens separately from output; here output includes them (30,302 visible + 12,037 reasoning), and both bill at the output rate.

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 data_dashboards; zero results
  • plain OpenCode config copy (providers only; no ECC instructions/agents)
  • default skills on: 79 skills in this run's xdg/config/opencode/skills
  • opencode export written to a file (not piped)
  • Mode: interactive TUI in tmux (160x48), inside bubblewrap sandbox
  • Isolation audit: outside paths seen
  • Renderer: inline SVG (first <svg> at index.html line 369) in one self-contained HTML file; no libraries, no CDN, no external assets. No WebGPU or WebGL needed.
  • Card video: the run's own video.mp4 (H.264 yuv420p, unchanged). Poster: the run's own render.png.
  • Same frozen prompt as the other rows on this test; configurations differ and all rows are unscored, so this is not a head-to-head result.