by camilleroux
Generative art skill for Claude Code — deterministic, hash-seeded, onchain-ready
# Add to your Claude Code skills
git clone https://github.com/camilleroux/genart-skillGuides for using ide extensions skills like genart-skill.
Last scanned: 8/29/2026
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"status": "PASSED",
"scannedAt": "2026-08-29T10:51:13.340Z",
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}genart-skill is an open-source ide extensions skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by camilleroux. Generative art skill for Claude Code — deterministic, hash-seeded, onchain-ready. It has 138 GitHub stars.
Yes. genart-skill passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/camilleroux/genart-skill" and add it to your Claude Code skills directory (see the Installation section above).
genart-skill is primarily written in JavaScript. It is open-source under camilleroux on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other IDE Extensions skills you can browse and compare side by side. Open the IDE Extensions category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh genart-skill against similar tools.
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⚠️ Third-Party Software Notice
This skill is third-party open-source software developed and hosted independently on GitHub. SkillsLLM is an informational directory and does not control or maintain the underlying repository.
Any security checks, ratings, or warnings displayed by SkillsLLM are automated and limited in scope. They do not constitute a security certification or guarantee that the software is safe, error-free, or free from malicious code, vulnerabilities, compromised dependencies, or prompt-injection risks.
Review the source code, permissions, dependencies, and configuration before installing or running any third-party skill. Use is at your own risk. To the maximum extent permitted by applicable law, SkillsLLM is not liable for losses arising from third-party software.
Create long-form generative art with AI assistance — deterministic, hash-seeded, ready for onchain platforms like Art Blocks, 256ART, Verse, Highlight, Plottables and bootloader.art — or for screens, via Artpoint.
This Claude Code plugin teaches Claude the working knowledge of the field: seeding a PRNG from a token hash, rendering the same composition at any resolution, designing traits and rarity tables, signalling preview capture, exporting for print and pen plotters, and where the ethical lines of generative art are. It covers creative coding with Canvas 2D, p5.js, three.js/WebGL and SVG — and ships runnable tools to verify that a sketch really is deterministic before you mint it.
Made by a generative artist, for generative artists using AI as a studio assistant — not as the artist.

Six seeds of Impossible Machine (Camille Roux) — hand-drawn technical blueprints, one hash each. The edition-level view the scripts are there to give you: same code, same rules, one sheet per seed.
/plugin marketplace add camilleroux/genart-skill
/plugin install genart@camilleroux-genart
Then just talk about your sketch — the skill loads on its own. Or invoke it with
/genart.
One skill, genart, with reference sheets loaded on demand:
Two scripts ship with the plugin and run in place — Claude (or you) never copies them into a project, so updating the plugin updates them everywhere:
node "$CLAUDE_PLUGIN_ROOT/scripts/check.mjs" myproject # determinism checks
node "$CLAUDE_PLUGIN_ROOT/scripts/render.mjs" myproject --hash 0x… # one PNG
node "$CLAUDE_PLUGIN_ROOT/scripts/render.mjs" myproject --grid 50 # contact sheet
node "$CLAUDE_PLUGIN_ROOT/scripts/render.mjs" myproject --census 5000 # rarity, measured
node "$CLAUDE_PLUGIN_ROOT/scripts/render.mjs" myproject --batch 50 # individual PNGs
render.mjs --hash is what lets Claude close the visual loop on its own: edit
the sketch, render a seed, look at the PNG, adjust. The grid and the census are
the edition-level views — what the rarity table actually produces.
What check.mjs prints on a sketch that holds:
myproject (size 600, 3 runs)
repeatability
ok 0xa3f1a3f1a3… → 06669011
ok 0x77c277c277… → 7e5f6b7f
distinctness
ok two different hashes produce two different renders
global state (A, B, A in one page)
ok A=06669011 B=7e5f6b7f A'=06669011
features
ok stable across 3 runs: {"Palette":"Ash","Density":"Sparse"}
all checks passed
And on the same sketch with one Math.random() left in — the broken variant CI
derives from the fixture on every push, and requires to fail:
repeatability
FAIL 0xa3f1a3f1a3… → e8dec1f3 / b40e8a1f / dc9b8f1f
FAIL 0x77c277c277… → 32fa5f55 / e04d40ad / a55fea14
global state (A, B, A in one page)
FAIL A=e127ff40 B=55a66c50 A'=05545a48
features
FAIL changed between runs: {"Palette":"Ash",…} vs {"Palette":"Ember",…} vs {"Palette":"Verdant",…}
4 failure(s)
distinctness still passes there: Math.random() does produce two different
images. Each check covers what it covers, and no more.
They need Playwright in your project (npm i -D playwright && npx playwright install chromium — they print this if it is missing). The plugin itself stays
dependency-free: no package.json, nothing embedded.
The contract a sketch must follow (three lines of shim for any platform) and
what the checks can and cannot prove are in references/verification.md.
They contain no version numbers, no figures and no field names — only the stable mental model of each platform, the canonical doc URLs, and the questions to ask those docs. Claude fetches the real documentation before writing platform code.
That is deliberate. A copied value goes stale in months and is then worse than nothing, because you believe it. A link stays right.
Nothing here can prove cross-machine determinism, and this plugin does not claim
to. In WebGL, shader compilers, float precision, rasterisers and MSAA differ
between GPUs; in JS, transcendental functions differ between engines. What is
actually checkable is same-machine reproducibility, perceptual stability across
sizes, and feature stability. references/verification.md is explicit about
where the line falls.
CI runs the scripts against a known-good fixture on every push (and against a broken variant derived from it, which must fail), and checks monthly that the URLs in the sheets still resolve — confirmed 404/DNS only, bot walls don't count — opening an issue when one dies. The sheets contain no volatile facts, so dead links are the only thing that rots.
If you mint something with it, I would genuinely like to see it — open a Discussion with a render and the platform you released on, or post it and tag @camillerouxart. Pieces made with the skill get shared onward.
Reference sheets are the easiest thing to contribute: a platform that is missing, a doc URL that moved, a mental model that is wrong. Issues and PRs welcome — the editorial rules are short.
If it saved you an afternoon, a ⭐ is how the next artist finds it.
Built and maintained by Camille Roux — generative/algorithmic artist. Maintainer of awesome-generative-art, the curated list of generative art platforms, libraries and resources.
Follow the art: art.camilleroux.com · X · Instagram · Farcaster · Bluesky · Mastodon · TikTok
MIT.