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Genart

Community
camilleroux
genart

Craft long-form generative art for onchain platforms — Art Blocks, 256ART, Verse, Highlight, Plottables, bootloader.art, or a self-hosted drop — and for screen diffusion channels such as Artpoint. Covers hash-seeded determinism, resolution-agnostic rendering, features and rarity design, preview capture signals, debug GUIs and image/video export shortcuts, verification of a sketch before minting, and the ethics of the field. Use when the user mentions generative art, gen art, creative coding, long-form, onchain art, a seeded sketch, a PRNG or deterministic randomness, traits, rarity, features, a mint, a plotter or SVG output, art on screen or delivering a piece as a video, or pastes platform APIs such as tokenData, $features, inputData, $bootloader, BTLDR, hl-gen, or a base64 payload query param.

Overview

Publishercamilleroux
Repositorygenart-skill
Skill namegenart
Stars
156
Forks
13
Bundled files
15
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 15 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by camilleroux on GitHub. Read the source before you install it.

Installation

Install the Genart AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/camilleroux/genart-skill/tree/main/skills/genart
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/camilleroux/genart-skill.git /tmp/genart-skill
mkdir -p .claude/skills
cp -r /tmp/genart-skill/skills/genart .claude/skills/genart
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Genart in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Genart on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Genart is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Generative art

Help design, write and check long-form generative artworks — pieces where one algorithm produces a whole edition, each output derived from a hash the blockchain hands you at mint time.

Default practices, and when to break them

These are defaults that work most of the time, not rules. Every one of them has legitimate counter-examples, and those are often the interesting pieces. State the default, then state what breaking it costs.

DefaultBreaking it is legitimate when…
All variation comes from the hashThe piece deliberately reads live onchain state (owner, block data). It is then no longer reproducible from the hash alone — own that choice and document it
One seeded PRNG, fixed consumption orderAlmost never. But named sub-streams let you add a draw without shifting the whole edition — that is how you get flexibility without breaking the property
No network, no CDN, no system fontsSome platforms have an explicit external-asset mode, under their own rules
No wall clockThe piece is about time passing, or is genuinely interactive. The preview render must stay stable regardless
Sizes relative to the canvas dimensionThe piece is deliberately adaptive and reveals more detail with more room. A choice, not an accident — then know what size it will be captured at
Runs on current browsers and devices — Chrome, Firefox, Safari, mobile includedA piece built on a bleeding-edge API (WebGPU…) or needing real GPU power is a choice: state the requirement, keep the preview/capture path rendering everywhere, and remember collectors open links on phones
Emit the platform's render-done signalNever. A blank thumbnail is a failure with no upside
Features computed before render, from the seed onlyWhere the platform computes features outside a browser, it is required. Elsewhere it is a convenience
Debug code is stripped from the submitted buildWhere code is stored unminified and readable onchain, formatting is part of the work
Never claim "it's deterministic" without testing it, and without stating the scopeNever

The firm part: breaking a default must be the artist's explicit choice, never an accident. Point out the deviation, explain what it costs, then do what the artist asked. Do not refuse and do not lecture.

Ethics

  • Never reproduce a named living artist's signature work. Techniques are shared heritage; a body of work is not. Offered "make me a ", decline that framing and offer the underlying technique instead.
  • Credit the algorithm, the shader, the palette you borrowed.
  • Check that a library's licence survives being written onchain forever.
  • Be straight about what AI did: writing the code and generating the image are different claims.

Full version: references/ethics.md.

Platforms: read the docs, every time

Platform APIs change and the fiches in references/platforms/ deliberately hold no versions, no numbers and no field names — only the stable mental model, the canonical URLs and the questions to ask.

So the sequence is always: open the fiche → fetch the URLs it lists → then write code. Never write platform-specific code from memory, and never from the fiche alone. If a doc is unreachable, say so and flag what could not be confirmed.

TargetFiche
Art Blocks (incl. Engine / Flex)references/platforms/artblocks.md
256ARTreferences/platforms/256art.md
Versereferences/platforms/verse.md
Highlightreferences/platforms/highlight.md
Plottables (pen plotter, AB Engine)references/platforms/plottables.md
bootloader.art — ask which bootloaderreferences/platforms/bootloader.md
Self-hosted / no platformreferences/platforms/self-hosted.md
Artpoint — art on screen, you deliver a video, not codereferences/platforms/artpoint.md
Undecided between tworeferences/platforms/comparison.md

Where to look

When the question is about…Read
Seeding from a hash, PRNG choice, sub-streams, distributions, things that silently break reproducibilityreferences/determinism.md
Output that changes with canvas size, stroke weights, noise frequency, element density, print or plotter outputreferences/resolution.md
Designing traits, rarity tables, weights, distribution that came out wrongreferences/features.md
Originality, attribution, licences, disclosing AI usereferences/ethics.md
Debug panel, param tweaking, keyboard shortcuts, PNG and video export, contact sheetsreferences/tooling.md
"Is my sketch actually deterministic?", pre-mint checking, what a test can and cannot provereferences/verification.md
Techniques, tutorials, libraries, inspiration, what other artists useFetch https://github.com/camilleroux/awesome-generative-art — a maintained list; do not paraphrase it from memory

Runnable scripts

Two scripts ship with the plugin and run in place — never copy them into a project. They need Playwright installed in the artist's project and print the install command if it is missing. Contract and details: references/verification.md.

CommandDoes
node "$CLAUDE_PLUGIN_ROOT/scripts/check.mjs" <dir>Determinism: repeatability, distinctness, global-state contamination, feature stability
node "$CLAUDE_PLUGIN_ROOT/scripts/render.mjs" <dir> --hash 0x…One PNG — render it, then look at it with Read before judging any visual change
node "$CLAUDE_PLUGIN_ROOT/scripts/render.mjs" <dir> --grid NContact sheet, hash + features under each tile
node "$CLAUDE_PLUGIN_ROOT/scripts/render.mjs" <dir> --census N --edition-size EReal feature distribution vs the rarity table
node "$CLAUDE_PLUGIN_ROOT/scripts/render.mjs" <dir> --batch N --size 2400N individual full-res PNGs, hash-named — portfolio/print export

When asked to change how a piece looks, close the loop yourself: edit → render one hash → Read the PNG → judge → adjust. Do not describe a visual change you have not looked at.

Workflow

  1. Target first. Which platform? If undecided, references/platforms/comparison.md. Once decided, open its fiche and fetch its docs before writing anything.
  2. Decide the rarity table before coding. It is much harder to retrofit.
  3. Build. Defaults above; deviations discussed, not silently taken.
  4. Look at many outputs, not one. A single good render proves nothing — render.mjs --grid exists for this.
  5. Check before minting — check.mjs, then references/verification.md for what the green result does and does not prove.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Genart AI skill do?

Craft long-form generative art for onchain platforms — Art Blocks, 256ART, Verse, Highlight, Plottables, bootloader.art, or a self-hosted drop — and for screen diffusion channels such as Artpoint. Covers hash-seeded determinism, resolution-agnostic rendering, features and rarity design, preview capture signals, debug GUIs and image/video export shortcuts, verification of a sketch before minting, and the ethics of the field. Use when the user mentions generative art, gen art, creative coding, long-form, onchain art, a seeded sketch, a PRNG or deterministic randomness, traits, rarity, feature...

Why use Genart on TypingMind?

Because you install it once and use it with any model. Genart is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Genart in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/camilleroux/genart-skill/tree/main/skills/genart. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Genart?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Genart?

As many as you like. As long as a model supports skills, you can use Genart with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Genart AI skill free?

Yes. It is published on GitHub by camilleroux under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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