No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by camilleroux · Claude Skill · ★ 136
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
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genart — a generative art skill for Claude Code 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. 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 M
| Stars | 136 |
| Forks | 14 |
| Language | JavaScript |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 70.5421300773452/100 |
| Last Updated | 2026-09-04 |
| Created | 2026-08-28 |
| Platforms | claude-code, node |
| Est. Tokens | ~14k |
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genart-skill is Generative art skill for Claude Code — deterministic, hash-seeded, onchain-ready. It is categorized as a Claude Skill with 136 GitHub stars.
genart-skill is primarily written in JavaScript. It covers topics such as algorithmic-art, art-blocks, claude-code.
You can find installation instructions and usage details in the genart-skill GitHub repository at github.com/camilleroux/genart-skill. The project has 136 stars and 14 forks, indicating an active community.
genart-skill is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to genart-skill on Agent Skills Hub include genjutsu, adversarial-spec, claude-elixir-phoenix. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: