by haorantang97 · Codex Skill · ★ 291
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Featured in: OpenAI Codex Skills
/plugin marketplace add haorantang97/LabArtTaken from the project's README on GitHub.
None of the 43 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 43 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 291 |
| Forks | 15 |
| Language | Python |
| Category | Codex Skill |
| Quality Score | 67/100 |
| Last Updated | 2026-10-29 |
| Created | 2026-07-25 |
| Platforms | codex, python |
| Est. Tokens | ~15k |
LabArt A small laboratory of visual-creation skills, packaged as a Claude / Codex plugin marketplace. Each plugin is a self-contained aesthetic system. Antibes Holiday Antibes Holiday is a portable visual-creation skill for original relaxed black-pen illustrations, narrative scenes, expressive marks, and early logo exploration.
These tools work well together with LabArt for enhanced workflows:
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 43 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: