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None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
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 | 263 |
| Forks | 45 |
| Language | Python |
| Category | AI Tool |
| License | MIT |
| Quality Score | 65/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-22 |
| Created | 2026-09-21 |
| Platforms | python |
| Est. Tokens | ~15k |
Laya Ultrafast ⚡ A local, open-weight port of browser-use/jev-ultrafast. [!NOTE] This project is a clone of jev-ultrafast by Browser Use, ported to make its decisions with Laya running locally through MLX. The browser agent, DOM snapshot, executor, safety checks, inspector and most of the design are theirs. All credit for the original work goes to the jev-ultrafast authors.
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 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: