by tigerless-labs · Agent Tool · ★ 204
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git clone https://github.com/tigerless-labs/paper-radarTaken from the project's README on GitHub.
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.
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 | 204 |
| Forks | 32 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 64/100 |
| Last Updated | 2026-09-01 |
| Created | 2026-08-04 |
| Platforms | python |
| Est. Tokens | ~6k |
paper-radar What 28 AI labs published on arXiv, over any date range paper-radar finds the AI papers 28 labs put on arXiv, over any date range you pick. Every count splits two ways — papers the lab led, and papers it merely appears on. Method: match against ROR and email domains, using the author block read off each paper's HTML. You need it because arXiv does not carry affiliation.
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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: