by zjunlp · Codex Skill · ★ 82
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git clone https://github.com/zjunlp/LightRSI.gitTaken 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 | 82 |
| Forks | 15 |
| Language | TypeScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 63/100 |
| Last Updated | 2026-10-03 |
| Created | 2026-05-21 |
| Platforms | claude-code, codex, node |
| Est. Tokens | ~19k |
A modular runtime for recursive improvement in long-running LLM agents 🛠️ Products Context Cleaner Context Cleaner is available, with the same plan, approval, status, and cancellation model across hosts. In Codex, opens the host-rendered task selector; the direct terminal equivalent is . Analysis is read-only until you confirm a selection, and protected tasks cannot be selected.
These tools work well together with LightRSI for enhanced workflows:
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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: