by zevorn · Codex Skill · ★ 650
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
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 | 650 |
| Forks | 48 |
| Language | C |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 64/100 |
| Open Issues | 3 |
| Last Updated | 2026-05-26 |
| Created | 2026-03-11 |
| Est. Tokens | ~736k |
Making AI Assistants Cheap Again 中文 | English RT-Claw is an OpenClaw-inspired intelligent assistant for embedded devices. Multi-OS support via OSAL (FreeRTOS, RT-Thread, Zephyr and Linux). Build swarm intelligence with networked nodes. ESP32-S3 WiFi support adapted from MimiClaw.
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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: