by RobotecAI · Agent Tool · ★ 613
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 | 613 |
| Forks | 79 |
| Language | Python |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 62/100 |
| Open Issues | 75 |
| Last Updated | 2026-11-06 |
| Created | 2024-06-04 |
| Platforms | python |
| Est. Tokens | ~14k |
RAI RAI is a flexible AI agent framework to develop and deploy Embodied AI features for your robots. 📚 Visit robotecai.github.io/rai for the latest documentation, setup guide and tutorials. 📚 🎯 Overview Features
Looking for a rai alternative? If you're comparing rai with other agent tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
One CLI for all your robots. Connect them, command them, and let them work together, each with an LLM for a br
Physical AI runtime for embodied agents — governed action, verified experience, physical memory, and skill evo
Awesome things about LLM-powered agents. Papers / Repos / Blogs / ...
A minimal yet powerful framework for creating AI agents with full control over tools, providers, and execution
An introduction to the world of AI Agents
Awesome LLM Papers and repos on very comprehensive topics.
Explore other popular agent tool tools:
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: