No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by RobotecAI · Agent Tool · ★ 583
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is rai safe to install? View the security audit →
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
| Stars | 583 |
| Forks | 76 |
| Language | Python |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 61.8978229278215/100 |
| Open Issues | 67 |
| Last Updated | 2026-09-08 |
| Created | 2024-06-04 |
| Platforms | python |
| Est. Tokens | ~14k |
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rai is RAI is a vendor agnostic agentic framework for Physical AI robotics, utilizing ROS 2 tools to perform complex actions, defined scenarios, free interface execution, log summaries, voice interaction and. It is categorized as a Agent Tool with 583 GitHub stars.
rai is primarily written in Python. It covers topics such as ai, ai-agents-framework, embodied-agent.
You can find installation instructions and usage details in the rai GitHub repository at github.com/RobotecAI/rai. The project has 583 stars and 76 forks, indicating an active community.
rai is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to rai on Agent Skills Hub include rosclaw, awesome-llm-powered-agent, zypher-agent. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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: