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 kairunwen · Agent Tool · ★ 116
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Awesome-Robot-Use-Agent safe to install? View the security audit →
Awesome Robot Use Agent (RUA) Articles · Papers · [Projects](#project
| Stars | 116 |
| Forks | 0 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 64.0126810502136/100 |
| Last Updated | 2026-09-18 |
| Created | 2026-09-11 |
| Platforms | browser, python |
| Est. Tokens | ~25k |
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Awesome-Robot-Use-Agent is A curated collection of papers, research blogs, open-source tools, benchmarks, and community demos for robot-use agents, including demos powered by GPT-6 Astra. —— Explore our searchable website.. It is categorized as a Agent Tool with 116 GitHub stars.
Awesome-Robot-Use-Agent is primarily written in Python. It covers topics such as ai-agents, awesome-list, robot-use.
You can find installation instructions and usage details in the Awesome-Robot-Use-Agent GitHub repository at github.com/kairunwen/Awesome-Robot-Use-Agent. The project has 116 stars and 0 forks, indicating an active community.
Awesome-Robot-Use-Agent is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to Awesome-Robot-Use-Agent on Agent Skills Hub include awesome-ai-coding-techniques, claudepro-directory, awesome-ai-agent-skills. 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: