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 qualisero · Agent Tool · ★ 1.1k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is awesome-pi-agent safe to install? View the security audit →
Started as a quick way to gather the (at the time small) number of contributions to the Pi Agent project. Now definitely outdated and overtaken by more dedicated projects, so time to retire!
| Stars | 1,099 |
| Forks | 66 |
| Language | JavaScript |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 49.4458367130748/100 |
| Open Issues | 31 |
| Last Updated | 2026-06-03 |
| Created | 2026-01-05 |
| Platforms | node |
| Est. Tokens | ~6k |
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awesome-pi-agent is Awesome list of add-ons, hooks, tools, skills, and resources for the pi coding agent (pi-mono).. It is categorized as a Agent Tool with 1.1k GitHub stars.
awesome-pi-agent is primarily written in JavaScript. It covers topics such as agentic-ai, llm, pi.
You can find installation instructions and usage details in the awesome-pi-agent GitHub repository at github.com/qualisero/awesome-pi-agent. The project has 1.1k stars and 66 forks, indicating an active community.
awesome-pi-agent is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to awesome-pi-agent on Agent Skills Hub include PPTAgent, ag2, EverMemOS. 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: