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 poco-ai · Codex Skill · ★ 1.4k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is poco-claw safe to install? View the security audit →
Poco: Your Pocket Coworker A safer, more beautiful, and easier-to-use OpenClaw alternative English | 简体中文 Core Features Secure Sandbox All tasks run in an isolated container. Feel free to install dependencies, modify files, and execute commands — without affecting the host environment. More Than a Chatbot Supports Plan Mode, conversation queueing, conversation termination ... Project management: organize and switch between tasks and contexts more effectively File uploads: accept and work with multiple file formats Polished, Productive UI Artifacts view: render and preview many formats (HTML, PDF, Markdown, images, videos, Xmind, Excalidraw, Drawio, and more) Playback view: rep
| Stars | 1,352 |
| Forks | 128 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 64.9921650347689/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-22 |
| Created | 2026-01-08 |
| Platforms | browser, claude-code, python |
| Est. Tokens | ~14k |
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poco-claw is A more beautiful and easier-to-use alternative to OpenClaw. It features a nicer Web UI, built-in IM support, a sandboxed runtime and channel-based team collaboration. Under the hood, it is powered by . It is categorized as a Codex Skill with 1.4k GitHub stars.
poco-claw is primarily written in Python. It covers topics such as agent, ai, chatbot.
You can find installation instructions and usage details in the poco-claw GitHub repository at github.com/poco-ai/poco-claw. The project has 1.4k stars and 128 forks, indicating an active community.
poco-claw is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to poco-claw on Agent Skills Hub include tokscale, openakita, Wegent. 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: