by b1rdmania · Codex Skill · ★ 84
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ghostclaw safe to install? View the security audit →
GhostClaw give it a machine. let it roam. Website · Learn · Install · Skills · Skill Repo · Security The OpenClaw alternative that actually works. A bare-metal fork of NanoClaw — containers stripped, full system access, Telegram-first. Give your spare computer its own accounts and let an AI agent run wi
git clone https://github.com/b1rdmania/ghostclaw.gitTaken from the project's README on GitHub. Check the security audit before running it.
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 →
| Stars | 84 |
| Forks | 8 |
| Language | TypeScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 69/100 |
| Last Updated | 2026-05-03 |
| Created | 2026-03-02 |
| Platforms | claude-code, node |
| Est. Tokens | ~778k |
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ghostclaw is an AI that lives on your computer and does stuff for you. Public beta.. It is categorized as a Codex Skill with 84 GitHub stars.
ghostclaw is primarily written in TypeScript. It covers topics such as ai, ai-agent, claude.
The README on GitHub (github.com/b1rdmania/ghostclaw) gives: git clone https://github.com/b1rdmania/ghostclaw.git. Usage details are in the same README.
ghostclaw is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to ghostclaw on Agent Skills Hub include GoGogot, tinyclaw, openclaw-command-center. 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: