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 clacky-ai · Codex Skill · ★ 1.2k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is openclacky safe to install? View the security audit →
OpenClacky From expertise to business — turn your professional knowledge into a monetizable OpenClaw Skill. OpenClacky is the creator-side platform for the OpenClaw ecosystem. Package your methods and workflows into encrypted, white-labeled Skills that your clients install and use — under your name, your brand, your price. Why OpenClacky? The OpenClaw ecosystem has 5,700+ Skills and growing. But almost all of them are open-sourced, free, and easily copied. The real scarcity isn't more Skills — it's expertise-backed, production-grade Skills worth paying for. OpenClacky is built for the people who have that expertise. | Rev
| Stars | 1,202 |
| Forks | 114 |
| Language | Ruby |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 75.035517150079/100 |
| Open Issues | 43 |
| Last Updated | 2026-10-11 |
| Created | 2025-12-30 |
| Platforms | ruby |
| Est. Tokens | ~14k |
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openclacky is The most Token-efficient open-source AI Agent. It is categorized as a Codex Skill with 1.2k GitHub stars.
openclacky is primarily written in Ruby. It covers topics such as agent, openclaw, skills.
You can find installation instructions and usage details in the openclacky GitHub repository at github.com/clacky-ai/openclacky. The project has 1.2k stars and 114 forks, indicating an active community.
openclacky is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to openclacky on Agent Skills Hub include awesome-agent-skills, n8n-claw, JoySafeter. 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: