openclacky: The most Token-efficient open-source AI Agent

by clacky-ai · Codex Skill · ★ 1.2k

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install openclacky

gem install openclacky
git clone https://github.com/clacky-ai/open-clacky.git

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 75/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agentopenclawskills

Quick Facts

Stars1,208
Forks112
LanguageRuby
CategoryCodex Skill
LicenseMIT
Quality Score75/100
Open Issues41
Last Updated2026-10-22
Created2025-12-30
Platformsruby
Est. Tokens~14k

About openclacky

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.

Compatible Skills

These tools work well together with openclacky for enhanced workflows:

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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:

View on GitHub → Browse Codex Skill tools