project-cairn: Turn project work into reusable knowledge — an AI-agent skill for Claude Code & Codex

by iBlinkQ · Claude Skill · ★ 243

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

How to install project-cairn

git clone https://github.com/iBlinkQ/project-cairn.git ~/.claude/skills/project-cairn
git clone https://github.com/iBlinkQ/project-cairn.git ~/.agents/skills/project-cairn

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 71/100

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.

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.

agent-skillsai-agentsclaude-codecodexknowledge-managementllm-agent

Quick Facts

Stars243
Forks45
LanguageShell
CategoryClaude Skill
LicenseMIT
Quality Score71/100
Open Issues1
Last Updated2026-10-22
Created2026-07-01
Platformsclaude-code, cli, codex
Est. Tokens~13k

About project-cairn

English | 中文 Project Cairn Turn project work into reusable knowledge. Open the interactive guide to learn more about the Skill Sound familiar? The same problem comes back in the next project. Start a new session or switch agents, and you are explaining the context and rules all over again. Plans, progress, and conclusions are scattered, so the agent keeps jumping between old and new directions.

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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:

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