infra-skills: A collection of specialized agent skills for AI infrastructure development, enabling Claude Code to write

by yzlnew · Agent Tool · ★ 142

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

How to install infra-skills

git clone https://github.com/yzlnew/infra-skills.git
git clone https://github.com/yzlnew/infra-skills.git .claude/skills-repo

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

Security audit verdict: SAFE · quality 67/100

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.

Quick Facts

Stars142
Forks11
LanguagePython
CategoryAgent Tool
Quality Score67/100
Last Updated2026-07-09
Created2026-01-07
Platformsclaude-code, python
Est. Tokens~16k

About infra-skills

AI Infrastructure Agent Skills ⚠️ WARNING This project is under active development and heavily generated by LLMs without strict proofreading. Use with caution and verify all code before production use. A collection of specialized agent skills for AI infrastructure engineers, covering both technical development (GPU kernels, distributed training, inference optimization) and soft skills (flowchart...

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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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