by luoling8192 · Claude Skill · ★ 172
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npx skills add luoling8192/ai-coding-principles
Taken from the project's README on GitHub. Check the security audit before running it.
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.
| Stars | 172 |
| Forks | 11 |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 63/100 |
| Last Updated | 2026-03-26 |
| Created | 2026-03-22 |
| Platforms | claude-code |
| Est. Tokens | ~1k |
AI Coding Principles A collection of Claude Code skills for coding discipline and system design knowledge. 中文文档 Skills ai-coding-discipline Mandatory rules loaded during all code writing tasks that prevent common AI coding anti-patterns. ddia-principles Distilled reference guide based on Martin Kleppmann's Designing Data-Intensive Applications.
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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.
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