by TsCarpe · Claude Skill · ★ 64
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
npx skills add TsCarpe/claude-sdlc-skills # 一行安装，先跑 sdlc-intent 零依赖
npx skills add TsCarpe/claude-sdlc-skills # 装到当前项目 .claude/skills/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 | 64 |
| Forks | 0 |
| Language | Python |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 66/100 |
| Last Updated | 2026-10-20 |
| Created | 2026-09-12 |
| Platforms | claude-code, python |
| Est. Tokens | ~15k |
claude-sdlc-skills AI-native SDLC skills for Claude Code (and other coding agents via skills.sh) — AI takes over the repetitive labor of requirement intake, test design, adversarial review, browser testing and release auditing; humans rule only at a few hard gates. Battle-tested end-to-end on a real production Java project. Docs in Chinese; skills trigger on Chinese and English phrases.
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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.
Sources & who's responsible: