by kishorkukreja · AI Tool · ★ 76
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npx skills add kishorkukreja/awesome-supply-chain --list
/plugin marketplace add kishorkukreja/awesome-supply-chainTaken 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 | 76 |
| Forks | 19 |
| Language | Python |
| Category | AI Tool |
| License | MIT |
| Quality Score | 62/100 |
| Open Issues | 4 |
| Last Updated | 2026-10-06 |
| Created | 2025-10-18 |
| Platforms | python |
| Est. Tokens | ~15k |
Awesome Supply Chain A comprehensive collection of research papers, implementations, libraries, and resources for supply chain management, organized by industry verticals. 133 AI agent skills available. The repository follows the open Agent Skills format and includes plugin metadata for Claude Code and Codex.
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Skip to content github / docs Code Issues 80 Pull requests 35 Discussions Actions Projects 2 Security Insights
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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: