by limingrui679-design · Agent Tool · ★ 832
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npx skills add limingrui679-design/high-stakes-analytics-decision-lab -g
npx skills add limingrui679-design/high-stakes-analytics-decision-lab -g -a codex -yTaken 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 | 832 |
| Forks | 101 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 64/100 |
| Open Issues | 3 |
| Last Updated | 2026-09-21 |
| Created | 2026-07-29 |
| Platforms | python |
| Est. Tokens | ~20k |
High-Stakes Analytics & Decision Lab A platform-neutral, evidence-constrained Skill for moving from an ambiguous question to a defensible analysis—and only then, when justified, to action. What the Skill does This Skill turns an ambiguous, consequential question into a reproducible evidence product and, only when justified, a bounded decision product.
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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: