by probabl-ai · Claude Skill · ★ 125
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
uvx --from skore-cli skills install
npx skills add probabl-ai/skillsTaken from the project's README on GitHub.
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.
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 | 125 |
| Forks | 9 |
| Language | Python |
| Category | Claude Skill |
| License | BSD-3-Clause |
| Quality Score | 69/100 |
| Open Issues | 10 |
| Last Updated | 2026-09-25 |
| Created | 2026-05-05 |
| Platforms | claude-code, python |
| Est. Tokens | ~14k |
Probabl Skills A set of skills to team up with you in your machine learning experimentation journey. It helps you at: organizing your workspace building your machine learning pipeline with the right libraries ensuring good methodologies evaluating and storing your results such that you can easily audit and get insights from them couple it with Skore Hub to get a comprehensive view of your...
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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: