by paiml · MCP Server · ★ 170
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git clone https://github.com/paiml/paiml-mcp-agent-toolkitTaken 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 | 170 |
| Forks | 30 |
| Language | Rust |
| Category | MCP Server |
| License | MIT |
| Quality Score | 76/100 |
| Open Issues | 72 |
| Last Updated | 2026-11-06 |
| Created | 2025-05-25 |
| Platforms | mcp, rust |
| Est. Tokens | ~25k |
PMAT Zero-configuration AI context generation for any codebase Installation Documentation Table of Contents What is PMAT? Installation Usage Features Architecture What is PMAT? PMAT (Pragmatic Multi-language Agent Toolkit) provides everything needed to analyze code quality and generate AI-ready context: Context Generation - Deep analysis for Claude, GPT, and other LLMs Technical Debt Grading - A+
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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: