by lawrence3699 · MCP Server · ★ 89
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
pip install "jev-style[mlx]" # Apple silicon (MLX)
pip install "jev-style[torch]" # Linux, Windows or an Intel Mac (PyTorch on CUDA or CPU)Taken 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 | 89 |
| Forks | 3 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 66/100 |
| Last Updated | 2026-11-04 |
| Created | 2026-09-25 |
| Platforms | claude-code, mcp, python |
| Est. Tokens | ~19k |
Jev-Style Small, calibrated decision models you run on your own machine, plus the tooling to put them to work in AI agents. <img alt="License: Apache-2.0" src="https://img.shields.io/badge/license-Apache--2.0-0a0a0a.svg?style=for-the-badge&labelColor=
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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: