env-doctor: Diagnose and Fix CUDA / GPU environments compatibility issues locally, in Docker, and CI/CD

by mitulgarg · MCP Server · ★ 172

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install env-doctor

pip install env-doctor
uv tool install env-doctor

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 71/100

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.

cicdcompatibility-toolcudacuda-librarycuda-supportcuda-toolkitcudnndiagnosticsgpumcp-server

Quick Facts

Stars172
Forks10
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score71/100
Open Issues8
Last Updated2026-10-01
Created2025-11-22
Platformscli, docker, mcp, python
Est. Tokens~17k

About env-doctor

Env-Doctor The missing link between your GPU and Python AI libraries

Compatible Skills

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How this security grade is produced

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:

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