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env-doctor

Skill Infrastructure Usable

Diagnose and Fix CUDA / GPU environments compatibility issues locally, in Docker, and CI/CD. CLI + MCP server available.

149 starsMIT (commercial OK)FreeQuick setup
Usable rating — This tool is functional but has notable gaps. Review the evaluation notes below before deploying.

Eliminates time spent diagnosing GPU/CUDA misconfigurations across development, containerized, and CI/CD environments—reducing deployment failures and accelerating ML/compute workload onboarding.

Infrastructure and ML engineering teams managing GPU-dependent applications across multiple deployment contexts.

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https://github.com/mitulgarg/env-doctor

By mitulgarg

How to Get It

Option 1: Claude Desktop App (Code Mode)Click the + button next to the prompt box → PluginsAdd plugin. Search and click Install. Skills work in Claude Code only.
Option 2: Paste into Claude CodeCopy the command below and paste it into your conversation. Claude will install it.
Command
claude plugins install mitulgarg/env-doctor

Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.

CostFree

Trust Signals Auto-scanned

Stars149Last updated2026-05-16LicenseMIT (OK for commercial use)Known CVEsNone foundSources: GitHub Advisory Database + OSV.dev · Scanned 2026-05-20 · scanner v1

Community Pulse Active

Discussed on Hacker News, Reddit

14 mentions across 2 sources

Reviewer notes

Auto-scanned review. These are observations, not a security certification.

Scored from trust signals (evidence-eval-v1): 149 GitHub stars; contributors unknown; last commit 4d ago; license MIT.

How to evaluate tools before deploying →

Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.

Evaluation

Ease of Use
3/5
Versatility
3/5
Reliability
3/5
Security
3/5
Overall score3.00 / 5.00 UsableEvaluatedMay 2026
Scored from trust signals (evidence-eval-v1): 149 GitHub stars; contributors unknown; last commit 4d ago; license MIT.

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