Env Doctor
Fix Python dependency hell without losing your afternoon
Diagnose and fix conda/pip conflicts, generate reproducible environment files, and containerize analytics projects. No more "it works on my machine" or spending an entire day getting dependencies to resolve.
PROMPT
Create a skill called "Env Doctor". Help me diagnose and fix Python environment issues. When I paste an error message (dependency conflicts, ImportError, version mismatches, conda solver failures), identify the root cause and provide a specific fix. When I point you at a Python project, analyze all imports and generate the minimal environment file (requirements.txt, environment.yml, or pyproject.toml) needed to run it. Detect conda/pip mixing issues (packages installed by both managers). If an environment is beyond repair, generate a Dockerfile that creates a clean, reproducible environment. Support conda, pip, poetry, and uv. For data science projects, know the common conflict patterns (e.g., numpy binary compatibility, tensorflow + CUDA version matrix, scikit-learn + scipy version coupling).
How It Works
Analytics teams lose entire days to Python environment issues — conda solver
hanging for hours, pip and conda fighting over numpy versions, a colleague's
notebook that only runs on their machine. This skill untangles the mess.
What You Get
- Dependency conflict diagnosis from error messages
- Auto-generated environment files (requirements.txt, environment.yml, pyproject.toml)
- Conda/pip conflict detection and resolution
- Environment recreation from a script's import statements
- Docker containerization for reproducible execution
- Migration between conda, pip, poetry, and uv
Setup Steps
- Ask your Claw to create an "Env Doctor" skill with the prompt below
- Paste the error message, point it at your project, or describe the issue
- Get back a diagnosis and fix
Tips
- Prevention beats cure: run the audit before sharing code with teammates
- The Docker containerization is the nuclear option when nothing else works
- uv is often the fastest fix for pip dependency resolution issues
- For data science stacks (numpy, scipy, scikit-learn, pandas), the skill knows the common version conflicts