claude_skills/python-cleanup/SKILL.md

Python Cleanup Skill

Clean up Python code by formatting, fixing lint issues, removing unused imports, and identifying dead code.

Usage

Invoke with /python-cleanup followed by an optional path or scope:

• /python-cleanup - Clean up changed files (git diff)
• /python-cleanup src/ - Clean up a specific directory
• /python-cleanup src/main.py - Clean up a specific file

Workflow

Step 1: Identify Target Files

If no path specified, find Python files with uncommitted changes:

git diff --name-only --diff-filter=ACMR HEAD | grep '\.py$'

If a path is specified, use that path directly.

Step 2: Format Code

Run ruff formatter to fix code style:

ruff format <target>

Step 3: Fix Lint Issues

Auto-fix all fixable lint issues including unused imports:

ruff check --fix --unsafe-fixes <target>

Key rules this fixes:

• F401 - Unused imports (removes them)
• F841 - Unused variables
• I001 - Import sorting
• UP - Python upgrade suggestions
• B - Bugbear issues

Step 4: Report Remaining Issues

Show any issues that couldn't be auto-fixed:

ruff check <target>

Step 5: Identify Dead Code (Optional)

Use vulture to find potentially unused code:

vulture <target> --min-confidence 80

If vulture is not installed, skip this step and note it in the summary.

Step 6: Summary

Provide a summary of:

• Files processed
• Issues auto-fixed (count by category)
• Remaining issues that need manual review
• Potential dead code identified (if vulture available)

Configuration

This skill respects project-level pyproject.toml or ruff.toml configuration if present.

Dependencies

• ruff (required) - Install with uv add ruff or pip install ruff
• vulture (optional) - Install with uv add vulture or pip install vulture