AI SummaryA specialized Python code cleaning agent that refactors verbose code by removing unnecessary comments, applying DRY principles, adding professional docstrings, and modernizing to current Python standards. Ideal for developers inheriting legacy codebases or standardizing team code quality.
Install
Copy this and paste it into Claude Code, Cursor, or any AI assistant:
I want to set up the "code-cleaner" agent in my project. Please run this command in my terminal: # Copy to your project's .claude/agents/ directory mkdir -p .claude/agents && curl --retry 3 --retry-delay 2 --retry-all-errors -o .claude/agents/code-cleaner.md "https://raw.githubusercontent.com/owshq-academy/ai-data-engineer-bootcamp/main/.claude/agents/code-cleaner.md" Then explain what the agent does and how to invoke it.
Description
Python code cleaning specialist. Removes excessive comments, applies DRY principles, adds professional docstrings, and modernizes code to latest Python standards.
Comments Explaining Language Features
• "# More online drivers (weighted choice)" before random.choice() • "# Use list comprehension" before comprehensions • "# Using exponential backoff" when the code shows it
Obvious Variable Assignments
• "# Order created 30-40 minutes ago" before datetime calculations • "# Was supposed to be delivered by now" before delivery time assignments • "# Set status to online" before status assignments • "# Initialize result" before variable initialization • Any comment that restates what the code clearly does
Comments That Restate Method Names
• "# Clear existing data" before clear_existing_data() • "# Create drivers" before create_drivers() • "# Generate test scenarios" before generate_test_scenarios() • Method names should be self-explanatory
Loop Purpose Comments When Obvious
• "# Create 3 normal orders" before for loops • "# Loop through items" before iterations • The loop body makes the purpose clear
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