Can it help with large, 1000+ line Python files?

Yes, it is designed to identify 'Red Flags' like oversized files and global variables, systematically breaking them down into logical modules and classes.

Does it automatically optimize for performance?

Its primary focus is readability and maintainability. It will not sacrifice performance by more than 2x and will prioritize clarity unless explicit performance optimization is requested.

Does this skill support procedural refactoring?

While it improves any code, the skill is specifically optimized to move away from procedural scripts toward class-based architecture for better long-term maintainability.

How does it ensure my code doesn't break during refactoring?

It uses a 'Safety by Design' workflow that includes creating migration plans, running static analysis (flake8) before and after changes, and requiring a 100% test pass rate at every step.

Python Refactor

Name: Python Refactor
Author: acaprino

byacaprino

API Development

Transforms complex, procedural Python scripts into maintainable, class-based architectures with guaranteed regression prevention.

About

Python Refactor is a specialized skill for Claude Code designed to modernize legacy codebases and eliminate 'spaghetti' logic. It prioritizes the transformation of disorganized scripts into structured, object-oriented systems following SOLID principles and dependency injection patterns. The skill operates with a safety-first mindset, requiring mandatory migration checklists, comprehensive static analysis via flake8, and continuous test validation to ensure that code quality improves without introducing functional regressions or performance bottlenecks.

Key Features

Mandatory conversion of procedural scripts to professional OOP architecture
Enforcement of PEP 8 standards, type hints, and self-documenting structures
Complexity metric analysis to target and simplify nested logic
Comprehensive migration planning for high-risk, destructive code changes
Automated regression prevention using flake8 and pytest validation cycles
0 GitHub stars

Use Cases

Modernizing legacy scripts that rely on global state and scattered functions
Standardizing codebases for team onboarding or educational purposes
Breaking down 'God Objects' and large files into modular, testable components

About

Key Features

Mandatory conversion of procedural scripts to professional OOP architecture
Enforcement of PEP 8 standards, type hints, and self-documenting structures
Complexity metric analysis to target and simplify nested logic
Comprehensive migration planning for high-risk, destructive code changes
Automated regression prevention using flake8 and pytest validation cycles
0 GitHub stars

Use Cases

Modernizing legacy scripts that rely on global state and scattered functions
Standardizing codebases for team onboarding or educational purposes
Breaking down 'God Objects' and large files into modular, testable components