
Code Simplifier
- 2 installs
- 512 repo stars
- Updated February 11, 2026
- meleantonio/chernycode
Simplifies and cleans up Python code after changes by reducing complexity, applying Pythonic patterns, and removing dead code.
About
Cleans up finished code by breaking up long functions, reducing nesting, applying comprehensions and f-strings, and removing unused imports and dead code. A developer runs it after a feature or fix to improve readability and maintainability.
- Reduces complexity: shorter functions, max 3 nesting levels, named constants
- Applies Pythonic patterns and removes unused/commented-out code
Code Simplifier by the numbers
- 2 all-time installs (skills.sh)
- Ranked #947 of 1,352 Code Review & Quality skills by installs in the Skillselion catalog
- Data as of Aug 4, 2026 (Skillselion catalog sync)
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| Installs | 2 |
|---|---|
| repo stars | ★ 512 |
| Last updated | February 11, 2026 |
| Repository | meleantonio/chernycode ↗ |
What it does
Simplifies and cleans up Python code after changes by reducing complexity, applying Pythonic patterns, and removing dead code.
Files
Code Simplifier
Clean up and simplify code after making changes.
When to Use
Run this skill after completing a feature or fix to ensure the code is clean, readable, and maintainable.
Simplification Goals
Reduce Complexity
- Break long functions into smaller, focused ones
- Reduce nesting depth (max 3 levels)
- Simplify complex conditionals
- Extract magic numbers to named constants
Improve Readability
- Use descriptive variable and function names
- Add clarifying comments for non-obvious logic
- Ensure consistent formatting
- Remove unnecessary comments
Apply Pythonic Patterns
- Use list/dict/set comprehensions where appropriate
- Use
withstatements for resource management - Use
enumerate()instead of manual indexing - Use
zip()for parallel iteration - Use f-strings for formatting
- Use
pathlibfor file paths
Clean Up
- Remove unused imports
- Remove unused variables
- Remove commented-out code
- Remove redundant code paths
- Consolidate duplicate logic
Workflow
1. Identify Changed Files
- Focus on files modified in the current session
- Or specify files/directories as arguments
2. Analyze Each File
- Check for simplification opportunities
- Prioritize high-impact improvements
3. Apply Simplifications
- Make incremental changes
- Preserve original behavior
- Run tests after each change
4. Format and Lint
- Run
ruff format . - Run
ruff check --fix .
5. Verify
- Run tests:
pytest - Ensure behavior unchanged
Arguments
Optionally specify files or directories to simplify.
Usage:
/code-simplifier- Simplify recently changed files/code-simplifier src/module.py- Simplify specific file/code-simplifier src/- Simplify entire directory
Example Transformations
Before:
result = []
for i in range(len(items)):
if items[i].is_valid == True:
result.append(items[i].value)After:
result = [item.value for item in items if item.is_valid]Before:
if x != None:
if y != None:
if z != None:
process(x, y, z)After:
if all(v is not None for v in (x, y, z)):
process(x, y, z)