code-smell-detector

# Code Smell Detector ## Overview Identify code quality and design smells in Python codebases, then provide specific refactoring recommendations to improve maintainability and design. ## Workflow ### 1. Understand the Analysis Scope Define what to analyze: **Questions to ask:** - What directory or files should be analyzed? - Focus on quality smells, design smells, or both? - Are there specific concerns (e.g., "this class is too complex")? - Should test files be included? **Determine scope:** ```bash # Check project structure ls -la # Count Python files find . -name "*.py" | wc -l # Identify large files (potential smells) find . -name "*.py" -exec wc -l {} + | sort -rn | head -10 ``` ### 2. Detect Code Smells Use multiple detection strategies. #### Strategy 1: Automated Detection Use the bundled script for AST-based analysis: ```bash # Scan entire project python scripts/detect_smells.py /path/to/project # Exclude specific directories python scripts/detect_smells.py /path/to/project venv,tests,docs ``` **What it detects:** - Long methods (>50 lines) - Too many parameters (>5) - Large classes (>15 methods) - God classes (>20 methods) - Magic numbers #### Strategy 2: Manual Code Review Read the code to identify design smells. See [smell-patterns.md](references/smell-patterns.md) for comprehensive catalog. **Look for:** **Code Quality Smells:** - Duplicate code blocks - Magic numbers (unexplained numeric literals) - Hardcoded values (paths, URLs, config) - Comm...