Identify and report code smells indicating poor design or maintainability issues in Python code, including duplicate code, magic numbers, hardcoded values, God classes, feature envy, inappropriate intimacy, data clumps, primitive obsession, and long parameter lists. Use when conducting code quality audits, preparing for refactoring, improving codebase maintainability, or performing design reviews. Produces markdown reports with severity ratings, locations, descriptions, and specific refactoring recommendations with before/after examples. Triggers when users ask to find code smells, identify design issues, suggest refactorings, improve code quality, or detect maintainability problems.
90
88%
Does it follow best practices?
Impact
93%
1.43xAverage score across 3 eval scenarios
Passed
No known issues
Full smell report structure and format
Uses detect_smells.py script
75%
100%
Emoji severity headers
0%
0%
File and line locations
100%
100%
Before/after code examples
100%
100%
Summary section with counts
100%
100%
Three-tier recommendations
60%
100%
CI/CD prevention commands
30%
100%
Code review checklist
12%
75%
God class severity
100%
100%
Magic number severity
0%
100%
Smell severity thresholds and categorization
Large class is medium severity
0%
100%
God class is high severity
100%
100%
Long method is medium severity
100%
100%
6-param function is medium severity
100%
100%
8-param function is high severity
100%
100%
Feature envy is high severity
100%
100%
Magic numbers are low severity
100%
100%
God class refactoring technique
100%
100%
Long parameter refactoring technique
100%
100%
Code quality tooling and prevention setup
radon cc command
100%
100%
radon mi command
100%
100%
pylint --disable=C0111
0%
100%
pylint --fail-under=8.0
0%
100%
Method length limit of 50
100%
100%
Class method limit of 15
0%
100%
Parameter count limit of 5
100%
100%
detect_smells.py script mentioned
0%
0%
No hardcoded config or magic numbers in checklist
40%
100%
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Table of Contents
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