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design-smell-detector

Identify design quality issues in code including high coupling, low cohesion, God classes, long methods, and other code smells. Use when: (1) Reviewing code architecture and design quality, (2) Identifying refactoring opportunities, (3) Detecting God classes or classes with too many responsibilities, (4) Finding high coupling or low cohesion issues, (5) Analyzing code maintainability and technical debt. Detects coupling smells, cohesion problems, complexity issues, size violations, and encapsulation problems with actionable refactoring suggestions.

90

1.05x
Quality

92%

Does it follow best practices?

Impact

79%

1.05x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Evaluation results

90%

41%

Legacy E-Commerce Platform Design Audit

Smell detection with script and JSON output

Criteria
Without context
With context

Uses detect_smells.py

0%

100%

JSON format flag

0%

100%

smell-report.json created

100%

100%

God Class identified

100%

100%

High Coupling identified

30%

100%

Long Method identified

0%

0%

Severity levels used

50%

100%

Critical smells prioritized

100%

100%

God Class refactoring strategy

100%

100%

Coupling refactoring strategy

50%

100%

92%

16%

Systematic Refactoring of a Bloated Order Management Module

Refactoring workflow with before/after verification

Criteria
Without context
With context

Pre-refactor detection run

0%

100%

Post-refactor verification run

0%

100%

Before/after metrics documented

100%

100%

Extract Class applied

100%

100%

Dependency Injection applied

100%

100%

Extract Method applied

100%

100%

God Class threshold respected

100%

100%

Smell count reduced

100%

30%

Critical smells resolved

100%

90%

55%

-45%

Automated Design Quality Gates for a Python Repository

CI/CD integration and pre-commit hooks

Criteria
Without context
With context

Pre-commit uses detect_smells.py

100%

0%

Pre-commit exit on critical

100%

0%

Pre-commit hook file created

100%

0%

CI workflow file created

100%

100%

CI triggers on push and PR

100%

100%

CI workflow runs detect_smells.py

100%

100%

Checkout step included

100%

100%

Source directory targeted

100%

50%

Python used to invoke script

100%

100%

Repository
ArabelaTso/Skills-4-SE
Evaluated
Agent
Claude Code
Model
Claude Sonnet 4.6

Table of Contents

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