---
name: code-smell-detector-e819a3f18211
description: Automated detection of code smells and anti-patterns to identify refactoring opportunities
allowed-tools: ["Bash", "Read", "Write", "Grep", "Glob", "Edit"]
graph:
  domains: [domain:software-engineering]
  specializations: [specialization:code-migration-modernization]
  skillAreas: [skill-area:code-analysis-linting, skill-area:dead-code-elimination]
  roles: [role:backend-engineer, role:tech-lead]
  workflows: [workflow:technical-debt-reduction]
  topics: [topic:refactoring]
---

# Code Smell Detector Skill

Automated detection of code smells, anti-patterns, and design issues that indicate deeper problems in the codebase. This skill identifies refactoring opportunities and prioritizes them by impact.

## Purpose

Enable systematic detection of code smells for:
- Refactoring prioritization
- Technical debt identification
- Code quality improvement
- Migration preparation
- Design pattern violations

## Capabilities

### 1. Long Method Detection
- Identify methods exceeding line thresholds
- Analyze parameter counts
- Detect high cyclomatic complexity
- Suggest extraction candidates

### 2. Large Class Identification
- Detect classes with too many responsibilities
- Identify god classes
- Analyze class cohesion
- Suggest decomposition strategies

### 3. Feature Envy Analysis
- Find methods using other classes' data excessively
- Identify misplaced functionality
- Suggest method relocation
- Map cross-class dependencies

### 4. Primitive Obsession Detection
- Identify overuse of primitives
- Find missing value objects
- Detect stringly-typed code
- Suggest domain type extraction

### 5. Parallel Inheritance Hierarchy
- Detect mirrored class hierarchies
- Identify inheritance coupling
- Suggest hierarchy consolidation
- Map inheritance relationships

### 6. Shotgun Surgery Detection
- Identify changes requiring multiple file edits
- Detect scattered functionality
- Map change propagation patterns
- Suggest consolidation points

### 7. God Class Identification
- Detect classes doing too much
- Analyze responsibility distribution
- Calculate lack of cohesion metrics
- Suggest single responsibility refactoring

## Tool Integrations

| Tool | Purpose | Integration Method |
|------|---------|-------------------|
| SonarQube | Code smell detection | MCP Server / API |
| PMD | Java smell detection | CLI |
| IntelliJ IDEA | IDE-based analysis | CLI / Export |
| Designite | Design smell detection | CLI |
| ast-grep | Pattern-based detection | MCP Server / CLI |
| ESLint | JavaScript smell rules | CLI |

## Output Schema

```json
{
  "analysisId": "string",
  "timestamp": "ISO8601",
  "target": {
    "path": "string",
    "filesAnalyzed": "number"
  },
  "smells": [
    {
      "type": "string",
      "severity": "high|medium|low",
      "file": "string",
      "line": "number",
      "element": "string",
      "description": "string",
      "metrics": {},
      "refactoringSuggestion": "string",
      "estimatedEffort": "string"
    }
  ],
  "summary": {
    "totalSmells": "number",
    "byType": {},
    "bySeverity": {},
    "hotspots": []
  }
}
```

## Integration with Migration Processes

- **code-refactoring**: Primary smell identification
- **technical-debt-remediation**: Debt quantification
- **legacy-codebase-assessment**: Quality assessment

## Related Skills

- `static-code-analyzer`: Broader quality analysis
- `refactoring-assistant`: Smell remediation
- `dead-code-eliminator`: Unused code removal

## Related Agents

- `code-transformation-executor`: Executes refactorings
- `technical-debt-auditor`: Prioritizes debt remediation


---
Source attribution: a5c-ai
Original project: https://github.com/a5c-ai/babysitter
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 Gabriel Moreira

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: a5c-ai
Original project: https://github.com/a5c-ai/babysitter
Attribution basis: Upstream repository explicitly recorded in package mirror path

Fields of work: Development & Engineering, Product Management
Roles: Backend Developer, Data Engineer, DevOps / SRE, QA / Test Engineer, Technical Product Manager
Specialties: Backend, Testing
Tools: Designite, Eslint, Pmd, Sonarqube, Ast Grep, Intellij Idea
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 4850006bd5b5872a7a805625ed50b690aaeb05dd019a7ac6d0c14d9f7092ae77