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score-style

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Score migrated code against style guidelines and best practices. Evaluates code quality independent of functional correctness.

General

What this skill does


Evaluate migrated code against style guidelines and best practices.

This skill scores code quality aspects that are independent of functional correctness — focusing on readability, maintainability, and adherence to conventions.

## Default Scoring Criteria

Unless a custom rubric is provided, score on these attributes (1-5 scale):

### Naming Conventions (1-5)
- 1: Inconsistent or meaningless names
- 3: Mostly follows conventions, some issues
- 5: Clear, consistent, idiomatic names

### Code Organization (1-5)
- 1: Monolithic, hard to navigate
- 3: Some structure, could be cleaner
- 5: Well-organized, logical structure

### Error Handling (1-5)
- 1: Missing or swallowed exceptions
- 3: Basic error handling present
- 5: Comprehensive, appropriate error handling

### Documentation (1-5)
- 1: No documentation
- 3: Some documentation, inconsistent
- 5: Thorough, helpful documentation

### Idiomaticity (1-5)
- 1: Non-idiomatic, smells like translated code
- 3: Mostly idiomatic, some foreign patterns
- 5: Fully idiomatic, natural code

## Output Format

Save scores as a JSON file:

```json
{
  "target_file_a.java": {
    "naming_conventions": 4,
    "code_organization": 3,
    "error_handling": 5,
    "documentation": 4,
    "idiomaticity": 4,
    "justification": "Good naming and error handling. Some methods could be extracted for better organization."
  }
}
```

## Custom Rubric

If a custom rubric is provided, use its attributes and scoring criteria instead of the defaults. The rubric should define:
- Attribute names
- Score meanings for each level (1-5)
- Examples of good/bad code for each attribute

## Evaluation Guidelines

### What to Look For

**Positive indicators:**
- Consistent naming (camelCase for Java, snake_case for Python)
- Appropriate class/method sizes
- Single responsibility principle followed
- Meaningful comments (not obvious ones)
- Standard library usage over custom implementations
- Defensive programming practices

**Negative indicators:**
- Literal translations (COBOL-style Java)
- God classes or methods
- Magic numbers
- Excessive comments or no comments
- Reinvented wheels
- Swallowed exceptions
- Hardcoded values

### Language-Specific Considerations

**Java:**
- Streams vs. for loops (both acceptable, but be consistent)
- Optional vs. null checks
- Record types for data classes
- Builder pattern for complex objects

**Python:**
- Type hints
- List comprehensions
- Context managers
- Pythonic idioms

## Incremental Scoring

If a score file already exists, update it with new scores rather than replacing it entirely.

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