style-learner

# Style Learning Skill

Extract and codify writing style from exemplar text for consistent application.

## Approach: Feature Extraction + Exemplar Reference

This skill combines two complementary methods:

1. **Feature Extraction**: Quantifiable style metrics (sentence length, vocabulary complexity, structural patterns)
2. **Exemplar Reference**: Specific passages that demonstrate desired style

Together, these create a comprehensive style profile that can guide content generation and editing.

## Required TodoWrite Items

1. `style-learner:exemplar-collected` - Source texts gathered
2. `style-learner:features-extracted` - Quantitative metrics computed
3. `style-learner:exemplars-selected` - Representative passages identified
4. `style-learner:profile-generated` - Style guide created
5. `style-learner:validation-complete` - Profile tested against new content

## Step 1: Collect Exemplar Text

Gather representative samples of the target style.

**Minimum requirements**:
- At least 1000 words of exemplar text
- Multiple samples preferred (shows consistency)
- Same genre/context as target output

```markdown
## Exemplar Sources

| Source | Word Count | Type |
|--------|------------|------|
| README.md | 850 | Technical |
| blog-post-1.md | 1200 | Narrative |
| api-guide.md | 2100 | Reference |
```

## Step 2: Feature Extraction

Load: `@modules/feature-extraction.md`

### Vocabulary Metrics

| Metric | How to Measure | What It Indicates |
|--------|----------------|-------------------|
| Average word length | chars/word | Complexity level |
| Unique word ratio | unique/total | Vocabulary breadth |
| Jargon density | technical terms/100 words | Audience level |
| Contraction rate | contractions/sentences | Formality |

### Sentence Metrics

| Metric | How to Measure | What It Indicates |
|--------|----------------|-------------------|
| Average length | words/sentence | Complexity |
| Length variance | std dev of lengths | Natural variation |
| Question frequency | que