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Extracts writing style patterns from exemplar text into a reusable profile. Use when creating a style guide or learning a specific author's voice.
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npx skills add https://github.com/athola/claude-night-market --skill style-learnerコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
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SKILL.md を表示中
SOC 職業分類に基づく
| name | style-learner |
| description | Extracts writing style patterns from exemplar text into a reusable profile. Use when creating a style guide or learning a specific author's voice. |
| globs | **/*.md |
| alwaysApply | false |
| category | writing-quality |
| tags | ["style","voice","tone","exemplar","learning","consistency"] |
| tools | [] |
| complexity | medium |
| model_hint | standard |
| estimated_tokens | 1800 |
| progressive_loading | true |
| modules | ["modules/feature-extraction.md","modules/exemplar-reference.md","modules/style-application.md"] |
| dependencies | ["scribe:slop-detector"] |
A style profile is metrics plus exemplars. Either alone is too weak to reproduce a voice.
Extract style from exemplar text and codify it as a profile
that downstream skills (scribe:doc-generator,
scribe:voice-generate) can apply consistently.
scribe:voice-extract)scribe:voice-review)The skill combines two methods because each fails alone:
Together they form a profile precise enough to score new text and rich enough to guide rewrites. Metrics catch what exemplars miss. Exemplars carry what metrics flatten.
style-learner:exemplar-collected - Source texts gatheredstyle-learner:features-extracted - Quantitative metrics computedstyle-learner:exemplars-selected - Representative passages identifiedstyle-learner:profile-generated - Style guide createdstyle-learner:validation-complete - Profile tested against new contentGather representative samples of the target style.
Minimum requirements:
## Exemplar Sources
| Source | Word Count | Type |
|--------|------------|------|
| README.md | 850 | Technical |
| blog-post-1.md | 1200 | Narrative |
| api-guide.md | 2100 | Reference |
Load: @modules/feature-extraction.md
| 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 |
| Metric | How to Measure | What It Indicates |
|---|---|---|
| Average length | words/sentence | Complexity |
| Length variance | std dev of lengths | Natural variation |
| Question frequency | questions/100 sentences | Engagement style |
| Fragment usage | fragments/100 sentences | Stylistic punch |
| Metric | How to Measure | What It Indicates |
|---|---|---|
| Paragraph length | sentences/paragraph | Density |
| List ratio | bullet lines/total lines | Format preference |
| Header depth | max header level | Organization style |
| Code block frequency | code blocks/1000 words | Technical density |
| Metric | Normal Range | Style Indicator |
|---|---|---|
| Em dash rate | 0-3/1000 words | Parenthetical style |
| Semicolon rate | 0-2/1000 words | Formal complexity |
| Exclamation rate | 0-1/1000 words | Enthusiasm level |
| Ellipsis rate | 0-1/1000 words | Trailing thought style |
Load: @modules/exemplar-reference.md
Select 3-5 passages (50-150 words each) that best represent the target style.
Selection criteria:
### Exemplar 1: [Label]
**Source**: [filename, lines X-Y]
**Demonstrates**: [what aspect of style]
> [Quoted passage]
**Key characteristics**:
- [Observation 1]
- [Observation 2]
Combine extracted features and exemplars into a usable style guide.
# Style Profile: [Name]
# Generated: [Date]
# Exemplar sources: [List]
voice:
tone: [professional/casual/academic/conversational]
perspective: [first-person/third-person/second-person]
formality: [formal/neutral/informal]
vocabulary:
average_word_length: X.X
jargon_level: [none/light/moderate/heavy]
contractions: [avoid/occasional/frequent]
preferred_terms:
- "use" over "utilize"
- "help" over "facilitate"
avoided_terms:
- delve
- leverage
- comprehensive
sentences:
average_length: XX words
length_variance: [low/medium/high]
fragments_allowed: [yes/no/sparingly]
questions_used: [yes/no/sparingly]
structure:
paragraphs: [short/medium/long] (X-Y sentences)
lists: [prefer prose/balanced/prefer lists]
headers: [descriptive/terse/question-style]
punctuation:
em_dashes: [avoid/sparingly/freely]
semicolons: [avoid/sparingly/freely]
oxford_comma: [yes/no]
exemplars:
- label: "[Exemplar 1 label]"
text: |
[Quoted passage]
- label: "[Exemplar 2 label]"
text: |
[Quoted passage]
anti_patterns:
- [Pattern to avoid 1]
- [Pattern to avoid 2]
Test the profile against new content:
When generating new content, reference the profile:
Generate [content type] following the style profile:
- Voice: [from profile]
- Sentence length: target ~[X] words, vary between [Y-Z]
- Use exemplar passage as tone reference:
> [exemplar quote]
- Avoid: [anti-patterns from profile]
modules/style-application.md for applying learned styles to new contentAfter generating content, run slop-detector to verify: