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style-learner
// Learn and extract writing style patterns from exemplar text for consistent
// Learn and extract writing style patterns from exemplar text for consistent
[HINT] Descarga el directorio completo de la habilidad incluyendo SKILL.md y todos los archivos relacionados
| name | style-learner |
| description | Learn and extract writing style patterns from exemplar text for consistent |
| version | 1.8.2 |
| triggers | ["style","voice","tone","exemplar","learning","consistency"] |
| metadata | {"openclaw":{"homepage":"https://github.com/athola/claude-night-market/tree/master/plugins/scribe","emoji":"✍️","requires":{"config":["night-market.scribe:shared","night-market.scribe:slop-detector"]}}} |
| source | claude-night-market |
| source_plugin | scribe |
Night Market Skill — ported from claude-night-market/scribe. For the full experience with agents, hooks, and commands, install the Claude Code plugin.
Extract and codify writing style from exemplar text for consistent application.
This skill combines two complementary methods:
Together, these create a comprehensive style profile that can guide content generation and editing.
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: