Learn author writing style from 5 to 10 existing blog posts and generate a voice profile for /blog style learn, VOICE.md, blog-persona, and blog-write when users ask to infer tone, analyze author voice, learn style, or build a writing baseline.
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Learn an author voice profile from existing posts, then use it as a baseline for VOICE.md, blog-persona, and blog-write. The profile captures measurable style signals so future drafts can preserve the author's cadence, vocabulary, and tone.
| Command | Purpose |
|---|---|
/blog style learn <paths> | Analyze sample posts and generate a voice profile |
Use 5 to 10 representative posts from the same author, brand, or editorial voice. Accept individual markdown files, MDX files, text files, or a directory containing posts.
Run the local learner:
python3 scripts/style_learn.py <paths> --format markdown
For machine-readable output:
python3 scripts/style_learn.py <paths> --format json --output voice-profile.json
For a VOICE.md-ready block:
python3 scripts/style_learn.py <paths> --format markdown --output VOICE.md
If fewer than the requested minimum sample count is supplied, warn and continue. The default minimum is 5 posts.
The learner aggregates the existing blog analyzer across each sample post:
Drop the markdown block into project VOICE.md when the goal is durable
project context. Blog-write can use the style baselines as drafting targets:
Feed the JSON output into blog-persona when a structured persona should be created or updated. Map the learned values to persona sentence length, passive voice, readability, vocabulary, and tone settings.
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