Blog Style - Writing Style Learning

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.

Commands

Command	Purpose
/blog style learn <paths>	Analyze sample posts and generate a voice profile

Learn Workflow

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.

Profile Fields

The learner aggregates the existing blog analyzer across each sample post:

• Sentence length mean and median
• Sentence length burstiness as corpus variance
• Vocabulary richness as type-token ratio
• Transition-word sentence rate
• Passive-voice sentence rate
• AI trigger words per 1,000 words as a baseline to preserve or avoid
• Paragraph-length distribution
• First-person usage rate
• Heading-as-question ratio
• Signature phrases from top 2-gram and 3-gram content phrases with stopwords removed
• Tone descriptors derived from the measured metrics

Consuming the Profile

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: