style-clone

name	style-clone
description	Analyze and match the author's unique writing voice
author	AuthorAgent
version	1.1.0
triggers	["learn my style","match my voice","style check","voice profile","analyze my writing","sound like me"]
permissions	["file:read","file:write"]

Style Clone Skill

Analyze the author's writing to create a quantitative Voice Profile, then use it to match their style.

Use the gateway's analyzer — do NOT hand-roll a freeform analysis. AuthorAgent already ships a 47-marker voice analyzer as a first-class service (StyleCloneService). It is deterministic, cheap (no AI call), and returns a structured StyleProfile plus an AI system prompt you can apply to every drafting/revision task. This skill's job is to CALL that service and save the result — not to re-describe the analysis in prose. A parallel markdown-only pass would drift from the real analyzer and produce a worse, unquantified profile.

How to run it

On raw text (5,000+ words → more is better)

Call the analyzer endpoint:

POST /api/style-clone/analyze
Content-Type: application/json

{ "text": "<the author's writing sample>", "source": "manual-paste" }

Response: { "profile": <StyleProfile> } — a 47-marker fingerprint across five axes (sentence structure, vocabulary, punctuation, syntax, voice) plus a ready-to-use systemPrompt for maintaining voice.

On a whole project's completed chapters

POST /api/projects/:id/style-clone

The service gathers the project's completed writing-phase chapters, concatenates them, and analyzes the combined text. Response is the same { "profile": ... }.

After analysis — persist the profile

1. Save the returned profile's systemPrompt (and key markers) to workspace/soul/VOICE-PROFILE.md so future creative_writing / revision tasks inherit the voice.
2. Because the analyzer is local and fast, re-run it on new chapters to detect voice drift — compare the fresh markers against the saved profile.

Style check (drift detection)

When asked to check new text against the author's style:

1. Analyze the new text via POST /api/style-clone/analyze.
2. Diff its markers against the saved VOICE-PROFILE.md baseline.
3. Report per axis: ✅ matches, ⚠️ minor drift, ❌ significant departure.
4. Offer specific suggestions (never rewrite without permission).

The 47 markers (what the service measures)

• Sentence structure — length, variance, rhythm, fragment rate, sentences/paragraph.
• Vocabulary — type-token ratio, rare-word rate, Latinate vs Germanic, Flesch reading ease, repetition index.
• Punctuation — em-dash / semicolon / colon / ellipsis / comma rates, etc.
• Syntax — passive voice, compound/subordinate rates, participial openers, nominalization.
• Voice — contraction, filter-word, adverb, dialogue density, sensory density, hedging, intensifiers, tense mix.

Commands

• "Learn my style from [text/file]" — run POST /api/style-clone/analyze and save the profile to VOICE-PROFILE.md.
• "Check this against my style" — analyze the new text and diff against the saved profile.
• "Show my voice profile" — display the current VOICE-PROFILE.md.