
hiro-inagawa/write-like-me
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Measures how you write and builds a voice profile, then enforces it with a deterministic checker: em dashes, filler, hedges, and AI tells are caught by code, not by asking the model to be careful.
概要
Clone the repo and run the checker on any Markdown or text file. No profile, no installs, Python 3.8+ only: python scripts/voice_check.py your-draft.md It prints every em dash, filler phrase, hedge, and AI tell with a line number and a fix, then a verdict. Building your own voice profile comes after, if you want it. A Claude Code skill that analyzes how you write and generates a personalized voice profile for writing and revising prose. It uses linguistic and psychological measurement methods rather than subjective descriptions to capture your actual style from a corpus of your own writing. The skill now ships a deterministic checker. After a draft is written, python scripts/voice_check.py draft.md --profile voices/ /profile.json reports every violation with a line number and a fix, and exits non-zero on a hard rule, so the voice is enforced by code instead of by asking the model to be careful. Each voice also gets a machine-readable profile.
README
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Try it in ten seconds. Clone the repo and run the checker on any Markdown or text file. No profile, no installs, Python 3.8+ only:
python scripts/voice_check.py your-draft.md
It prints every em dash, filler phrase, hedge, and AI tell with a line number and a fix, then a verdict. Building your own voice profile comes after, if you want it.
A Claude Code skill that analyzes how you write and generates a personalized voice profile for writing and revising prose. It uses linguistic and psychological measurement methods rather than subjective descriptions to capture your actual style from a corpus of your own writing.
New in v2 (September 2026). The skill now ships a deterministic checker. After a draft is written, python scripts/voice_check.py draft.md --profile voices//profile.json reports every violation with a line number and a fix, and exits non-zero on a hard rule, so the voice is enforced by code instead of by asking the model to be careful. Each voice also gets a machine-readable profile.json and a golden test set, and an eval harness gates every rule change. Details are in the sections “Checking a draft” and “Evaluating the checker” below, and in CHANGELOG.md.
The same skill supports multiple voices. You can build one from your primary writing register, another from a different register, and another from an author whose style you want to study, and switch between them within the same skill.
HOW IT WORKS
The skill has two modes.
When no voice is built yet, it runs a 7-stage analysis that discovers your corpus, extracts and filters the text, measures approximately 50 stylometric features per register, mines rules from the measurements and any existing style notes, pauses for your review, generates the voice profile, and runs a held-out verification test.
When a voice is already built, it reads your profile and writes or revises prose in that voice. The universal anti-AI baseline (references/00-universal-baseline.md) is always active, on top of whatever your profile specifies.
GETTING STARTED
Step 1. Gather your writing corpus.
Create a folder and put your writing in it. Good sources:
- Export your Claude conversation history: Settings → Data Controls → Export Data, then unzip the file into the folder
- Emails you have written
- Essays, articles, blog posts, papers
- Notes, journals, or any other text in your own voice
Aim for at least 20,000 words. 50,000 or more gives more reliable results.
Step 2. Run the skill.
推奨ツール
別のキーワードを試すか、フィルタを外してください。
インストール
npx skillfish add hiro-inagawa/write-like-me