whystrohm/digital-twin-of-yourself
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Reverse-engineer how you think, talk, and make decisions — then turn it into a stress-tested AI System Prompt. Works on any LLM. Full pipeline with Claude Code.
概要
*Every number and sentence in this film is the tool's real output on made-up sample writing. Rebuilt by tools/demo/make_demo.py.* The AI does the judgment calls. Everything that can be counted or checked is done by code: it runs on your machine, gives the same answer every time, and strips emails, phone numbers and money amounts before anything is saved. You need Python 3.9 or newer. Nothing to install. Nothing leaves your machine. Step 3 fails on purpose: the draft hedges, uses a dash, and runs one sentence to 37 words. examples/drafts/supplier-update.fixed.md passes. To run it on your own writing, copy your own .md or .txt files into one folder, scrub them (see Safety), and point --corpus at that folder. The extraction itself is a prompt. How deep it goes depends on what the model can read. 1. Copy EXTRACTION_PROMPT.md into a new chat. 2. Paste your writing at the bottom. Five pages or more. Your normal writing, not your best. 3.
README
以下は原文 README の抜粋です。原文を見る。
Digital Twin of Yourself
See how you actually write. Then check every draft, yours or an AI’s, against it.
Every number and sentence in this film is the tool’s real output on made-up sample writing. Rebuilt by tools/demo/make_demo.py.
What you get
| You get | What it is |
|---|---|
| A report on your writing | One page, opens in any browser. How long your sentences run, how often you hedge, which phrases you lean on, which documents sound unlike the rest, and the exact lines to fix. |
| A twin any AI can use | A System Prompt that captures your voice and how you decide, built from your writing plus up to five questions about what the writing does not show. |
| A checker for every draft | Rules code can check, line by line. Run it on a draft, or let it check every pull request so off-voice copy is caught before it ships. |
| A twin that keeps up | Show it drafts next to what you actually sent. It proposes new rules from your edits. You approve each one, and every change is logged. |
The AI does the judgment calls. Everything that can be counted or checked is done by code: it runs on your machine, gives the same answer every time, and strips emails, phone numbers and money amounts before anything is saved.
Built by WhyStrohm.
Try it in three minutes
You need Python 3.9 or newer. Nothing to install. Nothing leaves your machine.
git clone https://github.com/whystrohm/digital-twin-of-yourself.git
cd digital-twin-of-yourself
# 1. Measure a folder of writing (here, the made-up sample)
python3 scripts/twin_scan.py --corpus examples/sample-corpus --out patterns.json
# 2. Build the report and open it
python3 scripts/twin_report.py patterns.json --out twin-report.html
open twin-report.html # macOS; use xdg-open on Linux
# 3. Check a draft against a twin's rules
python3 scripts/twin_check.py --rules twins/example/twin.rules.json examples/drafts/supplier-update.md
Step 3 fails on purpose: the draft hedges, uses a dash, and runs one sentence to 37 words. examples/drafts/supplier-update.fixed.md passes.
To run it on your own writing, copy your own .md or .txt files into one folder, scrub them (see Safety), and point --corpus at that folder.
The layers
The extraction itself is a prompt. How deep it goes depends on what the model can read.
| Layer | Where | What it reads | Who measures |
|---|---|---|---|
| 1 | Any LLM (ChatGPT, Gemini, Claude) | Writing you paste in | The model estimates |
| 2 | Claude with memory on | Your conversation history | The model estimates |
推奨ツール
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インストール
npx skillfish add whystrohm/digital-twin-of-yourself