Does your writing sound like a person?
Paste a paragraph. The meter scores how close it reads to unedited human prose - the stock vocabulary, the reflexive “not X, but Y,” and the flat, even cadence that gives machine text away. It grew out of a tool I built to catch my own site drifting into that voice.
Name the subject and its own words stop counting against you - a post about a harness says “harness” because that’s the topic, not because a model reached for it.
This is a voice-fit meter, not an AI detector. It does not try to answer whether a machine wrote your text, which is both unanswerable on modern models and beside the point. It measures something smaller and more useful: how close your writing is to the way unedited humans actually write. It looks for the tells. Stock surge vocabulary. The reflexive "not X, but Y". Connective scaffolding like moreover and ultimately. And, underneath the words, the deeper signal the research points to: burstiness, the natural swing between long and short sentences that models tend to iron flat. Everything runs in your browser. Nothing you paste is sent anywhere or stored. The score is a mirror, not a verdict, and it is honest only inside those limits.
Keep reading
Why the meter calibrates on pre-model writing, and where it is honestly wrong.
All the browser tools →The rest of the small, private-by-default tools that run in your browser.
The AI benchmarks →The same show-your-work habit, pointed at how the models themselves score.
The reading lists →Another public, content-as-code corner of the site.