#Methodology

For a month, AI fact-check agents worked through seven books and two websites with a search box. When a search came back empty, they cut, hedged or de-quoted the sentence, wrote it into a registry so it could not return, and graded the build READY. The receipts, and the gate that now refuses any cut without proof.

The fake company in your evaluation is a real registered domain with a real owner. Check it before an agent does. Runs in your browser; nothing is sent anywhere.

Build a portable evidence receipt from any page — claim, actor, source, archive, tier — and export it as JSON the capture tools can ingest. A bookmarklet feeds it, not a browser extension. Runs in your browser; nothing is sent anywhere.

Paste any passage. The scanner surfaces its casual capture — the smuggled voice and smuggled judgment a writer or a model leaves behind — and tells you which loaded words are attributed to a source and which are asserted as the author’s own neutral voice. Runs in your browser; nothing is sent anywhere.

Anyone who has played ranked knows the difference between the casual lobby and the ladder. Most bias arguments are stuck in casual. The capture that matters is ranked — deliberate, resourced, climbing — and it is the one you can actually measure.

In May 2026, while preparing two manuscripts about hacker culture and adversarial AI behavior, the author’s AI editorial assistant refused to read several chapters. Then a second assistant blocked the workaround. The book is about safety infrastructure becoming a control grid. The book was written through one — and this is the working method that produced: route the refusal, split the labor between models, and lint the machine’s smuggled judgment.