The Field Kit

For new thinkers and lost innovators: everything needed to do serious, checkable work with AI — and to be taken seriously for it.

Download the kit (zip, ~15 KB) →

Three steps to working under the standard

1. Open the kit and paste EARNED TRUST PROTOCOL — paste this into any AI.md into whatever AI you use. The protocol instructs it to hold you to the method — including the two steps everyone skips: attacking your own work, and verifying every source yourself.

2. Work. The evidence folder builds itself around you: drafts, transcripts, critiques and your rulings on them, source checks — with a session manifest that updates as you go, not from memory afterward.

3. Before you publish, seal the record: one command writes a fingerprint manifest so anyone, years later, can prove your evidence unaltered. Deposit, disclose, done.

What's inside

EARNED TRUST PROTOCOL — paste this into any AI.md

The whole method in one file any AI can follow: eight steps, the one rule, the honest limits.

templates/00 INDEX — session manifest (template).md

The first page of your evidence: who, what, which services, which models, when.

make_evidence_folder.py

One command builds the standard evidence folder for a new work. Refuses to overwrite — evidence folders are never overwritten.

log_session.py

One command per session appends the manifest row — date and numbering automatic, model defaults to "not exposed" because guessing is worse than honesty.

seal_record.py

Seals the folder into a SHA-256 manifest; verifies any later copy against it, naming exactly what changed. Publish the manifest with your work.

The scripts need only Python 3 — no installs, no accounts, no network. Windows, Mac, Linux. Everything works without them too: the protocol and templates are plain text, usable with nothing but a chat window and a folder.

Then check anyone — including us

The Earned Trust Reader verifies any published file against its fingerprints — free, in your browser, forever.

Earned Trust Field Kit · protocol and templates CC BY 4.0 · tools AGPL-3.0-or-later · based on the Earned Trust (AIast) standard by William Stafford, ADN, LI-AIast5 · share this page: earnedtrust.org/kit