OPEN DATA SCHEMA · VERSION 1.0 · 2026-07-19

Publish AI coding evidence others can audit.

This open kit connects tasks selected before testing, every run observed during testing, and a bounded case summary. The files are blank by design: we do not present synthetic results as original research.

Reusable research assets

From preregistration to a publishable case.

CC0-licensed schemas make independent replication and comparison easier. Blank means unavailable; zero means measured zero. Cite the repository's versioned citation metadata when publishing results.

01 / CSV

Preregister tasks

Freeze the commit, acceptance criteria, allowed files, checks, security constraints, and timeout before testing.

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02 / CSV

Record every attempt

Keep accepted and rejected runs with versions, time, review effort, usage, cost, retries, and failure category.

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03 / CSV

Publish a bounded case

Report the evaluation window, sample size, baseline, decision, limitations, evidence, and publication consent.

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Minimum evidence standard

A case is evidence only when its boundaries remain visible.

Publish exact versions and sample counts, retain failures, link supporting artifacts, disclose conflicts, and obtain consent before naming an organization.

No cherry-picking

Every attempt remains in the run file, including setup, model, test, review, and policy failures.

No anonymous endorsement

An anonymized pilot can describe measured conditions, but must not imply customer approval.

No universal leaderboard

Results support decisions within the tested repository, model, environment, and time window.

CONTRIBUTE EVIDENCE

Run the protocol and publish a versioned dataset.