Pricing

Billable trust

Show clients your AI work got measurably better.

Before-and-after proof reports with scores, evidence, and version hashes you can hand to a stakeholder. Make "we improved it" a document, not a claim.

PROOF REPORT · sample

code-review skill

v3 · #a1f community

54

88

The deliverable

Reproducible evidence, not a claim.

A proof report is the artifact you hand over: score delta by dimension, the evidence behind each mark, and a version hash anyone can re-run. It sells reproducible evidence — never a certification. Sample shown below.

code-review skill

hash #a1f · re-runnable

Objective clarity

2/5

5/5

Output specification

2/5

4/5

Evaluation criteria

1/5

4/5

Evidence: v1 left “good” undefined; v2 adds an output contract and a stop rule. The eval case that v1 failed now passes.

What is in the report

A document, not a claim.

A proof report is the artifact you hand a stakeholder. It stands on its own and survives scrutiny because anyone can re-run it — the value is reproducible evidence, never a badge of authority.

Score delta by dimension

Before and after on each rubric dimension, so "better" is specific rather than a single headline number.

Evidence behind every mark

The finding that drove each score and the eval case that demonstrates the behaviour change.

A version hash

The exact artifact is identifiable, so the report points at something reproducible, not a moving target.

Re-runnable, not certified

We sell reproducible evidence — a client can run the same check and get the same result. We deliberately do not call it "certified."

FAQ

Answers before you start.

A before-and-after for one instruction: the rubric score delta broken down by dimension, the evidence behind each finding, the eval case that demonstrates the behaviour change, and a version hash so the exact artifact is identifiable. A document a stakeholder can read, not a claim.

Know which instructions are ready to run.

Generate a proof report
Newsletter

Follow the review loop as it ships.

Notes on AI artifact testing, rubr_flow conversion, evals, and proof reports.