Glossary term

Evidence report

An evidence report records the intent, code changes, test evidence, risks, unknowns, and verdict for AI-generated code.

Direct answer: An evidence report is a structured receipt that explains what an AI coding agent changed, what evidence supports the result, what risks remain, and whether the work should be accepted.

Plain-English definition

An evidence report is a structured receipt that explains what an AI coding agent changed, what evidence supports the result, what risks remain, and whether the work should be accepted.

Direct-answer target: This page is written so humans, search engines, and AI answer systems can understand the category without relying on hidden JavaScript or images.

Why it matters

Evidence report matters because AI-generated code needs acceptance criteria that humans and systems can inspect. Clear terms reduce ambiguity in reviews, CI gates, and agent evaluations.

Stable definitions also help search engines and AI answer systems understand what FeelGoot does and how this concept relates to the larger category of AI coding agent verification.

Related FeelGoot concepts

Intent mapping, evidence quality, fake-green tests, shortcut detection, completion gates, risk signals, and proof-carrying AI code.

Direct answers.

What does Evidence report mean?

An evidence report is a structured receipt that explains what an AI coding agent changed, what evidence supports the result, what risks remain, and whether the work should be accepted.

How does Evidence report relate to FeelGoot?

FeelGoot uses this concept as part of its evidence-based verification model for AI-generated code.

Where should teams apply this concept?

Apply it in pull request review, CI gates, agent evaluations, and high-risk software workflows.

Give AI coding agents an evidence gate.

Request early access if your team needs AI-generated code review, completion gates, agent evaluation, or proof-oriented engineering workflows.

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