reality-checker

To validate automated agent outputs against evidence, you can use an evidence-first validation gate that requires concrete artifacts like test logs or API responses for each claim. It checks provided proof and refuses to guess when evidence is missing.

Structured verdict validation for QA gates works by emitting a machine-readable JSON verdict containing the final verdict, grade, verified findings, gaps, conditions, and a summary. This structure allows downstream automation to programmatically assess certification status.

The best way to prevent hallucinations in headless agent workflows is to apply a skepticism gate that demands traceable artifacts, such as file outputs or API responses, before accepting any positive claim as complete.

Yes, you can use evidence-based validation to certify automated patch proposals in CI. By running it as the final step in an autonomous workflow, it validates produced outputs against provided evidence and returns a structured JSON verdict.

When evidence is missing during output validation, the system refuses to guess or accept the claim. Instead, it forces explicit gaps in the structured JSON verdict, ensuring that unverified or fabricated claims are never marked as complete.

Evidence-first validation for autonomous workflows is a certification mechanism that demands concrete artifacts like test results or API responses for each positive claim before marking work as complete, reducing hallucinations and ensuring traceability.