Metaharness adds adversarial reviews to catch AI reviewer errors

A new tool, Metaharness, uses cross-agent adversarial reviews to detect when AI reviewers produce plausible but incorrect feedback. It routes changes to human reviewers when confidence is low, costs exceed budget, or benchmark results are ambiguous. The approach aims to prevent bogus findings from blocking pull requests and eroding trust in automated review systems.