What problem does it solve? AI-generated outputs like code reviews, plans, and briefs can contain blind spots, unsupported claims, or missed methodology steps that go unnoticed without a second pass. This Skill challenges a prior skill output by orchestrating an attacker, a defender, and a judge so you can see which conclusions actually hold up under evidence-based scrutiny. ## Core Features & Use Cases - Adversarial multi-agent debate: Spawns Gilfoyle (attacker) and Dinesh (defender) in parallel, then a neutral Judge who audits citations, classifies findings as CONFIRMED, REFUTED, PARTIAL, or CONCEDED, and issues a final verdict. - Hallucination guardrails: Enforces a strict citation boundary — debaters may only cite inline source material you provide, and the Judge flags any hallucinated citation before weighing evidence. - Convergence-controlled rounds: Runs up to 3 rounds with explicit convergence rules, then delivers a structured verdict covering confirmed gaps, defended points, unresolved disputes, and methodology gaps. - Use Case: After running a PR review skill, invoke the debate on the review report with the actual diff pasted inline to discover which findings were wrong, which were missed, and whether the reviewer followed its own checklist. ## Quick Start Debate the most recent code review output using the actual PR diff as source material and show me the final verdict.