What problem does it solve?
It exposes gaps, contradictions, missing sections, unrealistic claims, and fragile architecture/metrics in PRDs, architecture docs, SOWs, and technical specs before they become expensive to fix.
Core Features & Use Cases
- Dual-agent adversarial review: Runs independent reviewers (Claude + Codex) and synthesises results into a single report.
- Evidence-driven findings: Produces prioritized P0–P3 findings with required fields, rationale, and suggested fixes.
- Structured outputs for actionability: Generates a full internal report, a send-ready author brief, and a forward-compatible JSON artifact.
- Proof Burden Mode for AI-ish documents: Automatically forces explicit answers on evaluation methods, fallbacks, human approvals, trust boundaries, and cost/latency when AI-generation signals appear.
- Independent Codex fact-checking pass: Verifies the opponent’s claims independently and surfaces disagreements.
Quick Start
Use adversarial-review to review the currently-open document by asking for a dual-agent adversarial critique that outputs a prioritized, evidence-backed report and an author brief.