What problem does it solve? Manual code audits miss entire bug classes because a single reviewer applies one perspective. This Skill runs parallel research lenses across correctness, security, performance, maintainability, and reliability, then consolidates everything into one ranked, evidence-capped findings report — without touching your code. ## Core Features & Use Cases - Two depth modes: depth:standard runs a quick single-wave scan across five lenses; depth:deep runs a pre-PR multi-wave audit with blast-radius tiering, STRIDE trust-boundary analysis, three blinded adversarial lenses, and rollback rehearsal that blocks on missing down-migrations. - Evidence-tiered severity capping: Findings are capped by evidence quality (T0 proven through T3 advisory), so a heuristic hunch can never masquerade as a Critical. - Blind-spot detection: Wave B adversarial researchers see only the raw diff, breaking confirmation bias and surfacing gaps context-aware analysis missed. - Use Case: Before opening a PR on a branch touching auth and database migrations, run a deep audit to get a consolidated findings report, a rollback plan with BLOCKING findings for missing down-migrations, and a persistent ledger entry tracking unresolved blockers. ## Quick Start Ask the AI to run a deep audit on the current branch before opening the pull request.