audit-code

You can automate code audits against a project plan by running a multi-pass static analysis that evaluates structure, wiring, backend, frontend, and sustainability to detect drift and enforce plan adherence before shipping.

Ledger-driven suppression reduces PR review noise by tracking previously identified issues across up to six audit rounds, capturing technical debt, and applying convergence checks to filter redundant findings.

Yes, you can validate incremental PR changes by orchestrating multi-pass audits with GPT and enforcing a mandatory final cross-model review using Gemini to catch implementation drift and surface actionable findings.

The best way to enforce plan compliance across repositories is to trigger scope-based audit commands against specific plan-file paths, applying convergence rules and a final Gemini review gate to ensure implementation aligns with the plan.

Your code audit loop requires a final cross-model review to provide an independent verification gate, ensuring that multi-pass static analysis findings are validated and implementation drift is caught before shipping.

When running up to six rounds of plan validation, convergence checks are applied to determine if the audit loop has stabilized, meaning further rounds may be suppressed if incremental PR changes no longer produce new actionable findings.