pdd-multi-review

Multi-round code review applies sequential rule checks, AI review, and cross-validation to systematically identify compliance and logic issues in PRs. This layered workflow increases problem discovery rates across interfaces, data models, and business logic.

Automate code review by triggering a three-stage pipeline on pull requests. The pipeline automatically executes rule checks, AI review, and cross-validation to verify feature implementations, API changes, and data models.

Yes, the code audit workflow standardizes issue tracking by automatically recording problems, assigning severity levels, and generating remediation suggestions. It includes an automated feedback loop to verify fixes and prevent regressions.

Cross-validation serves as the third review round to verify data models and business logic consistency. It operates alongside rule checks and AI review to ensure comprehensive coverage of feature implementations across PRs.

The best way to ensure compliance and prevent regressions is an automated feedback loop that validates remediation against specifications. Orchestrating rule checks, AI review, and cross-validation guarantees issues are tracked and verified before release.