Open Code Review – Multi-agent code review (Local First but CI-ready) (github.com)

Open Code Review (OCR) has introduced a new multi-agent code review system designed specifically for AI coding assistants, mimicking the collaborative and thorough nature of traditional engineering reviews. Unlike standard AI reviews that provide a single perspective, OCR leverages a team of specialized reviewer personas—including two Principal reviewers focusing on architecture, two Quality reviewers examining code style, and an optional Security reviewer—each analyzing the code independently before engaging in a discourse to challenge and connect their findings. This approach aims to surface new insights and ensure a more comprehensive evaluation of code changes. This development is significant for the AI/ML community as it enhances code review processes by providing a redundancy that is often absent in single-pass analyses. By incorporating a structured eight-phase workflow that includes context discovery, analysis, and synthesis, OCR ensures that feedback is not only prioritized but also aligned with specific project standards and requirements. The system supports various AI tools and configurations, making it adaptable for different development environments, thus advancing the efficiency and effectiveness of AI-assisted code reviews in software development.