English

RepoReviewer: A Local-First Multi-Agent Architecture for Repository-Level Code Review

Software Engineering 2026-03-18 v1 Artificial Intelligence

Abstract

Repository-level code review requires reasoning over project structure, repository context, and file-level implementation details. Existing automated review workflows often collapse these tasks into a single pass, which can reduce relevance, increase duplication, and weaken prioritization. We present RepoReviewer, a local-first multi-agent system for automated GitHub repository review with a Python CLI, FastAPI API, LangGraph orchestration layer, and Next.js user interface. RepoReviewer decomposes review into repository acquisition, context synthesis, file-level analysis, finding prioritization, and summary generation. We describe the system design, implementation tradeoffs, developer-facing interfaces, and practical failure modes. Rather than claiming benchmark superiority, we frame RepoReviewer as a technical systems contribution: a pragmatic architecture for repository-level automated review, accompanied by reusable evaluation and reporting infrastructure for future empirical study.

Cite

@article{arxiv.2603.16107,
  title  = {RepoReviewer: A Local-First Multi-Agent Architecture for Repository-Level Code Review},
  author = {Peng Zhang},
  journal= {arXiv preprint arXiv:2603.16107},
  year   = {2026}
}
R2 v1 2026-07-01T11:23:33.377Z