An autonomous, context-aware AI Code Review Agent for GitLab. Powered by multi-LLMs (OpenAI, Anthropic, Gemini) with a self-learning feedback loop to enforce repository best practices.
Azure devops extension for OpenCode
Agentic AI code review for GitLab MRs and GitHub PRs, with the LLM of your choice. Posts only actionable findings as inline review threads.
ML/LLM lab for vector search, RAG, code review agents, weather baselines, evaluation metrics, and enterprise AI integration with Python and Java ecosystems.
deep research agent for codebase
Local-first AI PR review agent for GitHub Pull Requests: diff parsing, lightweight repo context, conservative LLM findings, validation, and JSON/Markdown reports.
Multi-model code review skill — dispatches diffs to frontier LLMs in parallel, filters by confidence + cross-reviewer corroboration
OrcaCode Review — the open code review harness. Multi-model reviews, merge gates, and no markup. Pay only for inference.
Multi-agent academic peer-review panel as a Claude Code skill — anonymized reviewers, prior-art grounding, and a synthesized meta-review.
OpenAI Codex skill for multi-agent pull request review using multiple subagents
Add a description, image, and links to the code-review-agent topic page so that developers can more easily learn about it.
To associate your repository with the code-review-agent topic, visit your repo's landing page and select "manage topics."