code-review-expert

You can automate code review by submitting a pull request to trigger 5 parallel agents that evaluate security, architecture, performance, reliability, and quality simultaneously. The system uses git worktree isolation and Context7 documentation checks to produce a structured Markdown report.

Yes, the code review system is language-agnostic and applies to any tech stack including Go, Python, JS/TS, Rust, Java, and C#. It dispatches specialized agents to independently audit security compliance and architecture design, validating API usage against official documentation to eliminate hallucinations.

The best way to perform reliable static analysis is using Context7 MCP integration, which pulls the latest official documentation to verify API usage during the review. This anti-hallucination mechanism operates across 5 parallel agents analyzing branches in isolated git worktrees.

Yes, the multi-agent code review process automatically creates isolated git worktrees for parallel analysis and completely cleans up all generated artifacts after producing the final structured Markdown audit report. This ensures no residual files remain in your repository.

Context7 MCP prevents LLM hallucinations by fetching and cross-referencing the latest official documentation to verify API usage and framework patterns during the code review. This triple-verification mechanism ensures the 5 agents produce reliable and accurate audit outputs.

Using 5 parallel agents enables independent, deterministic phase-based analysis across security, architecture, performance, reliability, and quality dimensions without cross-interference. This isolated approach provides a comprehensive Markdown report that covers more vulnerabilities and design flaws than single-pass analysis.