multi-ai-review

You can run parallel AI code reviews by executing the /multi-ai-review command, which coordinates Codex, Gemini, and Claude to analyze your TS/JS files and produce a single integrated assessment report.

Using multiple AI models for code review provides diverse perspectives that identify edge cases, style issues, and potential risks before merging, reducing blind spots in code quality feedback compared to a single reviewer.

Yes, the review supports diff targets or explicit file lists to focus the parallel AI reviews on relevant code, enabling scalable and targeted code quality feedback for real-world development scenarios.

Yes, this workflow requires git, claude, codex, and gemini as dependencies, utilizing a script-driven approach with individual reviewer scripts and an integrated report generator to ensure reproducibility.

The best way is running the /multi-ai-review command on your diffs before merging, generating a combined report that ensures reproducibility and traceability across the three AI assessments.

While it supports scalable code quality feedback, the workflow targets TS/JS files and depends on coordinating three external AI dependencies, which may impact processing time for very large codebases.