How to get a multi-agent code review in Copilot CLI

By GitHub

Categories: Product, Tools

Summary

GitHub's Copilot CLI enables multi-agent code review by running the same prompt across different AI models (Gemini, Claude, GPT), surfacing bugs that single models miss. This approach increases code quality signal by leveraging model disagreements to catch diverse bug categories.

Key Takeaways

1. Use the /review command in Copilot CLI to automatically scan for bugs, security issues, and performance problems before human code review
2. Run multi-model code review across 3+ different LLMs (Gemini, Codex, Opus) to get higher signal—different models catch different bugs and don't necessarily agree
3. Leverage model disagreement as a feature: when different AI models flag different issues, you're catching a broader spectrum of potential bugs than any single model would find
4. Integrate AI code review into pre-submission workflow to reduce friction in human review cycles and catch issues at earliest stage of development
5. Multi-agent approach creates ensemble effect in code quality—competing model perspectives increase coverage across bug categories, security vulnerabilities, and performance regressions

Topics

• Multi-agent code review patterns
• Copilot CLI workflow automation
• LLM model disagreement as signal
• Pre-submission code quality gates
• AI-assisted security scanning

Transcript Excerpt

Hi, I'm Evan Boyle from the Copilot CLI team, and this is advanced tips and tricks for the Copilot CLI. Before I put code up for review, I like to run the slash review command. This uses a prompt that helps us look for bugs, potential security issues, performance problems, and raises these issues before you get the code review. The coolest thing about this is that you can run review and ask in your prompt, use multiple models. I often use Gemini, Codex, and Opus to get a multi-agent code review ...