optimus:code-review

To review uncommitted git changes for bugs and security vulnerabilities, run a local-first AI code review that analyzes your working directory against project guidelines to provide actionable findings and suggested fixes.

Yes, AI code review can evaluate your code against project-specific documentation like coding-guidelines.md and testing.md to detect guideline violations and ensure adherence to team standards.

The best way to automate code analysis before a git commit is using a multi-agent AI assistant that runs up to six parallel evaluations covering security, logic errors, and test coverage on your local changes.

Yes, AI code review works for both local development workflows and PR/MR reviews by analyzing uncommitted changes and providing confidence levels alongside suggested fixes for identified issues.

Multi-agent AI assistants detect logic errors by running parallel analysis agents that evaluate code changes against project guidelines, identifying potential bugs and providing actionable findings with confidence levels.