requesting-code-review

You can automate code review by dispatching a specialized subagent to analyze your git changes against requirements, categorizing feedback into critical, important, and minor issues to ensure production readiness before merging.

Structured feedback in code review categorizes identified issues into critical, important, and minor severity levels, alongside noted strengths, providing a clear report on potential issues to address before merging.

Yes, the code review process supports integration into subagent-driven development workflows as well as ad-hoc review workflows, allowing you to automatically send changes to a specialized AI reviewer after completing a feature.

To check code quality and production readiness, you dispatch a code-reviewer subagent to perform detailed checks on your latest changes, addressing the categorized critical and important issues in the generated report before merging.

No specific testing framework is required, as the review process focuses on analyzing code changes against implementation details and requirements rather than executing tests, though it integrates into broader quality assurance and development workflows.

The AI subagent reviews code changes against provided implementation details and requirements, meaning its analysis is limited to the context supplied and serves as a pre-merge quality check rather than replacing comprehensive manual testing.