requesting-code-review

Automating code review with subagents involves dispatching a dedicated reviewer to evaluate completed work against requirements, extracting relevant context and surfacing issues early without leaking session history.

AI-assisted code review is an automated process that evaluates completed work against requirements. You should use it after each task in subagent-driven development, after implementing major features, or before merging to main to ensure quality.

To enforce plan alignment and testing coverage before merging to main, dispatch a code-review subagent to evaluate completed work and report strengths, critical issues, important issues, minor notes, and recommendations.

Yes, you can use subagent-driven development management to catch issues early by dispatching a reviewer subagent after each task. This preserves context and surfaces critical issues before they cascade.

Context-preserving code review works by dispatching a dedicated subagent that extracts relevant context without leaking session history into the reviewer's perspective, ensuring a clean evaluation of completed work.

The best way to get structured feedback on code quality is dispatching a code-review subagent that reports strengths, issues categorized by severity (Critical, Important, Minor), and actionable recommendations.