Perform a local code review before pushing changes.

1. Gather Context — If not already provided, ask for: feature/branch description, list of modified files, relevant design doc(s) (e.g., docs/ai/design/feature-{name}.md), known constraints or risky areas, and which tests have been run. Also review the latest diff via git status and git diff --stat.
2. Use Memory for Context — Search memory for project review standards and recurring pitfalls: npx ai-devkit@latest memory search --query "code review checklist project conventions".
3. Understand Design Alignment — For each design doc, summarize architectural intent and critical constraints.
4. File-by-File Review — For every modified file: check alignment with design/requirements and flag deviations, spot logic issues/edge cases/redundant code, flag security concerns (input validation, secrets, auth, data handling), check error handling/performance/observability, and identify missing or outdated tests.
5. Cross-Cutting Concerns — Verify naming consistency and project conventions. Confirm docs/comments updated where behavior changed. Identify missing tests (unit, integration, E2E). Check for needed configuration/migration updates.
6. Store Reusable Knowledge — Save durable review findings/checklists with npx ai-devkit@latest memory store ....
7. Summarize Findings — Categorize each finding as blocking, important, or nice-to-have with: file, issue, impact, recommendation, and design reference.
8. Next Command Guidance — If blocking issues remain, return to /execute-plan (code fixes) or /writing-test (test gaps); if clean, proceed with push/PR workflow.