Who should use the Review code workflow?
Teams or solo builders working on development tasks who want a repeatable process instead of one-off tool experiments.
AI Workflow · Development
Practical execution plan for review code with clear steps, mapped tools, and delivery-focused outcomes.
Deliverable outcome
The code is merged with all review concerns resolved.
30-90 minutes
Includes setup plus initial result generation
Free to start
You can swap tools by pricing and policy requirements
The code is merged with all review concerns resolved.
Use each step output as the input for the next stage
Step map
Instead of relying on a single generic AI model, this pipeline connects specialized tools to maximize quality. First, you'll use Conductor (by Melty Labs) to you have a clean, compilable codebase and full context for the review. Then, you pass the output to CodeRabbit to a list of automated findings is ready, with critical issues flagged for immediate attention. Then, you pass the output to Graphite to you have identified all logical, design, and style issues that automated tools missed. Then, you pass the output to CodeReview.ai to a complete set of review comments ready to share with the author. Then, you pass the output to Korbit to the author understands all feedback and has a clear action plan for revisions. Finally, GitLab is used to the code is merged with all review concerns resolved.
Prepare the codebase and context
You have a clean, compilable codebase and full context for the review.
Perform static analysis and automated review
A list of automated findings is ready, with critical issues flagged for immediate attention.
Conduct manual code review
You have identified all logical, design, and style issues that automated tools missed.
Document review comments and suggestions
A complete set of review comments ready to share with the author.
Submit review and discuss with author
The author understands all feedback and has a clear action plan for revisions.
Verify fixes and approve (optional)
The code is merged with all review concerns resolved.
Gather all relevant files, pull request diffs, and any associated documentation or requirements. Ensure the code compiles and passes basic linting before review to avoid wasting time on trivial issues.
Why Conductor (by Melty Labs): Conductor automates git worktree management and parallel multi-agent execution, directly supporting codebase preparation and context gathering across repositories.
Run static analysis tools and AI-powered code reviewers to detect security vulnerabilities, code smells, and style violations. This automates the low-hanging fruit so you can focus on logic and design.
Why CodeRabbit: CodeRabbit directly performs automated pull request review, bug detection, and security scanning, matching the static analysis needs.
Read through the code line by line, focusing on logic correctness, edge cases, error handling, and adherence to the team's coding standards. Use a checklist to ensure consistency.
Why Graphite: Graphite provides code review and AI-powered code analysis, fitting the manual review step with diff viewing and checklist support.
Write clear, actionable comments for each issue found, categorizing them by severity (blocker, major, minor). Provide specific code suggestions or references to best practices to help the author fix them efficiently.
Why CodeReview.ai: CodeReview.ai automates pull request code review and style consistency checks, directly supporting documentation of comments.
Publish your review on the pull request or code review platform, then schedule a brief synchronous discussion (if needed) to clarify complex issues or negotiate solutions. Aim for a collaborative tone.
Why Korbit: Korbit provides automated code review and PR description generation, facilitating review submission and discussion.
After the author addresses the comments, re-review the changed sections to ensure all issues are resolved. If satisfied, approve the pull request and merge.
Why GitLab: GitLab orchestrates DevSecOps pipelines and automated code review, directly supporting CI verification and approval.
§ Before you start
Teams or solo builders working on development tasks who want a repeatable process instead of one-off tool experiments.
No. Start with the top pick for each step, then replace tools only if they do not fit your pricing, compliance, or output needs.
Open the mapped task page and compare top options side by side. Prioritize output quality, integration fit, and predictable cost before scaling.
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