Who should use the Code Review 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 code review with clear steps, mapped tools, and delivery-focused outcomes.
Deliverable outcome
Confirmation that merged code behaves correctly in the target environment.
30-90 minutes
Includes setup plus initial result generation
Free to start
You can swap tools by pricing and policy requirements
Confirmation that merged code behaves correctly in the target environment.
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 Docy to reviewer has the code changes and a clear checklist to guide the review. Then, you pass the output to CodeGrip to automated checks pass or produce a list of issues to address before manual review. Then, you pass the output to GitHub Copilot to all code changes are reviewed, with comments on issues and suggestions for improvement. Then, you pass the output to Factory to tests are present, relevant, and passing, ensuring code reliability. Then, you pass the output to CodeGrip to all review feedback is addressed, and the code is ready for final approval. Then, you pass the output to GitLab to code is merged into the main branch, completing the review cycle. Finally, Factory is used to confirmation that merged code behaves correctly in the target environment.
Prepare Code and Review Criteria
Reviewer has the code changes and a clear checklist to guide the review.
Automated Static Analysis
Automated checks pass or produce a list of issues to address before manual review.
Manual Code Review (Logic, Design, and Readability)
All code changes are reviewed, with comments on issues and suggestions for improvement.
Review Test Coverage and Run Tests
Tests are present, relevant, and passing, ensuring code reliability.
Address Feedback and Iterate
All review feedback is addressed, and the code is ready for final approval.
Approve and Merge
Code is merged into the main branch, completing the review cycle.
Post-Merge Verification (optional)
Confirmation that merged code behaves correctly in the target environment.
Gather the code changes (diff or pull request) and define the review scope: security, performance, style, logic, and compliance with team standards. Ensure the reviewer has context (ticket, requirements, test results).
Why Docy: Docy provides semantic documentation search and knowledge base version control, which aligns with managing style guides and review criteria documentation.
Run automated linters, formatters, and static analysis tools on the code to catch common issues (syntax, style, security vulnerabilities) before manual review. This filters out trivial problems and speeds up the human review.
Why CodeGrip: CodeGrip offers automated code review for bugs and vulnerabilities with custom rule configuration, directly matching static analysis needs like ESLint or SonarQube.
Review the code line by line for correctness, architecture, readability, and adherence to the defined criteria. Focus on logic errors, edge cases, naming, comments, and whether the code solves the intended problem. Leave constructive comments on the diff.
Why GitHub Copilot: GitHub Copilot provides code explanation and documentation, aiding manual review of logic and readability.
Ensure the code includes appropriate unit, integration, or end-to-end tests. Verify that existing tests still pass and new tests cover the changes. Run the test suite to confirm no regressions.
Why Factory: Factory provides automated unit and integration testing, directly supporting test coverage review and test execution.
The author responds to review comments, makes necessary changes, and re-requests review if needed. This loop continues until all concerns are resolved or acknowledged.
Why CodeGrip: CodeGrip tracks code quality trends and enforces standards, helping address feedback and iterate on code changes.
Once all automated checks pass and the reviewer is satisfied, approve the changes and merge into the target branch. Optionally, squash commits or rebase to maintain a clean history.
Why GitLab: GitLab orchestrates DevSecOps pipelines and automated code review, directly supporting approval and merge workflows.
After merge, monitor the deployment pipeline and production metrics to ensure the changes work as expected and no regressions occur. This step is optional but recommended for critical changes.
Why Factory: Factory provides automated testing, which can be integrated into CI/CD pipelines for post-merge verification.
§ 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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