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How do you review an AI agent pull request quickly without rubber-stamping it? Use a ten-minute first pass to understand the change, identify its risk, trace the code, and check the evidence—then spend longer or bring in a specialist if the change is consequential or unclear. Ten minutes is a time-box for triage, not a guaranteed review duration or a substitute for judgment.
1. Orient yourself to the change
Read the pull request (PR) description and the linked issue or requirement. Before opening the diff, write down the intended behavior in one sentence. If you cannot tell what the change is supposed to do, its scope is unclear; ask for clarification rather than guessing from the agent’s summary.
2. Set the risk level
Check whether the change affects authentication, authorization, secrets, user data, input handling, money, database migrations, public APIs, or external side effects such as sending messages or making payments. These areas raise the cost of a mistaken assumption. A high-risk change—or one whose behavior is poorly explained—is a reason to widen the review beyond this first-pass time box.
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Review the actual changed files and look for work that does not fit the stated goal. Pay particular attention to:
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- Unexpected files, unrelated edits, or broad rewrites that obscure a small intended change.
- Changed defaults, fallback behavior, or configuration that could alter behavior beyond the new feature.
- Dependency changes and generated files, which may carry implications not visible in the summary.
- Instruction or configuration files that affect how future agents or other tools behave.
A concise agent explanation helps orient you, but it is not evidence that the whole diff is necessary or correct.
4. Trace the behavior through the code
Follow the changed code through its callers and data flow. Compare what the implementation actually does with the requirement you identified—not merely with the agent’s account of its work. Check the ordinary path as well as edge cases, error handling, permission boundaries, and compatibility with existing behavior.
For repository guidance, GitHub documents support for repository-wide review instructions and path-specific instructions for code that needs different standards. An AGENTS.md file can also communicate architecture boundaries and review priorities. See GitHub Docs on custom instructions.
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Look for tests that exercise the changed behavior, including relevant failure cases. Inspect the CI results and, when appropriate, run the checks required by the project. A passing test suite is useful evidence, but it does not prove that the tests cover the requirement or that the implementation behaves correctly in every relevant case.
6. Inspect security-sensitive paths
Where the change touches sensitive behavior, verify validation, authorization, secret handling, data exposure, and external calls directly. Agent authorship by itself does not establish that code is vulnerable; it does not remove the need to inspect security-relevant behavior either. Empirical research has treated security in agent-authored pull requests as a substantive concern, but it should not be used to claim that every such PR is insecure or that a short checklist guarantees security. See the study, “Security in the Age of AI Teammates: An Empirical Study of Agentic Pull Requests on GitHub”.
7. Check what automated review covered
Automated review can provide useful feedback, but check what it actually examined. GitHub says Copilot code review reads applicable repository instructions and skills from the pull request’s head branch—the branch containing the proposed changes—and can use configured MCP context. GitHub also lists dependency-management files, log files, and SVG files among file types excluded from Copilot code review. Inspect relevant excluded changes yourself rather than assuming the automated review covered them. See GitHub Docs on Copilot code review.
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An automated review is not automatically the team’s approval decision. GitHub states: “By default, Copilot leaves a ‘Comment’ review, not an ‘Approve’ review or a ‘Request changes’ review.” The comment can inform your decision; it does not make that decision for you. See GitHub Docs on using Copilot code review.
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Approve only when you understand the intended change and its risk, and the project’s requirements are met. If something is unresolved, leave a specific question or request a change rather than approving on the strength of a summary or automated comment. For consequential or unfamiliar changes, involve the relevant code owner or ask for a deeper review.
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This checklist is a triage sequence, not a validated ten-minute method. Extend the review whenever risk, scope, or uncertainty calls for it.
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