How to Review Agent-Generated Pull Requests

How do I review agent-generated pull requests before merging

Review agent-generated pull requests like any other untrusted change, but add one extra question: did the agent preserve the real intent of the work Start with the summary, then inspect the diff, run the code or tests, and confirm that the change matches the issue, not just the prompt.

Agent-generated code often looks polished while missing context. The part people get wrong is trusting the shape of the diff, not the behavior. A neat refactor can still delete an edge case, weaken validation, or change a public interface in a way the agent did not notice.

Begin with the pull request description and the linked issue. Read the stated goal in plain language, then compare it to the files changed. If the PR claims to fix one bug but touches unrelated paths, look for hidden scope creep, accidental churn, or a prompt that pulled the agent into a broader rewrite.

GitHub recommends using pull requests to discuss and review changes before merging, and it highlights the value of line comments, approvals, and requested changes in that process. It also recommends keeping pull requests small and focused, because smaller changes are easier to review and safer to merge.

Read the diff in two passes. The first pass checks the shape of the change, for example new files, deleted files, renamed functions, dependency updates, and edits to configuration or build logic. The second pass checks the behavior: what inputs changed, what outputs changed, what failure paths changed, and what assumptions the code now makes.

Pay special attention to files that agents often touch badly, including tests, schema migrations, permissions, auth, error handling, and build scripts. A change in those areas can pass a casual read while still breaking production. If a generated test only proves the happy path, treat it as a clue, not as coverage.

Run the project’s normal checks yourself, not just the checks that the agent claims it ran. That includes unit tests, targeted integration tests, linting, type checks, and, when relevant, a local build. GitHub’s pull request guidance explicitly points reviewers to the Checks tab and to reviewing changes locally when needed.

If the change affects behavior in a way that is hard to see in code, reproduce it. Open the app, call the endpoint, or run the command that the PR changes. The inconvenient part is that a lot of agent output only looks correct until you actually execute it. A broken migration, a missing import, or a bad environment assumption often shows up only at runtime.

Review tests as code, not as paperwork. Ask whether the tests would fail for the right reason if the bug came back, whether they cover a real edge case, and whether they were written to match the implementation instead of the requirement. Agent-written tests can be overfit, especially when they mirror the new code too closely.

Check dependency changes separately from application logic. GitHub documents dependency review and code scanning as tools that surface known vulnerabilities and alerts on proposed changes. If an agent adds a package, updates a lockfile, or changes a version pin, verify why the dependency is needed and whether the new surface area is acceptable.

Security-sensitive changes need a slower pass. Look at authentication, authorization, secrets handling, logging, file access, network calls, and any path that accepts user input. GitHub’s review docs point out that code scanning and dependency review help catch issues before merge, but human review still has to decide whether the change introduces a new trust boundary or a new way to bypass an existing one.

Treat vague explanations as a warning sign. If the agent cannot explain why a function changed, why a test was added, or why a dependency appeared, stop and ask for a tighter summary. Good review requires a clear before-and-after story. GitHub’s guidance on helping others review your changes says clear context helps reviewers understand what changed and why it matters.

Use file-level review and mark files as viewed when your process supports it. That keeps large pull requests manageable and reduces the chance that one file gets skipped because the rest looked fine. For stacked or chained pull requests, review from the base upward, because an agent may produce correct code in one branch only if an earlier branch is also correct.

Do not approve a pull request just because the agent made a reasonable first draft. Approval means the change is ready to merge, not that it is a decent starting point. If you need more context, more tests, or a narrower scope, use requested changes. GitHub’s review flow distinguishes between comment, approve, and request changes for a reason.

A practical review checklist looks like this: confirm the problem statement, inspect every changed file, run the tests that matter, verify any dependency or config change, check security-sensitive paths, and confirm that the result still matches the original issue. If one of those steps fails, ask for a revision before merge.

When the PR is large, split the review into a sequence. Review the design first, then the implementation, then the tests, then the rollout risk. GitHub recommends smaller pull requests and stacked pull requests specifically because they make review easier and more reliable. An agent can produce a giant diff quickly, but speed is not the same as reviewability.

If the repository uses branch protection, required reviews, or code owners, keep those checks enabled. They are useful guardrails for agent output because they force a second human to look at the change before merge. GitHub documents code owners and protected branches as standard ways to route review to the right people and enforce review rules.

The part people get wrong is reviewing the agent, not the pull request. The agent is irrelevant once the code is on the page. What matters is whether the repository stays correct, secure, and maintainable after the merge. If the code would not pass review from a careful human author, it should not pass just because a tool wrote it.

If you want a lightweight operating rule, use this: read for intent, verify for behavior, and approve only after you have run something yourself. That keeps agent-generated pull requests in the same review standard as every other change, which is the only standard that holds up in production.

If you need a place to organize this kind of workflow around real app delivery, DevConnect keeps the process simple and free to use, so the review work stays on the code instead of the tooling: https://devconnectplatform.com