18 docs tagged with "ai-code-review"

Common questions and common failures for Harness AI Code Review, in one place.

What Harness AI Code Review does, how a review runs, and the concepts you need before you turn it on.

AI Code Review REST endpoints for onboarding, settings, review results, and pull request overviews.

Create review criteria that tell the AI Code Review agent what to check, and verify they run.

Turn on AI Code Review for a GitHub repository or a Harness Code repository, and verify the first review.

How Harness connects to a GitHub repository for AI Code Review, and what each connector type requires.

What AI Code Review posts to a GitHub pull request, including the summary comment, line-level findings, labels, reviewers, and check identifiers.

Where the AI Code Review results link sends a GitHub user, and what it requires.

How AI Code Review works on a repository that already lives in Harness Code.

What AI Code Review does and does not bound at beta, and what that means for large pull requests.

Which models AI Code Review supports, how the agent reaches them, and how to point a scope at a specific connector.

Which Harness permissions gate each AI Code Review action, and what the review agent itself can do.

Follow one change from opening a pull request to acting on an AI Code Review finding.

Write and place AI Code Review criteria so the findings get read rather than ignored.

How a repository resolves its effective AI Code Review configuration from the spaces above it.

Every AI Code Review setting field, its validation rules, and how updates behave.

Every Harness resource AI Code Review onboarding creates, by name, and what offboarding removes.

Supported source control platforms, models, scopes, and current boundaries for AI Code Review.