First Review Output
Find the generated PatchPatrol artifacts, understand the high-level result, and decide what to do next.
First Review Output
Supported public path: GitLab artifact-first
Treat the generated artifacts as the source of truth for the first successful review.
Where to look first
| Artifact | What it is for | Start here when |
|---|---|---|
ai-review.html | Static printable browser view of the validated review output | You want the cleanest management-facing read or a browser PDF export |
ai-review.md | Human-readable summary of the run, findings, and overall result | You want the fastest read of the outcome |
ai-review.json | Machine-readable review payload with the same run data in structured form | You need structured details for triage or automation |
Go to the completed review job in GitLab and open the artifact list under .ai-review/.
ai-review.html is optional, but when it is enabled it is only a presentation
layer over the same validated report payload used by ai-review.md and
ai-review.json. It can include report context, review summary, findings, token
usage, and risk-oriented visual treatment where that metadata is available.
Use it for reading and sharing, not as a separate source of truth.
Example: when to stay in ai-review.html, ai-review.md, and ai-review.json
Use this rule of thumb:
- Start with
ai-review.htmlwhen the run enabled HTML output and you want the cleanest printable presentation of the same validated report payload. - Stay in
ai-review.mdwhen you want the fastest human summary, top issues, and overall outcome. - Move to
ai-review.jsonwhen you need exact metadata such asmeta.limits,meta.provider_runtime,meta.trust_gate, ormeta.feedback.delivery.
What it means
The first successful review means more than “the job turned green.” It means:
- The review completed on the supported GitLab artifact-first path.
- The expected artifacts were written and can be opened.
- Your team can read the high-level result in
ai-review.mdand confirm whether follow-up is needed.
Use ai-review.html or ai-review.md to understand the headline outcome, then move to ai-review.json only when you need the structured representation of the same review.
If your team is building integrations, continue with the Artifacts & schema reference.
For version and release awareness, use Release and versioning.
What to do next
Once you can find and interpret the artifacts, choose the next supported step:
- Stay artifact-first if the team is still validating the basic workflow.
- Continue to Feedback modes when you are ready to compare artifact-only output with optional MR delivery.
- Use Reference or Troubleshooting if you need deeper follow-on guidance.
Next step: Feedback modes