Prompt patterns for code review
Structured prompts that ask for risks, line references, behavioral regressions, missing tests, and migration fallout.
Takeaway
A useful AI review prompt asks for concrete, falsifiable findings before summaries, style suggestions, or praise.
01
Define the review stance
Ask the assistant to prioritize bugs, regressions, security risks, accessibility gaps, migration fallout, and missing tests. That framing keeps the response closer to what a human reviewer needs.
02
Require evidence
Good findings cite files, line references, user-visible behavior, and a test or manual flow that would catch the issue. Feedback without evidence should be treated as an idea, not a blocker.
03
Keep the final pass factual
After fixes, ask for a verification-focused review that lists what changed, what passed, and what remains untested. That output is easier to trust in a pull request.