Lovable Labs PlatformWhat is the Code Review Checklist?
| What it answers | Risk-weighted review plan for any change. |
|---|---|
| How the answer is produced | Reviewing every pull request with the same checklist wastes attention on low-risk changes and under-reviews the dangerous ones. |
| What you need to enter | Select what the change touches, honestly including indirect effects. |
| Where it stops being reliable | A checklist cannot substitute for understanding the domain the code serves. |
| Cost and sign-up | Free, runs in your browser, no account and no stored inputs. |
How the review checklist is risk-weighted?
Reviewing every pull request with the same checklist wastes attention on low-risk changes and under-reviews the dangerous ones. The generator weights the checklist by what the change actually touches.
Risk rises sharply for anything touching authentication, authorisation, payments, database migrations, or public API contracts. Those categories pull in specific items — rollback plan, permission checks, backwards compatibility — that are irrelevant to a copy change and essential to a schema change.
Change size adjusts the ordering rather than the content. Large diffs get structural questions first, because a review that starts on line one of a 900-line diff runs out of attention long before it reaches the risky part.
How do you use the Code Review Checklist?
- 1.Select what the change touches, honestly including indirect effects.
- 2.Set the rough diff size so the ordering matches the review you can realistically give.
- 3.Work the checklist top-down and stop when you have found enough to send back — a review with thirty comments gets ignored.
- 4.Attach the checklist to the pull request so the author knows what was and was not examined.
What can this tool not tell you?
- A checklist cannot substitute for understanding the domain the code serves.
- It does not run tests, linting or static analysis, all of which should gate the review rather than occupy it.
- Team conventions vary and should be added on top of the generated list.
Why a flat checklist fails and a weighted one works?
A single universal checklist applied to every pull request trains reviewers to skim, because most items on it are irrelevant to most changes — asking about database rollback plans on a CSS tweak teaches people to stop reading the list carefully. Risk-weighting solves the attention problem rather than the coverage problem: it is not that the flat checklist misses items, it is that burying three critical questions among thirty irrelevant ones guarantees they get skimmed past exactly when they matter most, on the change that touches payments or auth.
Interpreting a risk-weighted checklist means trusting the ordering as much as the content — the first three items generated for a migration are there because migrations fail in specific, recurring ways, and skipping straight to style comments on such a change inverts the priority the tool is trying to enforce. A short checklist that gets followed beats a comprehensive one that gets rubber-stamped, so resist the urge to add every possible concern back in.
What changes the weighting most is blast radius, not line count — a five-line change to a feature flag default can be higher risk than a five-hundred-line refactor of an isolated internal utility, because the flag change ships to every user immediately. The most common mistake is under-declaring what a change touches, ticking only the obvious category and missing an indirect one, such as a logging change that also touches a field containing personal data. Follow up any generated checklist with the team's own domain-specific additions rather than treating it as exhaustive.
What do worked examples look like?
A database migration adding a non-nullable column
Selecting 'database migration' surfaces backwards-compatibility and rollback items first: does the deploy order handle old code running against the new schema, and can the migration be reversed without data loss. A reviewer who checked only for SQL syntax would have missed that the migration breaks any in-flight request from a pod still running the previous code version during a rolling deploy.
A copy-only change to a marketing page
Selecting no risk categories and a small diff size produces a short checklist focused on typos, broken links and accessibility of any new text, with none of the security or migration items shown. This confirms the change genuinely warrants a light-touch review, and a reviewer can approve within minutes rather than second-guessing whether something heavier is required.
A change to a public API's response shape
Selecting 'public API contract' surfaces items about additive versus breaking changes first: is a field being removed or renamed, rather than added, and does an existing consumer's parsing logic break silently if a field's type changes from a string to a number. A reviewer working from a generic checklist might approve the diff because the tests pass, missing that passing tests only cover the API's own code, not every external client depending on the old shape.
What do people ask most about this tool?
How long should a code review take?
Review quality collapses after around sixty minutes and after roughly 400 lines. Ask for large changes to be split rather than skim them.
What should a reviewer look for first?
Whether the change solves the right problem. Style and naming issues are cheap to fix later; a wrong approach is not.
Does this replace automated checks?
No. Formatting, linting and tests should run in CI so human review can focus on design, security and correctness.
What if a change touches more than one risk category?
Select every category it genuinely touches rather than the one that seems dominant. A change that adds a new field to a payments table is both a database migration and a payments change, and each category contributes checklist items the other would miss, such as rollback safety from the migration side and idempotency from the payments side.
Should junior reviewers use the same checklist as senior ones?
Yes, but pair it with a second, more experienced reviewer on anything scoring high risk. The checklist tells a junior reviewer what to look for; it does not substitute for the judgement to know when a technically correct-looking answer to a checklist item still hides a design problem.
Which related tools should you try next?
Written and reviewed by Jim Vernon, Editor, AI Intelligence International. Published by AI Answer Engine, a service of AI Intelligence International, and checked against our editorial standards.