Frontend quality review
Review AI-generated frontend code before it reaches production
Generated interfaces often look convincing before their edge cases are exercised. This audit path helps teams connect visible delivery evidence to the repository and browser checks needed for a reliable frontend.
Scan a website for free→Start with the user journey
Review the delivered experience before opening the code. Record the critical path, loading states, errors, keyboard behavior and responsive transitions so implementation findings stay connected to user outcomes.
Inspect the code boundaries
In the repository, trace data flow and responsibility boundaries instead of judging code by whether it was generated. Look for duplicated logic, unsafe assumptions, hidden side effects and components that make unrelated changes travel together.
- Stable types and explicit data states
- Server and client responsibilities
- Input validation and safe rendering
- Tests for critical journeys and failure states
Check accessibility and performance
Exercise the interface with keyboard navigation, zoom, assistive technology and slow networks. Confirm that semantics, focus, status messages, loading behavior and asset delivery support the actual audience.
Make the smallest coherent repair
Prioritize changes that improve user outcomes and reduce future change cost. Review generated patches, test regressions and verify the production result rather than optimizing for a diagnostic label.
Common questions
Can VibeFootprint review my private repository?+
No. The standard product reviews the public website only. Use the report to scope an authorized repository and application review.
Does code quality prove whether AI was used?+
No. Code origin cannot be reliably established from a public pattern score or a visual impression.
What should I review first?+
Start with critical user journeys, data boundaries, accessibility, error handling, security-sensitive actions and the tests that protect them.