Native-feel score
Touch target, density, margin, type, shadow, navigation, and control-pattern checks for iOS and Android.
Upload a screenshot, prompt, or Figma/HTML snippet, then get a native-feel score, issue heatmap, missing-state checklist, accessibility risks, and a repair prompt ready for Codex, Claude, Cursor, or Gemini.
Revise the checkout screen so the primary action respects bottom safe area insets, keeps a 48dp touch target, and adds an empty cart state.
Bottom CTA overlaps the safe area and the secondary action is too close to the gesture bar.
Two icon actions are below 44 pt and need expanded hit areas before release.
Generated cards feel web-like because vertical rhythm and section headers drift from iOS and Android norms.
Empty, offline, permission denied, and keyboard-covered states are missing from the handoff.
Contrast is acceptable, but dynamic type expansion breaks the lower action row.
NativeFeel QA is built for AI-generated mobile screens that look promising but still need platform-specific polish, missing states, accessibility evidence, and repair instructions.
Touch target, density, margin, type, shadow, navigation, and control-pattern checks for iOS and Android.
Loading, empty, error, offline, permission denied, keyboard-covered, and app-store screenshot readiness.
Specific tasks that can be pasted into Codex, Claude, Cursor, Gemini, or a mobile engineer's issue tracker.
Touch heat zones
Native controls
Gesture risk
QA export
Each guide answers a real review question and shows how to turn that review into product evidence or a checkout-ready workflow.
Native feel AI app QA checks the gap between a generated mobile interface and the patterns users expect from real iOS and Android apps. It looks at touch ta...
AI generated mobile UI testing focuses on the quality problems that appear when a prompt or model creates a mobile interface: inconsistent spacing, non-nati...
An Android native feel checklist verifies that generated screens behave like Android screens rather than generic responsive web pages. It should cover 48dp ...
iOS generated app QA reviews generated screens against iOS interaction expectations. Useful checks include safe areas, Dynamic Type, Human Interface Guideli...
Gemini app UI readiness is a structured review of AI-generated mobile screens before they move into engineering or release. It checks whether the generated ...
AI mobile accessibility QA catches accessibility defects that are common in generated mobile apps. It should check dynamic font expansion, contrast, semanti...
Generated app store QA checks whether an AI-generated app experience is credible enough for store listings and early users. It focuses on native polish, mis...
A mobile UI polish scanner reviews the details that decide whether a generated screen feels production-ready. The best scanner checks touch zones, spacing r...
Annual billing is selected by default and saves 50%. Team is the default plan for mobile teams that need baseline diffing and QA evidence.
Indie builders validating AI-generated mobile flows before demo or app-store upload.
Mobile product teams comparing generated screens against a native baseline.
Studios shipping multiple client apps with review portals and exportable evidence.
Live scans unlock after checkout.