Review your labels manually
Go through your navigation labels, button text, field names, and other UI terminology, flagging any that use jargon, are ambiguous, or are inconsistent with other labels.
LABEL-CLARITY SCORE
Label Lens
Enter how many labels you reviewed and how many were flagged as jargon, ambiguous, or inconsistent, and get a label-clarity score.
- Uses your inputs in a transparent calculation
- Instant result with practical next steps
- No signup required
Planning guidance only. Validate important decisions with customer evidence and your delivery team.
YOUR INPUTS
Build your result
Complete every field. The result updates only when you choose Calculate.
How it works
Enter your review counts
Enter the total number of labels reviewed and how many fell into each of the three flag categories.
Get a label-clarity score
The share of flagged labels becomes your clarity score out of 100, with fix recommendations grouped by issue type.
Continue learning: MVP UI design mistakes that confuse early users · Is your MVP navigation design simple enough?
Frequently asked questions
Does Label Lens scan my app and find bad labels automatically?
No. Label Lens computes a clarity score from the review counts you enter after manually checking your own labels — it does not scan a live app or codebase and does not run any AI/LLM step.
What counts as "jargon"?
Any internal, technical, or industry term that a typical user of your product would not recognize — an API name, a database field name, or an internal project codename showing up in the UI.
What is the difference between "ambiguous" and "inconsistent"?
Ambiguous means the label alone could mean more than one thing to a user encountering it for the first time. Inconsistent means the label is clear on its own, but a different label is used elsewhere in the product for the same concept.
Can one label be flagged in more than one category?
Yes — a label can be both jargon and inconsistent at once. The tool caps the total flagged count at your total reviewed count so the score never goes negative even with overlapping flags.
What should I fix first with a low score?
Start with jargon and ambiguous labels on your most-used screens — those cause the most confusion for the most users, whereas inconsistency issues on rarely-visited screens can wait.
How We Compare
| Feature | MVPHub | UXPressia | Figma |
|---|---|---|---|
| Label-clarity score from your own review | Included | Not included | Not included |
| Grouped fix list by jargon/ambiguity/consistency | Included | Not included | Not included |
| Persona-based terminology mapping | Not included | Included | Not included |
| Design and apply the corrected labels | Not included | Not included | Included |
UXPressia helps map terminology against user personas and journeys, and Figma is where corrected labels actually get applied to the design. Label Lens is the fast scoring step in between — quantifying how clear your current labels are before you invest time in either.
Related tools
Embed this tool
Add this tool to your site with the canonical iframe below. It remains hosted and maintained by MVPHub.