Analyzed automatically. Assessed 2026-10-05 from 1,905 user reviews, the store listing and its privacy label. We have not scanned the app's package, so nothing on this page was read from inside the app itself.
App Store
This analysis describes version 1.1.46 of the app, analyzed 2026-10-05 . The app may have changed since.
The store currently lists version 1.1.46, updated 2026-09-22.
Google Play
This analysis describes version 1.1.47 of the app, analyzed 2026-10-04 . The app may have changed since.
The store currently lists version 1.1.47, updated 2026-09-16.
What the analysis found
Positive evidence 1
Things this app does right, published at the same strengths as the catch list.
One source only — shown, not confirmed 2
A single kind of evidence. We publish these because withholding them would be the bigger distortion, and we do not treat any of them as a finding we stand behind.
What reviewers said
Verbatim excerpts from public store reviews, shown as corroborating user reports. They are not Appworthy audit evidence, and a quotation is not proof of the finding it sits under.
Aggressive ad load
not true i was on it for 2 months made nothing so many ads, thars how they make money
I like the games — There are a lot of ads. And the ads are hard to get out of.
Why download when the ads are lies?? — Someone please tell me what game gives you $10 dollars when you reach lev 15 and $40 when you reach lev 20.. like the ad claims. YOU CAN’T! THERE IS NONE! It’s literally like 5-10 CENTS for reaching…
Reports that the ads misrepresent the app
false advertisement definitely im highly upset, everytime you go for the bigger surveys they pick and choose for you about if you get paid from it based on your answers or they simply say you don't qualify they only want you to do the…
So confused as to what game u can make a 100 in a day — This is false advertisement because these games u have to play all day everyday just to try to make a 100
You can’t withdraw money until it clears and it’s a time frame — This app sucks false advertising
How the automated analysis works
This assessment is produced automatically. Three independent signals are read — user reviews, the store listing and the store privacy disclosure — and each candidate finding is filed under the sources that support it.
No charge stands on one kind of evidence — with one published exception. A finding is either a measured fact that anyone can reproduce (an ad SDK is in the package; every subscription bills weekly; the privacy label omits a tracker we can see), or it is an interpretation — and an interpretation needs independent sources to agree before it reaches the catch list. The exception is a harm only users can see: a charge may publish from reviews alone, as “Reported by N users”, once enough reviewers raise it to clear that charge’s own published bar. That agreement rule is what replaced the human reviewer, not a model’s confidence.
There is no overall score, on purpose. A 0–99 number was published here until 2026-09-15. It was withdrawn because it discriminated too weakly to be the instrument — 44.7% of every pair of apps tied — and because a single number is a verdict where a count is an observation. What publishes instead is a row of measurements, each of which says what was counted and, where we could not look, says that instead.
Findings under One source only are real reports we do not stand behind as findings. They are shown because withholding them entirely would hide a genuine complaint, and labelled because publishing them as charges would be an accusation off a single source.
Several measurements above say “Not assessed” because no artefact we hold can answer them. A human review is what resolves those — and it can remove a favourable band as easily as add one.
Hands-on inspections are not yet open.