Quick Cursor – use big Android phones with one hand

Hacker News

Free app without ads that makes it easy to use big Android phones with one hand. The app can be found in Play Store with the name Quick Cursor: https://play.google.com/store/apps/details?id=com.quickcursor It is an alternative to the already known Reachability Cursor app which, unfortunately, it is not maintained anymore (from 2018) and does not work on new Android versions. I need help to collect any feedback on this early version. I'm interested in opinions about the idea, feedback on how it works on other devices, bugs, interesting features that might be helpful, etc. Anything you have to say about it! Thanks HN!

Visit product View on Hacker NewsApr 25, 2020

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Product HuntOn track for Day 1 leaderboard · Strong signals: cursor, google, apps · Missing: mac, agents, macos

69%69% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

62%62% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: apps, google · Missing: mobile apps, ios, personal

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

30%30% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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