A macOS timer app you control like an elastic band

Hacker News

I've been using Gestimer, and I fell in love with its elastic band UI. I think it's a really cool way to interact with an app. I wanted something extremely minimal to set a timer. Maybe my wife is cooking something and shouting, "Count 15 minutes" or I want to do a 30min deep work session. So, I created Stretch It which uses the elastic band interface to set a timer. - I also set the OPT modifier to change the timer range to seconds in case you're measuring your apnea . - And the left SHIFT modifier to change the range to 12 hours. Link to app: https://apps.apple.com/us/app/stretch-it-easy-gesture-timer/... I'll be adding a few more options in the future, but I wanted to get the core functionality working properly first. If you like it, ratings on the App Store are always incredibly helpful!

Visit product View on Hacker NewsOct 14, 2024

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

75%75% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

64%64% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: apps, way · Missing: mobile apps, ios, personal

57%57% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

27%27% 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

16%16% 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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