AppTimer an open source tool to limit app usage and boost productivity

Hacker News

Hi HN, I’ve created AppTimer, a simple cli tool made to help you manage your time more effectively by limiting how long you use specific applications. If you’ve ever found yourself losing track of time while using an app or want to improve your focus during work, this might be helpful for you. Features: - Launch any application from the CLI and set a time limit. - Automatically terminates the application after the specified time. - Simple and lightweight, built with Go. Use Cases - Curbing screen time addiction by setting limits on entertainment apps. - Enhancing focus by controlling distractions during work hours. I’d love to hear your feedback, suggestions, or ideas for improvement. Contributions are also welcome This is my first ever solo project so help would be reallyyy appreciated

Visit product View on Hacker NewsAug 27, 2024

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

75%75% 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 · Strong signals: created · Missing: supports, reddit linkedin, podcasting

72%72% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

56%56% 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

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

33%33% 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

14%14% 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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