MagicQuit – closes apps when you don't use them anymore (free)

Hacker News

I often end up having 15+ applications open in my Dock. And, unfortunately, I tend to never close them. While Arc Browser does a great job for browser tabs, I didn’t find any fully satisfying solution for MacOS. One used way too much power and the other one would have taken quite some time to set it up. So instead I decided to develop an app which took x times more of my free time. MagicQuit is entirely free, open source, 100% offline and closes apps that you haven’t been using in the last 12 hours (customizable). Feature-wise I wanted to keep it as clean and simple as possible. It also uses nearly ~0% of cpu usage. Give it a try if you’re a Mac user and also having the same issue with many open applications: https://magicquit.com

Visit product View on Hacker NewsAug 9, 2023

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

89%89% 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

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

Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, io · Missing: https docs, excited, just released

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

nativeThis product was originally launched on this platform.

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

44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

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

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

12%12% 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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