Cut the Crap – I Made an App to Block Doom Scrolling

Hacker News

I realized I was spending way too much time on short-form content like Shorts, Reels, and TikToks, which severely impacted my attention span and felt like brain rot. To tackle this, I built BlockScroll, an app now available on the Play Store. It blocks shorts, reels, TikToks, and similar distractions without affecting other app features, helping enhance focus and reclaim your time. After building a Chrome extension to fight distractions [(30K+ users): https://chromewebstore.google.com/detail/remove-youtube-shor... ], I realized mobile is where short content fuels the most brain rot. So, after months of work, I built BlockScroll for mobile using Android (Java/Kotlin) and Accessibility APIs. I’d love your feedback on functionality, UX, and ideas for improvement!

Visit product View on Hacker NewsDec 14, 2024

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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.

best fitHighest predicted score across all platforms for this description.

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

59%59% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: users · Missing: plus, platform, intuitive

52%52% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

44%44% 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

25%25% predicted probability of success on Acquire.com, 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

19%19% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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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