Barbell – A subtle news ticker in the menu bar

Hacker News

Hey HN, Barbell is a tiny news ticker for the macOS menu bar. I get really distracted by notifications, and don’t always want to open newsfeeds, so this way I’m able to glance and only click on the news I find interesting. For me personally this has quickly become one of my essential macOS tools. Current features include: A max character length, refresh rate, mute for 1 hour, and sources from HN, Twitter, and Reddit. In the future I’d like to add support for RSS, a more advanced history, and integration with focus modes. If you have any other suggestions, please let me know, I’d like to make it as useful as possible.

Visit product View on Hacker NewsNov 23, 2022

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Did not reach leaderboard

Launch Intel predictions

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

86%86% 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, new · Missing: agents, agent, cursor

81%81% predicted probability of success on Product Hunt, 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

43%43% 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

33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

28%28% 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

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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