TapTab – Tab switching web extension for Safari

Hacker News

I like the tab-switching behaviour in Chrome/Firefox and wanted Safari to have something similar. Another wish of mine was for it to be a web extension that feels native to the browser vs an app extension that looks out of place. I posted a while back on HN to see if other people feel the same and the response was very positive : https://news.ycombinator.com/item?id=33811253 Say hello to TapTab : https://apps.apple.com/app/apple-store/id1659363738?pt=66324... TapTab feels right at home in Safari and is loaded with features to improve how you interact with tabs. You no longer have to miss the native tab-switching functionality that you love in Chrome/Firefox. I launched the app a few days ago, and the response has been great. Some of the features that users have been loving : - Keep your hands at the keyboard: navigate all tabs without your hands leaving the keyboard. - Fuzzy Search: Search through your tab titles and URLs at lightning speed. - Switch to previous tab: Comes with a handy shortcut to go back to the previous tab. Finally! - Dark Mode: The extension feels right at home in Safari. - Multi-Window support - Pin/Mute/Close tabs right from the extension. The app is written in ReactJS (apart from the very minuscule bit of Swift you have to write for using it as an extension in Safari) and uses Tailwind for design. If you are one of the dozen people like me who use Safari, let me know how you find it. I would love to hear if there are any features that would make it a better fit for you. I have a few things on my radar gathered from talking to users like an iPad version, custom shortcuts, etc. If you find the extension useful I would love it if you vote for it on Product Hunt to get this in front of a few more eyeballs : https://www.producthunt.com/posts/taptab Thank you!

Visit product View on Hacker NewsDec 24, 2022

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

93%93% 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

83%83% predicted probability of success on Indie Hackers, 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

47%47% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

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

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

15%15% 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.

Incorrect prediction on native model

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