Click the icons to turn history into favorites

Hacker News

https://i.imgur.com/7gXMBT2.gif This is a tool to go back to often-used URLs quickly There's 2 modes, Favorites, and History Favorites are items you save by clicking the icons on the left History searches the browser history so you can save favorites History is only fetched when necessary, so it's fast Type something to filter with a more precise search Items are ordered by last visit date, most recent at the top You can use the arrows to select items up and down You can use Tab to switch between Favorites and History You can use Shift + Enter to add/remove a favorite You can use the Delete key to clear the filter You can middle click an item to open without exiting Some settings are configurable in Configure Favorites and Configuration are sync'd to your account

Visit product View on Hacker NewsAug 21, 2022

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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

76%76% 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: open · Missing: mac, agents, macos

53%53% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

49%49% 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

39%39% predicted probability of success on AppSumo, 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

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 · Strong signals: arr · Missing: mrr, revenue, profit

19%19% 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

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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