Bookmarker – Simple CLI For saving your bookmarks

Hacker News

Just a simple utility script I created and thought it might be useful for anyone out there who likes to save links in a no-frills way. I use multiple browsers and always forget where I save my bookmarks, and sometimes I lose them because the browser changes their UI behaviour, causing me to not save something I thought I saved. So this is a simple CLI script which allows you to save a bookmark to an md file from anywhere in your terminal. Example: bookmark "hxxp://example.com" -d "this is the description" -f "Folder Name" -t "tag1, tag2, tag3"

Visit product View on Hacker NewsSep 7, 2023

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Actual performance

4points

Did not reach leaderboard

Launch Intel predictions

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TrustMRRFits verified-revenue profile · Strong signals: way · Missing: mobile apps, ios, personal

54%54% predicted probability of success on TrustMRR, 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 · Strong signals: created · Missing: supports, reddit linkedin, podcasting

50%50% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: using · Missing: mac, agents, macos

46%46% 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

42%42% 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 · 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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