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Linkbin, the Pastebin for Links

Hacker News

Linkbin, the Pastebin for Links

Link-in-bio tools like Linktree are great for sharing links, but they’re limited to just one list. Pastebin and similar tools allow sharing unlimited content, but the links are plain and unformatted. I built Linkbin to bridge this gap. It’s a simple tool where you can paste multiple links, and it generates a clean, shareable page with a link-in-bio style layout. You can create as many pages as you need—for link-in-bios, bookmarks, wishlists, etc. No account is needed!

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Actual performance

3points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
53%53% predicted probability of success on AppSumo, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntUnlikely to reach the leaderboard · Strong signals: plain · Missing: mac, agents, macos
50%50% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Strong signals: ios · Missing: supports, reddit linkedin, podcasting
46%46% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: ios · Missing: mobile apps, personal, entrepreneurs
42%42% predicted probability of success on TrustMRR, 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
34%34% 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
14%14% 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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