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Catchy.link: make urls short, memorable, manageable, and temporary

Hacker News

Catchy.link: make urls short, memorable, manageable, and temporary

I've just created the URL shortener I've always wanted: http://catchy.link The main reason I use catchy.link is to quickly make a short, memorable, and pronounceable link I can share with people in my group, class, meeting, conference, or chat room. I appreciate that I can change the destination for a link after I've created it, or even let the link expire. And doing so without using passwords is a plus. For example, the Show HN you're reading now is at: http://catchy.link/ShowHN/CatchyLink A few features of interest to HN readers: * emphasis on memorable URLS * quick creation and URL management without creating an account * no passwords (email is used when verification is necessary) * links are temporary (from 1 day to 1 year) but you can extend them * written in Go and running on Google App Engine I hope others find catchy.link as useful as I do. Thanks, y'all, for any feedback, and for not trying to break it. Website: http://catchy.link Documentation: http://catchy.link/CatchyLinkManual Source Code: https://github.com/BrentNoorda/catchy-link This Show HN announcement: http://catchy.link/ShowHN/CatchyLink

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Actual performance

4points
4comments
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · 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: google, email, using · Missing: mac, agents, macos
61%61% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: google, way · Missing: mobile apps, ios, personal
49%49% 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
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.
AppSumoMay struggle as an AppSumo deal · Strong signals: plus · Missing: platform, intuitive, reviews
39%39% 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
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
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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