The Fuck Cards – make a card for a friend or enemy

Hacker News

The Fuck Cards – make a card for a friend or enemy

The Fuck Card started years ago as a physical card I printed for some friends. Now it's this simple web app you can use to express yourself. Quickly make a card, copy the link and send it to someone who deserves it. It's fun and there's lots you can say with it. I built it built in 100% handcrafted in Vanilla HTML, CSS and JS. No frameworks, no BS. Fonts are provided by Google Fonts. Image generation thanks to html2canvas. No-tracking analytics by Matomo. It started as a weekend project to train my JS skills. I'd love to know your thoughts.

Visit product View on Hacker NewsApr 18, 2023

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Actual performance

18points

28comments

Made the leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · 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, physical · Missing: mac, agents, macos

73%73% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

54%54% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

45%45% 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: google · Missing: mobile apps, ios, personal

37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

18%18% 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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