Traditional Card Game Website

Hacker News

Hey guys, My friends and I have gotten really into playing traditional card games recently, especially trick-based ones. Our favorite one is called Tractor (or Sheng Ji), which was taught to us after our friend became frustrated that he could no longer play it with his hometown friends. I am moving soon, so there is demand for some way to play our games virtually. I wrote this site (with obvious help of AI) with our favorite games so we have a place to play after I move. Feel free to try some games out. It's new, so I there will likely be issues. Feel free to report them here. Also don't hesitate to recommend any games you think I should try or add. Thanks!

Visit product View on Hacker NewsMay 21, 2026

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

67%67% 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.

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

55%55% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

49%49% 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

41%41% 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: way · Missing: mobile apps, ios, personal

35%35% 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

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

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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