Tads Basic Game Objects, Lightweight JavaScript Library

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Tads Basic Game Objects, tabageos, is a JavaScript library for making games and applications. I've been working on it for the past 12 years in my spare time. Originally it was an AS3 library for Flex game making, starting in 2012 I ported it to JavaScript. One method many may find useful even outside of a game setting is the tabageos.loadSpriteSheetAndStart method. With a little setup you can effectively keep an image from showing up in dev tools using that method. I use it to generally secure sprite sheets for games. One major game released with the library so far is called Idle City Sim 2051. The github has complete games that are open source and there are examples of using each class individually.

Visit product View on Hacker NewsDec 20, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: using, open · Missing: mac, agents, macos

69%69% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, io · Missing: https docs, excited, just released

53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.

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AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

36%36% 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

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.

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