Red Panda Vibes – 3D platformer game built with Three.js (open source)

Hacker News

Hi, I'm Alan and I built this game using the three.js game engine and the help of Claude. I've been working on it for 2 weeks. Explore the pastel landscape, avoid monsters, and try to find all the easter eggs (can you find the in-game HN feed?). The game is free, open source, and runs on Desktop / Mobile. Github repo: https://github.com/collidingScopes/red-panda-vibes I'd love any feedback and suggestions for improvement.

Visit product View on Hacker NewsMar 30, 2025

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3points

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

76%76% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

49%49% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

33%33% 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

33%33% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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