GB

GBS Music – web based, open source Game Boy music editor/tracker

Hacker News

GBS Music – web based, open source Game Boy music editor/tracker

Hi HN, I've been working on an open-source, Electron (sorry) app for creating Game Boy games with no-code for a few years now. Recently I've been making some improvements to the inbuilt music editor/tracker and have got it running in the browser as a PWA. https://www.gbstudio.dev/music https://music.gbstudio.dev/ It runs entirely client-side (no backend), using the File System Access API where available, and works offline. The file format is that same as in https://superdisk.github.io/hUGETracker/ so you can take any files made with this and edit them with hUGETracker instead. And then you can drop these into a GB Studio project to make a quick GameBoy ROM too. Any feedback is appreciated. Thanks!

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Product HuntOn track for Day 1 leaderboard · Strong signals: using, code, open · Missing: mac, agents, macos
90%90% 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, ide, io · Missing: https docs, excited, just released
70%70% 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 HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
70%70% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
45%45% 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
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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