SilkDrop – MilkDrop port for web with live editor

Hacker News

MilkDrop visuals in a browser tab. 9,795 presets, running on your machine. SilkDrop compiles libprojectM( https://github.com/projectM-visualizer/projectm ) — the open-source MilkDrop engine — to WebAssembly and renders it through WebGL 2. Point it at a browser tab or your microphone and it reacts to whatever is playing. There is no backend. The site hands you ~10 MB on the first visit and is never involved again: rendering, preset compilation, audio analysis, search across all 9,795 presets, and every byte of storage are local. Load it once and it keeps working with the network off. There is plenty of other features as well like live presets editor, built in over 9k presets with search and favorites. Made it for fun as a pet project.

Visit product View on Hacker NewsJul 27, 2026

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Actual performance

2points

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Did not reach leaderboard

Launch Intel predictions

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

75%75% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

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

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.

TrustMRRFits verified-revenue profile · Strong signals: visualize · Missing: mobile apps, ios, personal

55%55% 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

41%41% 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

13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: audio · Missing: web3, chat, crypto

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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