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AnySwitch – a database of mechanical key switches

Hacker News

AnySwitch – a database of mechanical key switches

Hello there HN! I've decided to build a new mechanical keyboard, and found out that there are new switches that were created by the community. I have some switches I like and own, but I can't physically try every possible switch. So I was looking for a site that lists all the switches and their parameters, and I couldn't find one. So I made it myself! It's very early stage, and it's missing a lot of switches (mainly Gateron, and other small brands / manufacturers), but I think for an MVP - it's pretty good. Let me know what do you think about it. What would you like to see there. Any kind of feedback is appreciated! Cheers!

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, physical · Missing: mac, agents, macos
86%86% 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.
Indie HackersFits the IH revenue-focused audience · Strong signals: created, para · Missing: supports, reddit linkedin, podcasting
61%61% predicted probability of success on Indie Hackers, 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.
Hacker NewsMay not resonate with HN audience · Strong signals: ide · Missing: https docs, excited, just released
38%38% 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: para · 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
19%19% 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.

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