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OpenOTP – Autofill email verification codes on your Mac

Hacker News

OpenOTP – Autofill email verification codes on your Mac

Hey! I'm Jenin, a 14 year old in Toronto, Canada! This is my first proper Open Source software I made, called OpenOTP! I have 6 emails :sob: and grabbing OTP's from them can be hard, even with a good email client. So I built this tool to make it easier for me! I made it in native Swift :) I did this for Hack Club Horizons, which is an event where they're flying teens to 7 countries around the world for hackathons! You can find out more about Hack Club at https://hackclub.com and horizons at https://horizons.hackclub.com . I'd love if you guys could check out my software and let me know what you think :)

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Actual performance

3points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
77%77% predicted probability of success on Indie Hackers, 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, 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.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: mac, email, code · Missing: agents, macos, agent
43%43% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
41%41% 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
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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