DevUtils.app – Developer Utilities for macOS

Hacker News

This is a project I've been working on since the start of Covid-19. I built an app so that I don't have to put data into online tools like JWT debugger, JSON formatter, URL decoder, etc... https://devutils.app The app works entirely offline and is open-source. I'm selling the pre-built version of the app to earn some revenue for my time. If you want to try the app but can't afford the price or don't have XCode to build the app, drop me an email (my profile), I'll be happy to provide you a free build. I would love to hear all the feedback/suggestions. Thanks!

Visit product View on Hacker NewsSep 27, 2020

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Actual performance

241points

105comments

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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

85%85% 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.

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

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

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

43%43% 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

29%29% 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

27%27% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: revenue · Missing: arr, mrr, profit

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.

Incorrect prediction on native model

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