Easy Habits

Hacker News

Easy Habits

Build better habits. No stress. No account. 100% free & offline. Intended to be used on your phone - as it keeps all storage local there. I've felt the need for a simple & nice habit tracker for a long time, that keeps all your data local. So I built it and made it available as a free tool. (Disclaimer: in the context of another SaaS product, so it has some branding & small reminders to that in there.) Only static html, all data is saved in localstorage. Notification work, but only if you keep the webpage open. Open to suggestions, feedback, ...

Visit product View on Hacker NewsDec 31, 2025

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Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

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

74%74% 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.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

48%48% 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: io · Missing: https docs, excited, just released

37%37% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

25%25% 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.

Correct prediction on native model

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