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HabitCat, a simple mobile app to track your habits and routines

Hacker News

HabitCat, a simple mobile app to track your habits and routines

Hi HN crowd, In collaboration with my significant other we took advantage of the past few months of lockdown and reduced work to create a simple little mobile app. It's called HabitCat, and is a quick tool to manage your routines and build new habits. We were a bit annoyed by existing applications and thought that would be a neat project to do and get some experience building products together. Release announcement: https://sam.elborai.me/blog/habitcat-release. The android version: https://play.google.com/store/apps/details. It's nothing too fancy, and we aren't building a company here, but we are looking for feedbacks :)

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Product HuntOn track for Day 1 leaderboard · Strong signals: google, apps, new · Missing: mac, agents, macos
72%72% 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 · Missing: supports, reddit linkedin, podcasting
64%64% 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
46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: apps, month, google · Missing: mobile apps, ios, personal
41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, existing, io · Missing: https docs, excited, just released
40%40% 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 · Missing: arr, mrr, revenue
20%20% 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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