hō

hōki a maintenance tracker for iOS

Hacker News

Hello HN, When was the last time you swapped your toothbrush? What about your sheets? Life is full of these mundane tasks that have to be done at semi-regular intervals, but where the exact timing doesn't matter too much. I used to track these tasks with the built-in reminders app, but it wasn't a good match: the tasks only have two states, and the intervals are computed based on the due date rather than the completion date. It just didn't feel like the right tool for the job. I created hōki in my spare time to scratch my own itch, so to say, and I have been using it daily. Maybe you'll find it useful as well. It certainly has helped me wean off the all or nothing mentality that I had when doing chores.

Visit product View on Hacker NewsApr 23, 2024

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Actual performance

1points

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Launch Intel predictions

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

69%69% 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.

TrustMRRFits verified-revenue profile · Strong signals: ios · Missing: mobile apps, personal, entrepreneurs

62%62% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

60%60% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

38%38% 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

34%34% 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

18%18% 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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