I love this. My only gripe is that I wish habit trackers were more evidenced-based for some real accountability. "Work out 25 minutes" is such an easy habit to fudge by showing up late to the gym, but if you know 22 minutes can't get you the tick mark, you do the extra work required to create the space in your schedule.
With vision models, evidence-ing should be easy, but what's the best way to make it privacy first without needing a dedicate GPU tower at home?
Follow-up: Would also love a Rewards tab attached to a certain amount of growth in the habit-score Ala Habitica but with real-world rewards. Great setup so far though!
I don’t mind AI-written code. But an obviously generated README.md is such a turn off. If you don’t take the time to explain what your software does in your own words, I struggle to trust that it’s been thought about much at all.
Great work.
With vision models, evidence-ing should be easy, but what's the best way to make it privacy first without needing a dedicate GPU tower at home?
I use Loop Habit Tracker¹ on Android which at a glance seems similar.
I wish someone could pair a habit tracker with a CalDAV task tracker like jtx Board².
¹ https://f-droid.org/packages/org.isoron.uhabits ² https://f-droid.org/packages/at.techbee.jtx