Mastodawn

I built a self-hosted period tracker because I couldn't find one worth using

I built a self-hosted period tracker because I couldn't find one worth using - Lemmy.World

My wife needed a cycle tracker. Everything out there was either Flo (which got sued twice for sharing health data) or an abandoned GitHub project. So I built Ovumcy. Single Go binary, SQLite, Docker-ready. No analytics, no third-party APIs, no cloud. Your data stays on your server. Features: period tracking, symptom logging, predictions (ovulation, fertile window), statistics, CSV/JSON export, dark mode, Russian and English. Just pushed v0.2.5. Looking for feedback from real users.

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Rimu Mar 7

I was going to recommend this to someone I know but when I realised your readme.md is entirely AI-generated, I guess the whole project is probably vibe-coded. I can’t in good conscience recommend someone trust their health data to a vide-coded app because they tend to have security problems.

Also all ai-generated code is public domain so your AGPL license is kinda empty. Might as well use MIT.

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CameronDev Mar 7

Charitably, it could be an AI readme and hand rolled code, but it definitely is a smell.

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Rimu Mar 7

Yeah there are other signs too. Look at those commit messages, all vague, all perfectly capitalized. All with a nice long description with bullet points.

No one does that in a project they’re building for themselves.

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Helix 🧬

No one does that in a project they’re building for themselves.

Speak for yourself, I always did that and I found it easier with LLMs nowadays.

I hate most AI shite with a passion but when it helps my colleagues write commits which are more than “add stuff”, “fix some things” I’m fine with it.

I rarely use AI to generate code, usually only when I need a starting point. It’s much easier to unfuck AI code than to stare blankly at a screen for an hour. I’d never commit code I don’t fully understand or have read to the last byte.

I hope OP is doing the same. LLMs fail at 90% of coding tasks for me but for the other 10% (mostly writing tests, readmes, boilerplate) it’s really OK for productivity.

Ethics of LLMs aside, if you use them for exactly what they’re built for – being a supercharged glorified autocomplete – they’re cool. As soon as you try to use them for something else like “autocompletion from zero” aka “creativity”, they fail spectacularly.