I thought open-sourcing my project would get me stars.
Instead, strangers broke it.
And honestly, that was much more valuable.
Two months ago, I started building BOOTH, a small checkpoint layer that sits between an LLM call and your application and decides whether the response is trustworthy enough to use.
It's intentionally small. Zero dependencies. Just mine.
For Hacktoberfest, I opened one issue:
Test BOOTH against your favorite LLM provider. Document what breaks.
I expected silence.
Instead, people started finding things I hadn't seen.
A 7B model reported confidence: 1.0 on wrong answers
One contributor tested BOOTH with Ollama and a local 7B model.
The surprising part wasn't that the model got things wrong.
It was that the model reported confidence: 1.0 on every wrong answer.
That's not necessarily a bug in the model. It's a limitation of treating model-generated confidence as if it were an objective measurement.
I hadn't documented that behavior.
Now it's part of the project's reality.
Then came the API problems
Another contributor hit a 401 that only appeared with a newer API key format.
Someone else hit a 404 because the model they were testing had quietly been retired.
Neither issue appeared in my local testing.
That's the thing about testing your own project:
You test the environment you have.
Other people test the environments you don't.
Then a first-time contributor found an actual bug
This one mattered more.
When an underlying API call failed, BOOTH was swallowing the exception and returning a result that looked almost identical to the model simply being uncertain.
Those are completely different situations.
One means:
"The model answered, but we shouldn't trust the answer."
The other means:
"The model/API didn't actually give us a usable answer."
BOOTH was making those two states look the same.
A first-time open-source contributor found it.
I shipped the fix within a day.
That bug probably would have survived much longer without someone approaching the project with completely fresh eyes.
Then someone turned the chaos into documentation
After several people had tested different providers, another contributor volunteered to turn the accumulated discoveries into a TROUBLESHOOTING.md.
Not theoretical documentation.
Real-world:
symptom → cause → fix
The kind of documentation you only write after somebody actually hits the wall.
And it's better documentation because of that.
Four people. Four providers. A much better project.
So far, four independent contributors have tested BOOTH against different providers and environments.
OpenAI.
Groq.
Ollama.
Gemini.
Anthropic.
They didn't owe me stars.
They didn't have to tell me the project was great.
They just ran it, broke it, and told me exactly what happened.
That's probably the most valuable thing that has happened to the project so far.
The part nobody tells you about open source
When you open-source a project, it's tempting to measure everything by:
- GitHub stars
- forks
- contributors
- downloads
- social media likes
Those numbers are nice.
But they're not necessarily the most valuable outcome.
The real value can be much quieter.
Someone you've never met runs your software in an environment you've never used.
They find the edge case you never considered.
They report it.
You fix it.
Now your project is more honest than it was yesterday.
That's what happened with BOOTH.
It's still small.
But it's been tested against multiple LLM providers by people who had no reason to tell me what I wanted to hear.
They found limitations.
They found broken assumptions.
They found bugs.
And the project is better because of it.
If you're building something and wondering whether it's "ready" to open source, I'd argue that you don't necessarily need to wait until it's perfect.
You might learn more by letting someone else break it.
Your first contributors probably won't make your project popular.
They'll make it honest.
Want to try BOOTH?
If you're curious, you can:
- 📦 Install BOOTH from PyPI: https://pypi.org/project/boothpy/
- 🐛 Pick up the Hacktoberfest issue: https://github.com/Vedantgitbot/booth/issues/2
- ⭐ Explore the source code: https://github.com/Vedantgitbot/booth
If you try it with an LLM provider I haven't tested yet, I'd genuinely love to hear what happens.
Break it. Report it. Make it better.
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