This might be one reason why Claude Code uses XML for tool calling: repeating the tag name in the closing bracket helps it keep track of where it is during inference, so it is less error prone.
We see this especially with arrays of objects where each object has optional nested fields. The model will get 18 items right and then drop a closing bracket on item 19, or a invalid field of wrong type. That's why we put effort into the repair/recovery/sanitization layer — validate field-by-field and keep what's valid rather than throwing everything out.
Then langchain and structured schemas for the output along w/ a specific system prompt for the LLM. Do you know which open source models work best or do you just use gemini in production?
Also, looking at the docs, Gemini 2.5 flash is getting deprecated by June 17th https://ai.google.dev/gemini-api/docs/deprecations#gemini-2.... (I keep getting emails from Google about it), so might want to update that to Gemini 3 Flash in the examples.
It may or may not be, but if you want people to actually use this product I’d suggest improving your documentation and replies here to not look like raw Claude output.
I also doubt the premise that about malformed JSON. I have never encountered anything like what you are describing with structured outputs.
And it doesn't care about robots.txt.
Our main use case is retail price monitoring — comparing publicly listed product prices across e-commerce sites, which is pretty standard in the industry. But fair point, we should make that clearer in the README.
Yes. It is. You've just made an arbitrary choice not to define it as such.
Our main use case is retail price monitoring — comparing publicly listed product prices across e-commerce sites, which is pretty standard in the industry. But fair point, we should make that clearer in the README.