I love the @docs feature, but I haven’t yet figured out how to get it to index the parts of the docs I care about.
This morning I tried indexing https://mise.jdx.dev/ and it ended up only indexing the surface-level 10 pages, when the whole site has 50+ pages.
I tried a specific page, Getting Started | mise-en-place, and it indexed 16 pages.
The official Cursor documentation at Cursor – @Docs doesn’t mention the indexing depth. Does it only go one level deep? Two levels deep? Does it traverse arbitrary depths but max out at a certain point? Is it using LLM preprocessing to try to infer the most interesting pages?
What do you all do to ensure everything gets loaded in?
I’ve recently used GitHub - langchain-ai/mcpdoc: Expose llms-txt to IDEs for development to endow agent mode with the knowledge of the langgraph docs outside of the docs feature. langgraph LLMS-txt. If there was a way to turn an arbitrary docs site into a llms.txt file, I’d perhaps use that instead of cursor’s @docs …