Ideally: it shouldn't matter.
In practice: we (users) still need to figure it out.
So you're welcome to experiment and provide feedback.
I can explain how notes are currently processed:
- Notes are split into sections by headings. If you're using headings in a long note, each heading (no matter its level) will be processed separately.
- Each section is split into blocks (made up of sentences) with a maximal length of about 340 words. This length is dependent on the model's capabilities, and larger models may be able to process larger blocks in the future.
- This is the atomic unit of a note, as far as Jarvis is concerned. When excerpts of notes are given to GPT, these are the blocks that came up as most relevant to the user prompt.
- This also means that they are shorter than the maximal number of tokens that can be sent to the model, and there's even room to send a few of them to GPT in a single query.
- Every block includes, for additional context, the title of the note and the heading hierarchy leading up to that section, as well as note tags if they are present.
- Code blocks are handled separately from text. In fact, the default in v0.4.3 (new version) is to ignore them, but you can turn this option on. If Jarvis supports in the future models that can analyze code better, this may become handy.
This aims to capture the essence of short sections while taking into account the broader context of a note. It has its limitations. It remains to be seen how effective this approach is. I included all this information, as perhaps knowing the mechanism can inform your writing.
BTW, one more thing you could try, is to set the way multi-block notes are ranked. Check out the setting "Notes: Aggregation method for note similarity".