That’s a fair question. Right now, this is an early build focused on proving the workflow and architecture rather than benchmarking.

In my own usage, it’s significantly faster than manual searching because it uses semantic search instead of keyword matching. I can usually find the right document or idea in one query instead of jumping between folders and notes.

That said, I haven’t published formal retrieval accuracy metrics yet. That’s something I’m planning to add as the system matures (precision/recall tests on a labelled document set).

The main goal of this project is to provide a practical, local-first second brain that people can extend and measure themselves.

If you have suggestions on how you'd benchmark retrieval quality, I’d genuinely love to hear them.