This is really a nice tool. For parking oversized tool results on disk, how are you storing them? Is that in flat files by byte-range reads, or embedding a SQLite or RocksDB to manage cached tool outputs?
I'm also one of the people working on this project.
Oversized result artifacts are session-namespaced files cached on disc. Coordinator runs are given a lookup manifest and the internal scratchpad tool can search, grep, etc. to find only the pieces they need with inner loops. This enables a sort of model-driven targeted context engineering.
This is really a nice tool. For parking oversized tool results on disk, how are you storing them? Is that in flat files by byte-range reads, or embedding a SQLite or RocksDB to manage cached tool outputs?
I'm also one of the people working on this project.
Oversized result artifacts are session-namespaced files cached on disc. Coordinator runs are given a lookup manifest and the internal scratchpad tool can search, grep, etc. to find only the pieces they need with inner loops. This enables a sort of model-driven targeted context engineering.
You can explore the implementation here: https://github.com/mezmo/aura/tree/main/crates/aura/src/scra...