Really nice approach. Local-first + SQLite is the right call for offline-first agent memory without the overhead of a full embedding db. Two quick thoughts:

How do you handle memory eviction when context windows get large? Are you doing semantic similarity cutoffs or just recency? The 80-line constraint is impressive—did you consider supporting structured recalls (e.g., "all conversations about X topic")? Or is that out of scope for the minimalist angle?

Building this locally vs. cloud-hosted changes the whole game for AI CLI tools. Would use this.