- Add MAX_MEMORY_CHARS=800 Pydantic validation on MemoryStore.content
- Update auto-learn judge prompts: "ONE topic per event", 100-500 chars,
include the WHY not just the WHAT
- Split 9 mega-memories (800-2400ch) into 70 focused memories (100-500ch)
via migration script
Before: median 331ch, 11 memories >800ch, recall wastes 84% of returned tokens
After: median 213ch, 2 memories >800ch (dense single-topic refs), recall returns
only the relevant knowledge
Trade-off research: PostgreSQL ts_rank gives the same score regardless of
document size, so a 2400-char memory with 12 topics gets recalled for any
of its 12 topics but wastes context with the other 11. Focused memories
(100-500ch) give higher signal-to-noise per recall.
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