When content exceeds 500 chars, it's automatically split into multiple
memories on paragraph boundaries. Each chunk gets the same category,
tags (with part-N-of-M suffix), keywords, and importance. Removes the
old 800 char hard limit from the Pydantic model.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
With 375 memories and 1M context window, low limits just hide results.
Agents can still pass a smaller limit when they want fewer results.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- New migration 004: memory_shares and tag_shares tables with indexes
- Share individual memories or entire tags with other users (read/write)
- Tag shares are live rules: future memories with shared tags auto-visible
- Recall query merges own + shared memories via UNION, returns shared_by field
- Owner-only delete enforcement (403 for non-owners, even with write access)
- PUT /api/memories/{id} update endpoint with permission checks
- 5 new MCP SSE tools: memory_share, memory_unshare, memory_share_tag,
memory_unshare_tag, memory_update
- Permission helper checks ownership, individual shares, and tag shares
- 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.
- Add SyncEngine for background sync between local SQLite cache and
remote API with pending_ops queue for offline resilience
- Refactor MCP server to support three modes: SQLite-only, hybrid
(local cache + sync, new default), and HTTP-only (legacy)
- Add GET /api/memories/sync endpoint for incremental sync
- Change DELETE to soft delete (set deleted_at) for sync support
- Add deleted_at IS NULL filters to all read queries
- Scale API deployment to 2 replicas with pod anti-affinity, PDB,
and startup probe for high availability
- Add migration 003 for deleted_at column and updated_at index
- Add comprehensive tests for sync engine and API sync endpoint
