---
session_id: S-2026-0222-1642
timestamp: 2026-02-22T15:42:45Z
predecessor: S-2026-0222-1614
tasks_active: [T-245]
tasks_touched: [T-251, T-245, T-246]
tasks_completed: [T-245, T-246, T-251]
uncommitted_changes: 0
owner: claude-code
session_narrative: "Built sqlite-vec semantic search, memory read-path, and fixed fabric C-XXX display"
---

# Session Handover: S-2026-0222-1642

## Where We Are

Completed T-245 (sqlite-vec embedding layer), T-246 (memory read-path), and T-251 (fabric C-XXX display fix). All backlog tasks are now done. T-245 stays in active/ awaiting human AC check (subjective quality of semantic search). No active work remaining.

## Work in Progress

### T-245: "sqlite-vec embedding layer — semantic search for project knowledge"
- **Status:** work-completed (partial — human AC pending)
- **Last action:** Built web/embeddings.py, added CLI and Watchtower integration
- **Next step:** Human verifies semantic search quality
- **Blockers:** None
- **Insight:** 874 docs, 11.6K chunks in 15s build. RRF hybrid fusion effective.

## Gaps Register

**2 spec-reality gap(s) being watched** — see `.context/project/gaps.yaml`

- **G-004** [low]: Multi-agent collaboration untested
- **G-011** [low]: PostToolUse hooks are advisory-only — cannot block actions

Run `fw audit` to check if any trigger conditions are met.

## Decisions Made This Session

1. **all-MiniLM-L6-v2 for embeddings** — 384-dim, ~22MB, fast enough (15s full index build)
   - Why: Matches T-235 research recommendation, available via sentence-transformers
   - Alternatives rejected: Larger models (slower), custom embeddings (unnecessary complexity)
2. **RRF fusion for hybrid search** — k=60 standard constant
   - Why: Simple, well-understood, works with different score distributions
   - Alternatives rejected: Linear combination (needs tuning), learned fusion (over-engineering)

## Things Tried That Failed

1. **sqlite-vec LIMIT clause** — KNN queries require `k = ?` in WHERE, not SQL LIMIT. Fixed immediately.

## Open Questions / Blockers

No open blockers. All backlog tasks complete.

## Gotchas / Warnings for Next Session

- sqlite-vec index is in /tmp (ephemeral) — rebuilds automatically when stale (2 min)
- Embedding model loads on first query (~2s cold start)
- Memory recall in `fw context focus` adds ~3s to focus set (model load + search)

## Suggested First Action

No active work tasks. Await human direction or create new tasks.

## Files Changed This Session

- Created: `web/embeddings.py`, `agents/context/lib/memory-recall.py`
- Modified: `bin/fw`, `web/blueprints/discovery.py`, `web/templates/search.html`, `agents/context/lib/focus.sh`, `web/blueprints/fabric.py`, `web/templates/fabric_detail.html`

## Recent Commits

- 8272444 T-251: Complete — C-XXX IDs resolved in fabric detail page
- b2c449c T-251: Resolve C-XXX IDs in fabric detail dependency table
- e14d7fb T-246: Complete — project memory read-path operational
- 593eca6 T-246: Memory recall — surface prior knowledge on focus set
- 6f99d13 T-245: Complete — sqlite-vec semantic + hybrid search operational

---

## Handover Quality Feedback (for next session to complete)

- Did this handover help? [ ]
- What was missing?
- What was unnecessary?
