Three defects kept memories from being marked useful. Measured with live
headless A/B sessions against sandboxed copies of a real memory DB.

1. Nothing was ever rated. The Stop hook was registered async, but its
   RATE_MEMORIES sweep replies with a `decision: "block"` payload — a
   control-flow response Claude Code only honours from a blocking hook.
   Registered async it is silently dropped, so the rating turn never runs and
   the ranking/retention feedback loop never closes. Identical task, identical
   DB: async => 44 exposed / 0 rated / 0 useful; sync => 44 / 44 / 9 (20.45%).
   On the live DB, 30 of 39 sessions in the measured month had zero ratings.
   Ruled out by probe: pythonw.exe does NOT null stdout through a pipe.
   See docs/decisions/stop-hook-must-be-sync.md.

2. Retrieval was not conditioned on the task. memory.retrieve accepted only
   project/tech/phase/polarity and ranked by a pure popularity prior
   (useful_count + 3*times_overlooked), so every caller got the same rows
   whatever they were doing, and use_cases/hints — the columns describing when
   a reflection applies — were never scored against anything. Adds an optional
   `query`: BM25 over title/use_cases/hints, RRF-fused with the prior. It
   promotes, never discards; a query matching nothing degrades exactly to the
   previous order. Not marked required — that would break every existing
   caller for a param whose absence is already safe.

3. Nothing demoted memories that keep not mattering. `ignored` was a no-op on
   the memory row, so the ranking key had no negative term: a reflection served
   142 times and useful zero times sorted level with one never served at all.
   On a live DB, 55 such memories accounted for 27.5% of every rated exposure.
   Migration 0013 adds times_ignored/last_ignored_at and backfills them from
   existing rating history, so the signal is live immediately rather than
   relearned. Demotion applies only past a 10-session floor and only to
   memories with no useful history — the best-performing memory in the live DB
   is ignored more often than it is used.

Also drops the default limit_per_bucket from 20 to 5. An LLM working one task
draws on ~5 memories however many it is handed (measured 5.3 +/- 2.4 useful
against 42.7 exposed per session); the rest is dilution and burnt context.

Counts times_ignored once per session, not once per exposure row: a memory
retrieved five times in one session that lands nowhere failed once, not five
times. This matches how _apply_one already stamps every row for a memory with
a single classification.

Test-shape updates are golden-value assertions that pinned the old async /
pythonw Stop registration and the pre-Phase-6 absence of `query`, not
behavioural checks.

Full suite: 1492 passed, 22 skipped.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>