topic seeds get a query vector to score (V-547)

turnIsAbout scored t.vec, and t.vec was set in one place: queryEmbed, the
source at actions_query.go:125. Every topic source sits above it — attention,
list, feeds, home, network, weather. So best was handed an empty slice on every
deployed turn, returned ok=false, and all six recognisers ran on their keyword
floors. The seeds have decided nothing outside the tests since the mechanism
landed.

TestONNXTopics passes because it embeds each utterance itself and calls best
directly. That is the shape that hid this for a month: it measures the scorer
and never the wiring. Found on the box instead — "что мне нужно купить" was
answered from an old note about a monitor, and the seeds place it as the list by
0.0841.

turnVector computes the vector on first ask and caches it on the turn;
queryEmbed returns early when it is already set. Chosen over moving the embed
source up the list, because the cost is then paid only by turns that ask a
topic source, and the order of querySources keeps meaning what its comments
argue for.

One scenario assertion moved, and it is a behaviour change rather than a bent
test. morning_missed step 5 pinned "не знаю" for "что я пропустил?" with an
unresolved Praxis item on the board. isAttentionQuery does not match that
phrasing and the topicAttend seeds carry "что важное я пропустил" almost
verbatim, so she reads the item back now. Reading a surfaced item aloud is not
inventing a morning summary, so the floor that step exists for still holds;
what moved is which source answers.

cmd/mavend/actions_query.go

@@ -468,6 +468,10 @@ func (h *reactiveHandler) queryWeather(ctx context.Context, t *queryTurn) (strin
 // sources below both need, run once, in the position it always ran in. It
 // only claims the turn when the embedder fails.
 func (h *reactiveHandler) queryEmbed(ctx context.Context, t *queryTurn) (string, bool) {
+	// A topic source above already paid for this one; see turnVector.
+	if len(t.vec) > 0 {
+		return "", false
+	}
 	vec, err := router.EmbedQuery(ctx, h.recall.embedder, t.dec.Utterance)
 	if err != nil {
 		log.Printf("voice: embed query: %v", err)

cmd/mavend/testdata/scenarios/morning_missed.json

@@ -74,9 +74,9 @@
     },
     {
       "at": "08:50",
-      "note": "he asks. The query path answers from local recall only: nothing stored clears the score gate, so she refuses rather than inventing a morning summary, and the replier is never reached. That refusal is the no-hallucination floor and this step pins it. Note what the persona check here is and is not: the reply is a constant in the Go source, so expect_reply_lacks pins that constant, not anything the model wrote. The step below is the one that reads model output.",
+      "note": "he asks what he missed, and Praxis holds one unresolved item — the morning medicine — so she reads that back. This step pinned \"не знаю\" until 05-08-2026, and that was the keyword floor's blind spot rather than a rule: isAttentionQuery does not match \"что я пропустил\", while the topicAttend seeds carry \"что важное я пропустил\" almost verbatim. The seeds only started deciding when turnVector fixed the empty query vector every topic source was reading (V-547). Reading a surfaced item aloud is not inventing a morning summary, so the no-hallucination floor still holds; what moved is which source answers. Note what the persona check here is and is not: the reply is a constant in the Go source, so expect_reply_lacks pins that constant, not anything the model wrote. The step below is the one that reads model output.",
       "say": "что я пропустил?",
-      "expect_reply_contains": ["не знаю"],
+      "expect_reply_contains": ["требует внимания", "morning_medicine"],
       "expect_reply_lacks": ["рад ", "милый", "ваш"]
     },
     {

cmd/mavend/topics.go

@@ -249,6 +249,35 @@ func (x *topicIndex) best(vec []float32) (label topicLabel, margin float64, ok b
 	return label, first - second, true
 }
 
+// turnVector returns the turn's query vector, computing it on first ask and
+// caching it on the turn.
+//
+// It exists because every topic source sits ABOVE the "embed" source in
+// querySources, and that source was the only thing that ever set t.vec. So
+// turnIsAbout was reading an empty vector on every deployed turn, best returned
+// ok=false, and all six recognisers ran on their keyword floors — the seeds
+// decided nothing outside the tests, which embed the utterance themselves and
+// call best directly. Found on the box on 05-08-2026: "что мне нужно купить" was
+// answered from an old note, and the seeds place it as the list by 0.0841.
+//
+// Computing here rather than moving the embed source up: the cost is paid by the
+// turns that ask, the cache means queryEmbed below reuses this one, and the
+// order of querySources stays what its comments argue for.
+func (h *reactiveHandler) turnVector(ctx context.Context, t *queryTurn) []float32 {
+	if len(t.vec) > 0 || h.recall.embedder == nil {
+		return t.vec
+	}
+	vec, err := router.EmbedQuery(ctx, h.recall.embedder, t.dec.Utterance)
+	if err != nil {
+		// The floor answers. A topic source is not the place to fail a turn:
+		// the recall sources below hit the same embedder and report it there.
+		log.Printf("voice: topic vector for %q: %v", t.dec.Utterance, err)
+		return nil
+	}
+	t.vec = vec
+	return vec
+}
+
 // turnIsAbout — the recogniser every topic source calls. The seeds decide when
 // the embedder is there, which is every deployed box; floor is the source's own
 // keyword test, which answers when they are not.
@@ -261,7 +290,7 @@ func (x *topicIndex) best(vec []float32) (label topicLabel, margin float64, ok b
 // network by 0.0055; isNetworkQuery says no, so it stays the complaint it is.
 func (h *reactiveHandler) turnIsAbout(ctx context.Context, t *queryTurn, want topicLabel, floor func(string) bool) bool {
 	h.recall.topics.load(ctx, h.recall.embedder)
-	label, margin, ok := h.recall.topics.best(t.vec)
+	label, margin, ok := h.recall.topics.best(h.turnVector(ctx, t))
 	if !ok {
 		return floor(t.dec.Utterance)
 	}