perf: audit EmbeddingGemma 2 and reuse measured query embeddings

docs/PERFORMANCE.md

@@ -96,6 +96,16 @@ real Google inference remains required for product semantic search. Platform,
 large-corpus, concurrent-indexing and GPU performance gates remain independent.
 ## Worker round-trip diagnostics
 
+The retained hybrid service now keeps a bounded 32-query vector LRU. Debug
+`semantic.query_embedding` spans report `query_cache_hit` and `query_cache_miss`.
+A hit reuses an actual model vector and performs no neural inference; it must
+not carry the previous worker's tokenization/inference counters. Filters, current
+source eligibility, ANN retrieval and fusion still execute. Warmup performs an
+actual neural probe and does not seed an unseen foreground-query result.
+Compare fresh queries, repeats and filter changes separately. The current
+[EmbeddingGemma 2 audit](EMBEDDINGGEMMA2-AUDIT.md) includes paired real-CPU
+measurements, startup boundaries and remaining indexing/media costs.
+
 Measured desktop failures return `{message, metrics}` and retain the trace for
 the failed attempt. Busy retries are separate attempts. If an unexpected worker
 task failure loses its collector, elapsed time is retained, the trace is null,