test(usage): cover search metering hook; log dedup metering skip (round 4)

Round-4 claude-review findings (no blockers):

- 🟡 Untested server-layer metering hook (raised across rounds): extracted the
  nc_semantic_search embeddings_queries recording into a module-level
  record_search_usage() helper (mirroring record_indexing_usage) and added
  tests/unit/server/test_semantic_metering.py — value = query token count,
  flag-off no-op, None token → 0, doc_types metadata bounding, best-effort
  failure swallowed.
- 🟡 Dedup-hit skipped metering invisibly: the existing dedup info log now
  states "no embedding/usage recorded" so a "fewer embeddings_queries rows than
  expected" audit lands on the dedup path directly.

Deferred 🟢 nits (stated on the PR): search 0-token rows are recorded
deliberately (the query embedding ran; zero is a sum no-op) — documented in the
helper; embed_tokens closure locality and the OpenAI embed() dual path are
unchanged (correct as-is / separate refactor).

Deck #67.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

nextcloud_mcp_server/vector/processor.py

@@ -657,9 +657,13 @@ async def _index_document(
                     doc_type="file",
                     user_id=doc_task.user_id,
                 )
+                # No embedding ran, so no usage is recorded here — stated
+                # explicitly so a "fewer embeddings_queries rows than expected"
+                # audit lands on the dedup path rather than reconstructing it
+                # from Qdrant claim logs.
                 logger.info(
                     "Dedup hit for file %s (etag=%s); claimed for user %s "
-                    "without reprocessing",
+                    "without reprocessing (no embedding/usage recorded)",
                     doc_task.doc_id,
                     doc_task.etag,
                     doc_task.user_id,