feat(usage): rename metrics → tokens_embedded/pages_embedded + export token cost to Prometheus

Billing product model finalized (Deck #281): bill pages externally, record
tokens internally. Rename the data-plane metric literals to match the now-
canonical contract (Deck #284) — the control plane's METRIC_EVENT_NAMES is
already renamed, so the old names would be unmapped and never sync to Stripe.

Rename (values unchanged):
- embeddings_queries → tokens_embedded (value = real token count, already
  emitted by this PR; the unit upstream providers bill on).
- pages_chunks → pages_embedded (value kept as len(chunk_texts) interim;
  TODO(#282): real normalized "pages indexed" count — real pages for paginated
  types, chars/tokens-per-page constant otherwise — is deferred to the
  instrumentation card, this only lands the name/contract).
- All literals, log strings, docstrings, comments, the migration comment, and
  tests renamed; grep confirms zero old strings remain.

Observability (new): export embedding token cost to Prometheus as
astrolabe_embedding_tokens_total{provider,operation} (operation = index|query)
so the billed cost unit is visible in Grafana, not just the per-tenant billing
DB. Dedicated counter (doesn't inflate the existing chunk/request metrics) and
always-on (independent of USAGE_METERING_ENABLED, so OSS/self-host gets it).
Wired on both the indexing batch embed and the search query embed (query inside
the per-request cache-miss branch, so reused embeddings aren't double-counted).

Note: the rename orphans any pre-existing embeddings_queries/pages_chunks rows
in tenant app DBs (CP no longer maps them) — acceptable; pipeline is inert with
throwaway dev/sandbox data.

Deck #284 (folded into PR #875).

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

nextcloud_mcp_server/search/bm25_hybrid.py

@@ -9,7 +9,10 @@ from qdrant_client.models import Filter
 
 from nextcloud_mcp_server.config import get_settings
 from nextcloud_mcp_server.embedding import get_bm25_service, get_embedding_service
-from nextcloud_mcp_server.observability.metrics import record_qdrant_operation
+from nextcloud_mcp_server.observability.metrics import (
+    record_embedding_tokens,
+    record_qdrant_operation,
+)
 from nextcloud_mcp_server.observability.tracing import trace_operation
 from nextcloud_mcp_server.search.access_filter import build_base_filter_conditions
 from nextcloud_mcp_server.search.algorithms import (
@@ -158,6 +161,13 @@ class BM25HybridSearchAlgorithm(SearchAlgorithm):
                 self.query_embedding = dense_embedding
                 self.query_token_count = query_tokens
                 self._embedded_query = query
+                # Export query-embedding token cost to Prometheus
+                # (operation=query), mirroring the per-search billing record in
+                # server/semantic.py. Inside the cache-miss branch so a reused
+                # embedding isn't double-counted.
+                record_embedding_tokens(
+                    settings.get_embedding_provider_family(), "query", query_tokens
+                )
         logger.debug("Generated dense embedding (dimension=%s)", len(dense_embedding))
 
         # Generate sparse embedding for BM25 keyword search