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/server/semantic.py

@@ -64,7 +64,7 @@ async def record_search_usage(
     doc_types: list[str] | None,
     token_count: int | None,
 ) -> None:
-    """Record the billable ``embeddings_queries`` event for one semantic search.
+    """Record the billable ``tokens_embedded`` event for one semantic search.
 
     The value is the query embedding's token count (provider-reported or
     estimated) — the unit upstream providers bill on, and the same metric the
@@ -89,7 +89,7 @@ async def record_search_usage(
     try:
         store = await UsageEventStore.shared()
         await store.record_usage_event(
-            metric="embeddings_queries",
+            metric="tokens_embedded",
             value=token_count or 0,
             metadata={
                 "user_id": user_id,
@@ -111,9 +111,7 @@ async def record_search_usage(
         # (record_usage_event swallows its own write failures). Metering is on,
         # so warn — a silent DEBUG line would hide "operator enabled metering
         # but gets no data".
-        logger.warning(
-            "usage metering hook (embeddings_queries) skipped", exc_info=True
-        )
+        logger.warning("usage metering hook (tokens_embedded) skipped", exc_info=True)
 
 
 def configure_semantic_tools(mcp: FastMCP):
@@ -588,7 +586,7 @@ def configure_semantic_tools(mcp: FastMCP):
             logger.info("Returning %d results from BM25 hybrid search", len(results))
 
             # Usage metering (Deck #67): record the query embedding's token
-            # count as a billable 'embeddings_queries' event. query_token_count
+            # count as a billable 'tokens_embedded' event. query_token_count
             # is set by BM25HybridSearchAlgorithm during the search() above; the
             # doc_types loop reuses one search_algo instance for the same query
             # and the algorithm caches the dense embedding per query, so the