fix(telemetry): the two invisible retrievals log, and /api/search takes scope

#2463, the remaining findings (finding 3 landed with f11a547).

## The reuse slot logs (source: reuse_slot)

A real semantic query competing for an auto-inject menu slot, and the ledger
was asymmetric: the scored hit it DISPLACED was in retrieval_logs, the query
that displaced it was not — so the slot could never be evaluated against what
it replaced. #1038 and #2085 are gated on this ledger being complete.

## Browse search logs (source: browse_search)

The human's main search surface, and it logged nothing — so retrieval_logs
claimed the web's search was /api/search. Measured while fixing: /api/search
has ZERO frontend consumers; the web UI searches through /api/knowledge
exclusively. The table wasn't just under-describing the UI, it was describing
a surface the UI never touches.

The task's check — does folding human queries into the corpus skew the
precision signal thresholds are tuned against? — is answered by the source
column: distinct values (browse_search, reuse_slot beside the existing four)
mean tuning includes or excludes human traffic deliberately rather than by
accident. Same resolution as the mcp_/rest_ split in note_usage_events.

## /api/search takes project_id (and logs it)

The route logged project_id=None unconditionally while the MCP tool insists
the agent pass the active project. Now optional, default global: with no
frontend consumer, this route serves API callers, and an API caller states
its scope explicitly — the default-scope UI decision the task flagged is moot
until a UI actually consumes the route, which is recorded rather than guessed.

Refs #2463

src/scribe/services/knowledge.py

@@ -401,6 +401,8 @@ async def _semantic_knowledge_search(
             semantic_search_notes,
         )
         is_task_filter = True if note_type in ("task", "plan") else (False if note_type else None)
+        import time as _time
+        _t0 = _time.perf_counter()
         candidates = await semantic_search_notes(
             user_id=user_id,
             scope="read",
@@ -413,6 +415,18 @@ async def _semantic_knowledge_search(
             is_task=is_task_filter,
             project_id=project_id,
         )
+        # The human's MAIN search surface, and it logged nothing — so
+        # retrieval_logs claimed the web's search was /api/search, a narrower
+        # path with (measured) zero frontend consumers. Distinct source, so
+        # threshold tuning can include or exclude human queries deliberately
+        # rather than by accident (#2463).
+        from scribe.services.retrieval_telemetry import record_retrieval
+        record_retrieval(
+            user_id=user_id, source="browse_search", query=q,
+            threshold=INTERACTIVE_SEARCH_THRESHOLD, limit=min(200, limit * 4),
+            project_id=project_id, is_task=is_task_filter, results=candidates,
+            duration_ms=(_time.perf_counter() - _t0) * 1000.0,
+        )
         for _score, note in candidates:
             if note.deleted_at is not None:
                 continue