Add partial indexes for has_pending() and dashboard throughput queries

has_pending() scans jobs WHERE source_id=? AND status IN
('queued','claimed') on every poller sweep — without an index this
is a full table scan as the jobs table grows. Similarly,
count_succeeded_since() scans by completed_at for the dashboard's
rolling-throughput display.

Add two partial indexes:
- idx_jobs_pending_by_source: covers has_pending() lookups
- idx_jobs_succeeded_completed: covers count_succeeded_since()

Both use CREATE INDEX IF NOT EXISTS so they're idempotent on
existing databases.

haiku_rag_slim/haiku/rag/ingester/queue/schema.py

@@ -40,6 +40,18 @@ ON jobs(scheduled_at)
 WHERE status = 'queued'
 """
 
+JOBS_PENDING_BY_SOURCE_INDEX = """
+CREATE INDEX IF NOT EXISTS idx_jobs_pending_by_source
+ON jobs(source_id)
+WHERE status IN ('queued', 'claimed')
+"""
+
+JOBS_SUCCEEDED_COMPLETED_INDEX = """
+CREATE INDEX IF NOT EXISTS idx_jobs_succeeded_completed
+ON jobs(completed_at)
+WHERE status = 'succeeded'
+"""
+
 SYNC_STATE_DDL = """
 CREATE TABLE IF NOT EXISTS sync_state (
     source_id        TEXT NOT NULL,
@@ -67,6 +79,8 @@ ALL_DDL: tuple[str, ...] = (
     JOBS_DDL,
     JOBS_LIVE_INDEX,
     JOBS_CLAIMABLE_INDEX,
+    JOBS_PENDING_BY_SOURCE_INDEX,
+    JOBS_SUCCEEDED_COMPLETED_INDEX,
     SYNC_STATE_DDL,
     SCHEMA_VERSION_DDL,
     DLQ_VIEW,