feat(anomalies): a metric out of its normal is an anomaly to review (#5740)

#5740 "A metric that departs from its normal is recorded as an anomaly to
review, and is findable after it ends", milestone 513.

- Every minute each learned key's last 15 minutes is judged against its
  hour's normal: above the usual hold x1.25 and by the metric's floor opens
  an occurrence, which ends when the level comes back.
- metric_anomalies holds one row per item to review; a repeat while it
  still waits joins it as an occurrence (metric_anomaly_spans).
- An ended row nobody reviews within anomalies.review_days (14, Settings ->
  Thresholds) lapses; an ongoing one never does.
- Learning skips every hour an occurrence covers unless its anomaly was
  marked normal: no normal is learned without review.
- Alerts -> Anomalies lists those to review first, then the reviewed and
  lapsed under day dividers; marking is operator/admin and audited.
- The Overview widget and get_overview warn of open ones and count those
  to review; the host page shows its own; the weekly report lists the
  week's and the lapsed; MCP list_anomalies and review_anomaly.
- Reviewed and lapsed rows are pruned at data.retention_days, and kept
  in backups like alert history.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

docs/architecture.md

@@ -101,6 +101,16 @@ Each rolled-up hour keeps three figures:
 
 A two-minute spike raises the peak and leaves the p95 low; an hour spent at that level raises both. Learned normals use this to tell a recurring spike from a held level. Hours rolled up before the p95 was kept have it NULL; read those as their average.
 
+### Normals and anomalies
+
+A metric a plugin registers with `learn_normal()` gets a normal per hour of the day, then per hour of the week once three weeks of history exist (`metric_norms`, relearned hourly by `metric_norms`; `steward/core/norms.py`).
+
+Every minute, `metric_anomalies` averages each learned key's last 15 minutes and compares it with the normal for that hour. A level above the usual hold ×1.25, and above the metric's floor, opens an anomaly (`steward/core/anomalies.py`):
+- `metric_anomalies` holds one row per item to review. A repeat while the row still waits joins it as another occurrence (`metric_anomaly_spans`).
+- A row is `to_review` until someone marks it `normal` or `real` (Alerts → Anomalies, or MCP `review_anomaly`). An ended row nobody reviews within `anomalies.review_days` (14) becomes `lapsed`.
+- Learning skips every hour an occurrence covers unless its anomaly was marked `normal`, so a new level is never learned without review.
+- `data_cleanup` prunes reviewed and lapsed rows at `data.retention_days`; a row still to review is never pruned.
+
 ---
 
 ## Database Session Pattern