feat(norms): hosts, containers and monitor response times are graded against their own normal (#5742)

Host CPU, memory and load per core, container CPU and memory, and every
monitor's response time learn a normal per hour (milestone 513, System 182).
A reading past its fixed cutoff but within its normal reads healthy and says
what is usual at this hour; one well out of it keeps its grade and is a
metric anomaly. Disk, a monitor down and an agent offline keep their cutoffs.

- Each normal's floor, the smallest departure that counts, is a setting:
  Settings -> Thresholds -> Normals (norms.floor.*). Defaults: host CPU 10
  points, host memory 5, load per core 10, container CPU 10 points of one
  core, container memory 5, monitor response 100 ms; Traefik's 2-point 4xx
  and 50 ms p95 floors move there from constants. learn_normal takes a
  floor function (floor_setting) read at each pass.
- learn_normal(parts=False): a host learns, its cores don't.
- Ingest records load_pct (load_1m / cores x 100), the figure pages grade.
- Shared grading: anomalies.against / graded, worst_reading(normals=),
  hosts' host_grades, docker usage(thresholds=, norms=), monitors'
  latency_grade. Applied to host vitals, the Hosts widget, MCP overview,
  Docker usage, and the monitor list, widget and page.
- The monitor and container pages list their anomalies.

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

steward/mcp/tools/overview.py

@@ -111,6 +111,9 @@ def agent_findings(hosts, agent: dict, thresholds: dict) -> list[dict]:
                 "host agent has stopped reporting; its metrics are out of date",
                 since=a.get("last_at"), ids=ids, next=f'get_host(host="{h.id}")'))
             continue  # stale values would only add noise
+        # CPU and memory within the host's own normal for the hour aren't
+        # findings (#5742); the fullest disk keeps its cutoff.
+        normals = host_svc.host_normals(a.get("norms"), thresholds)
         for metric, kind, label in _AGENT_CHECKS:
             value = a.get(metric)
             th = thresholds.get(kind) or {}
@@ -122,6 +125,8 @@ def agent_findings(hosts, agent: dict, thresholds: dict) -> list[dict]:
                 sev = "warning"
             else:
                 continue
+            if kind in normals and not anom.against(value, normals[kind][0], normals[kind][1], "%")[0]:
+                continue
             out.append(finding(
                 sev, f"host_{kind}_high", h.name,
                 f"{label} at {rnd(value, 1)}% (warn {th['warn']}%, crit {th.get('crit')}%)",