feat(graph): dynamic force-directed Team-memory graph + honest metrics (on main's pipeline)

Lands the dynamic Team-memory redesign on top of main's continual-learning
pipeline. main already computes loop/activity in the API but its GraphView never
rendered them and kept a static-column graph; this swaps in the dynamic graph and
surfaces the rails, reusing main's richer PodLearningLoop / PodGraphActivity types.

Frontend (new frontend/src/components/graph/*, composed into GraphView.tsx):
- forceSim.ts: dependency-free force layout (charge, link springs, centroid
  recenter, 2-pass collision, bounds clamp, alpha anneal) — no new deps/lockfile churn.
- GraphCanvas.tsx: SVG render from the sim — draggable + pinnable nodes, curved
  edges, weight-sized shapes, fade-in, animated learned_from dash, risk-path
  lighting / rest dimmed, label collision-avoidance.
- MetricsRail / LearningLoop / ActivityStream / SelectedNodePanel / encoding.ts:
  the mock's rails + stream + detail panel in light shadcn. LearningLoop consumes
  main's PodLearningLoop (steps + activeStep); ActivityStream consumes
  PodGraphActivity (title + detail). SelectedNodePanel adds a Flow section that
  narrates the path through a clicked node (flowNarrative); default copy is
  mode-aware. Edge legend rounded out (editing/touches).
- GraphView polls every 5s and diffs (positions preserved), + ws /api/events nudge.
  Stale selection (node gone across a poll) dropped so the canvas can't dim entirely.

Backend (surgical — main's materializer + buildLoop kept):
- live.ts: headline metric cards derived from the FINAL de-noised graph (Open risk
  paths = distinct collision files; Learned owners = distinct owner engineers)
  instead of raw collision-signature / accepted-outcome counts that inflate with
  test churn (50 -> 4 risk files, 16 -> 1 owner on live). buildLoop untouched.
- demo.ts: metrics realigned to the demo graph (3 owners / 1 risk path / 100%).

Verified: lint + -r typecheck + -r build pass; Playwright confirmed the dynamic
graph (ticks on load, draggable), the loop rail (5 steps, ADAPT active) and
activity stream rendering main's shapes, honest metrics (3/1/100%), and the flow
narrative per node kind — zero page errors.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

backend/src/graph/demo.ts

@@ -11,21 +11,23 @@ export function createDemoPodGraph(podId: string): PodGraph {
   return {
     podId,
     generatedAt: new Date().toISOString(),
+    // Kept consistent with the graph below (3 owner engineers, 1 collision file,
+    // 1 of 1 interventions accepted) so the numbers never contradict the picture.
     metrics: [
       {
         label: 'Learned owners',
-        value: '5',
-        detail: 'Ownership edges retained from accepted interventions.',
+        value: '3',
+        detail: 'Distinct owners retained from accepted interventions.',
       },
       {
         label: 'Open risk paths',
-        value: '2',
-        detail: 'auth.ts and the memory API have converging editors.',
+        value: '1',
+        detail: 'File with two or more converging editors.',
       },
       {
         label: 'Accept rate',
-        value: '86%',
-        detail: 'Interventions accepted this session (+14%).',
+        value: '100%',
+        detail: 'Interventions accepted vs total this session.',
       },
     ],
     loop: {