feat(heads): auto-apply UI on the Concept-heads card (#114 auto-apply C)

Surfaces earned auto-apply + its observability in Settings → Tagging → Concept
heads:
- Auto-apply section: an on/off switch (writes head_auto_apply_enabled), the
  precision-target + min-examples-to-fire tuning inputs, a Preview (dry-run →
  "would apply N", per-concept chips) and Apply-now button, with live run state.
- "How auto-apply is landing": per-concept table from /api/heads/metrics —
  applied volume, misfires, realized misfire rate (green/amber/red), and missed
  (under-fires) — the signal to tune the precision target from.

store: autoApply(dryRun) / autoApplyStatus() / metrics(). Card polls the sweep
to completion, then refreshes counts + metrics. Completes the auto-apply task.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa

frontend/src/stores/heads.js

@@ -20,5 +20,22 @@ export const useHeadsStore = defineStore('heads', () => {
     return await api.post('/api/heads/train', { body: { params } })
   }
 
-  return { status, train }
+  // Earned auto-apply: trigger a sweep. dry_run previews (writes nothing);
+  // a real sweep needs head_auto_apply_enabled on (else 400).
+  async function autoApply(dryRun = false) {
+    return await api.post('/api/heads/auto-apply', { body: { dry_run: dryRun } })
+  }
+
+  // Recent sweeps + per-concept report (volume / projected per head).
+  async function autoApplyStatus() {
+    return await api.get('/api/heads/auto-apply')
+  }
+
+  // Observability: per-concept counts (volume, misfires, under-fires, realized
+  // misfire rate, head quality) + the daily time-series, to tune from.
+  async function metrics() {
+    return await api.get('/api/heads/metrics')
+  }
+
+  return { status, train, autoApply, autoApplyStatus, metrics }
 })