Add API Q1 CAPA: root cause, corrective action gate, effectiveness verification

Implements tester feedback against API Q1 §5.9.1.2 / §6.4.2:

- Root Cause field + 6M Root Cause Category lookup (Man/Machine/Method/
  Material/Measurement/Environment), separate from Deviation Detail/Category
- "Corrective Action Required?" Yes/No gate on every NCR with a required
  justification
- Corrective action plan with owner + due date; owner is notified by email
- Effectiveness verification (result, notes, server-stamped verifier/date)
  required before an NCR can close when corrective action is required —
  costing returns 409 listing the missing pieces
- Recurring-issue flag with bidirectional NCR-to-NCR links; prior NCRs show
  a warning when later NCRs reference them
- Dashboard metrics: % root cause completed, % CAPA verified effective,
  avg CAPA close time, overdue CAPA count, NCRs by root cause category
- CAPA section in the NCR detail UI, printable PDF, CSV export, and the
  vw_ncr_full Power BI view; admin list manager for root cause categories
- Migrations 0003 (schema + seeded 6M lookup) and 0004 (view refresh);
  demo seed data exercises every metric

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

backend/app/routers/reports.py

@@ -11,7 +11,7 @@ from sqlalchemy.ext.asyncio import AsyncSession
 from app.auth.deps import CurrentUser, get_current_user
 from app.database import get_db
 from app.domain import STAGE_LABELS, Stage
-from app.models import Department, DeviationCategory, Ncr, StageTransition
+from app.models import Department, DeviationCategory, Ncr, RootCauseCategory, StageTransition
 from app.models.base import utcnow
 from app.schemas.report import (
     AgingBucket,
@@ -70,9 +70,14 @@ async def reports_summary(
         c.id: c.name
         for c in (await db.execute(select(DeviationCategory))).scalars().all()
     }
+    rcc_names = {
+        c.id: c.name
+        for c in (await db.execute(select(RootCauseCategory))).scalars().all()
+    }
 
     by_dept: dict[str, int] = defaultdict(int)
     by_cat: dict[str, int] = defaultdict(int)
+    by_rcc: dict[str, int] = defaultdict(int)
     by_month: dict[str, int] = defaultdict(int)
     cost_by_month: dict[str, dict[str, Decimal]] = defaultdict(
         lambda: {"labor": Decimal(0), "material": Decimal(0), "service": Decimal(0), "other": Decimal(0)}
@@ -83,12 +88,38 @@ async def reports_summary(
     open_count = 0
     closed_count = 0
     now = utcnow()
+    today = now.date()
+
+    # ── CAPA metrics (API Q1 §6.4.2) ─────────────────────────────────────────
+    root_cause_done = 0
+    ca_required_count = 0
+    ca_verified_effective = 0
+    capa_close_days: list[float] = []
+    overdue_capa = 0
 
     for n in ncrs:
         by_dept[dept_names.get(n.department_id, "?")] += 1
         by_cat[cat_names.get(n.deviation_category_id, "?")] += 1
         by_month[n.created_at.strftime("%Y-%m")] += 1
         job_counts[n.job_number] += 1
+        if (n.root_cause or "").strip():
+            root_cause_done += 1
+        if n.root_cause_category_id is not None:
+            by_rcc[rcc_names.get(n.root_cause_category_id, "?")] += 1
+        if n.corrective_action_required:
+            ca_required_count += 1
+            effective = n.effectiveness_result == "effective"
+            if effective:
+                ca_verified_effective += 1
+                if n.corrective_action_opened_at and n.effectiveness_verified_at:
+                    capa_close_days.append(
+                        (
+                            n.effectiveness_verified_at - n.corrective_action_opened_at
+                        ).total_seconds()
+                        / 86400
+                    )
+            elif n.corrective_action_due_date and n.corrective_action_due_date < today:
+                overdue_capa += 1
         if n.stage == Stage.CLOSED.value:
             closed_count += 1
             month = (n.closed_at or n.created_at).strftime("%Y-%m")
@@ -152,6 +183,24 @@ async def reports_summary(
         open_ncrs=open_count,
         closed_ncrs=closed_count,
         total_cost=total_cost,
+        root_cause_pct=(
+            round(100 * root_cause_done / len(ncrs), 1) if ncrs else None
+        ),
+        effectiveness_verified_pct=(
+            round(100 * ca_verified_effective / ca_required_count, 1)
+            if ca_required_count
+            else None
+        ),
+        avg_capa_close_days=(
+            round(sum(capa_close_days) / len(capa_close_days), 2)
+            if capa_close_days
+            else None
+        ),
+        overdue_capa_count=overdue_capa,
+        by_root_cause_category=sorted(
+            (CountByName(name=k, count=v) for k, v in by_rcc.items()),
+            key=lambda x: -x.count,
+        ),
         by_department=sorted(
             (CountByName(name=k, count=v) for k, v in by_dept.items()),
             key=lambda x: -x.count,