Merge PR #391: Add workflow provenance quality metrics and classification

- Introduce task provenance tracking: agent_proposal, llm_backfill, controlled_fallback
- Add quality computation function to classify workflows as 'AI-personalized' or 'guided baseline'
- Calculate agent origin ratio, fallback ratio, and per-pillar coverage metrics
- Implement configurable agent personalization threshold (default 35%)
- Enhance plan metadata with comprehensive quality dimensions:
  - agentOriginRatio, agentOriginPercent, agentOriginTaskCount
  - agentOriginPillars, fallbackRatio, fallbackPercent, fallbackTaskCount
  - totalTaskCount and configurable thresholds
- Simplify task provenance metadata handling in sanitization
- Add backfill logic for existing plans to populate missing quality metrics
- Maintain backward compatibility with existing plan storage

backend/api/today_workflow.py

@@ -161,6 +161,9 @@ async def get_today_workflow(
         except Exception:
             pass
 
+    plan_json = plan.plan_json if isinstance(plan.plan_json, dict) else {}
+    quality = plan_json.get("quality") if isinstance(plan_json.get("quality"), dict) else None
+
     return {
         "success": True,
         "data": {
@@ -180,6 +183,7 @@ async def get_today_workflow(
                 "id": plan.id,
                 "date": plan.date,
                 "source": plan.source,
+                "quality": quality,
                 "created_at": plan.created_at.isoformat() if plan.created_at else None,
                 "updated_at": plan.updated_at.isoformat() if plan.updated_at else None,
                 "generation_mode": (plan.plan_json or {}).get("generation_mode"),