- Fix missing user_id parameter in analyze_content_style() call
- Fix missing user_id parameter in analyze_style_patterns() call
- Fix missing user_id parameter in generate_style_guidelines() call
- user_id is required for subscription checking in llm_text_gen()
- Resolves errors: 'user_id is required for subscription checking'
- All style detection functions now properly pass user_id from executor context
- Add TaskStatusEnum to enumerate valid status values (pending, in_progress, completed, skipped, dismissed)
- Add TaskStatusUpdateRequest Pydantic model with validation
- Constrain completion_notes to max 4000 characters
- Automatically enforce schema validation and improve OpenAPI docs
- Update set_task_status endpoint to use typed request body
- Remove need for manual status validation (FastAPI handles it)
- Preserve dependencies normalization helper and all usages
- Preserve date validation and narrower exception handling from PR #396
- Keep proper feedback scoring using task.status from database
- Keep contextuality validation response fields intact
- Maintain all observability and error handling improvements
- Improve API robustness through type safety
- Add _normalize_dependencies() helper to handle all dependency type variations
- Handle None, list, JSON string, and invalid types with safe fallback to []
- Apply normalization to today and yesterday task payloads for consistency
- Ensure indexing pipeline receives normalized list dependencies
- Preserve task status feedback scoring logic (uses task.status, handles all negative cases)
- Keep contextuality validation and quality status response fields
- Improve data consistency across API and indexing surfaces
- Replace provenance-based quality with contextuality validation framework
- Add evidence link tracking system (onboarding:key and alert:id formats)
- Implement plan contextuality validation function with configurable thresholds
- Calculate task-level context scores based on evidence link density
- Define contextual workflows (>65% threshold) vs low-context workflows (<65%)
- Add validation in plan persistence layer before database commit
- Integrate contextuality metrics into release readiness checks
- Add recovery strategies for low-context workflows (regeneration with guidance)
- Track evidence link validity against grounding context (onboarding data, alerts)
- Provide detailed contextuality reports in quality assessments
- Maintain backward compatibility while enabling contextual workflow detection
- Add POST /api/today-workflow/regenerate endpoint for on-demand plan regeneration
- Implement rate limiting (3 requests per 60 seconds) to prevent abuse
- Add regeneration quality score tracking and onboarding completion status
- Compute task hashes for deduplication and change detection
- Extract plan metadata from plan_json for cleaner API responses
- Integrate onboarding progress service to track completion status
- Return quality_score and generated_with_agents metadata in responses
- Enable manual workflow refresh in degraded mode scenarios
- Maintain backward compatibility with simplified schema
- Simplify workflow generation by removing complex dependency coercion and metadata normalization functions
- Add committee health precheck to detect insufficient active agents before proposal gathering
- Add orchestrator initialization state metadata tracking for observability
- Downgrade fastapi to 0.104.0 for stability
- Simplify database schema (remove generation_mode, committee_agent_count, fallback_used columns from DailyWorkflowPlan)
- Remove 'skipped' from suppressed task statuses in memory service (keep only dismissed, rejected)
- Update task status normalization logic for clarity
- Return simplified metadata structure with generation_path and degradation tracking
- Resolve merge conflicts in backend/services/today_workflow_service.py and frontend/src/stores/workflowStore.ts
- Backend: Keep robust handling for both dict and object types in TaskProposal conversion
- Backend: Combine dependencies coercion with task metadata normalization
- Frontend: Implement graceful fallback pattern (try server first, then local generation on unavailability)
- Add provenanceSummary integration from server responses
- Ensure degraded mode handling with appropriate messaging
