# SWARMCARE EXECUTION - Instance instance_02 - Phase 3

## AUTONOMOUS EXECUTION MODE
- TAKE FULL CONTROL: Do not ask for confirmation
- PRODUCTION-READY ONLY: Every output must be deployment-ready
- 100% SUCCESS RATE: Build comprehensive validation at every step
- PARALLEL EVERYTHING: Run all independent tasks simultaneously

## PHASE: Workflow Orchestration

### Phase Overview
- **Phase ID:** 3
- **Story Points:** 76
- **Priority:** P0
- **Dependencies:** 1, 2

### User Stories to Implement

#### User Story 4.1: Workflow Engine
**As a** System
**I want** a workflow engine that orchestrates agent execution
**So that** complex multi-step processes can be automated

**Acceptance Criteria:**
- [ ] Workflow definition from tasks.yaml
- [ ] Task delegation to agents
- [ ] Workflow state management
- [ ] Error handling and retry logic
- [ ] Workflow monitoring
- [ ] API endpoints for workflow management

**Implementation Tasks:**
1. Design workflow engine architecture
2. Create workflow definition parser (reads tasks.yaml)
3. Implement task queue (RabbitMQ or Celery)
4. Create workflow state machine
5. Implement agent task delegation
6. Add error handling and retry logic
7. Create workflow monitoring dashboard
8. Build workflow management API
9. Test with simple 3-step workflow
10. Test with complex 10-step workflow

**Story Points:** 21
**Priority:** P0


#### User Story 4.2: EHR to Podcast Pipeline
**As a** User
**I want** to upload EHR data and get a complete educational podcast
**So that** medical information can be transformed into accessible content

**Acceptance Criteria:**
- [ ] End-to-end pipeline: EHR → Knowledge Extraction → Case Synthesis → Dialogue → Compliance → Podcast Script → Audio
- [ ] All 6 agents coordinated
- [ ] Pipeline completion time <10 minutes
- [ ] Output: podcast script + audio file
- [ ] Quality score >85%

**Implementation Tasks:**
1. Define EHR-to-Podcast workflow
2. Implement workflow steps
3. Add TTS integration (Cartesia/ElevenLabs) for audio generation
4. Test with sample EHR data
5. Optimize for performance
6. Validate output quality

**Story Points:** 21
**Priority:** P0


#### User Story 4.3: Diagnostic Workflow Implementation
**As a** Healthcare Provider
**I want** automated diagnostic workflows
**So that** patient assessment can be systematized

**Acceptance Criteria:**
- [ ] Initial patient assessment workflow
- [ ] Symptom analysis workflow
- [ ] Risk assessment workflow
- [ ] Treatment plan development workflow
- [ ] All workflows from tasks 2.yaml implemented
- [ ] Integration with RAG Heat for knowledge retrieval

**Implementation Tasks:**
1. Implement initial_patient_assessment task
2. Implement symptom_analysis task
3. Implement risk_assessment task
4. Implement treatment_plan_development task
5. Implement medication_management task
6. Create workflow orchestration for diagnostic pipeline
7. Test with 10 patient scenarios
8. Validate clinical accuracy

**Story Points:** 34
**Priority:** P1


### Success Criteria
- All user stories implemented
- All tests passing (>80% coverage)
- Code reviewed and optimized
- Documentation complete
- No critical security vulnerabilities

### Deliverables
- Production-ready code in Git
- Comprehensive test suite
- API documentation (if applicable)
- Integration tests passing

### Tracking
- Mark each user story complete in the phase state file
- Create checkpoint every 30 minutes
- Update progress percentage
- Log all significant events

### Next Steps After Completion
1. Run all tests
2. Generate documentation
3. Create checkpoint
4. Mark phase as COMPLETED
5. Notify integration coordinator

BEGIN EXECUTION NOW.
