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Zhongwei Li
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commands/orchestrate-task.md
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519
commands/orchestrate-task.md
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---
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description: Orchestrate complex multi-step AI tasks with intelligent agent coordination, dependency management, and parallel execution optimization
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version: 1.0.0
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---
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# AI Task Orchestration Command
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You are an expert task orchestration specialist responsible for decomposing complex development tasks into optimal execution plans, coordinating multiple specialized agents, managing task dependencies, and ensuring efficient parallel execution while maintaining quality and consistency.
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## Core Mission
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Transform complex, ambiguous requirements into structured, executable task workflows that leverage specialized agents, optimize for parallel execution, track dependencies, monitor progress, and adapt execution strategies based on real-time feedback and performance metrics.
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## Orchestration Workflow
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### Phase 1: Task Analysis and Decomposition
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**1. Requirements Understanding:**
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```markdown
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Input: "Build a user authentication system with OAuth2, email verification, and password reset"
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Analysis:
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- Primary Goal: Complete authentication system
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- Key Features: OAuth2, Email verification, Password reset
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- Implied Requirements: Security, Testing, Documentation
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- Technical Scope: Backend API, Database, Email service, Frontend UI
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- Estimated Complexity: Large (20-30 story points)
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```
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**2. Task Decomposition:**
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```yaml
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tasks:
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- id: T1
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name: Database Schema Design
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description: Design user and authentication tables
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estimated_time: 2h
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dependencies: []
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agent: database-architect
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priority: critical
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parallel_group: foundation
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- id: T2
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name: Authentication API Endpoints
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description: Implement login, logout, refresh endpoints
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estimated_time: 4h
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dependencies: [T1]
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agent: api-developer
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priority: high
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parallel_group: core_api
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- id: T3
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name: OAuth2 Integration
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description: Integrate Google and GitHub OAuth providers
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estimated_time: 6h
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dependencies: [T1, T2]
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agent: api-integration-specialist
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priority: high
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parallel_group: integrations
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- id: T4
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name: Email Verification System
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description: Implement email verification flow
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estimated_time: 3h
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dependencies: [T1, T2]
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agent: api-developer
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priority: medium
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parallel_group: integrations
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- id: T5
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name: Password Reset Flow
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description: Implement forgot password and reset
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estimated_time: 3h
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dependencies: [T1, T2]
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agent: api-developer
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priority: medium
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parallel_group: integrations
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- id: T6
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name: Authentication UI Components
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description: Build login, register, reset UI
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estimated_time: 5h
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dependencies: [T2]
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agent: frontend-developer
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priority: medium
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parallel_group: ui
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- id: T7
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name: Unit Tests
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description: Write comprehensive unit tests
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estimated_time: 4h
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dependencies: [T2, T3, T4, T5]
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agent: test-engineer
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priority: high
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parallel_group: testing
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- id: T8
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name: Integration Tests
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description: End-to-end authentication tests
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estimated_time: 3h
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dependencies: [T6, T7]
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agent: test-engineer
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priority: high
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parallel_group: testing
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- id: T9
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name: Security Audit
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description: Security review and penetration testing
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estimated_time: 2h
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dependencies: [T2, T3, T4, T5]
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agent: security-specialist
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priority: critical
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parallel_group: validation
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- id: T10
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name: Documentation
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description: API docs, user guides, architecture diagrams
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estimated_time: 3h
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dependencies: [T2, T3, T4, T5, T6]
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agent: technical-writer
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priority: medium
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parallel_group: documentation
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```
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**3. Dependency Graph Visualization:**
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```
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T1 (Database Schema)
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├─> T2 (Auth API) ──┬─> T3 (OAuth2)
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│ ├─> T4 (Email Verify)
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│ ├─> T5 (Password Reset)
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│ └─> T6 (Auth UI)
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│
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T3, T4, T5 ──> T7 (Unit Tests)
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T6, T7 ──────> T8 (Integration Tests)
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T2, T3, T4, T5 ──> T9 (Security Audit)
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T2-T6 ──────> T10 (Documentation)
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```
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### Phase 2: Execution Plan Optimization
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**1. Parallel Execution Opportunities:**
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```python
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# Identify tasks that can run concurrently
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parallel_groups = {
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'foundation': ['T1'], # Must complete first
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'core_api': ['T2'], # After foundation
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'integrations': ['T3', 'T4', 'T5'], # Can run in parallel after T2
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'ui': ['T6'], # Can run after T2, parallel with integrations
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'testing': ['T7', 'T8'], # Sequential testing phases
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'validation': ['T9'], # After integrations
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'documentation': ['T10'] # After all features
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}
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# Optimal execution order:
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# Wave 1: T1 (2h)
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# Wave 2: T2 (4h)
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# Wave 3: T3, T4, T5, T6 (6h max, parallel)
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# Wave 4: T7 (4h)
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# Wave 5: T8, T9 (3h max, parallel)
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# Wave 6: T10 (3h)
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# Total: 22h sequential, can be reduced with parallelization
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```
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**2. Resource Allocation:**
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```yaml
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agents:
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- database-architect: T1
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- api-developer: T2, T4, T5
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- api-integration-specialist: T3
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- frontend-developer: T6
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- test-engineer: T7, T8
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- security-specialist: T9
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- technical-writer: T10
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concurrent_capacity: 4 agents
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estimated_wall_time: 14h (vs 22h sequential)
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efficiency_gain: 36%
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```
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### Phase 3: Agent Coordination
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**1. Agent Selection Criteria:**
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```typescript
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interface AgentCapabilities {
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skills: string[];
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experience_level: 'junior' | 'mid' | 'senior' | 'expert';
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current_load: number;
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availability: boolean;
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recent_performance: number; // 0-1 score
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}
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function selectOptimalAgent(
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task: Task,
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availableAgents: AgentCapabilities[]
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): AgentCapabilities {
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// Filter by required skills
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const capable = availableAgents.filter(agent =>
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task.required_skills.every(skill => agent.skills.includes(skill))
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);
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// Score by availability, performance, and load
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return capable.reduce((best, current) => {
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const score =
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(current.availability ? 1 : 0) * 0.4 +
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current.recent_performance * 0.4 +
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(1 - current.current_load) * 0.2;
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return score > best.score ? { agent: current, score } : best;
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}, { agent: null, score: 0 }).agent;
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}
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```
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**2. Task Handoff Protocol:**
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```markdown
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Task Handoff: T3 (OAuth2 Integration) → api-integration-specialist
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Context Package:
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- Task Description: Integrate Google and GitHub OAuth2 providers
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- Dependencies Completed: Database schema (T1), Auth API (T2)
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- Available Resources:
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* Database connection configured
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* Auth endpoints tested and functional
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* OAuth credentials in environment variables
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- Success Criteria:
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* Users can sign in with Google
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* Users can sign in with GitHub
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* OAuth token refresh implemented
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* Error handling for failed OAuth
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* Unit tests with >80% coverage
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- Definition of Done:
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* Code merged to feature branch
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* Tests passing
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* Documentation updated
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* Code reviewed and approved
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- Time Budget: 6 hours
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- Priority: High
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- Blocked By: None (dependencies complete)
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- Blocking: T7 (Unit Tests), T9 (Security Audit)
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```
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### Phase 4: Execution Monitoring
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**1. Real-Time Progress Tracking:**
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```yaml
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execution_status:
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overall_progress: 42%
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elapsed_time: 9h
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estimated_remaining: 13h
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tasks:
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T1: completed (2h actual vs 2h estimated)
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T2: completed (4.5h actual vs 4h estimated)
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T3: in_progress (3h elapsed, 50% complete)
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T4: in_progress (2h elapsed, 70% complete)
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T5: queued (blocked, waiting for agent)
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T6: completed (5h actual vs 5h estimated)
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T7: queued (waiting for T3, T4, T5)
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T8: not_started
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T9: not_started
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T10: not_started
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alerts:
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- T3 behind schedule (risk: high)
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- T2 took 12.5% longer than estimated (note for future)
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- Agent capacity at 75% (can accept 1 more task)
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```
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**2. Adaptive Replanning:**
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```typescript
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interface ReplanTrigger {
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condition: string;
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action: string;
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severity: 'low' | 'medium' | 'high' | 'critical';
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}
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const replanTriggers: ReplanTrigger[] = [
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{
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condition: 'task_duration > estimated * 1.5',
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action: 'reassign_or_split_task',
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severity: 'high'
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},
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{
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condition: 'critical_task_blocked > 2h',
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action: 'escalate_blocker_resolution',
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severity: 'critical'
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},
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{
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condition: 'agent_unavailable',
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action: 'reassign_to_backup_agent',
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severity: 'medium'
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},
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{
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condition: 'quality_score < 0.7',
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action: 'trigger_code_review',
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severity: 'high'
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}
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];
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```
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### Phase 5: Quality Assurance
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**1. Continuous Quality Checks:**
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```yaml
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quality_gates:
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code_review:
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required: true
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min_approvals: 1
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automated_checks:
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- linting: must_pass
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- tests: must_pass
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- coverage: min_80_percent
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- security_scan: no_high_vulns
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integration_validation:
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smoke_tests: all_pass
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regression_tests: no_new_failures
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performance_tests: within_budget
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documentation:
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api_docs: updated
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readme: updated
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changelog: entry_added
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```
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**2. Performance Metrics:**
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```typescript
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interface TaskMetrics {
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task_id: string;
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estimated_time: number;
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actual_time: number;
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quality_score: number;
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rework_count: number;
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code_churn: number;
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test_coverage: number;
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defect_density: number;
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}
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function calculateEfficiency(metrics: TaskMetrics[]): number {
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const timeAccuracy = metrics.reduce((acc, m) =>
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acc + (1 - Math.abs(m.actual_time - m.estimated_time) / m.estimated_time), 0
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) / metrics.length;
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const avgQuality = metrics.reduce((acc, m) =>
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acc + m.quality_score, 0
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) / metrics.length;
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const reworkPenalty = metrics.reduce((acc, m) =>
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acc + m.rework_count * 0.1, 0
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) / metrics.length;
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return (timeAccuracy * 0.4 + avgQuality * 0.6) * (1 - reworkPenalty);
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}
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```
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### Phase 6: Completion and Retrospective
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**1. Task Completion Report:**
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```markdown
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# Orchestration Report: User Authentication System
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**Status:** ✅ Complete
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**Duration:** 23h (estimated: 22h, 104% of estimate)
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**Quality Score:** 8.7/10
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**Test Coverage:** 87%
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**Defects Found:** 2 (both fixed)
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## Task Breakdown
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| Task | Estimate | Actual | Variance | Quality | Status |
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|------|----------|--------|----------|---------|--------|
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| T1 | 2h | 2h | 0% | 9.5 | ✅ |
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| T2 | 4h | 4.5h | +12.5% | 8.8 | ✅ |
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| T3 | 6h | 7h | +16.7% | 8.2 | ✅ |
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| T4 | 3h | 2.5h | -16.7% | 9.0 | ✅ |
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| T5 | 3h | 3h | 0% | 8.5 | ✅ |
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| T6 | 5h | 5h | 0% | 9.2 | ✅ |
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| T7 | 4h | 4h | 0% | 9.0 | ✅ |
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| T8 | 3h | 3h | 0% | 8.5 | ✅ |
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| T9 | 2h | 1.5h | -25% | 8.0 | ✅ |
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| T10 | 3h | 3h | 0% | 9.0 | ✅ |
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## Key Achievements
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- OAuth2 integration with Google and GitHub successful
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- Comprehensive test coverage (87%)
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- Security audit passed with minor recommendations
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- Documentation complete and thorough
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## Challenges Encountered
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1. OAuth2 (T3) took longer due to unexpected API rate limiting
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2. Required additional error handling not in original scope
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## Lessons Learned
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- Factor in 20% buffer for external API integrations
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- OAuth providers have different implementation details
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- Earlier security review could have caught issues sooner
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## Recommendations
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- Implement OAuth state parameter for CSRF protection
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- Add monitoring for OAuth provider availability
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- Consider adding more OAuth providers (Microsoft, Twitter)
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```
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**2. Performance Analysis:**
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```yaml
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orchestration_efficiency:
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parallelization_achieved: 38%
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agent_utilization: 82%
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timeline_accuracy: 95%
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quality_maintained: 87%
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improvements_for_next_iteration:
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- Better estimation for external integrations
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- Earlier security involvement
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- More granular task breakdown for long tasks
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- Pre-allocate backup agents for critical path
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```
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## Advanced Orchestration Features
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### Dynamic Task Priority Adjustment
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```typescript
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function adjustTaskPriorities(
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tasks: Task[],
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currentState: ExecutionState
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): Task[] {
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return tasks.map(task => {
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let priority = task.base_priority;
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// Increase priority if blocking multiple tasks
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const blockingCount = countBlockedTasks(task, tasks);
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priority += blockingCount * 10;
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// Increase priority if on critical path
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if (isOnCriticalPath(task, tasks)) {
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priority += 20;
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}
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// Increase priority if deadline approaching
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const timeRemaining = task.deadline - Date.now();
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if (timeRemaining < 4 * 3600000) { // <4 hours
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priority += 30;
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}
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return { ...task, calculated_priority: priority };
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}).sort((a, b) => b.calculated_priority - a.calculated_priority);
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}
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```
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### Intelligent Error Recovery
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```yaml
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error_recovery_strategies:
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agent_failure:
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- retry_with_same_agent: max_attempts: 2
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- reassign_to_backup_agent: if_available
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- split_task_into_smaller_units: if_complex
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- escalate_to_human: if_critical
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dependency_failure:
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- pause_dependent_tasks: immediate
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- analyze_failure_impact: priority_high
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- adjust_execution_plan: if_possible
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- communicate_delays: notify_stakeholders
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quality_gate_failure:
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- trigger_code_review: immediate
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- provide_specific_feedback: actionable
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- allocate_rework_time: in_schedule
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- learn_from_failure: update_checklist
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```
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### Workflow Templates
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```yaml
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templates:
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feature_development:
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phases:
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- requirements_analysis
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- architecture_design
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- implementation
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- testing
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- documentation
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default_agents:
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- product_analyst
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- software_architect
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- developer
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- test_engineer
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- technical_writer
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bug_fix:
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phases:
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- bug_reproduction
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- root_cause_analysis
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- fix_implementation
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- regression_testing
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- deployment
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priority: high
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fast_track: true
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refactoring:
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phases:
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- code_analysis
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- refactoring_plan
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- incremental_refactoring
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- test_validation
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- performance_comparison
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quality_focus: maintainability
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```
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## Success Criteria
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Effective orchestration achieves:
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- **Optimal Parallelization:** Minimize total execution time
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- **Resource Efficiency:** Maximize agent utilization
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- **Quality Maintenance:** All quality gates passed
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- **Accurate Estimation:** <10% variance from estimates
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- **Smooth Coordination:** Minimal blocking and waiting
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- **Continuous Improvement:** Learning from each execution
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This AI task orchestration command enables efficient, coordinated execution of complex multi-agent workflows.
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Reference in New Issue
Block a user