Task Orchestra

Coordinate multiple agents and tasks for complex workflows.

When to Use

• - Multi-step operations requiring coordination
• Parallel execution of independent tasks
• Complex workflows with dependencies
• Orchestrating subagents for large projects

Core Capabilities

1. Task Coordination

• - Break down complex tasks into manageable steps
• Manage dependencies between tasks
• Coordinate parallel execution
• Handle task sequencing and scheduling

2. Agent Orchestration

• - Spawn and manage multiple subagents
• Route tasks to appropriate agents
• Monitor progress and handle failures
• Aggregate results from multiple sources

3. Workflow Management

• - Define workflow patterns and templates
• Implement error handling and recovery
• Manage state and progress tracking
• Coordinate handoffs between agents

4. Dependency Resolution

• - Analyze task dependencies
• Create execution order
• Handle conditional execution
• Manage resource conflicts

Orchestration Patterns

1. Sequential Execution

2. Parallel Execution

3. Pipeline Processing

4. Supervisor Pattern

5. Event-Driven Processing

Quick Actions

• - orchestrate [workflow] - Execute complex workflow
• INLINECODE1 - Run tasks in parallel
• INLINECODE2 - Chain tasks in sequence
• INLINECODE3 - Manage multiple agents
• INLINECODE4 - Analyze and resolve dependencies

Usage Examples

CODEBLOCK5

Workflow Templates

Research Project

Content Creation

Software Development

Agent Management

Spawning Agents

Monitoring Progress

Handling Failures

Dependency Resolution

Types of Dependencies

• - Data Dependencies: Task B needs output from Task A
• Resource Dependencies: Tasks sharing same resources
• Order Dependencies: Tasks must run in specific order
• Conditional Dependencies: Task runs only if condition met

Resolution Process

Error Handling

Common Failure Scenarios

• - Agent Failure: Subagent crashes or times out
• Dependency Failure: Required task fails
• Resource Conflict: Multiple agents need same resource
• Network Issues: API calls fail or timeout

Recovery Strategies

• - Retry: Attempt failed task again
• Alternative: Use different approach or agent
• Skip: Continue without failed task
• Rollback: Undo previous steps

State Management

Progress Tracking

• - Track completed tasks
• Monitor current execution
• Record task results
• Maintain workflow state

Checkpointing

• - Save progress at key points
• Enable restart from checkpoints
• Maintain consistency across failures

Communication Patterns

Parent → Child

Child → Parent

Agent → Agent

Performance Optimization

Parallel Execution

• - Identify independent tasks
• Run in parallel when possible
• Aggregate results efficiently

Resource Management

• - Monitor agent resource usage
• Balance load across agents
• Avoid resource conflicts

Efficiency Metrics

• - Task completion time
• Resource utilization
• Error rates
• Success rates

Safety Considerations

Agent Limits

• - Max 10 concurrent subagents
• Max 2 levels of nesting
• 10-minute timeout per agent
• Automatic cleanup

Data Integrity

• - Validate task inputs/outputs
• Maintain consistency
• Handle partial failures
• Ensure atomic operations

Advanced Patterns

1. Hierarchical Orchestration

2. Dynamic Work Allocation

3. Event-Driven Workflows

4. Adaptive Planning

Integration with Other Skills

Self-Evolution

• - Use for complex self-improvement tasks
• Coordinate multiple evolution agents
• Manage long-term capability building

Analysis Skills

• - Orchestrate research projects
• Coordinate data analysis
• Manage multi-step investigations

Content Creation

• - Coordinate content production pipelines
• Manage multi-agent content creation
• Orchestrate publication workflows

Quick Reference

Common Commands

Workflow Examples

Best Practices

1. 1. Start Simple: Begin with sequential execution
2. Add Parallelism: Identify independent tasks
3. Handle Failures: Implement robust error handling
4. Monitor Progress: Track execution and results
5. Optimize Performance: Balance load and resources

Success Metrics

• - Task completion rate
• Execution time efficiency
• Resource utilization
• Error recovery effectiveness
• Overall workflow success