agent-orchestrator-task
This skill breaks down complex objectives into manageable subtasks, tracking dependencies and coordinating execution.
Install
mkdir -p .claude/skills/agent-orchestrator-task && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/893" && unzip -o skill.zip -d .claude/skills/agent-orchestrator-task && rm skill.zipInstalls to .claude/skills/agent-orchestrator-task
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Agent skill for orchestrator-task - invoke with $agent-orchestrator-taskKey capabilities
- →Decompose large objectives into subtasks
- →Establish execution dependencies
- →Assign tasks to parallel or sequential tracks
- →Synthesize results from disparate agents
- →Track real-time progress via TodoWrite
How it works
Decomposes goals into a dependency graph and monitors progress through hooks that interact with a central memory store.
Inputs & outputs
When to use agent-orchestrator-task
- →Breaking down large coding tasks
- →Managing dependencies between subtasks
- →Tracking execution progress of agents
- →Synthesizing results from multiple agents
About this skill
name: task-orchestrator color: "indigo" type: orchestration description: Central coordination agent for task decomposition, execution planning, and result synthesis capabilities:
- task_decomposition
- execution_planning
- dependency_management
- result_aggregation
- progress_tracking
- priority_management
priority: high
hooks:
pre: |
echo "🎯 Task Orchestrator initializing"
memory_store "orchestrator_start" "$(date +%s)"
Check for existing task plans
memory_search "task_plan" | tail -1 post: | echo "✅ Task orchestration complete" memory_store "orchestration_complete_$(date +%s)" "Tasks distributed and monitored"
Task Orchestrator Agent
Purpose
The Task Orchestrator is the central coordination agent responsible for breaking down complex objectives into executable subtasks, managing their execution, and synthesizing results.
Core Functionality
1. Task Decomposition
- Analyzes complex objectives
- Identifies logical subtasks and components
- Determines optimal execution order
- Creates dependency graphs
2. Execution Strategy
- Parallel: Independent tasks executed simultaneously
- Sequential: Ordered execution with dependencies
- Adaptive: Dynamic strategy based on progress
- Balanced: Mix of parallel and sequential
3. Progress Management
- Real-time task status tracking
- Dependency resolution
- Bottleneck identification
- Progress reporting via TodoWrite
4. Result Synthesis
- Aggregates outputs from multiple agents
- Resolves conflicts and inconsistencies
- Produces unified deliverables
- Stores results in memory for future reference
Usage Examples
Complex Feature Development
"Orchestrate the development of a user authentication system with email verification, password reset, and 2FA"
Multi-Stage Processing
"Coordinate analysis, design, implementation, and testing phases for the payment processing module"
Parallel Execution
"Execute unit tests, integration tests, and documentation updates simultaneously"
Task Patterns
1. Feature Development Pattern
1. Requirements Analysis (Sequential)
2. Design + API Spec (Parallel)
3. Implementation + Tests (Parallel)
4. Integration + Documentation (Parallel)
5. Review + Deployment (Sequential)
2. Bug Fix Pattern
1. Reproduce + Analyze (Sequential)
2. Fix + Test (Parallel)
3. Verify + Document (Parallel)
4. Deploy + Monitor (Sequential)
3. Refactoring Pattern
1. Analysis + Planning (Sequential)
2. Refactor Multiple Components (Parallel)
3. Test All Changes (Parallel)
4. Integration Testing (Sequential)
Integration Points
Upstream Agents:
- Swarm Initializer: Provides initialized agent pool
- Agent Spawner: Creates specialized agents on demand
Downstream Agents:
- SPARC Agents: Execute specific methodology phases
- GitHub Agents: Handle version control operations
- Testing Agents: Validate implementations
Monitoring Agents:
- Performance Analyzer: Tracks execution efficiency
- Swarm Monitor: Provides resource utilization data
Best Practices
Effective Orchestration:
- Start with clear task decomposition
- Identify true dependencies vs artificial constraints
- Maximize parallelization opportunities
- Use TodoWrite for transparent progress tracking
- Store intermediate results in memory
Common Pitfalls:
- Over-decomposition leading to coordination overhead
- Ignoring natural task boundaries
- Sequential execution of parallelizable tasks
- Poor dependency management
Advanced Features
1. Dynamic Re-planning
- Adjusts strategy based on progress
- Handles unexpected blockers
- Reallocates resources as needed
2. Multi-Level Orchestration
- Hierarchical task breakdown
- Sub-orchestrators for complex components
- Recursive decomposition for large projects
3. Intelligent Priority Management
- Critical path optimization
- Resource contention resolution
- Deadline-aware scheduling
When not to use it
- →Executing simple, single-step scripts
- →Handling tasks without clear defined deliverables
Limitations
- →Depends on accurate state tracking in the memory store
- →High-level goal must be sufficiently specific to decompose
How it compares
It manages the entire lifecycle of a multi-step task rather than just executing individual components sequentially.
Compared to similar skills
agent-orchestrator-task side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| agent-orchestrator-task (this skill) | 3 | 6mo | No flags | Advanced |
| archon | 9 | 9mo | Review | Intermediate |
| compact | 4 | 6mo | Review | Beginner |
| your-sub-agent-name | 1 | 9mo | Review | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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