multi-agent-orchestration
Use when coordinating multiple specialized agents for complex distributed tasks. Keywords: multi-agent, orchestrator, subagent, handoff, swarm, supervisor, agent topology, coordination.
Install
npx skills add https://github.com/VoDaiLocz/kilo-kit-mcp/tree/main/skills/agent-frameworks/multi-agent-orchestration
claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install vodailocz-kilo-kit-mcp@llmmart
git clone https://github.com/VoDaiLocz/kilo-kit-mcp.git
The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole vodailocz/kilo-kit-mcp collection as a plugin from our marketplace. Git is the plain clone.
Skill manifest
Multi-Agent Orchestration
Overview
This skill provides a framework for designing and managing multi-agent systems where specialized agents collaborate on complex, multi-stage workflows. It emphasizes clear agent boundaries, structured communication, and robust error isolation.
When To Use
- When tasks are too large or diverse for a single agent (scope creep).
- When specific domain expertise (e.g., database design, UI/UX, security) is required in separate, modular contexts.
- To maintain clean separation of concerns and reduce context window degradation.
- When you need to delegate parallelizable work to maximize throughput.
Topology Patterns
- Hierarchical Supervisor: A central supervisor agent delegates sub-tasks to specialized workers, aggregates their results, and provides final synthesis.
- Swarm Handoffs: Agents pass tasks directly to the next appropriate agent based on completion criteria, forming a chain or graph of expertise.
- Router-Worker: A router analyzes incoming requests and dispatches them to a specific pool of workers based on classification.
- Blackboard: Multiple agents read from and write to a shared persistent state (the "blackboard") until a task objective is satisfied.
- Round-Robin Debate: Agents with opposing viewpoints propose solutions, iterate, and refine based on peer criticism to improve quality.
Communication Protocols
- Agent-to-Agent (A2A): Always use structured message framing.
- Structured Payloads: Encapsulate tasks, constraints, and dependencies in a common JSON format or structured Markdown.
- Return Summaries: Every subagent MUST return a concise summary of work done, resources created, and final status (SUCCESS/FAIL/BLOCKED) before closing the conversation.
Context Isolation & Boundary Hand-offs
- Ephemeral Context: Spawn subagents with only the minimal, high-signal information needed for their specific task.
- Avoid Token Bloat: Do not pass the entire parent conversation history unless strictly necessary. Pass pointers to file locations or artifact links instead.
- Clean State: Each subagent should operate within its own branched workspace to prevent side effects on the parent or other subagents.
Failure Isolation
- Localized Faults: Subagent crashes must be caught by the parent via message timeout or error reporting mechanisms.
- Graceful Retries: Implement retry logic for discrete sub-tasks. If a worker fails, the supervisor should attempt to diagnose the root cause (using Root Cause Tracing) before retrying or pivoting strategy.
- Never Crash Parent: A subagent failure should trigger an alert in the parent agent, not an unhandled exception that propagates to the user.
Task Decomposition Strategies
- Parallel Execution: Use when tasks are independent (e.g., unit tests for different modules, gathering info from multiple docs).
- Sequential Execution: Use when tasks have strict causal dependencies (e.g., design -> implement -> review -> deploy).
- Merge Points: Define clear synchronization points where context from different agents is consolidated, validated, and refined by the supervisor.
State Sharing Patterns
- Shared Artifacts: Write common results to files in the shared artifacts/ directory.
- Blackboard Memory: Use shared databases or documented state files for common configurations or global project context.
- Message Bus: Use the parent agent as the hub for all inter-agent messages.
Anti-patterns
- God Orchestrator: A single agent attempting to do everything; leads to poor specialization and context degradation.
- Circular Dependencies: Agents waiting on each other indefinitely; always define a clear directed acyclic graph (DAG) of task flow.
- Context Explosion: Passing the entire project state to every subagent; use selective scoping instead.
- Silent Failures: Subagents finishing without reporting status; every interaction must have an explicit "done" or "blocked" signal.
Quality Gates
- Pre-Handoff Check: Does the subagent have everything it needs? (Requirements, constraints, deadline).
- Post-Handoff Review: Does the output meet the original task intent? Does it need further refinement before the next step?
- Final Integration: Verify the combined results of all subagents against original user acceptance criteria.
References
- KILO-KIT Core Principles (skills/kilo-kit/SKILL.md)
- Systematic Debugging (skills/systematic-debugging/SKILL.md)
- Architecture Decision Making (skills/architecture/SKILL.md)
Files (kilo-kit-mcp)
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SKILL.md 4.7 KB
--- name: "multi-agent-orchestration" description: >- Use when coordinating multiple specialized agents for complex distributed tasks. Keywords: multi-agent, orchestrator, subagent, handoff, swarm, supervisor, agent topology, coordination. --- # Multi-Agent Orchestration ## Overview This skill provides a framework for designing and managing multi-agent systems where specialized agents collaborate on complex, multi-stage workflows. It emphasizes clear agent boundaries, structured communication, and robust error isolation. ## When To Use - When tasks are too large or diverse for a single agent (scope creep). - When specific domain expertise (e.g., database design, UI/UX, security) is required in separate, modular contexts. - To maintain clean separation of concerns and reduce context window degradation. - When you need to delegate parallelizable work to maximize throughput. ## Topology Patterns - **Hierarchical Supervisor**: A central supervisor agent delegates sub-tasks to specialized workers, aggregates their results, and provides final synthesis. - **Swarm Handoffs**: Agents pass tasks directly to the next appropriate agent based on completion criteria, forming a chain or graph of expertise. - **Router-Worker**: A router analyzes incoming requests and dispatches them to a specific pool of workers based on classification. - **Blackboard**: Multiple agents read from and write to a shared persistent state (the "blackboard") until a task objective is satisfied. - **Round-Robin Debate**: Agents with opposing viewpoints propose solutions, iterate, and refine based on peer criticism to improve quality. ## Communication Protocols - **Agent-to-Agent (A2A)**: Always use structured message framing. - **Structured Payloads**: Encapsulate tasks, constraints, and dependencies in a common JSON format or structured Markdown. - **Return Summaries**: Every subagent MUST return a concise summary of work done, resources created, and final status (SUCCESS/FAIL/BLOCKED) before closing the conversation. ## Context Isolation & Boundary Hand-offs - **Ephemeral Context**: Spawn subagents with only the minimal, high-signal information needed for their specific task. - **Avoid Token Bloat**: Do not pass the entire parent conversation history unless strictly necessary. Pass pointers to file locations or artifact links instead. - **Clean State**: Each subagent should operate within its own branched workspace to prevent side effects on the parent or other subagents. ## Failure Isolation - **Localized Faults**: Subagent crashes must be caught by the parent via message timeout or error reporting mechanisms. - **Graceful Retries**: Implement retry logic for discrete sub-tasks. If a worker fails, the supervisor should attempt to diagnose the root cause (using Root Cause Tracing) before retrying or pivoting strategy. - **Never Crash Parent**: A subagent failure should trigger an alert in the parent agent, not an unhandled exception that propagates to the user. ## Task Decomposition Strategies - **Parallel Execution**: Use when tasks are independent (e.g., unit tests for different modules, gathering info from multiple docs). - **Sequential Execution**: Use when tasks have strict causal dependencies (e.g., design -> implement -> review -> deploy). - **Merge Points**: Define clear synchronization points where context from different agents is consolidated, validated, and refined by the supervisor. ## State Sharing Patterns - **Shared Artifacts**: Write common results to files in the shared artifacts/ directory. - **Blackboard Memory**: Use shared databases or documented state files for common configurations or global project context. - **Message Bus**: Use the parent agent as the hub for all inter-agent messages. ## Anti-patterns - **God Orchestrator**: A single agent attempting to do everything; leads to poor specialization and context degradation. - **Circular Dependencies**: Agents waiting on each other indefinitely; always define a clear directed acyclic graph (DAG) of task flow. - **Context Explosion**: Passing the entire project state to every subagent; use selective scoping instead. - **Silent Failures**: Subagents finishing without reporting status; every interaction must have an explicit "done" or "blocked" signal. ## Quality Gates - **Pre-Handoff Check**: Does the subagent have everything it needs? (Requirements, constraints, deadline). - **Post-Handoff Review**: Does the output meet the original task intent? Does it need further refinement before the next step? - **Final Integration**: Verify the combined results of all subagents against original user acceptance criteria. ## References - KILO-KIT Core Principles (skills/kilo-kit/SKILL.md) - Systematic Debugging (skills/systematic-debugging/SKILL.md) - Architecture Decision Making (skills/architecture/SKILL.md)
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