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Use when a single agent demonstrably cannot handle the task and multi-agent coordination is justified.
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Based on SOC occupation classification
Use when the workflow is too slow, too expensive, or both and needs latency, cost, or token usage optimization.
Use when porting a workflow to a different AI provider, deployment environment, model tier, or organizational context.
Use when any Maestro command is invoked — provides foundational workflow design principles across prompt engineering, context management, tool orchestration, agent architecture, feedback loops, knowledge systems, and guardrails.
Use when the workflow works but needs to handle more complex cases or produce higher-quality output through better tools, context, prompts, or models.
Use when workflow components are inconsistent, naming conventions vary, or a new team member's work needs alignment to project standards.
Capture a session summary — what was done, what decisions were made, and what to do next.
| name | compose |
| description | Use when a single agent demonstrably cannot handle the task and multi-agent coordination is justified. |
| argument-hint | [workflow description] |
| category | enhancement |
| version | 2.0.0 |
| user-invocable | true |
Invoke /agent-workflow — it contains workflow principles, anti-patterns, and the Context Gathering Protocol. Follow the protocol before proceeding — if no workflow context exists yet, you MUST run /teach-maestro first. Consult the agent-architecture reference in the agent-workflow skill for topology patterns and when multi-agent is justified.
Design a multi-agent system. But first — are you sure you need one?
Answer these before proceeding:
If you can't articulate a specific limitation, use /amplify on the single agent instead.
Choose the right architecture pattern (consult the agent-architecture reference in the agent-workflow skill):
For each agent in the system, define:
## Agent: [Name]
Role: [One sentence]
Responsibilities: [What it does]
Boundaries: [What it does NOT do]
Tools: [List of tools this agent has access to]
Input: [What it receives]
Output: [What it produces]
For each agent-to-agent connection:
## Handoff: [Agent A] → [Agent B]
Trigger: [When does A hand off to B?]
Payload: [What data is passed?]
Expected response: [What does A expect back?]
Timeout: [How long to wait?]
Failure handling: [What if B fails?]
Every multi-agent system needs a supervisor:
After composition, run /fortify to add error handling at every handoff, then /evaluate to test the multi-agent system end-to-end.
NEVER: