/compose
Use when a single agent demonstrably cannot handle the task and multi-agent coordination is justified.
$ npx -y skills add sharpdeveye/maestro --skill compose --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/compose
Context preview
The summary Claude sees to decide when to auto-load this skill.
Use when a single agent demonstrably cannot handle the task and multi-agent coordination is justified.
SKILL.md
compose.SKILL.mdname: 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
MANDATORY PREPARATION
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?
Step 1: Pre-Composition Check
Answer these before proceeding:
1. **Has a single agent been tried and failed?** (If no, try single agent first) 2. **What specific limitation requires multiple agents?** (If you can't name it, you don't need multi-agent) 3. **Is the cost/latency increase justified?** (Multi-agent = 2-10x cost and latency)
If you can't articulate a specific limitation, use /amplify on the single agent instead.
Step 2: Design the Topology
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]
Step 3: Design Handoffs
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?]
Step 4: Design the Supervisor
Every multi-agent system needs a supervisor:
- Monitors agent health and performance
- Routes tasks to appropriate agents
- Handles failures and escalation
- Enforces global constraints (budget, time, quality)
Composition Checklist
- [ ] Each agent has a clear, non-overlapping role
- [ ] Handoff protocols are defined for every connection
- [ ] A supervisor pattern is in place
- [ ] Cost/latency budget accounts for all agents
- [ ] Failure modes are handled at every handoff point
- [ ] The system can be understood by reading the topology diagram
Recommended Next Step
After composition, run `/fortify` to add error handling at every handoff, then `/evaluate` to test the multi-agent system end-to-end.
**NEVER**:
- Build multi-agent for a problem a single agent can handle
- Create agents with overlapping responsibilities
- Skip the supervisor (autonomous swarms are unpredictable)
- Pass full context between all agents (pass only what's needed)
- Compose without defining handoff protocols
Read more
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
MANDATORY PREPARATION
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?
Step 1: Pre-Composition Check
Answer these before proceeding:
1. **Has a single agent been tried and failed?** (If no, try single agent first) 2. **What specific limitation requires multiple agents?** (If you can't name it, you don't need multi-agent) 3. **Is the cost/latency increase justified?** (Multi-agent = 2-10x cost and latency)
If you can't articulate a specific limitation, use /amplify on the single agent instead.
Step 2: Design the Topology
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]
Step 3: Design Handoffs
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?]
Step 4: Design the Supervisor
Every multi-agent system needs a supervisor:
- Monitors agent health and performance
- Routes tasks to appropriate agents
- Handles failures and escalation
- Enforces global constraints (budget, time, quality)
Composition Checklist
- [ ] Each agent has a clear, non-overlapping role
- [ ] Handoff protocols are defined for every connection
- [ ] A supervisor pattern is in place
- [ ] Cost/latency budget accounts for all agents
- [ ] Failure modes are handled at every handoff point
- [ ] The system can be understood by reading the topology diagram
Recommended Next Step
After composition, run `/fortify` to add error handling at every handoff, then `/evaluate` to test the multi-agent system end-to-end.
**NEVER**:
- Build multi-agent for a problem a single agent can handle
- Create agents with overlapping responsibilities
- Skip the supervisor (autonomous swarms are unpredictable)
- Pass full context between all agents (pass only what's needed)
- Compose without defining handoff protocols
Workflow fluency for AI coding agents. 1 core skill · 25 commands · 7 domain references · memory layer · audit trail — works across Cursor, Claude Code, Gemini CLI, Copilot, and 6 more.
Repo: sharpdeveye/maestro
Other skills on maestro.
- /accelerate
Use when the workflow is too slow, too expensive, or both and needs latency, cost, or token usage optimization.
Open skill - /adapt-workflow
Use when porting a workflow to a different AI provider, deployment environment, model tier, or organizational context.
Open skill - /agent-workflow
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.
Open skill - /amplify
Use when the workflow works but needs to handle more complex cases or produce higher-quality output through better tools, context, prompts, or models.
Open skill - /calibrate
Use when workflow components are inconsistent, naming conventions vary, or a new team member's work needs alignment to project standards.
Open skill - /capture
Capture a session summary — what was done, what decisions were made, and what to do next.
Open skill

