By name: mpm-orchestration-demo description: Reference implementation demonstrating the Command → Agent → Skill orchestration pattern in Claude MPM, showing both preloaded-skill and dynamic-skill-invocation styles argument-hint: "[topic]" user-invocable: true disable-model-invocation: true version: 1.1.0 category: universal author: Claude MPM Team license: MIT progressive_disclosure: entry_point: summary: "Canonical MPM orchestration example: Command → Agent → Skill with two invocation styles" when_to_use: "When building new MPM workflows, onboarding to MPM patterns, or referencing orchestration best practices" quick_start: "Run /mpm-orchestration-demo to see the pattern in action" references: - orchestration-patterns.md context_limit: 600 tags:
- orchestration
- patterns
- reference
- mpm
- agents
- skills requires_tools: []
MPM Orchestration Demo
Overview
This skill is the canonical reference for the Command → Agent → Skill orchestration pattern in Claude MPM. It demonstrates a code review workflow that shows how commands, agents, and skills compose together — and the two distinct ways a skill can be invoked.
Understanding this pattern is the foundation for building any non-trivial MPM workflow.
The Two Invocation Styles
Style 1: Preloaded Skills (Frontmatter)
A skill is listed in an agent's skills: frontmatter. The full skill content is injected into the agent's context at startup, becoming embedded domain knowledge.
# .claude/agents/code-reviewer.md
---
name: code-reviewer
description: Reviews code for quality, security, and correctness
skills:
- code-review-checklist # Injected at startup
model: sonnet
---
When to use: The agent always needs this knowledge. It's core to the agent's purpose — not situational.
Characteristics:
- Content is present from the first turn
- No tool call overhead
- Consumes context tokens even if not needed
- Best for 1–3 essential knowledge bases
Style 2: Dynamic Invocation (Skill Tool)
A skill is invoked at runtime using the Skill tool. The command or agent calls Skill(skill: "skill-name") when it needs that capability.
# In a command or agent's instructions
Skill(skill: "security-scanner")
When to use: The capability is situational — only needed under certain conditions or after gathering initial data.
Characteristics:
- Invoked only when needed
- Preserves context tokens otherwise
- Enables conditional logic ("if security issues found, invoke scanner")
- Best for optional, conditional, or heavyweight operations
Concrete Example: Code Review Orchestration
This demo implements a three-component code review system.
Flow
╔══════════════════════════════════════════════════════════════════╗
║ CODE REVIEW ORCHESTRATION ║
║ Command → Agent → Skill ║
╚══════════════════════════════════════════════════════════════════╝
┌─────────────────────┐
│ User invokes │
│ /code-review-demo │
└──────────┬──────────┘
│
▼
┌──────────────────────────────────────────────────┐
│ /code-review-demo — Command (Entry Point) │
│ 1. Accept file path argument │
│ 2. Invoke code-reviewer agent (Agent tool) │
│ 3. If issues found: Skill("issue-formatter") │
└──────────────────────┬───────────────────────────┘
│
Agent tool call
│
▼
┌──────────────────────────────────────────────────┐
│ code-reviewer — Agent │
│ skills: [code-review-checklist] ← Style 1 │
│ │
│ Uses preloaded checklist to review the file │
│ Returns: list of issues (or "no issues") │
└──────────────────────┬───────────────────────────┘
│
Returns issues
│
┌──────────────────────▼───────────────────────────┐
│ Command receives issues │
│ Conditionally invokes: │
│ Skill("issue-formatter") ← Style 2 │
└──────────────────────┬───────────────────────────┘
│
▼
┌─────────────────────┐
│ issue-formatter │
│ Formats and writes │
│ review-report.md │
└─────────────────────┘
Component Definitions
Command: /code-review-demo
---
# .claude/commands/code-review-demo.md
description: Demo orchestration command for code review workflow
model: haiku
---
# Code Review Demo
Accept a file path as $ARGUMENTS.
1. Use the Agent tool to invoke code-reviewer:
Agent(subagent_type="code-reviewer", prompt="Review $ARGUMENTS for quality and security issues")
2. If the agent returns any issues:
Skill(skill: "issue-formatter")
3. Report: file reviewed, issue count, report location (if written)
Agent: code-reviewer
---
# .claude/agents/code-reviewer.md
name: code-reviewer
description: Reviews code files for quality, security, and correctness
tools: Read
model: sonnet
skills:
- code-review-checklist
---
You are a code reviewer. Use your preloaded code-review-checklist skill to
evaluate the file specified in the prompt. Return a structured list of issues,
or "NO_ISSUES" if the code is clean.
Preloaded Skill: code-review-checklist
---
# .claude/skills/code-review-checklist/SKILL.md
name: code-review-checklist
user-invocable: false
---
# Code Review Checklist
Review code against these criteria:
1. Input validation — are all inputs validated before use?
2. Error handling — are errors caught and handled gracefully?
3. Null safety — are null/undefined values handled?
4. Security — SQL injection, XSS, hardcoded secrets?
5. Complexity — functions over 20 lines or cyclomatic complexity > 5?
Return findings as:
ISSUE: [line] [severity] [description]
Dynamic Skill: issue-formatter
---
# .claude/skills/issue-formatter/SKILL.md
name: issue-formatter
description: Formats code review findings into a structured markdown report
---
# Issue Formatter
Format the issues from the current conversation into review-report.md.
Structure:
- Summary: total issues by severity
- Critical issues (fix before merge)
- Warnings (should fix)
- Suggestions (optional improvements)
Pattern Template
Copy this template when building a new MPM orchestration workflow:
COMMAND (.claude/commands/my-workflow.md)
├── Accepts user arguments
├── Invokes specialized AGENT via Agent tool
│ └── Agent has PRELOADED SKILL(s) for core knowledge (Style 1)
├── Receives structured result from agent
└── Conditionally invokes DYNAMIC SKILL via Skill tool (Style 2)
└── Skill formats or persists the result
Checklist for New Workflows
- Command is the single entry point and orchestrator
- Agents are specialized (one responsibility)
- Preloaded skills contain always-needed domain knowledge
- Dynamic skills contain conditional or output-specific logic
- Agent returns structured data, not prose
- Command handles the "what to do with results" logic
Anti-Patterns
Don't preload everything. Loading 5 skills into an agent wastes context tokens and slows startup. Preload only core domain knowledge; invoke the rest dynamically.
Don't put orchestration logic in agents. An agent should do one thing and return data. Decision logic ("if issues found, format them") belongs in the command.
Don't invoke subagents from subagents. Subagents cannot invoke other subagents via bash. All agent invocations must go through the Agent tool from a command or orchestrator context.
Don't skip structured return values. An agent that returns unstructured prose is hard to act on. Define a clear return format (e.g., ISSUE: [line] [severity] [desc]) so the command can make decisions.
Don't duplicate skill content. If two agents need the same knowledge, create one shared skill and preload it into both. Never copy-paste skill content into agent definitions.
Navigation
- Orchestration Patterns: Deep-dive reference — annotated weather system example, when to use each style, the
context: forkpattern for forked sub-agents that inherit parent context, agent communication patterns, error handling