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AI & Agents
Skill

/onboard-agent

Use when starting a new project, adding a new agent to an existing system, or setting up workflow infrastructure from scratch.

From plugin
maestro
41125 skills
Install
$ npx -y skills add sharpdeveye/maestro --skill onboard-agent --agent claude-code

How 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/onboard-agent

Context preview

The summary Claude sees to decide when to auto-load this skill.

Use when starting a new project, adding a new agent to an existing system, or setting up workflow infrastructure from scratch.

SKILL.md

onboard-agent.SKILL.md
name: onboard-agent
description: "Use when starting a new project, adding a new agent to an existing system, or setting up workflow infrastructure from scratch."
argument-hint: "[project or agent name]"
category: utility
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.

---

Bootstrap a new agent workflow from scratch, or add a new agent to an existing system.

Step 1: Establish Conventions

## Workflow Conventions
### Prompt Format
- Delimiter style: [XML tags / markdown headers / triple-dash]
- Section order: [System → Context → Instructions → Input]
- Output format: [JSON with schema / markdown template]

### Tool Conventions
- Naming: [verb_noun / noun.verb / camelCase]
- Description template: [What → When → When Not → Returns]
- Error format: [{ code, message, details }]

### Logging
- Format: [JSON structured]
- Required fields: [workflow_id, step, timestamp, level]

### File Structure
- Prompts: [prompts/workflow-name/v1.md]
- Tools: [tools/tool-name.{ext}]
- Config: [config/environment.yaml]
- Tests: [tests/workflow-name/]

Step 2: Create Initial Structure

project/
├── prompts/          # System prompts, versioned
├── tools/            # Tool definitions
├── config/           # Environment-specific configuration
├── tests/            # Golden test sets and evaluation suites
├── logs/             # Runtime logs (gitignored)
└── .maestro.md       # Workflow context

Step 3: Create the First Agent

1. **System prompt**: Role definition with constraints 2. **2-3 essential tools**: Start with the minimum viable tool set 3. **Output schema**: Define expected output format 4. **One golden test**: At least one test case with known-good output 5. **Basic error handling**: Structured error responses 6. **Logging**: Structured log output for each run

Step 4: Verify

  • Run the agent with the golden test case
  • Verify error handling works (send bad input)
  • Verify logging captures useful context

Recommended Next Step

After onboarding, run `/diagnose` for a baseline health check, then `/fortify` to add production-grade error handling.

**NEVER**:

  • Start building without establishing conventions
  • Create tools without descriptions
  • Skip the golden test case
  • Over-scope the initial agent (start minimal, amplify later)
Read more
Ships withmaestro

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.

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TypeScript
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MIT
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3mo ago
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4mo ago
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Repo: sharpdeveye/maestro