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Skill

/teach-maestro

Use when starting a new project with Maestro or when no .maestro.md context file exists yet. Run once per project.

From plugin
maestro
41125 skills
Install
$ npx -y skills add sharpdeveye/maestro --skill teach-maestro --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/teach-maestro

Context preview

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

Use when starting a new project with Maestro or when no .maestro.md context file exists yet. Run once per project.

SKILL.md

teach-maestro.SKILL.md
name: teach-maestro
description: "Use when starting a new project with Maestro or when no .maestro.md context file exists yet. Run once per project."
argument-hint: "[project name]"
category: utility
version: 2.0.0
user-invocable: true

BOOTSTRAP — First Command to Run

This is the entry point for Maestro. It creates the `.maestro.md` context file that all other Maestro commands depend on. No other preparation is needed — this IS the preparation.

---

You are conducting a structured interview to understand this project's AI workflow setup. Be conversational but thorough.

Interview Questions

Ask these questions one section at a time. Wait for answers before proceeding.

**Section 1 — Models & Providers**

  • What AI model(s) are you using? (e.g., GPT-4, Claude, Gemini, local models)
  • Are you using APIs directly or through a framework? (e.g., LangChain, LlamaIndex, custom)
  • What are your context window sizes?

**Section 2 — Workflow Architecture**

  • Describe your current workflow at a high level (what goes in, what comes out)
  • Do you have multiple agents/steps, or is it a single-agent system?
  • What tools/functions are available to your agent(s)?

**Section 3 — Quality & Evaluation**

  • How do you currently evaluate output quality?
  • Do you have test cases or golden examples?
  • What are the most common failure modes?

**Section 4 — Constraints**

  • What are your cost constraints? (budget per request, per day)
  • What are your latency requirements? (real-time, batch, async)
  • Are there compliance requirements? (HIPAA, GDPR, SOC2, etc.)

**Section 5 — Priorities**

  • Rank these from most to least important: Quality, Speed, Cost, Safety
  • What's the single biggest workflow problem you want to solve?

Output Format

After gathering all answers, generate a `.maestro.md` file:

# Maestro Workflow Context
Generated: [date]

## Models & Providers
[answers from section 1]

## Workflow Architecture
[answers from section 2]

## Quality & Evaluation
[answers from section 3]

## Constraints
[answers from section 4]

## Priorities
[answers from section 5, with ranked priorities]

Save this file to the project root as `.maestro.md`.

Context Completeness

| Section | Status | Impact if Missing | |---------|--------|-------------------| | Models & Providers | ? | Commands can't tailor advice to your stack | | Workflow Architecture | ? | Commands can't assess complexity | | Quality & Evaluation | ? | `/iterate` and `/evaluate` less effective | | Constraints | ? | `/guard` and `/accelerate` can't set limits | | Priorities | ? | All commands default to generic guidance |

Interview Checklist

  • [ ] All 5 sections asked and answered
  • [ ] Answers are specific (not vague)
  • [ ] `.maestro.md` file generated and saved
  • [ ] User confirmed accuracy of the generated context

Recommended Next Step

After creating `.maestro.md`, run `/diagnose` for a baseline health check of your workflow.

**NEVER**:

  • Skip questions — every section matters for downstream commands
  • Make assumptions — ask if unclear
  • Overwrite an existing `.maestro.md` without asking
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
License
3mo ago
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4mo ago
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Repo: sharpdeveye/maestro