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Compose

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sharpdeveye
compose

Use when a single agent demonstrably cannot handle the task and multi-agent coordination is justified.

Overview

Publishersharpdeveye
Repositorymaestro
Skill namecompose
Stars
591
Forks
73
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by sharpdeveye on GitHub. Read the source before you install it.

Installation

Install the Compose AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/sharpdeveye/maestro/tree/main/source/skills/compose
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/sharpdeveye/maestro.git /tmp/maestro
mkdir -p .claude/skills
cp -r /tmp/maestro/source/skills/compose .claude/skills/compose
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Compose in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Compose on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Compose is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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:

markdown
## 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:

markdown
## 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

Frequently asked questions

What does the Compose AI skill do?

Use when a single agent demonstrably cannot handle the task and multi-agent coordination is justified.

Why use Compose on TypingMind?

Because you install it once and use it with any model. Compose is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Compose in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/sharpdeveye/maestro/tree/main/source/skills/compose. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Compose?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Compose?

As many as you like. As long as a model supports skills, you can use Compose with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Compose AI skill free?

Yes. It is published on GitHub by sharpdeveye under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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