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Multi Agent

Organization
memi-design
multi-agent

Orchestrate multiple Claude instances on Figma canvas with box widgets, coordinated handoffs, error recovery

Overview

Publishermemi-design
Repositorydesign-skills
Skill namemulti-agent
Stars
7
Forks
0
Bundled files
1
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by memi-design on GitHub. Read the source before you install it.

Installation

Install the Multi Agent 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/memi-design/design-skills/tree/main/skills/multi-agent
  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/memi-design/design-skills.git /tmp/design-skills
mkdir -p .claude/skills
cp -r /tmp/design-skills/skills/multi-agent .claude/skills/multi-agent
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Multi Agent 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 Multi Agent 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 Multi Agent 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.

/multi-agent — Parallel Agent Workflows in Figma

Orchestrate multiple Claude instances on the Figma canvas with full transparency via box widgets, coordinated handoffs, and error recovery. Requires /figma-use.

Freedom Level: High

Each agent operates autonomously within its scope. The orchestrator coordinates handoffs and resolves conflicts.

Architecture

Port Allocation

Port 9223 → Primary agent (orchestrator)
Port 9224 → Token engineer
Port 9225 → Component architect
Port 9226 → Layout designer
Port 9227 → Code generator
Port 9228-9232 → Additional specialists

The Mémoire plugin auto-discovers all instances via port scanning (9223-9232) every 5 seconds.

Instance Identification

Each agent instance should use a distinct bridge session name:

memi connect --name "Token Agent"
memi connect --name "Component Agent"
memi connect --name "Layout Agent"

Box Widget Protocol

Every agent creates a status box on the Figma canvas for human visibility.

Creating a Box

javascript
let agentSection = figma.currentPage.findOne(
  n => n.type === 'SECTION' && n.name === 'Active Agents'
);
if (!agentSection) {
  agentSection = figma.createSection();
  agentSection.name = 'Active Agents';
  agentSection.x = -400;
  agentSection.y = 0;
}

const box = figma.createFrame();
box.name = `[${role}] ${task}`;
box.layoutMode = 'VERTICAL';
box.primaryAxisSizingMode = 'AUTO';
box.counterAxisSizingMode = 'FIXED';
box.resize(300, 1);
box.paddingLeft = box.paddingRight = 12;
box.paddingTop = box.paddingBottom = 10;
box.itemSpacing = 4;
box.cornerRadius = 8;
box.fills = [{ type: 'SOLID', color: { r: 0.06, g: 0.06, b: 0.12 }, opacity: 0.95 }];
box.strokes = [{ type: 'SOLID', color: statusBorderColor }];
box.strokeWeight = 1.5;
agentSection.appendChild(box);

Status Colors

javascript
const statusColors = {
  idle:  { r: 0.3, g: 0.3, b: 0.4 },   // Gray-blue
  busy:  { r: 0.96, g: 0.62, b: 0.04 }, // Amber
  error: { r: 0.94, g: 0.27, b: 0.27 }, // Red
  done:  { r: 0.06, g: 0.73, b: 0.51 }, // Green
};

Updating & Collapsing

javascript
// Update status
myBox.name = `[${role}] ${newTask}`;
myBox.strokes = [{ type: 'SOLID', color: statusColors[status] }];

// Collapse on completion
myBox.resize(300, 28);
myBox.name = `✓ [${role}] Complete`;
myBox.fills = [{ type: 'SOLID', color: { r: 0.04, g: 0.45, b: 0.34 }, opacity: 0.3 }];

Coordination Patterns

Pattern 1: Pipeline (Sequential Handoff)

Token Engineer → Component Architect → Layout Designer → Code Generator
     ↓                   ↓                    ↓                ↓
  Variables         Components            Pages           React code

Each agent waits for the previous to broadcast completion.

Pattern 2: Parallel Atoms (Fan-Out)

Orchestrator
├── Agent A: builds Button, Badge, Avatar, Icon
├── Agent B: builds Input, Label, Select, Checkbox
├── Agent C: builds Card, Separator, Tooltip, Dialog
└── Merge: all atoms ready → continue to molecules

Pattern 3: Page Parallel (Independent)

Orchestrator
├── Agent A: designs Dashboard page
├── Agent B: designs Auth pages (Login, Signup, Forgot)
├── Agent C: designs Settings pages
└── Each agent runs full atomic pipeline for its scope

Pattern 4: Research + Design (Concurrent)

Research Agent: analyzing data, producing insights
Design Agent: building components as research completes
Code Agent: generating code as designs stabilize
All three work simultaneously, communicating via agent-broadcast

Error Recovery Protocol

When an agent encounters an error:

1. Update box widget: status → "error", show error message
2. Publish visible status with the canvas widget and bridge `agent-status`
3. Attempt self-fix (max 2 retries)
4. If unrecoverable:
   a. Broadcast failure to orchestrator
   b. Orchestrator reassigns task or adjusts plan
   c. Box widget stays red until resolved
5. Never silently fail — always visible in Figma

Message Protocol

typescript
// Agent announcing status
{ type: 'agent-status', role: string, task: string, status: 'idle'|'busy'|'error'|'done' }

// Agent sending results to others
{ type: 'agent-broadcast', text: string, data: any, target?: string }

// Requesting agent list
{ type: 'agent-list' }
// Response: { agents: [{ id, role, task, status, capabilities }] }

Anti-Patterns

  • Two agents modifying the same component simultaneously (use locking)
  • Agents not announcing their role on connect
  • Skipping box widgets (humans lose visibility)
  • Not collapsing boxes on completion (visual clutter)
  • Agents working without checking what others have built
  • Silently failing without updating box widget status

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Multi Agent AI skill do?

Orchestrate multiple Claude instances on Figma canvas with box widgets, coordinated handoffs, error recovery

Why use Multi Agent on TypingMind?

Because you install it once and use it with any model. Multi Agent 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 Multi Agent in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/memi-design/design-skills/tree/main/skills/multi-agent. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Multi Agent?

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 Multi Agent?

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

Is the Multi Agent AI skill free?

Yes. It is published on GitHub by memi-design 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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