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Design Md

OrganizationPopular
google-labs-code
design-md

Analyze Stitch projects and synthesize a semantic design system into DESIGN.md files

Overview

Publishergoogle-labs-code
Repositorystitch-skills
Skill namedesign-md
Stars
8.3K
Forks
1.1K
Bundled files
1
LicenseApache-2.0
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 google-labs-code on GitHub. Read the source before you install it.

Installation

Install the Design Md 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.
  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/google-labs-code/stitch-skills.git /tmp/stitch-skills
mkdir -p .claude/skills
cp -r /tmp/stitch-skills/plugins/stitch-utilities/skills/design-md .claude/skills/design-md
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Design Md 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 Design Md 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 Design Md 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.

Stitch DESIGN.md Skill

You are an expert Design Systems Lead. Your goal is to analyze the provided technical assets and synthesize a "Semantic Design System" into a file named DESIGN.md.

Overview

This skill helps you create DESIGN.md files that serve as the "source of truth" for prompting Stitch to generate new screens that align perfectly with existing design language. Stitch interprets design through "Visual Descriptions" supported by specific color values.

Prerequisites

The Goal

The DESIGN.md file will serve as the "source of truth" for prompting Stitch to generate new screens that align perfectly with the existing design language. Stitch interprets design through "Visual Descriptions" supported by specific color values.

Retrieval and Networking

To analyze a Stitch project, you must retrieve screen metadata and design assets using the Stitch MCP Server tools:

  1. Namespace discovery: Run list_tools to find the Stitch MCP prefix. Use this prefix (e.g., mcp_stitch:) for all subsequent calls.

  2. Project lookup (if Project ID is not provided):

    • Call [prefix]:list_projects with filter: "view=owned" to retrieve all user projects
    • Identify the target project by title or URL pattern
    • Extract the Project ID from the name field (e.g., projects/13534454087919359824)
  3. Screen lookup (if Screen ID is not provided):

    • Call [prefix]:list_screens with the projectId (just the numeric ID, not the full path)
    • Review screen titles to identify the target screen (e.g., "Home", "Landing Page")
    • Extract the Screen ID from the screen's name field
  4. Metadata fetch:

    • Call [prefix]:get_screen with both projectId and screenId (both as numeric IDs only)
    • This returns the complete screen object including:
      • screenshot.downloadUrl - Visual reference of the design
      • htmlCode.downloadUrl - Full HTML/CSS source code
      • width, height, deviceType - Screen dimensions and target platform
      • Project metadata including designTheme with color and style information
  5. Asset download:

    • Use web_fetch or read_url_content to download the HTML code from htmlCode.downloadUrl
    • Optionally download the screenshot from screenshot.downloadUrl for visual reference
    • Parse the HTML to extract Tailwind classes, custom CSS, and component patterns
  6. Project metadata extraction:

    • Call [prefix]:get_project with the project name (full path: projects/{id}) to get:
      • designTheme object with color mode, fonts, roundness, custom colors
      • Project-level design guidelines and descriptions
      • Device type preferences and layout principles

Analysis & Synthesis Instructions

1. Extract Project Identity (JSON)

  • Locate the Project Title
  • Locate the specific Project ID (e.g., from the name field in the JSON)

2. Define the Atmosphere (Image/HTML)

Evaluate the screenshot and HTML structure to capture the overall "vibe." Use evocative adjectives to describe the mood (e.g., "Airy," "Dense," "Minimalist," "Utilitarian").

3. Map the Color Palette (Tailwind Config/JSON)

Identify the key colors in the system. For each color, provide:

  • A descriptive, natural language name that conveys its character (e.g., "Deep Muted Teal-Navy")
  • The specific hex code in parentheses for precision (e.g., "#294056")
  • Its specific functional role (e.g., "Used for primary actions")

4. Translate Geometry & Shape (CSS/Tailwind)

Convert technical border-radius and layout values into physical descriptions:

  • Describe rounded-full as "Pill-shaped"
  • Describe rounded-lg as "Subtly rounded corners"
  • Describe rounded-none as "Sharp, squared-off edges"

5. Describe Depth & Elevation

Explain how the UI handles layers. Describe the presence and quality of shadows (e.g., "Flat," "Whisper-soft diffused shadows," or "Heavy, high-contrast drop shadows").

Output Guidelines

  • Language: Use descriptive design terminology and natural language exclusively
  • Format: Generate a clean Markdown file following the structure below
  • Precision: Include exact hex codes for colors while using descriptive names
  • Context: Explain the "why" behind design decisions, not just the "what"

Output Format (DESIGN.md Structure)

markdown
# Design System: [Project Title]
**Project ID:** [Insert Project ID Here]

## 1. Visual Theme & Atmosphere
(Description of the mood, density, and aesthetic philosophy.)

## 2. Color Palette & Roles
(List colors by Descriptive Name + Hex Code + Functional Role.)

## 3. Typography Rules
(Description of font family, weight usage for headers vs. body, and letter-spacing character.)

## 4. Component Stylings
* **Buttons:** (Shape description, color assignment, behavior).
* **Cards/Containers:** (Corner roundness description, background color, shadow depth).
* **Inputs/Forms:** (Stroke style, background).

## 5. Layout Principles
(Description of whitespace strategy, margins, and grid alignment.)

Usage Example

To use this skill for the Furniture Collection project:

  1. Retrieve project information:

    Use the Stitch MCP Server to get the Furniture Collection project
  2. Get the Home page screen details:

    Retrieve the Home page screen's code, image, and screen object information
  3. Reference best practices:

    Review the Stitch Effective Prompting Guide at:
    https://stitch.withgoogle.com/docs/learn/prompting/
  4. Analyze and synthesize:

    • Extract all relevant design tokens from the screen
    • Translate technical values into descriptive language
    • Organize information according to the DESIGN.md structure
  5. Generate the file:

    • Create DESIGN.md in the project directory
    • Follow the prescribed format exactly
    • Ensure all color codes are accurate
    • Use evocative, designer-friendly language

Best Practices

  • Be Descriptive: Avoid generic terms like "blue" or "rounded." Use "Ocean-deep Cerulean (#0077B6)" or "Gently curved edges"
  • Be Functional: Always explain what each design element is used for
  • Be Consistent: Use the same terminology throughout the document
  • Be Visual: Help readers visualize the design through your descriptions
  • Be Precise: Include exact values (hex codes, pixel values) in parentheses after natural language descriptions

Tips for Success

  1. Start with the big picture: Understand the overall aesthetic before diving into details
  2. Look for patterns: Identify consistent spacing, sizing, and styling patterns
  3. Think semantically: Name colors by their purpose, not just their appearance
  4. Consider hierarchy: Document how visual weight and importance are communicated
  5. Reference the guide: Use language and patterns from the Stitch Effective Prompting Guide

Common Pitfalls to Avoid

  • ❌ Using technical jargon without translation (e.g., "rounded-xl" instead of "generously rounded corners")
  • ❌ Omitting color codes or using only descriptive names
  • ❌ Forgetting to explain functional roles of design elements
  • ❌ Being too vague in atmosphere descriptions
  • ❌ Ignoring subtle design details like shadows or spacing patterns

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 Design Md AI skill do?

Analyze Stitch projects and synthesize a semantic design system into DESIGN.md files

Why use Design Md on TypingMind?

Because you install it once and use it with any model. Design Md 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 Design Md in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/google-labs-code/stitch-skills/tree/main/plugins/stitch-utilities/skills/design-md. 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 Design Md?

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 Design Md?

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

Is the Design Md AI skill free?

Yes. It is published on GitHub by google-labs-code under the Apache-2.0 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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