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Design System

Community
RealTask
design-system

Audit, document, create, and safely extend a product design system with semantic tokens, component rules, themes, and migration guidance.

Overview

PublisherRealTask
RepositoryMAX-DESIGN
Skill namedesign-system
Stars
4
Forks
0
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 RealTask on GitHub. Read the source before you install it.

Installation

Install the Design System 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/RealTask/MAX-DESIGN/tree/main/skills/design-system
  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/RealTask/MAX-DESIGN.git /tmp/MAX-DESIGN
mkdir -p .claude/skills
cp -r /tmp/MAX-DESIGN/skills/design-system .claude/skills/design-system
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Design System 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 System 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 System 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.

Design system

When to use

Use when a project needs a coherent design language, styles have drifted, tokens should be documented, a theme is required, or repeated UI components need consistent visual and behavioral rules.

Workflow

1. Audit existing signals

Inspect repository guidance, design documentation, global styles, theme configuration, component libraries, CSS variables, utility configuration, UI primitives, Storybook, and representative screens. Record what exists before suggesting changes. Distinguish observed values from inferred ones.

2. Classify the project

Choose one path:

  • Document: a useful system exists; describe it and fill evidence-based gaps.
  • Extend: the system is sound but lacks specific tokens or components; add only what is missing.
  • Propose: no coherent system exists; offer a direction and identify decisions needing confirmation.
  • Migrate: conflicting patterns exist; map old values to target tokens and stage the change.

Do not silently replace an established brand or delete tokens that may be in use.

3. Define token layers

Separate raw values from semantic roles.

  • Primitive tokens: underlying color, dimension, font, radius, and timing values.
  • Semantic tokens: roles such as page background, raised surface, primary text, muted text, border, focus ring, positive status, and destructive action.
  • Component tokens: optional component-specific values where a genuinely repeated need exists.

Prefer names that describe purpose rather than appearance. A semantic token such as surface-raised adapts better than pale-gray-card.

4. Cover the full design vocabulary

Document color roles and theme behavior; typography families, weights, scales and line heights; spacing, layout widths and breakpoints; shape, border, elevation and focus; motion durations and reduced-motion alternatives; component anatomy, variants, states, content and responsive behavior; plus iconography, imagery, empty states, and content tone.

5. Encode for the actual stack

Use the project's existing token format when possible: CSS custom properties, theme objects, utility configuration, design-token JSON, or another native convention. The example at examples/design-tokens.json is a reference, not an instruction to migrate every project to JSON.

Keep values centralized. Avoid duplicate tokens, circular aliases, opaque abbreviations, and unexplained one-off values.

6. Plan a safe migration

Map existing values to semantic replacements. Migrate a small representative surface first, inspect visual differences, then apply systematically. Preserve names that may be externally consumed until usage is understood. Make changes reviewable and reversible.

7. Validate and document

Check token resolution, theme completeness, consistent component states, and whether examples match implementation. Document exceptions and reasons. If exact values cannot be measured, mark them as estimates rather than extracted facts.

Quality gates

  • Existing styles and conventions were inspected first.
  • Reused values have a clear role and stable name.
  • Components use tokens rather than duplicated magic values.
  • States and themes maintain contrast and meaning.
  • Responsive, focus, and motion behavior are defined where needed.
  • Migration impact and exceptions are documented.
  • Tokens validate in the project's actual format.

Frequently asked questions

What does the Design System AI skill do?

Audit, document, create, and safely extend a product design system with semantic tokens, component rules, themes, and migration guidance.

Why use Design System on TypingMind?

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

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

Which AI models can use Design System?

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 System?

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

Is the Design System AI skill free?

Yes. It is published on GitHub by RealTask 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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