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Extract

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fengshao1227
extract

Extract and consolidate reusable components, design tokens, and patterns into your design system. Identifies opportunities for systematic reuse and enriches your component library. Use when the user asks to create components, refactor repeated UI patterns, build a design system, or extract tokens.

Overview

Publisherfengshao1227
Repositoryccg-workflow
Skill nameextract
Stars
5.9K
Forks
446
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 fengshao1227 on GitHub. Read the source before you install it.

Installation

Install the Extract 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/fengshao1227/ccg-workflow.git /tmp/ccg-workflow
mkdir -p .claude/skills
cp -r /tmp/ccg-workflow/templates/skills/impeccable/extract .claude/skills/extract
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Extract 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 Extract 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 Extract 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.

Identify reusable patterns, components, and design tokens, then extract and consolidate them into the design system for systematic reuse.

Discover

Analyze the target area to identify extraction opportunities:

  1. Find the design system: Locate your design system, component library, or shared UI directory (grep for "design system", "ui", "components", etc.). Understand its structure:

    • Component organization and naming conventions
    • Design token structure (if any)
    • Documentation patterns
    • Import/export conventions

    CRITICAL: If no design system exists, ask before creating one. Understand the preferred location and structure first.

  2. Identify patterns: Look for:

    • Repeated components: Similar UI patterns used multiple times (buttons, cards, inputs, etc.)
    • Hard-coded values: Colors, spacing, typography, shadows that should be tokens
    • Inconsistent variations: Multiple implementations of the same concept (3 different button styles)
    • Reusable patterns: Layout patterns, composition patterns, interaction patterns worth systematizing
  3. Assess value: Not everything should be extracted. Consider:

    • Is this used 3+ times, or likely to be reused?
    • Would systematizing this improve consistency?
    • Is this a general pattern or context-specific?
    • What's the maintenance cost vs benefit?

Plan Extraction

Create a systematic extraction plan:

  • Components to extract: Which UI elements become reusable components?
  • Tokens to create: Which hard-coded values become design tokens?
  • Variants to support: What variations does each component need?
  • Naming conventions: Component names, token names, prop names that match existing patterns
  • Migration path: How to refactor existing uses to consume the new shared versions

IMPORTANT: Design systems grow incrementally. Extract what's clearly reusable now, not everything that might someday be reusable.

Extract & Enrich

Build improved, reusable versions:

  • Components: Create well-designed components with:
    • Clear props API with sensible defaults
    • Proper variants for different use cases
    • Accessibility built in (ARIA, keyboard navigation, focus management)
    • Documentation and usage examples
  • Design tokens: Create tokens with:
    • Clear naming (primitive vs semantic)
    • Proper hierarchy and organization
    • Documentation of when to use each token
  • Patterns: Document patterns with:
    • When to use this pattern
    • Code examples
    • Variations and combinations

NEVER:

  • Extract one-off, context-specific implementations without generalization
  • Create components so generic they're useless
  • Extract without considering existing design system conventions
  • Skip proper TypeScript types or prop documentation
  • Create tokens for every single value (tokens should have semantic meaning)

Migrate

Replace existing uses with the new shared versions:

  • Find all instances: Search for the patterns you've extracted
  • Replace systematically: Update each use to consume the shared version
  • Test thoroughly: Ensure visual and functional parity
  • Delete dead code: Remove the old implementations

Document

Update design system documentation:

  • Add new components to the component library
  • Document token usage and values
  • Add examples and guidelines
  • Update any Storybook or component catalog

Remember: A good design system is a living system. Extract patterns as they emerge, enrich them thoughtfully, and maintain them consistently.

Frequently asked questions

What does the Extract AI skill do?

Extract and consolidate reusable components, design tokens, and patterns into your design system. Identifies opportunities for systematic reuse and enriches your component library. Use when the user asks to create components, refactor repeated UI patterns, build a design system, or extract tokens.

Why use Extract on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/fengshao1227/ccg-workflow/tree/main/templates/skills/impeccable/extract. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Extract?

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 Extract?

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

Is the Extract AI skill free?

Yes. It is published on GitHub by fengshao1227 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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