Figma Design System Inventory logo

Figma Design System Inventory

Organization
southleft
figma-design-system-inventory

One call to inventory an entire Figma design system — variables/tokens (grouped by collection + mode), components and component sets (with property definitions and per-variant visual specs), and styles (color/text/effect with resolved values). Use when you need the whole design-system picture before generating code or auditing coverage — triggers: 'inventory my design system', 'extract all tokens and components', 'what's in this design system', 'dump the design system kit', 'give me every variable, component, and style', 'build a design-system manifest', 'audit my Figma library'. Has a verbosity/scope guard so big files don't blow the response budget. Goes well beyond the native MCP's get_design_context (single-selection) / get_metadata.

Overview

Publishersouthleft
Repositoryfigma-console-mcp-skills
Skill namefigma-design-system-inventory
Stars
94
Forks
4
Bundled files
2
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.

  • 2 bundled files

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

  • Open source

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

Installation

Install the Figma Design System Inventory 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/southleft/figma-console-mcp-skills/tree/main/skills/figma-design-system-inventory
  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/southleft/figma-console-mcp-skills.git /tmp/figma-console-mcp-skills
mkdir -p .claude/skills
cp -r /tmp/figma-console-mcp-skills/skills/figma-design-system-inventory .claude/skills/figma-design-system-inventory
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Figma Design System Inventory 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 Figma Design System Inventory 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 Figma Design System Inventory 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.

figma-design-system-inventory — unified tokens + components + styles extraction

A single use_figma call that walks the whole file and returns a structured kit: tokens (every local variable, grouped by collection and mode), components (standalone components + component sets, with property definitions and a compact visualSpec per variant), and styles (paint/text/effect styles with their resolved values). It is the "read everything once" front door for code generation and library audits.

Skill boundaries

  • use_figma rules — load the official figma-use skill first; it is the full Figma Plugin API reference. Essentials these scripts rely on: plain JS with top-level await + return (no IIFE, no figma.closePlugin(); console.log is not returned), inputs inlined as const at the top of each script, colors in 0–1 range, load fonts before any text op, await figma.getNodeByIdAsync(...), and atomic errors (a failed script applies nothing — read the error, fix, retry).
  • The exact shape of each visualSpec → references/visual-spec.md.
  • One component in unlimited depth (full tree, reactions, instance refs) → use figma-deep-component. One variant set as a CSS state machine → use figma-analyze-component-set. Token files on disk → use figma-export-tokens.
  • This is a whole-system design capability the native MCP does not have: get_design_context works on a single selection and get_metadata returns flat structure, neither gives a unified tokens+components+styles kit on ANY plan.

Workflow

  1. Pick scope & verbosity to control response size on big files. Edit the constants in scripts/inventory.js:
    • INCLUDE — any of "tokens", "components", "styles" (default: all three).
    • VERBOSITY — "full" (per-variant visual specs), "summary" (component metadata + props, no per-variant specs), or "inventory" (names/ids/counts only — for huge files).
    • COMPONENT_NAME_FILTER — substring to limit components (e.g. "Button").
  2. Run via use_figma (skillNames: "figma-design-system-inventory"). Reads variables through the Plugin API, so it works on every Figma plan (no Enterprise REST requirement).
  3. Consume. Use tokens for color/spacing/typography values, components[].properties for the component API, components[].variants[].visualSpec for per-state appearance, and styles for any style-based (non-variable) values.
  4. If the result is still large, drop to a lower VERBOSITY or narrow INCLUDE / COMPONENT_NAME_FILTER and re-run — don't try to page a giant full dump.

Notes

  • Colors are emitted as hex (Figma stores 0–1 RGBA internally); spacing/size values are px.
  • Variables resolve aliases to token names ({Color.Brand.Primary}-style) where possible.
  • Per-variant visual specs come from each variant component node — see references/visual-spec.md for the fields (fills, strokes, effects, cornerRadius, opacity, layout/padding/spacing, typography).
  • This script is the open-coded, root+first-level equivalent of the bundled figma_get_design_system_kit tool, written in the native use_figma idiom so it runs without the Desktop Bridge. It captures each component/variant's root visual spec plus its direct children (childSpecs); it does not recurse deeper.

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 Figma Design System Inventory AI skill do?

One call to inventory an entire Figma design system — variables/tokens (grouped by collection + mode), components and component sets (with property definitions and per-variant visual specs), and styles (color/text/effect with resolved values). Use when you need the whole design-system picture before generating code or auditing coverage — triggers: 'inventory my design system', 'extract all tokens and components', 'what's in this design system', 'dump the design system kit', 'give me every variable, component, and style', 'build a design-system manifest', 'audit my Figma library'. Has a verb...

Why use Figma Design System Inventory on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/southleft/figma-console-mcp-skills/tree/main/skills/figma-design-system-inventory. 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 Figma Design System Inventory?

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 Figma Design System Inventory?

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

Is the Figma Design System Inventory AI skill free?

Yes. It is published on GitHub by southleft 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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