Export Tokens Figma logo

Export Tokens Figma

Organization
southleft
export-tokens-figma

Export Figma variables to design token files in DTCG, CSS custom properties, Tailwind v4/v3, SCSS, TypeScript, JSON, Style Dictionary, or Tokens Studio. Use when the user wants to pull design tokens OUT of Figma into code — triggers: 'export tokens', 'export Figma variables', 'generate CSS variables from Figma', 'turn my Figma variables into a tokens.json / Tailwind config / SCSS', 'sync design tokens to code'. Works on ANY Figma plan (reads via the Plugin API, not the Enterprise-only Variables REST API). For the reverse direction (code → Figma) use import-tokens-figma.

Overview

Publishersouthleft
Repositoryskills-for-figma
Skill nameexport-tokens-figma
Stars
20
Forks
1
Bundled files
3
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.

  • 3 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 Export Tokens Figma 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/skills-for-figma/tree/main/skills/export-tokens-figma
  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/skills-for-figma.git /tmp/skills-for-figma
mkdir -p .claude/skills
cp -r /tmp/skills-for-figma/skills/export-tokens-figma .claude/skills/export-tokens-figma
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Export Tokens Figma 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 Export Tokens Figma 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 Export Tokens Figma 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.

export-tokens-figma — Figma variables → design tokens

Read every local variable in a Figma file and emit design-token files. The canonical output is DTCG (W3C Design Tokens Community Group JSON); CSS, Tailwind, SCSS, TS, and JSON derive from it.

Why this beats a raw REST export: Figma's Variables REST API is Enterprise-only (403 on Starter/Pro/Org). This skill reads through the Plugin API via use_figma, so it works on every plan and resolves aliases + multi-mode values that get_variable_defs (default mode only) drops.

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).
  • Reverse direction (code → Figma variables) → use the import-tokens-figma skill.

Workflow

  1. Confirm scope & format. Ask (or infer) the target format (dtcg is the safe default), whether to split by mode/collection, and the output path. Get the file key from the active Figma file or a URL the user provides.
  2. Read the variables. Run scripts/read-variables.js via use_figma (skillNames: "export-tokens-figma"). It returns the normalized collections/modes/variables tree with hex colors, resolved alias references, scopes, and code syntax.
  3. Save the read output to a file, e.g. variables.json.
  4. Convert — deterministically. Run the bundled converter (Node 18+, zero dependencies). Do not hand-write the conversion — this script is the source of truth and produces identical output every run:
    bash
    node scripts/convert-tokens.mjs variables.json --format dtcg --out tokens/
    # --format: dtcg (default) | css-vars | tailwind-v4 | tailwind-v3 | scss | ts-module
    #           | json-flat | json-nested | style-dictionary-v3 | tokens-studio
    #           (aliases: css, tailwind, ts)
    # --out <dir>  write file(s) — tokens-studio writes several; omit to print to stdout
    # --prefix <p>            prefix CSS/SCSS var names
    # --modes Light,Dark      include only these modes (default: all)
    # --collection <substr>   include only collections whose name contains <substr>
    This matches the Console figma_export_tokens formatters. It handles exactly what freehand conversion gets wrong: per-type units (opacity/line-height unitless, spacing/radius px); multi-mode output (CSS & Tailwind v4 emit :root + .dark/[data-theme]; TS/JSON emit {mode: value}; SCSS suffixes modes; DTCG keeps them in $extensions); aliases → var()/{ref}; font-weight names → numbers; DTCG round-trip metadata; and it warns on slug collisions and non-numeric weights. (style-dictionary-v3 and tailwind-v3 use the primary mode, matching the Console — those formats have no native multi-mode encoding.)
  5. Report. Surface the written path(s) and any warnings the converter printed (collisions / weight issues are real findings about the Figma file, worth flagging to the user).

Notes

  • The converter is deterministic and authoritative. references/token-formats.md documents the formats it emits; it is reference, not a thing to re-implement by hand.
  • Where it runs: read-variables.js runs anywhere via use_figma. convert-tokens.mjs is Node, so it needs a terminal-capable agent (Claude Code, the Code tab in Claude Desktop, Cursor, Codex, Gemini CLI). In plain Desktop/web chat (no shell), run the converter on your own machine against the saved variables.json, or accept a best-effort inline conversion for DTCG only.
  • Large systems: if the read is huge, scope it to specific collection names before saving.
  • Aliases across collections become var(--…) / {ref} — export all collections together so those references resolve.

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 Export Tokens Figma AI skill do?

Export Figma variables to design token files in DTCG, CSS custom properties, Tailwind v4/v3, SCSS, TypeScript, JSON, Style Dictionary, or Tokens Studio. Use when the user wants to pull design tokens OUT of Figma into code — triggers: 'export tokens', 'export Figma variables', 'generate CSS variables from Figma', 'turn my Figma variables into a tokens.json / Tailwind config / SCSS', 'sync design tokens to code'. Works on ANY Figma plan (reads via the Plugin API, not the Enterprise-only Variables REST API). For the reverse direction (code → Figma) use import-tokens-figma.

Why use Export Tokens Figma on TypingMind?

Because you install it once and use it with any model. Export Tokens Figma 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 Export Tokens Figma in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/southleft/skills-for-figma/tree/main/skills/export-tokens-figma. 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 Export Tokens Figma?

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 Export Tokens Figma?

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

Is the Export Tokens Figma 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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