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Gdd Figma Extract

Community
hegemonart
gdd-figma-extract

Off-context Figma design-system extraction into a compact local digest (DESIGN.md + tokens.json + components.json). Pulls the file via the Figma REST API and digests it without the raw JSON ever entering the model context.

Overview

Publisherhegemonart
Repositoryget-design-done
Skill namegdd-figma-extract
Stars
3
Forks
1
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 hegemonart on GitHub. Read the source before you install it.

Installation

Install the Gdd Figma 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.
    https://github.com/hegemonart/get-design-done/tree/main/scripts/skill-templates/figma-extract
  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/hegemonart/get-design-done.git /tmp/get-design-done
mkdir -p .claude/skills
cp -r /tmp/get-design-done/scripts/skill-templates/figma-extract .claude/skills/gdd-figma-extract
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Gdd Figma 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 Gdd Figma 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 Gdd Figma 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.

gdd-figma-extract

Pull a whole Figma design system into a compact, queryable local digest - without the raw JSON ever entering Claude context. The heavy lifting runs in tested .cjs tools; the model reads only the digest outputs.

Usage

{{command_prefix}}figma-extract <file-key-or-url>                  # full design-system digest
{{command_prefix}}figma-extract <file-key-or-url> --component Button  # ~500-token single-component slice

<file-key-or-url> is a Figma file URL (https://www.figma.com/file/<key>/… or /design/<key>/…) or a bare file key.

Behavior

  1. Preflight (D-10). Confirm FIGMA_TOKEN is set in the environment:

    node -e "process.exit(process.env.FIGMA_TOKEN||process.env.FIGMA_PERSONAL_ACCESS_TOKEN?0:1)"

    If unset, tell the user to export FIGMA_TOKEN=figd_… (from https://www.figma.com/developers/api#access-tokens). The token comes from the environment only - never ask the user to paste it into a file or the chat, and never echo it back.

  2. Stage 1 - pull. Pull the file's REST endpoints into the gitignored raw cache (D-09):

    node scripts/lib/figma-extract/pull.cjs "<file-key-or-url>"

    This caches to .figma-extract-cache/raw/<file-key>/ and skips re-pulling when Figma's version is unchanged (D-11). Add --force to bypass the cache, --out <dir> to relocate the cache. The tool prints a JSON summary (endpoints, bytes, cached) on stdout - the raw bodies stay on disk.

  3. Stage 2 - plugin sync (OPTIONAL, Path C). Only when the design tokens live in Figma Variables that the REST API cannot return (non-Enterprise plans → the pull summary shows variables skipped) and the user wants token coverage:

    node scripts/lib/figma-extract/receiver.cjs --out .figma-extract-cache/raw/<file-key>

    This binds 127.0.0.1:5179 (D-06). Tell the user to run the dev-installed "GDD Sync" plugin in Figma and click "Export to GDD" - see figma-plugin/README.md for the one-time dev-install. The receiver writes variables.json into the cache and exits on receipt or timeout. Skip this stage entirely for design systems whose tokens already come through the REST pull.

  4. Stage 3 - digest. Transform the cache into the compact digest:

    node scripts/lib/figma-extract/digest.cjs --raw .figma-extract-cache/raw/<file-key> --out .figma-extract-cache/digest

    This writes DESIGN.md, tokens.json, and components.json. Add --prefer-styles to invert the token priority to styles-first (D-04). Add --component <name> (D-08) to emit a single-component slice instead of the full digest.

  5. Read the digest. Open only .figma-extract-cache/digest/DESIGN.md (plus tokens.json / components.json when you need structured data). For a single component, pass --component <name> in Stage 3 and read the ~500-token slice instead of the full ~16K-token spec.

Required Reading

  • .figma-extract-cache/digest/DESIGN.md - the compact human/LLM-readable spec
  • .figma-extract-cache/digest/tokens.json - resolved design tokens (when structured token data is needed)
  • .figma-extract-cache/digest/components.json - components with variants/props/defaults (when structured component data is needed)

Notes

  • Two-stage pipeline (D-01): re-run Stage 3 against an existing cache without re-pulling. The digest does zero network calls.
  • The spike proved 0 Claude tokens during extraction (898× compression, 223 MB → 254 KB). That property holds only because this skill never surfaces the raw cache.
  • Figma MCP remains the right tool for spot questions on a single live component; this skill is the cheaper path for whole-design-system workflows.

Do Not

  • Do NOT read or cat the raw/*.json cache (e.g. .figma-extract-cache/raw/<file-key>/file.json). It is tool-internal and often 100+ MB; loading it into context defeats the off-context guarantee (D-12). Read only the digest outputs above.
  • Do not persist, log, echo, or print FIGMA_TOKEN (D-10). It belongs in the environment only - never write it to a file, a commit, or chat output.

FIGMA-EXTRACT COMPLETE

Frequently asked questions

What does the Gdd Figma Extract AI skill do?

Off-context Figma design-system extraction into a compact local digest (DESIGN.md + tokens.json + components.json). Pulls the file via the Figma REST API and digests it without the raw JSON ever entering the model context.

Why use Gdd Figma Extract on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hegemonart/get-design-done/tree/main/scripts/skill-templates/figma-extract. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Gdd Figma 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 Gdd Figma Extract?

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

Is the Gdd Figma Extract AI skill free?

Yes. It is published on GitHub by hegemonart 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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