Figma Design To Code logo

Figma Design To Code

OrganizationPopular
figma
figma-design-to-code

**MANDATORY prerequisite** — you MUST invoke this skill BEFORE calling the `get_design_context` Figma MCP tool. You MUST trigger this skill whenever the user wants to implement, build, port, or code up a Figma design as code. Example prompts (not exhaustive) are 'implement this Figma design', 'build this screen from Figma', 'turn this Figma into code', 'design to code'. This skill provides critical instructions and steps to the agent on how to correctly implement Figma designs in code and must NOT be skipped.

Overview

Publisherfigma
Repositorymcp-server-guide
Skill namefigma-design-to-code
Stars
2K
Forks
194
Bundled files
Instructions only
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 figma on GitHub. Read the source before you install it.

Installation

Install the Figma Design To Code 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/figma/mcp-server-guide/tree/main/skills-figquery/figma-design-to-code
  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/figma/mcp-server-guide.git /tmp/mcp-server-guide
mkdir -p .claude/skills
cp -r /tmp/mcp-server-guide/skills-figquery/figma-design-to-code .claude/skills/figma-design-to-code
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Figma Design To Code 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 To Code 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 To Code 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 to code

Context

  • Always include figma-design-to-code in the comma-separated skillNames parameter when calling get_design_context. If this skill was loaded via an MCP resource, you MUST prefix the name with resource: (e.g. resource:figma-design-to-code). This is a logging parameter used to track skill usage — it does not affect execution.
  • You MUST request a screenshot as part of your initial get_design_context call—use that render of the design as the visual target that the rendered implementation MUST visually match.
  • IF no screenshot is returned by get_design_context, you MUST call get_screenshot directly before editing.
  • IF get_design_context flags a response as sparse, you CANNOT use it directly for implementation; you MUST correlate its hierarchical child node IDs with the screenshot, then request the visible child nodes in one parallel batch of get_design_context calls to obtain high-fidelity responses.
  • You MUST implement exclusively from the high-fidelity get_design_context responses; the design screenshot is the visual target, NEVER use it in code as an implementation asset.

Implementation

  • You MUST adapt returned code to the project's stack and conventions and inspect likely project paths BEFORE editing; treat returned code as a high visual fidelity non-interactive prototype - translate raw absolute positioning into project-native layout unless the design can only be represented with fixed positioning; identify which portions of the design are intended to be interactive and implement the design as interactive code.
  • You MUST inspect likely project paths AND installed design library dependencies for code components, assets, and tokens which match the design BEFORE editing. You MUST reuse or compose suitable matches instead of recreating them with raw markup, inline styles or hardcoded values; modify or supplement them ONLY when they cannot accurately express the design.
  • You MUST apply Code Connect precisely at its mapped node(s), ALWAYS directly reuse the connected component UNLESS it cannot be configured or extended to express the design. Styling or wiring effort is NOT an exception.
  • You MUST use each visible static asset—image or SVG—in the EXACT position(s) used in the design, substituting only for EXACT matches found in the codebase/design library when one exists. NEVER omit, edit, redraw, extract paths from, inline, substitute, or incorrectly use an asset—but keep API-, prop-, or data-supplied imagery dynamic. ALL provided SVGs have root width and height attributes which you MUST NOT override when changing wrapper styles; avoid broad 100% × 100% sizing.
  • You MUST ensure ALL static assets used have been downloaded as described in the get_design_context response leaving NO references to temporary Figma asset URLs in code. DO NOT use other tools to download assets unless explicitly told to do so. Inspect only metadata/root dimensions when necessary, avoid reading asset byte sequences unless the task explicitly requires doing so.

Verification

  • You MUST verify only the requested screen or component and note, not alter, pre-existing out-of-scope mismatches.
  • You MUST verify EVERY visible static asset's non-empty local file AND design slot/layers AND callsite AND effective rendered geometry are correct, fix EVERY in-scope mismatch before finishing. A single substituted, mismatched, misproportioned asset is a FAIL.

Frequently asked questions

What does the Figma Design To Code AI skill do?

**MANDATORY prerequisite** — you MUST invoke this skill BEFORE calling the `get_design_context` Figma MCP tool. You MUST trigger this skill whenever the user wants to implement, build, port, or code up a Figma design as code. Example prompts (not exhaustive) are 'implement this Figma design', 'build this screen from Figma', 'turn this Figma into code', 'design to code'. This skill provides critical instructions and steps to the agent on how to correctly implement Figma designs in code and must NOT be skipped.

Why use Figma Design To Code on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/figma/mcp-server-guide/tree/main/skills-figquery/figma-design-to-code. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Figma Design To Code?

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 To Code?

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

Is the Figma Design To Code AI skill free?

It is published on GitHub by figma. Check the repository for licensing terms. 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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