Figma Check Design Parity

Organization

southleft

figma-check-design-parity

Compare a Figma node's actual specs against a code spec (the values your component renders) and get a 0–100 parity score, a list of discrepancies, and fix suggestions. Use to detect design-to-code DRIFT: triggers 'check design parity', 'does my code match the Figma', 'compare this component to the design', 'is my implementation faithful', 'find differences between design and code', 'verify the build matches Figma', 'design QA against code', 'parity score'. Reads the node's visual / typography / spacing / token / accessibility specs via use_figma (any plan) and diffs them against a codeSpec you provide. Complements the native get_design_context: instead of GENERATING code, it VALIDATES that existing code stayed in sync with the design.

Overview

Publisher	southleft
Repository	`figma-console-mcp-skills`
Skill name	`figma-check-design-parity`
Stars	94
Forks	4
Bundled files	2
License	MIT
Links	Skill source Repository

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 Check Design Parity AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/southleft/figma-console-mcp-skills/tree/main/skills/figma-check-design-parity
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/southleft/figma-console-mcp-skills/tree/main/skills/figma-check-design-parity

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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-check-design-parity .claude/skills/figma-check-design-parity

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Figma Check Design Parity 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 Check Design Parity 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 Check Design Parity 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-check-design-parity — design vs code drift checker

Pull a Figma node's real specs and diff them against a codeSpec (what your implementation actually renders). Returns a weighted parity score, per-property discrepancies with severity, and suggested fixes. This is the inverse of code generation: get_design_context turns a design into code; this skill confirms the code didn't drift away from the design.

All design reads go through use_figma, so it works on any Figma plan.

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).
Generating code from a design → that's the native get_design_context; this skill validates, not generates.
CODE-side a11y to feed codeSpec.accessibility → use figma-scan-code-accessibility (--map-to-codespec emits exactly that object).
Design-side WCAG lint → use figma-lint-design.

Workflow

Assemble the codeSpec. Gather the values your component renders into the codeSpec object (references/parity-scoring.md has the full shape). You only need to fill the sections you want compared — visual, spacing, typography, accessibility. Tip: figma-scan-code-accessibility --map-to-codespec builds codeSpec.accessibility automatically.
Read the design specs. Set NODE_ID and paste your codeSpec into scripts/check-parity.js. Run it via use_figma (skillNames: "figma-check-design-parity"). It extracts the node's fills, strokes, corner radius, opacity, padding/gap, and text properties, then diffs them against the codeSpec.
Read the scorecard. summary.parityScore is max(0, 100 − (critical×15 + major×8 + minor×3 + info×1)). discrepancies[] lists each mismatch with category, property, severity, designValue, codeValue, and a suggestion.
Decide which side to fix. Each discrepancy says what design has vs what code has. Update code to match the design, or push the design to match an intentional code change (via figma-manage-variables / figma-use), then re-run to confirm the score rose.

Key rules

Colors are 0–1 in Figma; the script converts to hex and normalizes both sides before comparing.
Only filled codeSpec sections are compared. Omit a section to skip it — no false positives for data you didn't provide.
Numeric tolerance: dimensions compare with a small epsilon (≈2px for width/height, 0.01 for opacity) so sub-pixel rounding doesn't register as drift.
Severity drives the score: color/spacing mismatches are major (−8), radius/border-width/opacity are minor (−3). See parity-scoring.md for the full weighting.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

references/parity-scoring.md5 KB
scripts/check-parity.js13 KB

Frequently asked questions

What does the Figma Check Design Parity AI skill do?

Why use Figma Check Design Parity on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/southleft/figma-console-mcp-skills/tree/main/skills/figma-check-design-parity. 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 Check Design Parity?

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 Check Design Parity?

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

Is the Figma Check Design Parity 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

figma-check-design-parity — design vs code drift checker

Skill boundaries

Workflow

Key rules

Bundled files

Frequently asked questions

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