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Audit Design System

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schudarin
audit-design-system

Analyze, audit, inventory, and document an existing Figma design system through the Figma MCP server — components, variables, tokens, patterns, design debt, usage rules, causal relationships — and create design-system documentation pages in Figma on request. Use when the user asks to audit, inventory, map, document, or find debt in a Figma file, page, frame, component set, or selection. Read-only by default; modify Figma only when the user explicitly asks. Not for designing or building screens — that is design-screens; not for repairing broken variable bindings — that is figma-fix-variable-bindings.

Overview

Publisherschudarin
Repositorychudarin-design-skills
Skill nameaudit-design-system
Stars
4
Forks
0
Bundled files
9
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.

  • 9 bundled files

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

  • Open source

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

Installation

Install the Audit Design System 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/schudarin/chudarin-design-skills/tree/main/skills/audit-design-system
  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/schudarin/chudarin-design-skills.git /tmp/chudarin-design-skills
mkdir -p .claude/skills
cp -r /tmp/chudarin-design-skills/skills/audit-design-system .claude/skills/audit-design-system
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Audit Design System 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 Audit Design System 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 Audit Design System 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 Audit Design System

Use this skill to analyze real Figma files and help build a tokenized design system grounded in actual layouts, components, variables, and product flows.

Operating mode

Work read-only by default.

You may inspect Figma files, pages, frames, components, instances, variables, screenshots, libraries, styles, layout structure, and usage patterns.

A read-only use_figma script is inspection: run it without asking. Read-only means the script only returns data and sets nothing on any node, variable or style.

Do not create, edit, delete, rename, move, or reorganize Figma content unless the user explicitly asks to do so.

If the user asks to analyze, audit, find, compare, document, propose, or recommend, stay read-only.

If the user asks to create, add, insert, update, modify, rename, organize, or publish in Figma, you may use write-capable Figma MCP tools, but do not modify source product screens unless the user specifically asks.

Do not analyze the codebase or Code Connect mappings.

Primary objective

Build design-system knowledge from evidence, not assumptions.

For every important finding, connect:

  1. Product scenario
  2. User intent
  3. Interface decision
  4. Component or pattern
  5. Token dependency
  6. Design-system rule
  7. Evidence from Figma
  8. Confidence level

MCP workflow

When the user provides a Figma URL or selection:

Load references/analysis-framework.md at the start of any file audit — it carries the scope map, the file-map table, the inventory method and the P0–P3 prioritisation.

  1. Determine the scope: file, page, frame, selection, component set, or flow.
  2. Use Figma MCP tools to inspect metadata, design context, screenshots, variables, libraries, and existing components.
  3. Build a file map.
  4. Build a component inventory.
  5. Build a token inventory.
  6. Build a pattern inventory.
  7. Detect repeated UI decisions and infer causal relationships.
  8. Separate components, variants, states, patterns, templates, local exceptions, and design debt.
  9. Recommend tokenization only when a value has repeatable semantic meaning.
  10. Produce the requested output or prepare Figma documentation pages.

Use tools in this order when applicable:

  1. get_metadata
  2. get_design_context
  3. get_screenshot
  4. get_variable_defs
  5. get_libraries
  6. search_design_system
  7. use_figma: read-only scripts for what the tools above do not return — component description and componentPropertyDefinitions, collections, modes, scopes and code syntax of variables, variable bindings on text styles, unbound fills, unstyled text. Writes only after an explicit write instruction. Before the first call, read-only included, load your tool's own Figma API instructions (figma-use, or the MCP resource skill://figma/figma-use/SKILL.md) plus figma-plugin-api-rules

If a listed tool is unavailable in the current MCP server, use the closest available Figma MCP tool and state which expected data could not be inspected.

Evidence rules

For each important conclusion, include:

  • Figma page or frame
  • Node or component name when available
  • Observed value or variable
  • Repeated usage count when available
  • Screenshot reference when useful
  • Source: script or screenshot
  • Confidence: high, medium, or low

A screenshot shows what is drawn on the canvas. Descriptions, component properties, bindings, scopes, code syntax and modes live in the panel, so a finding about them rests on a script read. When no script could run, such a finding is low confidence and goes into the list of what could not be inspected.

Use confidence levels:

  • High: three or more examples, plus component or variable evidence.
  • Medium: two or three examples, with partial structure.
  • Low: one example or insufficient MCP structure.

Label recommendations clearly. Do not present recommendations as existing facts.

Classification rules

Classify every repeated UI element as one of:

  • Primitive token
  • Semantic token
  • Component token
  • Component
  • Component variant
  • Component state
  • Pattern
  • Template
  • Local exception
  • Design debt

A component candidate should be recommended only when it passes the new-component gate in references/governance-rules.md and meets at least one condition:

  • Appears in three or more places
  • Has multiple states
  • Has multiple variants
  • Supports a critical product flow
  • Is used across multiple product areas
  • Has accessibility implications
  • Should be governed centrally

Component analysis

For each component or component candidate, document:

  • Purpose
  • Product scenarios
  • User intent
  • Anatomy
  • Variants
  • States
  • Properties
  • Token dependencies
  • Accessibility requirements
  • Usage rules
  • Do and don't examples
  • Examples from Figma
  • Design debt
  • Recommendations

Load references/component-checklist.md when documenting or auditing components — the spec structure, the required checks per interactive component, and a coverage list of common component families.

Check states for all interactive components:

  • default
  • hover
  • pressed
  • focused
  • disabled
  • loading
  • selected
  • error
  • success
  • warning
  • empty
  • skeleton/loading where applicable

Pattern analysis

Separate components from patterns and templates.

Use this distinction:

  • Component: reusable UI unit with properties, variants, and states.
  • Pattern: reusable solution to a user or product problem, often composed of several components.
  • Template: page or layout structure for a type of screen.

Example:

  • Input = component
  • Search with filters = pattern
  • Catalog page = template

Load references/pattern-checklist.md when the user asks for pattern analysis, product-flow analysis, or template recommendations.

Tokenization methodology

Use three token layers:

  1. Primitive tokens
  2. Semantic tokens
  3. Component tokens

Primitive tokens represent raw values.

Examples:

  • color.blue.500
  • color.gray.900
  • space.4
  • space.8
  • radius.md
  • font.size.16
  • shadow.1
  • motion.duration.fast

Semantic tokens represent interface roles.

Examples:

  • color.bg.canvas
  • color.bg.surface
  • color.text.primary
  • color.text.secondary
  • color.border.default
  • color.border.focus
  • color.action.primary.bg.default
  • color.action.primary.bg.hover
  • color.feedback.danger.bg

Component tokens represent component-specific decisions.

Examples:

  • component.button.container.bg.primary.default
  • component.button.container.bg.primary.hover
  • component.button.label.color.primary.default
  • component.input.border.color.error
  • component.card.container.radius.default

Do not create a semantic token only because a raw value repeats.

Create a semantic token when the value:

  • Has a repeatable role
  • Needs centralized governance
  • Appears across multiple components or patterns
  • Needs mode, theme, or brand switching
  • Has accessibility implications
  • Is likely to change as a design decision

Create component tokens only when the component needs independent control over variants, states, modes, or theming.

Avoid token names based on appearance:

  • blueButton
  • grayText
  • primaryBlue
  • lightGray2

Prefer role-based names:

  • color.action.primary.bg.default
  • color.text.secondary
  • color.border.focus

Load references/token-taxonomy.md for detailed naming, variable structure, mode mapping, and token-decision rules.

Figma Variables structure

When proposing Figma Variables, use this collection structure unless the user provides another standard:

  • Primitive
  • Semantic
  • Component
  • Typography
  • Motion

Use modes when needed:

  • Light
  • Dark
  • High contrast, if required

Use slash-style Figma variable names when appropriate:

  • color/bg/canvas
  • color/text/primary
  • color/action/primary/bg/default
  • component/button/container/bg/primary/default

Causal relationship format

For repeated elements, and whenever the user asks why elements are used, how components relate to scenarios, or which rule should be documented, use the template in references/causal-map-template.md.

Figma documentation pages

When the user asks to create design-system documentation in Figma, create only the pages this run fills.

Do not modify product screens unless the user explicitly asks.

For documentation frames, use clear headings, tables, examples, and source references.

When the file already has documentation boards, they set the look of every new or rebuilt one. A board shows itself by its make-up: a header with a title, text blocks next to component samples, labelled rows of states or widths, a name or a page that marks it as documentation. Take their header, text styles, colours, spacing and board width in full. A reference library the user points to lends only the way of showing: which sections a board has, how states and widths sit side by side, where the grid is drawn. Its styling is never copied over boards the file already has; one board that looks different from its neighbours is a defect.

Load references/figma-documentation-structure.md before creating documentation pages in Figma: the page list, the build rules and the check that must pass before the boards are shown.

Default output

If the user does not specify a format, return:

  1. Short summary
  2. File map
  3. Component inventory
  4. Token inventory
  5. Pattern inventory
  6. Causal map
  7. Design debt
  8. Recommended Figma documentation structure
  9. Prioritized next actions

If the user explicitly asks to create documentation in Figma, create Figma pages and frames instead of only responding in chat.

Quality gates

Before finalizing recommendations, check:

  • Similar elements use the same tokens.
  • Component variants are not duplicates.
  • States are complete for interactive components.
  • Naming is consistent.
  • Raw values are not used where semantic tokens are needed.
  • Primitive, semantic, and component tokens are not mixed.
  • Accessibility states are documented.
  • Design debt is separated from intentional exceptions.
  • Every major conclusion has evidence and confidence.

Load references/accessibility-checklist.md when the user asks for component specs, interactive states, or accessibility review.

Load references/governance-rules.md when the user asks how to maintain, version, approve, or evolve the design system.

Do not

  • Do not modify Figma unless explicitly asked.
  • Do not analyze the codebase or Code Connect.
  • Do not invent components without labeling them as recommendations.
  • Do not treat every repeated value as a token.
  • Do not create components from one-off layout details.
  • Do not ignore existing variables, styles, libraries, or components.
  • Do not present guesses as facts.
  • Do not overwrite or restructure product screens without explicit permission.

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 Audit Design System AI skill do?

Analyze, audit, inventory, and document an existing Figma design system through the Figma MCP server — components, variables, tokens, patterns, design debt, usage rules, causal relationships — and create design-system documentation pages in Figma on request. Use when the user asks to audit, inventory, map, document, or find debt in a Figma file, page, frame, component set, or selection. Read-only by default; modify Figma only when the user explicitly asks. Not for designing or building screens — that is design-screens; not for repairing broken variable bindings — that is figma-fix-variable-...

Why use Audit Design System on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/schudarin/chudarin-design-skills/tree/main/skills/audit-design-system. 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 Audit Design System?

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 Audit Design System?

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

Is the Audit Design System AI skill free?

Yes. It is published on GitHub by schudarin 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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