design-dna (Claude Skill) — Use Cases, Install & Live Demo

Why use it

Key features

Extracts tokens (color, type, spacing, radii) from references
Captures qualitative style (editorial / brutalist / glassy)
Captures effects (shadow, blur, grain, gradients) with parameters
Outputs portable JSON — feed to any code-gen LLM
Works from images, screenshots, or live URLs

Live Demo

What it looks like in practice

ready

Install

Pick your client

~/Library/Application Support/Claude/claude_desktop_config.json · Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "design-dna-skill": {
      "command": "git",
      "args": [
        "clone",
        "https://github.com/zanwei/design-dna",
        "~/.claude/skills/design-dna"
      ],
      "_inferred": true
    }
  }
}

Open Claude Desktop → Settings → Developer → Edit Config. Restart after saving.

~/.cursor/mcp.json · .cursor/mcp.json

{
  "mcpServers": {
    "design-dna-skill": {
      "command": "git",
      "args": [
        "clone",
        "https://github.com/zanwei/design-dna",
        "~/.claude/skills/design-dna"
      ],
      "_inferred": true
    }
  }
}

Cursor uses the same mcpServers schema as Claude Desktop. Project config wins over global.

VS Code → Cline → MCP Servers → Edit

{
  "mcpServers": {
    "design-dna-skill": {
      "command": "git",
      "args": [
        "clone",
        "https://github.com/zanwei/design-dna",
        "~/.claude/skills/design-dna"
      ],
      "_inferred": true
    }
  }
}

Click the MCP Servers icon in the Cline sidebar, then "Edit Configuration".

~/.codeium/windsurf/mcp_config.json

{
  "mcpServers": {
    "design-dna-skill": {
      "command": "git",
      "args": [
        "clone",
        "https://github.com/zanwei/design-dna",
        "~/.claude/skills/design-dna"
      ],
      "_inferred": true
    }
  }
}

Same shape as Claude Desktop. Restart Windsurf to pick up changes.

~/.continue/config.json

{
  "mcpServers": [
    {
      "name": "design-dna-skill",
      "command": "git",
      "args": [
        "clone",
        "https://github.com/zanwei/design-dna",
        "~/.claude/skills/design-dna"
      ]
    }
  ]
}

Continue uses an array of server objects rather than a map.

~/.config/zed/settings.json

{
  "context_servers": {
    "design-dna-skill": {
      "command": {
        "path": "git",
        "args": [
          "clone",
          "https://github.com/zanwei/design-dna",
          "~/.claude/skills/design-dna"
        ]
      }
    }
  }
}

Add to context_servers. Zed hot-reloads on save.

claude mcp add design-dna-skill -- git clone https://github.com/zanwei/design-dna ~/.claude/skills/design-dna

One-liner. Verify with claude mcp list. Remove with claude mcp remove.

Use Cases

Real-world ways to use design-dna

Build a component matching a screenshot you love

👤 Devs without a designer, building polished UIs ⏱ ~25 min intermediate

When to use: You see a great UI screenshot on Twitter and want to capture its vibe.

Prerequisites

Skill installed — git clone https://github.com/zanwei/design-dna ~/.claude/skills/design-dna

Flow

Extract DNA

Use design-dna. Extract DNA from /screens/inspiration.png. Save as dna.json.✓ Copied

→ JSON with tokens + style + effects
Generate component

Using dna.json, generate a React Card component. Match the radii, shadow, gradient parameters.✓ Copied

→ TSX with matching aesthetic
Compare visually

Render side-by-side; tweak any drift in shadow strength.✓ Copied

→ Visual match within tolerance

Outcome: On-brand component without copying code from the original.

Pitfalls

DNA misses subtle effects (grain texture) — Pass --high-fidelity for slower but richer extraction

Combine with: filesystem

Generate new components that match an existing product's design

👤 Devs adding features to a designed product ⏱ ~30 min intermediate

When to use: You're adding a screen to an existing app and want it to feel native.

Flow

DNA from live URL

Use design-dna. Extract DNA from https://app.example.com/dashboard (logged-in screenshot).✓ Copied

→ DNA reflects the actual product
Audit token diff

Compare DNA to our existing tailwind.config — flag drift.✓ Copied

→ Drift list (e.g., 'shadow-md inconsistent across pages')
Generate new screen

Generate the new 'Settings' screen using our reconciled DNA.✓ Copied

→ Screen indistinguishable from rest of app

Outcome: Cohesive product, even when adding screens months later.

Pitfalls

Live URL is behind auth — DNA from public landing page misleads — Use authenticated screenshot, not the marketing page

Bootstrap a design system from references

👤 Solo founders / small teams without a designer ⏱ ~60 min advanced

When to use: You're starting an app and want a coherent design system fast.

Flow

Pick 3 references

Use design-dna. Extract DNA from 3 screenshots I admire (editorial, app, marketing).✓ Copied

→ 3 separate DNA objects
Synthesize

Synthesize a single DNA emphasizing the editorial type scale and the app's spacing.✓ Copied

→ Merged DNA
Output a starter system

Generate tailwind.config, CSS vars, and a Button + Card + Input set using the merged DNA.✓ Copied

→ Starter design system in repo

Outcome: A cohesive baseline you can iterate on instead of starting from default Tailwind.

Pitfalls

Synthesizing wildly different aesthetics yields chaos — Pick references that share a 'family' — variations within a style, not opposites

Combine with: frontend-slides-skill

Combinations

Pair with other MCPs for X10 leverage

design-dna-skill + filesystem

Persist DNA + generated components in repo

Save design.dna.json under /design/ and check in; treat it as design source-of-truth.✓ Copied

design-dna-skill + frontend-slides-skill

Generate slide decks that match your product aesthetic

Use design-dna to capture our brand; pass to frontend-slides-skill for matching deck templates.✓ Copied

Tools

What this MCP exposes

Tool	Inputs	When to call	Cost
extract_dna	image_path or url, fidelity?	First step from any reference	Vision LLM tokens
synthesize_dna	dna[]	Combining multiple references	LLM tokens
generate_component	dna, component_spec	On-brand component generation	LLM tokens
diff_dna	dna_a, dna_b	Audit drift between reference and current product	0

Cost & Limits

What this costs to run

API quota: Vision-LLM dependent
Tokens per call: Extraction ~3000–8000 tokens (image input + JSON output)
Monetary: Free; pay LLM provider
Tip: Cache DNA per project; only re-extract on real brand refresh

Security

Permissions, secrets, blast radius

Minimum scopes: filesystem-read (images) Outbound HTTPS (URL refs)

Credential storage: None (vision LLM auth via env var)

Data egress: Vision LLM provider; URL fetcher (if used)

Don't extract DNA from copyrighted assets you don't have rights to use as reference; output may carry signature features

Troubleshooting

Common errors and fixes

Extraction misses gradients

Use --fidelity high; default skips subtle gradients to save tokens

DNA tokens differ run-to-run

Vision models are stochastic — set seed if supported; or extract twice and pick median values

Generated code uses inline styles instead of design tokens

Pass --token-mode strict; skill will refuse to inline values that exist as tokens

Live URL extraction blank

Site requires JS; use a fully-rendered screenshot instead of URL fetch

Alternatives

design-dna vs others

Alternative	When to use it instead	Tradeoff
design-extract (Manavarya09)	You want full design-token export including DTCG + multi-platform emitters	Heavier; full design-system pipeline vs lightweight DNA
Manual style guide curation	You have a designer and a pattern library	Slower; more authoritative

More

Resources

📖 Read the official README on GitHub

🐙 Browse open issues

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