Skip to main content
Glama

design_doc

Extract design tokens from any public URL to document or analyze a site's design system.

Instructions

Scrape a public URL and extract its design system as a structured DESIGN.md document.

Fetches the page HTML and all linked stylesheets, parses CSS custom properties, color values, font families, spacing, radii, and shadows, then uses Claude to synthesize a structured DESIGN.md.

Prerequisites: URL must be publicly accessible (no authentication required). ANTHROPIC_API_KEY must be set for AI synthesis mode — use raw=true as a fallback when the key is not available.

Returns on success (raw=false): A full DESIGN.md markdown document with sections: ## Color System, ## Typography, ## Spacing, ## Borders & Surfaces, ## Component Patterns, ## Voice & Tone, ## Do / Don't, ## Tailwind Config Sketch. Values are drawn from the page's actual CSS.

Returns on success (raw=true): JSON object with shape { url, title, tokens: { cssVarCount, colorCount, fontCount, cssVars: Record<string,string>, colors: string[], fonts: string[], fontSizes: string[], spacing: string[], radii: string[], shadows: string[] } }

Error behavior: Returns isError if the URL is unreachable or returns no usable CSS. Returns isError with "ANTHROPIC_API_KEY required" message if AI synthesis is needed but the key is missing.

Use this tool: to reverse-engineer a competitor's or reference site's design system before creating specs, to quickly document a client's existing web style guide, or to extract tokens for comparison with the project's own system. Pass raw=true when you want to programmatically process the token data rather than read a document.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesFully-qualified public URL to extract design tokens from (e.g. 'https://stripe.com', 'https://linear.app'). Must be accessible without authentication.
rawNoIf false (default), returns an AI-synthesized DESIGN.md document (requires ANTHROPIC_API_KEY). If true, returns the raw parsed token data as JSON without calling the AI — useful when ANTHROPIC_API_KEY is unavailable or you want structured data.
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description fully covers behavior: fetches page HTML and stylesheets, parses CSS custom properties, uses AI for synthesis, returns different formats based on raw flag, error behavior (unreachable URL, missing API key). Discloses output structure and sections.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with paragraphs for overview, prerequisites, return values, errors, and use cases. Front-loaded with main purpose. Slightly long but each sentence adds value; could be slightly more concise without losing clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite no annotations or output schema, the description is highly complete: covers inputs, prerequisites, two output modes with detailed shapes, error conditions, and practical use cases. The user has full understanding of what the tool does and how to interpret results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but description adds significant meaning beyond schema: for 'url' it notes public accessibility requirement; for 'raw' it explains default behavior, use cases (programmatic processing, fallback) and implications for AI synthesis.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear verb+resource: 'Scrape a public URL and extract its design system as a structured DESIGN.md document.' It details specific actions (fetches HTML, parses CSS) and distinguishes from sibling tools by focusing on design system extraction into a document format.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly describes when to use: 'to reverse-engineer a competitor's... design system, to quickly document a client's existing web style guide, or to extract tokens for comparison.' Also provides prerequisites and fallback option. Lacks explicit 'when not to use' or alternatives among siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/sarveshsea/memi'

If you have feedback or need assistance with the MCP directory API, please join our Discord server