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Extract Design System From a Live Site

extract-from-url
Read-onlyIdempotent

Fetches a public web page, reads its stylesheets and renders it in a headless browser to sample the colors, fonts and radii of its body, headings, links, buttons, inputs and cards, then returns the brand as an oklch token sheet. It reads the page the way a browser does and calls no other API. A call takes about 10 to 45 seconds.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesPublic http(s) URL of the page to read, usually the homepage.
nameNoOptional label for the extracted system. Defaults to the site's hostname.
maxTokensNoMaximum tokens to return. Truncates the token sheet to fit.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, openWorld), but the description adds genuinely new operational context: it renders in a headless browser, reads stylesheets, calls no other API, and takes 10–45 seconds per call. The latency disclosure in particular is valuable for call planning. It stops short of describing failure modes for pages it cannot render.

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?

Three sentences, front-loaded with the core action and each carrying distinct information (what it reads, that it is browser-like and self-contained, and how long it takes). No filler, though the sampling enumeration is dense.

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

Completeness4/5

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

With no output schema, the description correctly names the return value (an oklch token sheet) and notes truncation via maxTokens is handled in the schema. Annotations carry the safety profile and latency is stated, so an agent has nearly everything needed; only sibling disambiguation and public-page-only restrictions are unstated.

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

Parameters3/5

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

Schema description coverage is 100%, so all three parameters (url, name, maxTokens) are already documented with constraints and defaults. The description only reinforces that the target must be a 'public' page; it adds no syntax, format, or defaulting detail beyond the schema, so the baseline 3 applies.

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

Purpose4/5

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

The description gives a precise verb+resource ('fetches a public web page... returns the brand as an oklch token sheet') and enumerates exactly what it samples (colors, fonts, radii of body, headings, links, buttons, inputs, cards). It does not, however, differentiate itself from the very similar sibling 'extract-design-system' (or 'find-design-system'), so an agent cannot tell the two apart from the text alone.

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

Usage Guidelines2/5

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

There is no when-to-use guidance and no mention of alternatives, despite several close siblings ('extract-design-system', 'find-design-system', 'create-design-system', 'preview-design-system'). The agent is left to infer that this tool is for live-site extraction while the others handle stored/created systems.

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

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