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get_component

Get one product's UI component fully specified — its anatomy read from the LIVE DOM (exact padding / height / border_radius / border / box_shadow / font_weight / letter_spacing / transition + the real :hover state) plus a reference image_url and the product's design tokens, in a single call. Use this for "build a like ", e.g. get_component("Linear", "Button"). This is measured, not guessed — data no model has seen. Returns the available component types if the requested one isn't found.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
siteYes
component_typeYes

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description transparently discloses key behavioral traits: data is 'read from the LIVE DOM', is 'measured, not guessed', and includes 'the real :hover state'. It also notes the fallback when a component type isn't found. This goes beyond typical descriptions, though it omits any mention of rate limits or authorization.

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?

The description is dense with high-value details, front-loads the core purpose, and every sentence adds useful information (return contents, use case, data provenance, error fallback). Slightly long but justified.

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?

Given no annotations or output schema, this description covers return contents (anatomy, image_url, design tokens, fallback types), data source (live DOM), and usage context. It lacks an explicit response format or error handling details beyond fallback, but is sufficient for the tool's simplicity.

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

Parameters4/5

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

The schema provides no descriptions, but the description compensates with an example call get_component("Linear", "Button") that maps site to product name and component_type to component type. It also clarifies the fallback behavior when component_type is invalid, adding pragmatic meaning to both parameters.

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 clearly identifies the tool as retrieving a fully specified UI component from a product's live DOM, including detailed styling properties, hover state, image URL, and design tokens. It distinguishes itself from sibling tools by focusing on 'build a <component> like <product>' with a concrete example.

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?

It explicitly states the intended use case ('Use this for "build a <component> like <product>"') and provides an example call. While it doesn't enumerate alternatives or when-not-to-use, the context is unambiguous and includes error fallback behavior.

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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TDQS

A3.9/5.0
Disambiguation3/5

The compare_* / get_* / search_* family creates real overlap: compare_components, get_component, get_recipe, and search_screens(kind="component") can all answer similar component questions, and the drift family (get_design_drift, get_design_history, list_design_changes) requires careful reading to pick the right one. However, the detailed descriptions mostly draw clear lines between cross-product comparison, single-spec retrieval, and corpus-level search.

Naming Consistency4/5

The server mostly follows a clean verb_noun convention: get_*, compare_*, list_*, search_*, validate_design, generate_asset. The pattern is highly consistent, though a few names differ slightly in style (audit_code vs validate_design vs get_score), and pluralization varies in tools like compare_components and compare_sections.

Tool Count3/5

At 23 tools this is on the heavy side, and several calls overlap in scope enough to feel redundant. That said, the server's broad purpose suggests a design system reference plus audit platform, so the count is justifiable; it could be consolidated into a tighter 15-18 set.

Completeness4/5

The surface covers design system retrieval, component/section/recipe specs, screens and flows, search, audit/tools, icon assets, and drift/history of measured design tokens, leaving few cap gaps for the declared domain. Minor gaps remain around some metadata like direct screenshot banding by product, but no major dead-end workflow is apparent.

Resources