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get_section

Read-only

Get one product's specific section fully specified — its decoded spec + reference image_url + the parent product's design tokens — in a single call. Use this for "build a like ", e.g. get_section("Linear", "Pricing / Plans"). Deep-decoded products' design_tokens also carry measured button hover/focus states, shadows and motion — measured live, not guessed. Returns the available section types if the requested one isn't found.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
siteYes
section_typeYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint=true, openWorldHint=false), so the description's added value is the fallback behavior ('Returns the available section types if the requested one isn't found') and the note that deep-decoded tokens include measured hover/focus states, shadows, and motion. No auth or rate-limit context, but the behavioral disclosure is solid.

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?

Purpose and payload are front-loaded, and the example plus fallback note each earn their place. Slightly padded with em-dash asides, but no sentence is wasted.

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 carries the return-value burden and does list what comes back. The fallback-return behavior is disclosed. Missing only minor details such as output size/limits or what the 'available section types' response looks like.

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?

Schema description coverage is 0%, so the description must compensate — and it does by showing an example call, get_section("Linear", "Pricing / Plans"), which clarifies that 'site' is a product name and 'section_type' is a path-like label. It doesn't define the valid value space or case sensitivity, but the format is far clearer than the bare schema.

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?

States a specific verb and resource ('get one product's specific section') and enumerates the payload contents (decoded spec, reference image_url, parent product's design tokens), which cleanly separates it from siblings like get_component, get_screen, and get_screen_sections.

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?

Gives a concrete usage scenario ('build a <section> like <product>') with an example invocation, which tells the agent when this tool fits. It stops short of naming alternative siblings (e.g., get_component or get_screen_sections) for adjacent needs, so it lacks explicit exclusions.

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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