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get_design_context

Get a semantic outline of a Figma page or screen, listing buttons, cards, inputs, and flow starting points to understand UI structure without vector noise.

Instructions

Retrieve a token-efficient semantic outline of the active document page or a specific screen (screens, buttons, cards, inputs, and flow starting points) without heavy vector noise

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
screenIdNoOptional Screen/Frame node ID to inspect. If omitted, outlines all screens on the current page.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

There are no annotations, so the description carries the burden of behavioral disclosure. It states the output is a token-efficient semantic outline and explicitly says it avoids heavy vector noise, which are useful behavioral traits. It does not mention side effects, prerequisites, auth needs, or response shape, but 'retrieve' implies a read operation and this is a low-risk getter.

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 one front-loaded sentence with no fluff, and the parenthetical list of outline contents is useful. 'Token-efficient' and 'without heavy vector noise' are slightly redundant, but the overall length is appropriate.

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

Completeness3/5

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

For a single-optional-parameter read tool, the description conveys the main use and parameter semantics. However, with no output schema and no annotations, it omits the exact return shape and fails to provide sibling differentiation, leaving some ambiguity for an agent deciding between similar inspection tools.

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 coverage is 100% for the single optional screenId parameter, and the description aligns with the schema by describing screen-level inspection versus the whole page. The description does not add much beyond the schema, but with full coverage the baseline 3 is appropriate.

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 names a specific operation ('retrieve a token-efficient semantic outline') and a concrete resource scope (active document page or a specific screen), and it enumerates outline contents such as screens, buttons, cards, inputs, and flow starting points. It does not explicitly contrast with sibling tools like get_selection, inspect_node, or generate_ui_tree, so it misses the top differentiation bar.

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?

The description implies the tool is for lightweight semantic exploration ('without heavy vector noise') but gives no explicit when-to-use guidance, exclusions, or named alternatives. With many sibling navigation/inspection tools present, an agent cannot tell when to choose this over generate_ui_tree or inspect_node.

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