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get_design_context

Read-only

Resolve design token counts, component names, and conflicts before building UI. Filter by category or token type to get a full machine-readable contract summary without side effects.

Instructions

Get the resolved design system context before building UI. Read-only, no side effects. Default (no category) returns a JSON summary of token counts, component names, conflict counts, and contract metadata. Pass category: 'all' | 'tokens' | 'components' | 'conflicts' to get full detail. Pass tokenCategory to filter tokens: colors, spacing, sizes, typography, borderRadius, shadows, zIndex, breakpoints, motion (unknown/aliased categories return an actionable error, not a silent empty result). Use this as the first call to understand what exists. For lookups by name, use get_token or get_component instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryNo
tokenCategoryNo
Behavior5/5

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

Annotation readOnlyHint is reinforced and expanded with 'no side effects' and details about error behavior for unknown categories, adding value beyond annotations. No contradiction.

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 and structured, front-loading purpose with subsequent sentences adding detail. Slightly verbose but each clause carries useful info.

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?

Given no output schema, it describes the default summary output and category-specific detail, including error handling for unknown categories, making it complete for the agent to assess its use.

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 0%, so description fully compensates by explaining category values ('all', 'tokens', 'components', 'conflicts') and tokenCategory list, plus behavior for valid and invalid inputs.

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 states the tool gets the resolved design system context, distinguishes it from lookups by name with 'For lookups by name, use get_token or get_component instead.'

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

Usage Guidelines5/5

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

Explicitly says to use this as the first call to understand what exists, and names alternatives for specific lookups, providing clear context for when to use versus not.

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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