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kiettt8-product

figma-ui-mcp

design_system_context

Load semantic design-system rules from the configured bundle, covering fonts, spacing, typography, and component roles. Use these rules instead of guessing values from screenshots.

Instructions

Load prompt-ready semantic design-system rules from the configured bundle. Includes font dependencies, spacing tokens, typography roles, component roles, generation policies, and an optional screen recipe with an Auto Layout blueprint. Use this instead of guessing values from screenshots.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
recipeNoSemantic recipe ID such as 'voucher-pocket'. Omit to load only global design-system rules.
reloadNoReload bundle files before building context.
sessionIdNoScope the pre-write gate to a specific Figma tab when multiple files are connected.
Behavior3/5

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

With no annotations, the description must convey behavioral traits. It lists the contents (font dependencies, spacing tokens, typography roles, etc.) and mentions the optional recipe with Auto Layout blueprint, adding context. Yet it does not disclose whether the operation is read-only, has side effects, or requires specific configuration or permissions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is only two sentences long, with the first sentence front-loading the core purpose and the second adding useful content details and a directive. No wasted words, making it concise and well-structured.

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 gives a good sense of what is returned by listing the categories of rules and mentioning the optional recipe blueprint. However, it does not specify the exact output structure or what 'prompt-ready' means in terms of formatting, leaving a slight gap in completeness.

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?

All three parameters have detailed descriptions in the schema (recipe, reload, sessionId), covering 100% of the parameters. The description itself adds no parameter-specific information, so it relies entirely on the schema, justifying the baseline score.

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 loads prompt-ready semantic design-system rules from a configured bundle, using the specific verb 'load' and naming the resource. It also distinguishes itself from guessing values from screenshots, which sets it apart from sibling tools like figma_read.

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?

The description explicitly directs users to 'Use this instead of guessing values from screenshots', providing a clear use case. However, it does not name alternative tools or detail when not to use them, so guidance is clear but not exhaustive.

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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