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lnksoul1

UI Design MCP Server

by lnksoul1

Set Design Token

design_set_token
Idempotent

Set or update a design token for colors, typography, spacing, shadows, radii, or transitions, with real-time dashboard updates.

Instructions

Set or update a single design token. The client dashboard updates in real-time.

Categories: colors, typography, spacing, shadows, radii, transitions

Args:

  • category (string): Token category (colors, typography, spacing, shadows, radii, transitions)

  • key (string): Token key (e.g. "color-primary", "font-display", "space-md")

  • value (string): Token value (e.g. "#FF5733", "1.5rem", "12px")

Example:

  • design_set_token(category="colors", key="color-primary", value="#FF5733")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesToken key (e.g. 'color-primary')
valueYesToken value
categoryYesToken category
Behavior4/5

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

Annotations already convey readOnly=false, destructive=false, and idempotent=true. The description adds that the client dashboard updates in real-time, which is useful behavioral context beyond the structured fields. There is no contradiction with the annotations.

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 compact and well-structured: a purpose sentence, categories, arguments, and an example. The Args section somewhat repeats schema metadata, but it earns its place with value examples and a concrete invocation pattern, so there is no meaningful waste.

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?

For a simple 3-parameter setter with strong annotations and no output schema, this description is sufficient. It covers purpose, allowed categories, parameter formats, and the real-time effect. No significant behavioral or usage context is missing.

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 input schema has 100% description coverage, so the baseline is 3. The description adds concrete value examples (e.g., '#FF5733', '1.5rem') and clarifies token key patterns, which enriches parameter meaning beyond the 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?

The description clearly states the verb ('Set or update') and the resource ('a single design token'). The word 'single' effectively distinguishes it from bulk-generation siblings like ui_generate_design_tokens, and the example and categories further specify its precise scope.

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

Usage Guidelines3/5

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

Usage is implied: this is for updating one token, not generating a token system. However, it never explicitly states when to prefer this over alternatives such as ui_generate_design_tokens or design_update_component, and there are no exclusion criteria or when-not-to-use instructions.

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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