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update_token

Update a design token value in the local registry and optionally push the change to Figma for immediate propagation.

Instructions

Update a design token value in the local registry, and optionally push the change back to Figma.

Prerequisites: Token must already exist in the registry (use get_tokens to list names). To push to Figma, a plugin connection is also required.

Returns on success: Plain confirmation string Token "<name>" updated.

Error behavior: Returns isError if the token name is not found in the registry. If pushToFigma is true but Figma is not connected, the local update still succeeds — the push is silently skipped (no error thrown). To verify the push landed in Figma, capture a screenshot afterward.

Use this tool: to apply a token override (e.g. change a brand color for a client theme) and optionally propagate it to Figma immediately. For bulk token mapping to Tailwind, use sync_design_tokens instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesExact token name as it appears in get_tokens output (e.g. "Colors/Primary", "Spacing/XS"). Case-sensitive.
valuesYesMode-to-value map to merge into existing values (e.g. { "Light": "#FF0000", "Dark": "#FF6666" }). Only the modes you provide are updated — other modes are preserved.
pushToFigmaNoIf true and Figma is connected, push this token change to the Figma file immediately. Defaults to false (local registry only).
Behavior5/5

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

No annotations provided, but description fully discloses success return value, error condition (token not found returns isError), and edge case (silent skip when Figma not connected). Also advises verifying push via screenshot.

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?

Well-structured with clear sections (prerequisites, returns, error, use case). Every sentence adds value, no wasted words.

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?

Despite no output schema or annotations, the description covers prerequisites, return type, error handling, edge cases, and usage advice, making it fully contextual for correct tool selection and invocation.

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 100%, but the description adds extra context beyond schema, such as that only provided modes are updated and that pushToFigma defaults to false and skips silently if Figma not connected. This enhances parameter understanding.

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 that the tool updates a design token value in the local registry with an option to push to Figma. It also distinguishes from the sibling sync_design_tokens by indicating that tool is for bulk token mapping.

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?

Provides explicit prerequisites (token must exist, plugin connection for Figma push), a clear use case (apply token override and optionally propagate to Figma), and an explicit alternative (sync_design_tokens for bulk mapping).

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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