Extract design tokens like colors, spacing, typography, and shadows from Storybook CSS variables. Filter by category to retrieve specific token sets.
Extract design tokens (colors, spacing, typography, shadows, etc.) from Storybook CSS variables.
| Name | Required | Description | Default |
|---|---|---|---|
| category | No |
Changes observed during successful MCP inspections.
v0.4.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of disclosing behavior. 'Extract' implies a read-only operation)Skip, but the description does not state what is returned, whether tokens are grouped, how the optional category parameter affects output, or what happens when no category is supplied. For a tool with no output schema, this leaves meaningful behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence with no filler. The core verb and resource are front-loaded, and the parenthetical examples add useful detail without bloating the definition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with only one optional parameter and no required inputs, the description is minimally workable: an agent can infer that calling it extracts tokens. However, with no output schema and no annotations, it should at least clarify the default category behavior or the shape of the extraction result. The gaps are not fatal but prevent full autonomy.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage for the single parameter is 0%, and the description only repeats token categories already visible in the enum. It does not explain the role of the optional category parameter, its default behavior, or what 'other' and 'all' mean semantically. The enum values are self-describing, but the description adds little beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Extract') and clearly identifies the resource ('design tokens' sourced 'from Storybook CSS variables'), with concrete examples of token types. It is readily distinguishable from all sibling tools, which focus on components, stories, and versions rather than token extraction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes the use case obvious: call this tool when design tokens need to be pulled from Storybook CSS variables. It does not explicitly name alternatives or exclusion criteria, but the sibling list contains no competing token-extraction tool, so the implied usage is clear and sufficiently contextual.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.