get_style
Returns every design token of an extracted brand style: colours, typography, CSS variables and the generated DESIGN.md.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Style slug from list_styles. |
Returns every design token of an extracted brand style: colours, typography, CSS variables and the generated DESIGN.md.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Style slug from list_styles. |
Changes observed during successful MCP inspections.
Input schema / properties / slug / descriptionPrevious value: -"Style-Slug aus list_styles."New value: +"Style slug from list_styles."Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It does disclose the returned artifact set, which is useful behavioral context, but it never states that this is a non-mutating read, nor what happens for an unknown slug or whether a style must first be extracted.
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?
One sentence, front-loaded with the verb and resource, with the enumerated payload as a compact tail. No filler or redundancy.
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?
There is no output schema, so the description must convey return values, and it does so by enumerating the token categories plus DESIGN.md. The main remaining gap is error/edge-case behavior for an invalid or unextracted slug.
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 is 100%, so the single 'slug' parameter is already documented as coming from list_styles; the description adds no syntax, format, or validation detail beyond that, which is the expected baseline when the schema does the heavy lifting.
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?
States a specific verb ('Returns') and resource ('every design token of an extracted brand style'), then enumerates the payload (colours, typography, CSS variables, DESIGN.md). It is clear and concrete, though it never names a sibling to contrast with, so sibling differentiation is left to inference.
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?
Usage is only implied via the slug parameter's schema note ('Style slug from list_styles'), which does hint at the prerequisite tool. There is no statement of when to use this versus get_component_styled or other lookups, and no exclusions.
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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