Skip to main content
Glama

StyleKit

Get StyleKit style detail

stylekit_get_style
Read-onlyIdempotent

Get one style's full profile: philosophy, palette, do/don't rules, keywords, and what's available (tokens, recipes, shadcn install). Style data is read from the live catalogue with a five-minute cache; when live data is unavailable, a bundled snapshot may be returned and marked with origin and fallbackReason.

Args:

  • slug (string): style identifier, e.g. "glassmorphism", "neo-brutalist".

Returns JSON: { slug, name, nameEn, category, tags, description, philosophy, colors, doList, dontList, keywords, hasTokens, hasRecipes, recipeIds, shadcnInstall, url, quality, origin, fallbackReason? }. The content provenance is separate from origin when returned by the implementation brief.

Examples:

  • "how should I use neo-brutalist?" -> slug: "neo-brutalist"

  • Returns an error with a hint if the slug is unknown.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesStyle slug, e.g. 'glassmorphism'

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
nameYes
slugYes
tagsYes
colorsYes
doListYes
nameEnYes
originYes
qualityYes
categoryYes
dontListYes
keywordsYes
hasTokensYes
recipeIdsYes
hasRecipesYes
philosophyYes
descriptionYes
shadcnInstallYes
fallbackReasonNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Beyond the readOnly/idempotent/non-destructive annotations, the description discloses meaningful behavior: a five-minute live-catalogue cache and a bundled-snapshot fallback marked with origin and fallbackReason. That fallback/origin disclosure is genuinely useful and not derivable from the annotations. The sentence about 'content provenance is separate from origin when returned by the implementation brief' is muddy and undercuts it slightly.

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

Conciseness3/5

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

Purpose is front-loaded, which is good, but the full JSON return shape is restated at length even though an output schema exists (redundant), and the provenance sentence is confusing filler. Several lines do not earn their place against the structured fields.

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?

Covers purpose, arg example, fallback/caching behavior, and error handling; with an output schema present it need not explain return values (though it does, redundantly). It is largely complete for a single-parameter read tool, missing only explicit sibling routing.

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?

Schema description coverage is 100% and the single slug parameter is already documented in the schema, so the baseline is 3. The description adds only extra example values ('glassmorphism', 'neo-brutalist') beyond the schema's example, which is marginal added meaning.

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?

States a specific verb+resource ('Get one style's full profile') and enumerates the exact fields returned (philosophy, palette, do/don't rules, keywords, availability flags). An agent can distinguish this from siblings like stylekit_get_style_tokens and stylekit_get_component_recipe because it describes the aggregate profile rather than the individual artifact.

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?

Provides a usage example ('how should I use neo-brutalist?' -> slug) and notes the error behavior for unknown slugs, which implies when to call it. However it never states when to use this versus stylekit_search_styles (to discover a slug) or the token/recipe/shadcn siblings, leaving the routing to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.