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vibecraft-mcp

vibecraft-mcp

by satyamuiux-byte
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

get_layout_blueprint

Retrieve NN/g-based layout scaffolds and design system task patterns to build accessible React/Tailwind interfaces with proven IA structure.

Instructions

Retrieves Nielsen Norman Group (NN/g) Information Architecture (IA) macro page layout scaffolds and Design System Task Patterns (AI Co-pilot generation, Destructive actions, SaaS Dashboards, Settings, Onboarding, Pricing).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_layout_blueprint"
  }
}

Input Schema

NameRequiredDescriptionDefault
idNoBlueprint ID e.g. 'saas-dashboard', 'saas-settings', 'ai-generation-pattern', 'destructive-confirm-pattern'
typeNoFilter layout type

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.8.0

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are provided, so the description carries the behavioral disclosure burden. 'Retrieves' does establish a read-only operation and the content categories are explicit, but the description nothing about behavior when parameters are omitted or how optional parameters interact, and it does not mention error or fallback behavior.

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?

A single dense sentence front-loads the verb and primary resource, with the remaining space devoted to useful examples. There is no filler or redundant phrasing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple 2-parameter retrieval tool the description is mostly adequate, but it does not disclose the default behavior when no `id` or `type` is provided, and the distinction between returning one blueprint vs a filtered list is unclear. With no output schema and no annotations, that is a meaningful ambiguity.

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 coverage is 100%, so the baseline is 3. The description adds value by distinguishing the two retrievable resource types — macro layout scaffolds vs task patterns — which isn't fully spelled out in the schema's enum alone. The parenthetical examples reinforce the categories an agent can expect to find.

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 opens with a specific verb ('Retrieves') and clearly names the resources: NN/g IA macro page layout scaffolds and Design System Task Patterns. The listed example patterns (AI Co-pilot generation, Destructive actions, SaaS Dashboards, Settings, Onboarding, Pricing) make the tool's scope concrete and distinguish it from siblings like get_ux_guidelines, get_component_code, or get_design_tokens.

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

Usage Guidelines2/5

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

The description provides no guidance about when to use this tool versus alternatives. It does not name any sibling tools or exclude situations, so an agent must infer the usage context from the content list alone.

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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