agent-toolbelt

Brand Kit Generator

generate_brand_kit

Create a complete brand kit with color palettes, typography pairings, and design tokens from company details and aesthetic preferences. Outputs in JSON, CSS, or Tailwind formats with WCAG accessibility scoring.

Instructions

Generate a complete brand kit from a company name, industry, and aesthetic keywords. Returns a color palette with WCAG accessibility scores, curated typography pairings, and design tokens in JSON, CSS, or Tailwind format.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

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

Input Schema

Name	Required	Description	Default
`name`	Yes	Company or brand name
`industry`	No	Industry (e.g., 'fintech', 'healthcare', 'fashion')
`vibe`	No	Aesthetic keywords: 'modern', 'playful', 'luxurious', 'minimal', 'bold', etc.
`format`	No	Output format	full

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Mar 30, 2026

TDQS

A4.3/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively compensates by specifying output quality (WCAG accessibility scores), available export formats (JSON, CSS, Tailwind), and the structured components returned (typography pairings, design tokens), giving the agent clear expectations of the generation 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?

Two well-structured sentences with zero waste: the first covers inputs and core function, the second covers outputs and formats. Information is front-loaded and every clause earns its place.

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?

Given the absence of an output schema, the description excellently compensates by detailing the return structure (color palette with accessibility scores, typography, design tokens) and available formats. For a 4-parameter tool with full schema coverage, this provides complete contextual information for successful invocation.

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?

The input schema has 100% description coverage with clear examples (e.g., 'fintech', 'modern'). The description mentions the parameters ('company name, industry, and aesthetic keywords') but does not add semantic meaning, constraints, or relationships beyond what the schema already provides, meeting the baseline for high-coverage schemas.

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 explicitly states the tool generates a 'complete brand kit' using specific inputs (company name, industry, aesthetic keywords). It clearly distinguishes itself from the sibling tool 'generate_color_palette' by emphasizing the comprehensive nature of the output (including typography and design tokens, not just colors).

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

Usage Guidelines4/5

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

While it does not explicitly name sibling alternatives, it provides clear contextual differentiation by detailing the full scope of outputs (color palette + typography + design tokens). This enables an agent to infer this is the comprehensive choice versus more specialized tools, though explicit when/when-not guidance would strengthen it further.

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