Skip to main content
Glama
Sign In
Agent Genesis Tools

Agent Genesis Tools

by xvacorx
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_brand_design

Retrieve color palettes, typography, shadows, and layout rules for 74 digital brands to style UI components and pages with authentic brand aesthetics.

Instructions

Retrieves design specifications, color tokens, typography scales, elevation shadows, and layout rules for 74 digital brands from the local design library. Safe, read-only operation: performs local disk read with no side effects, mutations, network requests, or authentication requirements. If an unknown brand slug is requested, falls back to substring matching or returns an alphabetical index of available brands.

When to use: Call whenever styling UI components, design tokens, or pages to follow authentic brand aesthetics. When NOT to use: Do not use to calculate color accessibility compliance; use check_contrast to validate contrast ratios of retrieved colors. Returns: Full markdown design specification containing color palettes, typography, spacing, and component patterns; or a comma-separated index of all 74 brand names when brand='list'.

Input Schema

NameRequiredDescriptionDefault
brandNoLowercase brand slug (e.g. 'linear', 'stripe', 'apple', 'supabase', 'vercel', 'raycast', 'figma'). Pass 'list' or empty string to retrieve all 74 available brand slugs. Defaults to 'list'.list

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv2.1.2
    • changedInput schema / properties / brand / description
      Previous value: -"Brand slug identifier (e.g. 'linear', 'stripe', 'apple', 'supabase', 'vercel', 'raycast', 'figma', 'notion') to fetch its design tokens, or 'list' to view all 74 indexed brand design systems."New value: +"Lowercase brand slug (e.g. 'linear', 'stripe', 'apple', 'supabase', 'vercel', 'raycast', 'figma'). Pass 'list' or empty string to retrieve all 74 available brand slugs. Defaults to 'list'."
  2. Changed1 schema field changedv0.1.2
    • changedInput schema / properties / brand / description
      Previous value: -"Brand name (e.g. 'linear', 'stripe', 'supabase', 'vercel') or 'list' to see all 74 brands"New value: +"Brand slug identifier (e.g. 'linear', 'stripe', 'apple', 'supabase', 'vercel', 'raycast', 'figma', 'notion') to fetch its design tokens, or 'list' to view all 74 indexed brand design systems."
  3. First observedv0.1.0

TDQS

A4.9/5.0
Behavior5/5

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

No annotations are supplied, so the description carries the full burden and does so: it discloses that this is a local disk read with no side effects, mutations, network requests, or authentication requirements, and it describes fallback behavior on unknown slugs (substring matching or alphabetical index). These are behavioral traits an agent cannot infer from the schema.

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?

Front-loaded with the core action, then clearly labeled "When to use" / "When NOT to use" / "Returns" blocks. Every sentence carries distinct information — contents, safety profile, fallback, routing, return format — with no restatement of the tool name or filler.

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?

For a single optional-parameter read tool with no output schema, the description covers purpose, safety, fallback, routing, and return format (markdown spec or comma-separated brand index). Nothing an agent needs in order to call it correctly is missing.

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 baseline is 3; the description earns extra by explaining the degenerate-input behavior — an unknown brand slug triggers substring matching or an alphabetical index — which is meaningfully beyond the schema's enumeration of example slugs and the 'list'/empty-string convention.

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 and resource ("Retrieves design specifications... for 74 digital brands") and enumerates the contents (color tokens, typography scales, elevation shadows, layout rules). The scope (local design library, 74 brands) is concrete enough that an agent can distinguish it from siblings like check_contrast or query_codebase_graph without opening a schema.

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

Usage Guidelines5/5

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

Explicit "When to use" (styling UI components/tokens/pages) and "When NOT to use" with a named alternative and the condition that selects it: "Do not use to calculate color accessibility compliance; use check_contrast." This is exactly the routing information an agent needs among the five siblings.

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

Deploy Server

Other Tools