get_brand_system

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

Annotations already establish the tool as read-only, idempotent, and non-destructive. The description adds meaningful behavioral context: matching is limited to 12 known design systems and returns the closest match with ready-to-use CSS. This sets realistic expectations about approximate matching, which is useful beyond the annotations.

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?

The description is compact, front-loaded, and every sentence earns its place: purpose, trigger example, and output expectations. It contains no filler or redundant explanation.

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, but the description explicitly names what the tool returns: full token set, style guide, implementation instructions, and ready-to-use CSS. It could add more on fallback behavior when no close match exists, but the core call context is covered.

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?

The input schema provides 100% parameter coverage, including enums, defaults, and examples. The description adds little beyond restating that CSS output is possible and showing a company example, so the schema carries the main semantic load.

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?

The description states a specific verb and resource: get a complete design system built around a specific company's branding, with a concrete example (Spotify). It clearly differentiates itself from generic siblings like get_design_system and list_design_systems by emphasizing company-matching branding.

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?

The description gives a clear trigger phrase ('Say "Make me an app with branding like Spotify"') and describes what the tool returns. However, it does not explicitly explain when to prefer this tool over alternatives like get_design_system or what to do if the requested company is not among the 12 known systems.

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