mercari_master

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

With no annotations provided, the description fully discloses behavioral traits: the data is large (tens of thousands of brand entries), effectively static, credential-free, and sourced from an anonymous, login-free session. It also includes caching guidance, which is valuable for an AI agent deciding how to invoke and use the tool.

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 three sentences long, front-loaded with the core purpose. Every sentence earns its place: the first states what it does, the second elaborates on the contents, and the third provides scale, stability, and auth context. No fluff or redundancy.

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?

For a simple no-parameter, no-output-schema tool, the description is highly complete. It covers purpose, response contents, scale, stability, and authentication requirements. The only minor gap is that it doesn't speficy the exact JSON response structure or field names, but the description is still more than adequate for an agent to use it correctly.

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 tool has zero parameters and an empty input schema, so there are no parameter semantics to clarify. The description adds context by detailing what the response contains (categories with parent linkage, every recognized brand, clothing/shoe/apparel sizes), which helps the agent understand the output scope.

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 opens with 'Get Mercari full taxonomy (categories, brands, sizes)', which is a specific verb+resource that clearly states what the tool does. It distinguishes itself from sibling tools like mercari_search or mercari_item by focusing on taxonomy retrieval, not individual listings or items.

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 provides clear context: it returns the full reference taxonomy in one call, and explicitly advises caching because the data is large and static. It implies usage for one-time taxonomy retrieval, but does not explicitly name alternative tools or state when not to use it.

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