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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds useful context that the taxonomy is public and that no transactional fields are returned, clarifying the output scope without contradicting 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?

Two compact sentences with no redundancy. The primary purpose is front-loaded, followed by a single clarifying note about the absence of transactional fields.

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 one-parameter, read-only list tool, the description covers the purpose, the public nature, and the output scope. It lacks explicit output structure and limit-default behavior, but annotations cover safety and the overall complexity is low.

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?

Schema description coverage is 0%, and the description gives no information about the 'limit' parameter beyond what the schema min/max already state. It does not explain default behavior, pagination, or how the limit affects results, so the description fails to compensate for the low coverage.

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 uses a specific verb ('List') and specific resource ('public product-category taxonomy'), and explicitly states what is returned ('names and descriptions for machine classification'). It also contrasts with sibling tools by noting 'No transactional fields are returned,' making its scope clear.

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: use this tool to get public taxonomy data for machine classification. The note about no transactional fields helps route away from transactional data tools, but it does not explicitly name alternatives or state when not to use this tool.

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