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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so safety is covered. The description adds behavioral context beyond annotations: it discloses that the tool does not fabricate a rate for countries without a national rate, instead reporting a jurisdiction requirement. This is a meaningful, non-obvious behavior that an agent must know before calling.

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 two sentences with no filler. The primary output is front-loaded, and the exception is stated clearly and concisely. Every word earns its place, making it easy for an agent to parse quickly.

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 tool with only two parameters (one required) and an output schema, the description is complete. It covers the core behavior, the special case, and the return fields. An agent has all necessary information to call it correctly and interpret the result, with no missing details about prerequisites or response format.

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 100%, so both parameters are already documented. The description adds value by explaining the semantic nuance of the 'country' parameter: for certain countries (e.g., US), the tool will report a jurisdiction need rather than a numeric rate. This enriches the agent's understanding of how to interpret the response, going beyond the schema's basic format.

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 ('look up') and resource ('tax rule'), and details exactly what is returned: published rate, name, currency, and source, across 195 countries. It also clarifies the special case of countries without a national rate (like the US), which further defines scope. It is clearly distinct from siblings like build_document or calculate_totals.

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 implies when to use this tool (when you need tax information for a country) and provides a crucial usage caveat: for countries like the US, no single rate is returned; instead, the result indicates a jurisdiction is needed. It does not explicitly name alternative tools, but the sibling list makes the distinction obvious, and the caveat effectively guides the agent on expectations.

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