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

Beyond the readOnlyHint annotation, the description discloses the exact output structure (answer line, MFN base, Chapter-99 provisions with citations, receipts_reality), explains that measures are matched by ORIGIN and SECTOR rather than HS code alone, and warns against summing addon_pct or misquoting the tariff. This is substantial behavioral context that prevents misuse.

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 dense but well-structured, starting with a bold directive, then enumerating return values, then key warnings with 'IMPORTANT:', and ending with an example and disclaimer. Every sentence adds value; it's longer than typical but justified by the tool's complexity and the need to prevent misinterpretation.

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?

With no output schema, the description fully specifies what the tool returns and in what order. It also covers edge cases (product-specific measures, matching logic), provides an alternative tool, and includes a disclaimer. The description is complete for a tool of this complexity and read-only nature.

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?

While schema coverage is 100%, the description adds critical semantics about the origin parameter: it 'adds in-force measures and receipts reality' and clarifies that measures are matched by origin and sector, not the HS code. It also provides a concrete example ('tariff on 9401.61 from China') and warns about product-specific scope, going beyond the raw schema.

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 a direct command 'CALL THIS' and explicitly states the tool's purpose: retrieving the tariff schedule behind one HS code. It clearly distinguishes from siblings by directing users to tariff_story for 'what does X from Y pay' queries, making the tool's specific role unambiguous.

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 explicit when-to-use guidance ('CALL THIS for the schedule behind one HS code'), warns against reciting from memory, and explicitly excludes the alternative ('For 'what does X from Y pay' prefer tariff_story'). It also cautions about product-specific measures not applying, giving clear behavioral boundaries.

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