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

Beyond the readOnlyHint annotation, the description discloses that data is sourced from actual duty receipts (not the rulebook), covers 2017-present, is US national level, and is cross-checked against US Treasury receipts. It also notes 'No API key required.' These details add significant context about what the tool returns and how it behaves.

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 a single paragraph but effectively front-loaded with a strong 'CALL THIS' imperative and then packed with key details. Each sentence contributes to understanding, though the final 'No API key required' is a minor extra. It is efficient but not as lean as a two-sentence description.

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?

Given the tool's complexity (3 optional parameters, an output schema exists), the description fully covers the return values (monthly duty, effective rate, overall burden), the level of aggregation (origin, commodity, time range, national level), and the usage context. It leaves no major gaps for an AI agent to invoke 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 input schema already provides 100% coverage with descriptions for all three parameters, including acceptable formats (Census code, HS2 chapter name). The description adds little beyond examples that combine parameters (e.g., 'China vs India pays on auto parts'), but does not introduce new semantics or constraints. Baseline 3 is appropriate.

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 clearly states its purpose: returning actual US tariff receipts paid, measured from official duty receipts. It distinguishes itself from rulebook-based tools and training knowledge, and gives explicit examples of the kind of questions it answers (e.g., 'what China vs India pays on auto parts'). The verb+resource is specific and 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 begins with 'CALL THIS' and explicitly warns not to answer from training knowledge, marking a clear when-to-use signal. It further states that 2025-26 trade-war rates are ONLY correct from this tool, providing a strong exclusion for memorized answers. Examples of queries reinforce the intended scenarios.

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