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

With no annotations provided, the description carries the full burden and does well: it explains fallback behavior (returns a normalized code, Italian VAT rate, and TARIC link even when a practitioner-verified duty is unavailable), the automatic x402 payment model, and the non-binding reference nature of the data. This goes well beyond a bare operation statement.

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 information-dense but every major point earns its place: purpose, fallback behavior, primary use case, data volatility caveat, pricing/payment method, and an example. It is slightly long, but the density is justified; key purpose is front-loaded in the first sentence.

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?

There is no output schema, so the description reasonably covers what the caller receives: duty when available, normalized code, Italian VAT rate, and a TARIC deep link. The payment mechanism and example round out the practical context needed to invoke the tool correctly. A fully formal return structure is missing, but the description is sufficient for an agent to use the tool.

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 the baseline is 3. The description adds a concrete example code and clarifies that the returned code is normalized/validated, but it does not materially expand on the parameter definitions already present in the 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 specific verb and resource: 'Expert-verified import duty and Italian import VAT for any EU HS/CN code.' This cleanly distinguishes get_tariff from siblings like classify_product, get_origin_rule, and check_restrictions by naming the exact data domain (duty/VAT) and input type (HS/CN code).

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?

It explicitly tells the agent when to use it: 'Use it to estimate landed cost or confirm the duty on a classified good.' While it does not name alternative sibling tools or say when not to use it, the use cases are concrete and clearly scoped, and the caveat about rates changing adds a practical boundary.

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