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

Annotations already declare the operation read-only, idempotent, and non-destructive. The description adds meaningful behavioral context beyond those annotations: the result is the authoritative table actually used by the engine, with its source and verification date. No contradiction exists, and no additional behavioral risks need to be disclosed for a read-only lookup.

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 focused sentences with no redundant phrases. The first sentence front-loads the tool's purpose and legal context; the second explains the return value's provenance. Every clause earns its place, and the structure is easy to scan.

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 read-only lookup with two well-documented parameters, an output schema, and strong annotations, the description is complete. It covers both supported kinds, states the authoritative nature of the result, and mentions source and verification date. There are no obvious gaps an agent would need filled to invoke it 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?

Input schema coverage is 100%, and both parameters have clear descriptions including the enum values and the country pattern. The description reinforces the two modes by naming the underlying regulations, but it does not add substantive parameter semantics beyond what the schema already provides. 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 names two precise resources, the country benchmark tier under Regulation (EU) 2025/1093 and the Annex I commodity-to-HS mapping under Regulation (EU) 2023/1115, and attaches a specific verb ('Look up'). It also states what is returned, the authoritative table with source and verification date. It clearly distinguishes itself from the action-oriented siblings like eudr_import_shipments or eudr_assess_evidence_gaps.

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 makes the intended use obvious: look up reference data used for EUDR compliance. It provides clear context about both lookup modes and emphasizes that the returned table is the one the engine actually evaluates against, which helps an agent treat it as authoritative. It does not explicitly name alternatives or exclusions, so it stops short of a 5.

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