resolve_rate_card_country

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly states this is a preview operation with no side effects, returns either the exact sheet or a clearly marked fallback, and explicitly discloses that it does not guess company names—a key behavioral constraint. It could add details about error handling or authentication, but the core behavior is well-covered for a simple preview tool.

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 short paragraphs, front-loaded with the primary purpose in the first sentence. Each sentence adds necessary information: purpose, return behavior, input guidance, and a rationale for not guessing. There is no filler or redundancy—every sentence earns its place.

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 has only one parameter and an output schema exists (though not shown), the description sufficiently covers the essential context: what the tool does, what it returns, and how to supply input. It could mention edge cases (e.g., unknown countries not in the fallback) or authentication requirements, but for a straightforward preview resolver with a clear fallback mechanism, it is adequately complete.

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 schema has zero description coverage for the 'country' parameter, so the description must compensate and does so excellently. It clarifies that 'country' means a geographical country, not a company name, and provides sourcing guidance (from the brief or trusted research). It also explains why a company name is insufficient, adding semantic depth beyond the schema's bare type definition.

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 a specific verb ('Preview'), a specific resource ('rate-card selection'), and a context ('before creating a proposal'). It distinguishes from sibling tools by explaining it resolves which rate card applies to a country, rather than simply listing or fetching rate cards. The return type (exact sheet or fallback) is also specified, making the tool's purpose 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 gives explicit guidance on what input to pass ('client's country as supplied in the brief or confirmed by trusted company research') and what not to pass ('A company name alone is intentionally not guessed'), which is strong usage direction. It also frames the tool as a pre-proposal step ('before creating a proposal'), implying when to use it. However, it does not explicitly name alternative tools for when this tool is not appropriate, leaving some inference to the agent.

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