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

The only annotation is openWorldHint: true, which gives minimal behavioral context. The description adds useful details like the returned fields and per-run pricing of 0.2 credits, but it does not disclose pagination behavior, possible empty results, or any read-only guarantees. Since annotations are sparse, the description carries much of the burden but only partially fulfills it.

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 one concise sentence that front-loads the core purpose, followed by a compact pricing block. There is no fluff or redundancy, and every element serves a clear communication purpose.

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 lookup tool with one required parameter, an existing output schema, and complete parameter descriptions, the description covers the essential intent and cost. It lacks caveats such as whether the company name must be an exact legal name or whether credit ratings exist for all companies, but these are minor gaps given the tool's simplicity and schema richness.

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 parameters (page, limit, company_name) are already fully documented. The description adds no additional semantic detail beyond restating that company_name must be explicitly specified, which matches the schema. 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 the tool's function: query credit rating information for a specified company, listing key return fields (主体评级、评级展望、评级机构、评级时间). This verb+resource structure is specific and distinguishes it from sibling tools that cover other company data such as violations, executives, or subsidies.

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 phrase '基于明确指定的企业名称' provides clear context that the tool requires a specific, known company name. It implies the intended use case without explicitly naming alternative tools or stating when not to use it, so it falls at 4 rather than 5.

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