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

The annotation openWorldHint=true is present, but the description does not contradict it. The description adds context about the scope of data (basic information changes) and what is not included, but it does not disclose behavioral traits like data freshness, pagination, or error handling. Since annotations are minimal, the description carries some burden but does not fully disclose behavior beyond the scope.

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 detailed but well-structured, with clear sections for what it does, what it includes, what it excludes, and typical questions. It is longer than necessary but each part adds value. The front-loading is good: the first sentence states the core purpose. The pricing information is also included, which is useful.

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 (many possible query types) and the presence of an output schema, the description is fairly complete. It lists the specific indicators covered, exclusions, and typical questions. It does not explain the output format, but the output schema exists, so that is not required. The description is sufficient for an agent to understand the tool's scope and usage.

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 description coverage is 100%, with both parameters (company_name and country_name) having descriptions. The description adds context about the type of queries (basic information changes) and provides example values, but it does not add significant meaning beyond the schema. The baseline is 3 because the schema already documents the parameters well.

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 queries basic information periodic changes for a specific enterprise by name, covering operational status, industry classification, registered capital, scale financing, and group overview. It explicitly distinguishes from sibling tools by stating it is not for four-shang/listed/state-owned institutional attribute tagging, and lists exclusions like non-category indicators and batch screening by park/industry chain.

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 provides explicit usage context: it is for querying basic information changes by enterprise name, and explicitly states when not to use it (not for institutional attribute tagging, not for batch screening). It also provides typical question examples, which helps the agent understand the intended use cases. However, it does not explicitly name alternative tools, but the exclusions are clear enough.

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