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

The description discloses the key metric scope ('近两年有对外投资的企业数量') and what is not included, which is useful beyond the openWorldHint annotation. It does not, however, explain how the optional year parameter interacts with the 'past two years' window, nor does it describe behavior for unmatched park names or data availability. The annotation is not contradicted, but the description adds only moderate behavioral context.

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 well-structured: a one-sentence purpose, a short 'included/excluded' section, and three typical-question examples. The examples are somewhat repetitive but each serves to demonstrate the expected phrasing. It is concise for the information content, with no filler beyond the optional pricing block.

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 two-parameter tool with an output schema and openWorldHint, the description covers the core purpose, metric, and exclusions. The notable gap is the unspecified relationship between the '近两年' (past two years) default and the optional 'year' parameter; this ambiguity could lead to incorrect invocations when a user specifies a year. Overall, the description is adequate but leaves this important semantic question unresolved.

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 already documents both parameters with 100% coverage, so the baseline is 3. The description adds natural-language examples for park_name and clarifies that the result is a count rather than a list, but it does not add any new semantic detail about the year parameter. The parameter meaning is adequately covered by the schema, with only marginal added value from the description.

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 clear verb+resource statement: '基于具体园区名称近两年有对外投资的企业数量查询' (query the count of companies with outward investment in the past two years for a specific park). It explicitly scopes the tool to a count metric and excludes list details ('不包含：其他企业分类的统计；企业名单明细'), distinguishing it from the sibling park_invest_company_list and other category-count tools. The typical-question examples further cement the purpose.

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 context for when to use the tool: for a park-specific count of companies with outward investment in the past two years. It states exclusions ('不包含：其他企业分类的统计；企业名单明细'), which implicitly steers an agent away from list-style or other-statistic tools. However, it does not explicitly name alternative tools such as park_invest_company_list or chain_invest_company_num, so it stops short of a fully explicit when-to-use/alternatives guidance.

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