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

Annotations only provide openWorldHint, placing some burden on the description. The description discloses that it returns counts only (not lists), but it does not discuss data assumptions, freshness, or how the count is computed. It adds minimal behavioral context beyond the annotation, so a score of 3 is appropriate.

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 compact, starting with the main purpose, then metric, exclusions, and examples. It includes pricing metadata, which is somewhat extraneous but not problematic. The structure is logical and front-loaded, with no unnecessary fluff. Slightly less tight than the ideal, but efficient.

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 count tool with only two parameters and an output schema, the description covers the essential aspects: what it does, what it excludes, and typical queries. It does not explain edge cases or data limitations, but given the low complexity and presence of output schema, 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 input schema provides full descriptions for both parameters (park_name and year), covering 100% of them. The tool description does not add extra semantics beyond the schema, and the schema descriptions are self-explanatory. Thus, a baseline of 3 is warranted.

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 counts enterprises without patents for a specific park ('基于具体园区名称没有专利的企业数量查询'), explicitly mentions the metric type, and excludes list details and other categories, which distinguishes it from sibling list tools like park_have_no_patent_company_list. It also provides typical question examples, making the 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 implies usage for count-only queries by stating exclusions ('不包含：其他企业分类的统计；企业名单明细'), which suggests using list tools for details. Typical questions give context, but it does not explicitly name alternative tools (e.g., park_have_no_patent_company_list). This is clear enough but not as explicit as referencing specific alternatives.

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