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

Annotations only provide openWorldHint, so the description bears most of the transparency burden. It adds useful scope details: park-specific, specialized enterprise list, and exclusion of count-only output. However, it does not disclose pagination, result detail level, or data freshness. No contradiction with annotations exists.

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, with logical sections for the query type, included/excluded behaviors, typical questions, and pricing. The phrasing '仅返回数量不返回名单' under '不包含' may be slightly ambiguous, but overall the content is efficient and 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?

For a simple 2-parameter tool with an output schema present, the description covers the core purpose, usage examples, exclusions, and pricing. It could explicitly mention the count-vs-list sibling alternative, but the tool name and sibling list make this inferable. The description is adequate for the tool's complexity.

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 already provides 100% coverage with descriptions for both parameters, including examples for park_name and a clear optional note for year. The description adds little beyond reinforcing that park_name is the key input and restating examples in typical question form, so it does not substantially exceed schema-level meaning.

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 '基于具体园区名称专精特新企业列表查询' (query list of specialized enterprises by park name) and lists the metric type. The '不包含' clause explicitly excludes other classifications and count-only behavior, distinguishing it from sibling tools like park_specialized_company_num. Typical question examples reinforce the intended use.

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 clear contextual signals through typical question patterns (e.g., '中关村软件园专精特新企业名单') and states exclusions (other enterprise classifications; count-only responses). However, it stops short of explicitly naming alternative tools such as park_specialized_company_num for counts or chain_specialized_company_list for chain-level queries.

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