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

The description adds useful behavioral context by stating it merges return text for total/production/sales/dependent categories and excludes other classifications. However, annotations are minimal (only openWorldHint), so the description still lacks details on pagination, data source, read-only guarantees, or how 'no patent' is determined, leaving some transparency gaps.

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 and front-loaded: it opens with the core purpose, then lists included metrics, exclusions, typical questions, and pricing. Each section earns its place, though the pricing block adds some extra length beyond the functional description.

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 3-parameter list query with an output schema, this description is highly complete. It covers required and optional parameters, gives examples for each kind of input, clarifies what is not returned, and distinguishes from the count-only sibling. Minor gaps like error handling or empty-result behavior are not critical given the output schema.

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?

Input schema coverage is 100%, so the schema already documents all three parameters. The description reinforces this with realistic examples ('2024年', '全国', '集成电路'), but does not add materially new semantic information beyond what the schema provides.

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 this is a query for a list of companies without patents, scoped by specific region and industry chain name. It explicitly distinguishes itself from sibling tools by listing included metric types (total/production/sales/dependent) and excluding count-only returns, making its 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 provides typical example questions and explicit exclusions ('不包含：其他企业分类的统计；仅返回数量不返回名单'), which tells an agent when not to use this tool. However, it does not explicitly name the sibling tool `chain_have_no_patent_company_num` as the alternative for count-only requests, so guidance is strong but not fully explicit.

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