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

With only an openWorldHint annotation, the description carries most behavioral weight. It discloses that the result merges total/production/sales/other text, and explicitly excludes count-only returns and other classification statistics. It does not discuss pagination/defaults, but the query/list behavior is clearly conveyed.

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 core intent is front-loaded and examples are useful, but the '涉及指标/类型' section repeats the same no-patent-list types nearly verbatim from the opening parenthesis, adding redundancy and making the description longer than necessary.

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 3-parameter list query with an output schema, the description is complete enough: it includes required scope, excluded cases, and typical examples. A direct mention of the numeric sibling tool would make it slightly more complete, but it is already actionable.

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 covers all parameters, and the description adds useful semantics by specifying region granularity: country, province, city, and district. Concrete examples further clarify chain_name and year usage beyond the schema examples.

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 states a specific verb-plus-resource: querying a list of companies without patents based on region and industry chain. It clearly separates this from the sibling 'num' tools and from 'have_patent' list tools.

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?

It defines when the tool is appropriate: specific region + chain name, with three typical user-phrasings. The '不包含' clause clarifies this tool is not for count-only output or other enterprise categories, though it does not explicitly name the alternative count tool.

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