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

The description adds some behavioral context by stating that the response merges text for total/production/sales/dependent types, which is beyond the schema. It also notes the exclusion of count-only returns. However, it does not mention pagination, authentication, or other behavioral traits. With only openWorldHint annotation, the description carries some burden, but it does not fully disclose all relevant behaviors.

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: it opens with the core purpose, then lists indicator types, exclusions, and typical queries. It is slightly verbose due to the inclusion of pricing JSON, which is not strictly needed for tool usage. However, the main content is concise and front-loaded, making it effective without excessive length.

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?

Given that the tool has an output schema, the description doesn't need to explain return values. It covers the key aspects: inputs (region, chain), what types of lists are returned, exclusions, and typical uses. It does not mention any limitations like regional granularity (though that's in the first line) or prerequisites, but for a list tool with an output schema, it is sufficiently complete. The many sibling tools are not explicitly referenced, but the exclusions help narrow down usage.

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 descriptions for all three parameters with examples (coverage 100%), so the schema does most of the work. The description adds value by explaining that the output merges multiple sublists (total/production/sales/dependent) and clarifying what is not included, which gives context for how the parameters influence results. This goes beyond the schema, so a 4 is appropriate.

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's purpose: it queries the list of enterprises with patents based on region and industry chain name. It explicitly lists the types of lists returned (total, production, sales, dependent) and differentiates from sibling tools by asserting it returns a list, not just a count, and does not include other classifications. This distinguishes it from chain_have_patent_company_num and other similar 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?

The description provides typical query examples and explicitly states what the tool does NOT include (other classifications and count-only results). This gives clear boundaries for when to use this tool versus count-only or other classification tools, though it does not name sibling tools directly. The exclusions imply alternatives, but without explicit naming it is not a full 5.

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