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

The tool has openWorldHint annotation, meaning results are an open set. The description clarifies the return contains combined text for total/production/sales/dependent types and excludes other categories, but it doesn't disclose pagination, email formatting, or whether it returns full lists or sampled. It also doesn't mention the 100 credits cost, which is available in the description but not emphasized. The annotation doesn't contradict the description.

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 organized with clear sections: purpose, included metrics, exclusions, and example queries. It's concise at around 150 Chinese characters and front-loads the core purpose. The pricing line is separated and relevant. Minor redundancy with listing metrics that are clear from the tool name.

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 the tool has an output schema (though not provided in detail) and clear parameters, the description covers the essential scope, exclusions, and examples. It doesn't explain the return structure but the output schema presumably handles that. The openWorldHint is offset by the description's explicit exclusions. Missing details on pagination or result size, but acceptable for a list tool with typical patterns.

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?

Schema coverage is 100%, so each parameter has a description. The description adds context via example question formats (region like '海淀区' and chain like '人工智能') that map directly to the parameters, but doesn't provide additional syntax or format details beyond what the schema offers. It explicitly shows how to combine region and chain_name in queries, adding value slightly above baseline.

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 it queries companies with software copyrights by region and industry chain, listing the specific metrics included. It distinguishes from sibling tools like chain_have_copyright_company_num (which returns count only) and chain_company_list (which returns all companies), but doesn't explicitly name alternatives.

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 by providing typical question examples and specifying what is excluded (other company classifications, count-only returns). However, it doesn't explicitly state when to use this vs. the companion count tool or other chain_*_list tools, only implicitly distinguishing via scope.

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