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

The description mentions the output is a merged text with totals and categories, which is useful. It also mentions pricing, which is beyond annotations. However, it doesn't clarify pagination, sorting, or the exact format of the returned list beyond that. The annotation only has openWorldHint, which is not a contradiction.

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 concise, uses bullet points and examples for clarity, and front-loads the core purpose. No redundant information.

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's simplicity and the existence of an output schema, the description covers the main use case, exclusions, and examples. It could add a note on sorting or default behavior of year, but it's not critical for an agent to invoke it correctly.

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%, but the description adds context to the 'region' and 'chain_name' parameters by giving examples like '全国', '成都', '集成电路'. It also clarifies 'year' is optional and defaults to current year (though not explicitly stated, the schema says optional). Overall, the description reinforces and supplements the schema.

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 returns a list of companies that closed in a given year, filtered by region and industry chain, with a merged text of totals and subtypes. It distinguishes from the sibling tool 'chain_close_company_num' which likely returns only counts, by explicitly stating it returns the list.

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 is not included (other categories, only counts). It implies when to use this tool, but does not directly compare with the sibling 'chain_close_company_num' directly, but the name and description suffice for most cases.

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