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

The annotation only includes openWorldHint: true, which is vague. The description explains that the tool returns a combined text of total/production/sales/dependent lists, and that it excludes other classifications. This is some behavioral context beyond annotations. However, it does not clarify whether the response is a single aggregated text or separate lists, or any pagination/limit behavior, but that might be in the output schema. No contradiction noted.

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 and well-structured, using bullet points for metrics and exclusions, and providing clear examples. Every sentence adds value, no fluff. It is front-loaded with the core purpose.

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?

The tool has a rich output schema (though not shown), and the description covers purpose, included metrics, exclusions, and examples. Given the complexity of the chain context and the availability of the output schema, the description is sufficiently complete. It does not explain the combined text structure in detail, but that may be covered by 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?

The schema covers all parameters with descriptions. The description adds context by mentioning region granularity (country, province, city, district) and chain name examples, which align with the schema. Since schema coverage is 100%, baseline is 3. No additional syntax or format details beyond the schema, so score stays at 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 identifies the tool's purpose: querying a list of companies that closed in a given year, filtered by region and industry chain. It lists the included metrics/types (e.g., total, production-type, sales-type) and explicitly excludes other categories, distinguishing it from sibling tools like chain_close_company_num which returns counts.

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 (e.g., '2024年全国集成电路当年注销的企业名单') which illustrate usage. However, it does not explicitly state when not to use this tool versus alternatives like chain_close_company_num (which returns only counts), though the examples imply that this tool is for lists. It lacks explicit exclusion guidance.

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