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

No annotations exist, so the description must disclose behavior. It mentions pagination (分页) and return fields, but lacks details on pagination defaults, rate limits, or side effects. The description is adequate but could be more transparent.

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: purpose, filters, return fields, examples, sibling guidance. It is slightly long but each sentence adds value. It could be slightly more concise, but overall efficient.

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 complexity (21 params, output schema exists), the description covers the high-level purpose and return fields but omits details on many parameters (e.g., cursor, page_size, provinces). It is adequate for basic understanding but not fully complete.

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?

With 0% schema description coverage, the description must compensate. It lists filter categories in prose (keyword, industry, etc.) but does not map them to parameter names or provide format details. For 21 parameters, this is insufficient for precise usage.

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 searches closed companies with many filters, lists return fields, and gives examples. It distinguishes itself from siblings like search_companies and count_closed_companies by explicitly naming them and providing context.

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 explicit guidance: 'if user only asks for total count, use count_closed_companies' and lists typical use cases (recent closures, sector list, by cause). It effectively tells when to use this tool over alternatives.

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