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

With no annotations, the description carries the full behavioral burden and does disclose several useful traits: cost (0.011 USDC per call), that only one array is returned, that history may be incomplete, and that additional pages require separate requests. It says nothing about permissions/auth or the shape of returned fields, so the disclosure is partial rather than thorough.

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 useful purpose statement is front-loaded, but the remainder is padded boilerplate: the completeness/safety caveat is stated twice ('not guaranteed complete history' and 'No completeness or safety guarantee'), and generic disclaimer sentences dilute the actionable content. Multiple sentences do not earn their place.

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?

For a tool with opaque parameters, no output schema and no annotations, the description does cover cost, pagination, the company_id source and a schema-discovery pointer. It still leaves the actual argument list and return structure undocumented, so an agent needs a second lookup call before it can use this reliably.

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 0% and the single 'arguments' property is an opaque object with additionalProperties=true, so the schema provides essentially nothing. The description partially compensates by naming company_id as the key input and pointing to get_cn_data_tool_schema("v3_patent_law_count") for the full argument shape, but it never enumerates the actual required fields.

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 Chinese phrase '查询专利法律状态统计' states a specific verb (query) and resource (patent legal status statistics), which is far more informative than the machine name alone. However, it does nothing to differentiate this tool from the many neighboring patent tools (cn_data_v3_patent_type_count, cn_data_v3_patent_apply_trend, cn_data_v3_patent_header), so an agent still has to guess which patent metric it wants.

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?

'Use company_id from cn_data_v3_company_detail' and 'One selected Chinese company data tool call' give real context about the expected input source and call granularity. There is still no when-to-use/when-not guidance relative to the sibling patent count/trend tools, so usage is only partially implied by the surrounding boilerplate.

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