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

No annotations are provided (openWorldHint is present but not relevant to behavior). The description mentions what is included and excluded (e.g., '不包含其他企业分类的统计；仅返回数量不返回名单') but does not disclose any side effects, permissions, rate limits, or data freshness. Behavior is partially transparent but lacks important details.

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, with clear sections for '涉及指标/类型', '不包含', and '典型问法'. It avoids redundancy and is well-structured. The repetition of the same text in description and schema examples is minor but acceptable.

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 description provides enough context for a typical use case (querying A-level taxpayer companies by region and chain). However, it lacks details about the output format (e.g., whether it returns a list of company names or detailed data), and no output schema is given. The exclusion of '仅返回数量' hints that it returns entity lists, but further specification would improve completeness.

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 input schema covers all three parameters (year, region, chain_name) with descriptions and examples. The description additionally clarifies that the result includes merged types, but does not explain the exact meaning of '依赖型' or how year affects results if omitted. Schema coverage is 100%, so baseline is 3; description adds some nuance but not substantial.

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 queries A-level taxpayer company lists by region and industry chain, distinguishing it from similar list tools by specifying the A-level taxpayer type. It mentions the merged return of total/production/sales/dependent types, which adds specificity.

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 includes typical question examples (e.g., '2024年全国集成电路A级纳税人企业名单') but does not explicitly state when to use this tool versus alternatives like park_a_taxpayer_company_list or chain_a_taxpayer_company_num. Usage context is implied but not clearly differentiated.

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