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

Annotations only include openWorldHint, so the description carries much of the disclosure burden. It reveals that the result is a merged text combining total/production/sales/dependent counts, specifies exclusions, and states the per-run credit cost. It does not discuss auth or rate limits, but for a query/count tool this is adequate and no contradiction with annotations exists.

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 compact and front-loaded with the core purpose, followed by included metrics, exclusions, examples, and pricing. There is minor redundancy between the first sentence and the listed metric types, but overall every section earns its place and the structure is easy to scan.

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 simple 3-parameter interface, the presence of an output schema, and the clear annotation, the description is largely complete: it covers purpose, scope, exclusions, concrete examples, and cost. The only notable omission is the default year behavior, but this is minor since the schema marks year as optional.

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% with clear inline descriptions for year, region, and chain_name, so the baseline is 3. The tool description adds example questions and region granularity, but does not clarify default behavior when year is omitted or specify the exact structure of the merged text, leaving some semantic gap for the optional parameter.

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 states a specific query action ('查询') for newly established company counts by region and industrial chain, with explicit mention of merged total/production/sales/dependent metrics. It clearly distinguishes itself from siblings by excluding company list details and other classification statistics, particularly differentiating from chain_new_start_company_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 usage questions and explicit exclusions ('不包含：其他企业分类的统计；企业名单明细'), signaling when not to use this tool. However, it does not explicitly name alternative tools like chain_new_start_company_list or specify criteria for choosing this over other chain_*_num variants, so it stops short of full alternative guidance.

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