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

The description adds some behavioral context beyond annotations: it specifies the scope of indicators (industry status, certification, credit rating) and what is not included. The annotation openWorldHint=true is present, and the description does not contradict it. However, it does not disclose details like whether the tool returns historical changes, how far back the data goes, or any rate limits. The pricing info is provided but that's not behavioral transparency. Given the annotation is minimal, the description carries some burden but could be richer.

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, with a clear main sentence, a list of included indicators, a list of exclusions, and typical question examples. It is front-loaded with the core purpose. The pricing info is appended but not part of the description. No wasted words, though the phrase '合作品牌方面的周期变化' could be more precise.

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 tool has an output schema (not shown but indicated), the description doesn't need to explain return values. The description covers the purpose, scope, exclusions, and examples. It is complete enough for an agent to select and invoke the tool correctly. The only gap is that it doesn't specify the exact nature of the '周期变化' (periodic changes) output, but the output schema likely covers that. The complexity is moderate, and the description handles it well.

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 description coverage is 100% for both parameters (company_name and country_name), with clear examples in the schema. The description adds typical question formats and clarifies the scope of the query, but it does not add much beyond the schema for the parameters themselves. The description mentions '基于具体企业名称' which aligns with the schema. Baseline 3 is appropriate since the schema already documents the parameters well.

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 periodic changes in cooperation brands based on a specific enterprise name, covering industry status, certification qualifications, and credit rating. It distinguishes from sibling tools by explicitly listing what it does not include (e.g., certification year, brand details, batch filtering by park/industry chain). However, the phrase '合作品牌方面的周期变化' is somewhat ambiguous and could be clearer about the exact output.

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 usage context: it is for querying industry status, certification qualifications, and credit rating changes for a specific enterprise. It also gives exclusions (not for certification year or brand details, not for batch filtering) and provides typical question examples. However, it does not explicitly mention when to use this tool over specific sibling tools like enterprise_change_certification or company_credit_rating, though the exclusions help.

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