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

Beyond the single openWorldHint annotation, the description clarifies the tool's scope: it returns only a count and excludes list-level company details. The verb '查询' also makes the read-only nature apparent. It does not disclose edge-case behavior such as unknown park names or data coverage, but it provides meaningful boundary information.

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 purpose, followed by exclusions and example queries. The appended Pricing JSON is not directly relevant to tool selection/invocation and adds minor noise, but overall the structure is 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?

For a simple count-by-park tool with one required and one optional parameter and an output schema, the description covers purpose, scope, exclusions, and typical user phrasings. It lacks explicit guidance on fuzzy matching/unknown park names, but this is not critical given the simple schema and examples.

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 description coverage is 100%, so park_name and year are already documented with examples. The description's typical questions reinforce these same examples but do not add new parameter-level meaning such as year constraints, format rules, or matching behavior.

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 the tool queries high-tech enterprise counts by specific park name (基于具体园区名称高新技术企业数量查询). It explicitly excludes other enterprise classifications and company list details, distinguishing it from list-style siblings like park_high_tech_company_list and other park metric tools.

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 when-to-use context through typical questions and states exclusions (不包含：其他企业分类的统计；企业名单明细), so an agent knows not to use this for lists or other classifications. It stops short of explicitly naming alternative tools, but the exclusions are enough to orient selection.

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