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

The only annotation is openWorldHint, so the description carries most of the behavioral disclosure burden. It adds useful scope boundaries (what is and is not counted), but it does not describe edge cases, unknown park behavior, or whether the result is a simple numeric count versus a structured object. The output schema helps, but the description itself lacks deeper behavioral context.

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 well-structured: purpose first, followed by included/excluded items, then typical questions. Every sentence contributes, and the pricing metadata is separated clearly.

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 2-parameter tool with full schema coverage and an output schema, the description is sufficiently complete: it explains purpose, scope, exclusions, and provides examples. It could be slightly stronger by pointing users to the corresponding list tool for detailed company names, but that is not essential.

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%, with both park_name and year described with examples. The tool description repeats some examples but adds little semantic value beyond the schema, so the baseline score of 3 applies.

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 precisely states the tool queries the count of enterprises in a named park that have existed for more than 5 years. It explicitly lists included metrics, excluded categories, and gives three realistic example questions, clearly distinguishing it from list/detail siblings.

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 query phrasings and explicit exclusions ('does not include list details or other enterprise category statistics'), making when-to-use clear. However, it does not explicitly name alternative tools such as park_year5_company_list or chain_year5_company_num, 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.