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

The description adds the behavioral note that the tool only returns counts and excludes list details, complementing the openWorldHint in annotations. It does not mention any side effects, permissions, or rate limiting, but the presence of an output schema mitigates the need for return-format explanations. No contradiction with annotations.

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, starting with the main purpose, then noting exclusions, and providing typical queries. However, it includes a block of pricing information that is unrelated to tool selection and could be seen as clutter, slightly reducing efficiency.

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 that there is an output schema and the tool is a straightforward count query, the description adequately covers what the tool does, its exclusions, and typical usage patterns. It omits details like year range but these are not critical given the schema. The description is sufficiently complete for the tool's complexity.

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 already covers both parameters fully (park_name and year). The description reinforces the meaning of park_name by giving concrete examples and clarifies that year is optional. It adds value by providing example questions that illustrate how the parameters are used in practice, which is beyond the schema's dry descriptions.

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 that the tool queries the number of A-level taxpayer companies based on a specific park name. It distinguishes from sibling tools by explicitly noting that it does not include the list of companies (specifically mentioning '企业名单明细'), and the name pattern (num vs list) reinforces this.

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 question formats (e.g., 'How many A-level taxpayers are in Zhongguancun Software Park?') and clarifies what is not included (other company categories and details). However, it does not explicitly name alternative tools like the corresponding list tool or other count tools, leaving the agent to infer based on the naming convention.

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