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

The description indicates a read-only query and mentions the time frame (近两年), but does not explain how the optional 'year' parameter interacts with the two-year window or any limitations (e.g., data coverage). Annotations only include openWorldHint, so the description carries moderate burden but leaves some behavioral ambiguity.

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 front-loaded with the purpose, followed by exclusions and examples. The pricing block is extra but not verbose. Overall, each sentence contributes value without fluff.

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 tool with an output schema and clear input schema, the description covers purpose, exclusions, and examples adequately. The only gap is the unclear interaction between 'year' and the '近两年' window, but it is not critical for basic usage.

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 both parameters clearly described (park_name with examples, year with format and optionality). The description adds minimal parameter-specific semantics beyond the schema, so the baseline 3 is appropriate.

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 returns the count of enterprises that participated in bidding in the last 2 years for a specific park. It distinguishes from siblings by explicitly listing exclusions (other enterprise categories, company list details) and providing typical query examples that match the tool's functionality.

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 gives clear context: it is for counting, not listing, and excludes other categories. However, it does not explicitly name alternative tools like park_participated_tender_company_list or chain_* variants, so the guidance is implicit rather than explicit. Typical questions help identify use cases.

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