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

The description adds a useful boundary: it does not include other enterprise category statistics and explicitly excludes the count-only return mode. However, given the minimal annotations (only openWorldHint), it does not clarify pagination, data freshness, or whether the list is complete for a park, though these are not necessarily required for a simple list query.

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 short and front-loaded with the core purpose, followed by exclusions and example queries. The '涉及指标/类型：高新技术企业列表' line is somewhat redundant with the opening sentence, but the overall structure is tight and scannable.

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 low-complexity tool with two parameters, one required, and an output schema, the description covers the essential purpose, scope, and exclusions. The typical questions add practical context, and because an output schema is present, detailed return-value documentation is not needed. Minor ambiguity remains around the exact interpretation of the '不包含' clause, but it does not undermine completeness.

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 already documents both parameters with 100% coverage, including examples for park_name and the optional year. The description's typical questions reuse the same park examples from the schema and add no new parameter-specific meaning, so it stays at the baseline of 3.

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 a high-tech enterprise list based on a specific park name ('基于具体园区名称高新技术企业列表查询'). It distinguishes itself by the '不包含' clause, which rules out other enterprise classification statistics and the count-only behavior, aligning it with list-style siblings like park_high_tech_company_num.

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 user questions ('典型问法：中关村软件园高新技术企业名单...') that imply when the tool should be used. However, it does not explicitly name or contrast alternatives such as park_high_tech_company_num or chain_high_tech_company_list, leaving the when-not-to-use guidance implicit rather than explicit.

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