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

Annotations only provide openWorldHint, so the description carries most of the transparency burden. It adds useful context such as scope exclusions and per-run pricing (100 credits), but it does not describe pagination, list-size limits, or invalid-input behavior. The phrase '仅返回数量不返回名单' is also slightly ambiguous, though it is likely intended as an excluded scenario.

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 and example questions, and the '不包含' line packs useful scope information into one line. The embedded Pricing JSON is minor noise and the count-only sentence could be clearer, but overall length and structure are appropriate.

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 two-parameter read-oriented list tool with full schema descriptions and an output schema, the description covers purpose, scope, exclusions, and typical user phrasings. It lacks explicitly named sibling tools, but the exclusions plus the sibling naming convention (park_company_num vs park_company_list) provide enough context for correct selection.

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 has 100% coverage with descriptions and example values for both park_name and year, so the description adds little parameter-level meaning. The typical-question examples mainly restate park_name examples that are already present in the schema.

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 opens with a specific statement of what the tool does: query a company list for a named park ('基于具体园区名称企业列表查询'). It also differentiates from sibling count/category tools by saying it is not category-specific statistics and not count-only, and the typical question examples ('中关村软件园企业名单') confirm list-returning behavior.

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 concrete example phrasings and explicit when-not cases: it excludes other enterprise category statistics and count-only requests, implying the agent should use sibling tools for those. However, it stops short of naming alternatives like park_company_num, so it is not fully explicit.

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