company_equity_freeze基于明确指定的企业名称，查询该企业涉及的股权冻结信息，包括被执行人、股权数额、执行通知文书号、类型、状态等。
Pricing: {"unit": "credits", "billing_model": "per_run", "per_run": 0.2}
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | 指定返回第几页结果，从 1 开始，默认 1；与 limit 配合使用。 | |
| limit | No | 指定单次请求最多返回的记录数，默认 20，最大 100。 | |
| company_name | Yes | 企业名称（必填）。用于查询该企业的股权冻结信息。示例：通威股份有限公司 |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description only states what the tool queries and provides no additional behavioral context beyond the 'openWorldHint' annotation. It does not disclose potential side effects, rate limits, or that it is a read-only operation (though 'query' implies read). With no contradiction to annotations, but with minimal added value, the transparency score remains low.
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, consisting of a single clear sentence about the tool's purpose, followed by pricing information. While the pricing info is not directly related to the tool's function, it is structured as a separate note and does not detract from the core description. The text is front-loaded with the key action and resource.
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?
The tool is simple, and the description covers the primary action, parameters, and expected output fields. The output schema exists, so detailed return values are handled there. However, given the large number of sibling tools, a note on when to use this versus similar tools would improve completeness. Overall, it is adequate for its simplicity.
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%, so all parameters have descriptions in the schema. The description does not add meaningful semantics beyond what the schema already provides; it merely reiterates the required company_name and provides an example already present in the schema. Therefore, the baseline of 3 is appropriate, as the schema carries the heavy lifting.
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's function: 'query the equity freeze information' based on an explicitly specified enterprise name, and lists the specific fields returned (executed person, equity amount, document number, type, status). This is a specific verb+resource combination that distinguishes it from other company-related tools, especially the sibling company_equity_pledge which deals with pledges rather than freezes.
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 implies usage for querying equity freeze data for a given company, but does not provide explicit when-to-use guidance or alternatives. It does not differentiate from similar tools like company_equity_pledge, nor does it state situations where this tool should not be used. The context is clear but lacks explicit exclusions or comparisons.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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大量工具功能高度重叠，例如chain_*和park_*系列均为按不同筛选条件查询企业列表或数量，只是参数不同却拆分为独立工具；enterprise_change_*系列同样针对不同指标逐一拆分。虽然描述清楚各自区别，但代理面对198个工具时极易选错，且许多工具本质应合并为带参数的单一接口。
多数工具采用snake_case加领域前缀（如chain_、park_、company_、gov_data_、poi_data_），但存在明显变体如company_certlist、company_randomin_spection（拼写异常）、corporate_exception_report、due_diligence_report、sg_chokepoint等，混用英文抽象名词与动词短语，整体模式可辨认但不统一。
工具总数高达198个，远超合理范围（即使复杂领域也应控制在25个以内）。大量工具是同一逻辑的不同参数变体（如list/num、不同资质条件），完全可以通过参数化减少数量，严重冗余，代理难以有效浏览和选择。
工具覆盖领域广泛，包括企业信息、产业链分析、园区统计、地区宏观、POI明细、供应链风险、关税计算等，基本覆盖了商业数据查询的主要需求。虽缺少更新/删除等操作（但作为查询服务器可接受），且部分细分领域可能有遗漏，但整体功能较为完整。