company_copyright基于明确指定的企业名称，查询该企业拥有的软件著作权信息，包括登记号、软件名称、软件简介、版本号、软件著作分类、行业分类、登记日期、软件著作人、国籍等。
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）。用于查询该企业的软件著作权。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?
Annotations only include openWorldHint=true, and the description does not elaborate on what that implies (e.g., incomplete coverage or no-match behavior). It implies a read-only query by its wording and lists returned fields, but it does not disclose potential edge cases, pagination behavior, or data completeness caveats beyond what the schema already provides. 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 purpose is front-loaded in a single, information-dense sentence followed by a compact pricing block. The pricing JSON is slightly extraneous to tool invocation but does not create significant noise. Overall, it is efficient and avoids redundancy with the schema.
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?
This is a low-complexity query tool with a fully documented input schema and an output schema present. The description names the key output fields and required input, making it sufficient for basic invocation. It lacks explicit usage exclusions and behavioral caveats, but these are not critical given the simple read-only purpose and available structured metadata.
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%, with company_name, page, and limit already fully documented including defaults, maximum value, and an example. The description adds no additional parameter semantics beyond restating that company_name is required, so the schema carries the load.
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 uses a specific verb ('查询' / query) and a clearly identified resource ('该企业拥有的软件著作权信息') with an enumerated list of returned fields (登记号, 软件名称, 软件简介, 版本号, etc.). This clearly distinguishes it from sibling tools like company_patent or company_trademark.
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 clearly establishes when to use the tool: to query software copyright records for a specified company name. It does not explicitly mention alternatives or exclusion cases, but the context is unambiguous enough for an agent to select it appropriately among the sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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。