company_works基于明确指定的企业名称，查询该企业拥有的作品著作权信息，包括登记号、作品类别、作品名称、创作完成日期、首次发表日期、登记日期等。
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）。用于查询该企业登记的作品著作权信息。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 annotations only contain openWorldHint:true and convey no read/write or destructiveness info, so the description carries the burden. The description usefully discloses the exact fields returned (登记号、作品类别、作品名称、创作完成日期、首次发表日期、登记日期等), which is genuinely helpful. However, it doesn't disclose pagination behavior beyond schema defaults or behavior for unknown companies, leaving it merely adequate.
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 a single front-loaded sentence that starts with the action (query copyright of the specified company) and then lists useful return fields, followed by cleanly structured pricing metadata. No wasted words, though the field list makes it slightly dense.
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 lives in a namespace of 200+ siblings with several near-duplicates (company_copyright, chain_have_copyright_company_list, company_patent, company_trademark). Given an output schema exists and parameters are fully documented, the main gap is disambiguation. The description provides no help distinguishing this from company_copyright, leaving an agent genuinely uncertain which to choose.
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%: all three params (page, limit, company_name) are already well-documented in the schema with types, defaults (page=1, limit=20/max 100), requiredness, and an example. The description adds nothing parameter-specific beyond what the schema provides, so the baseline of 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 uses a specific verb (查询/query) and clearly identifies the resource: copyright data belonging to a company, listing the returned fields (registration number, work category, dates, etc.). However, it does not distinguish itself from the nearly identical sibling tool 'company_copyright', and the close cousin 'chain_have_cpright_company_list' operates on similar data, so it fails to differentiate from very similar siblings.
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 phrase '基于明确指定的企业名称' implies the name must be explicit/exact, which is a weak usage hint, and pricing is provided separately. But there is no when-to-use guidance, no mention of alternatives, no note on what to do when no records exist, and no disambiguation among the many sibling copyright tools.
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。