company_credit_rating基于明确指定的企业名称，查询该企业的信用评级信息，包括主体评级、评级展望、评级机构、评级时间等。
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）。用于查询该企业的信用评级。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 include openWorldHint=true but no readOnlyHint or destructiveHint. The description does not specify whether the tool is read-only (likely) or if there are any side effects. It also does not disclose potential limitations such as missing data, pagination behavior, or performance. With limited annotations, the description should carry more burden but does not.
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, one focused sentence, and includes a pricing note which might be useful for cost-aware agents. It is front-loaded with the key action and resource. No unnecessary words, though the pricing note could be considered extra but is brief.
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?
Given the tool has an output schema and well-documented parameters, the description covers the basic purpose. However, for a tool querying credit ratings, it could benefit from noting that data may be incomplete or subject to third-party sources, and that the company name must exactly match. The openWorldHint suggests the world may have more data than known, but description doesn't clarify.
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 the description adds no additional parameter semantics beyond the schema. The description does mention the output includes rating agency and time, which aligns with the purpose but does not detail parameter syntax or behavior. Baseline of 3 is appropriate since the schema fully documents parameters.
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 credit rating information for a specified company, including entity rating, outlook, agency, and time. It distinguishes from siblings by focusing on credit rating specifically, though siblings like 'company_data_search' might also return similar data. The verb 'query' is clear and the resource (credit rating) is specific.
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 credit ratings by company name, but provides no explicit guidance on when to use this tool versus alternatives like 'company_data_search' or 'due_diligence_report'. It does not state exclusions or prerequisites (e.g., need for exact company name). Usage context is clear but alternatives are not mentioned.
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。