company_app基于明确指定的企业名称，查询该企业开发的APP信息，包括app名字、APP分类、简介等。
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）。用于查询该企业拥有的APP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 clearly indicates a read-style query ('查询') and adds operational context via per-run pricing. However, with only openWorldHint as an annotation, it does not disclose behavior such as empty-result handling, pagination beyond what schema provides, or any limitations.
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 and front-loaded, stating the tool's purpose in one clear sentence and then including the necessary pricing detail. There is no redundant or filler content; every sentence earns its place.
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, has full schema coverage, includes an output schema, and the description covers the core return fields. It could be slightly stronger with explicit guidance on when to choose this tool over siblings, but overall it is sufficiently complete for the agent to use it correctly.
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 coverage is 100% and the schema already documents company_name, page, and limit with defaults and an example. The description adds little beyond restating that the company name must be explicitly specified, so it meets the baseline but does not meaningfully enhance param understanding.
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) with a clear resource: APP information developed by a specified company. It enumerates the returned content (app name, category, introduction), and this focus on company-developed apps distinguishes it from the many sibling company_* tools.
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 when to use it: when you have an explicitly specified company name and want the apps developed by that company. However, it does not explicitly state when not to use it or name any alternative tools, so usage guidance remains implied rather than explicit.
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。