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SupplyGraph.AI.Daasmart

Enterprise Change International Coop

enterprise_change_international_coop

基于具体企业名称,按企业查询合作品牌方面的周期变化,用于查询国际合作研发、跨国团队分布及合作国家地区。不用于进出口贸易合规或外贸政策冲击排查。 涉及指标/类型:是否有国际合作研发项目受影响或终止;研发团队是否分布在多个地区或国家;技术合作主要涉及哪些国家/地区 不包含:非本分类指标;按园区/产业链批量筛企业名单 典型问法:中国比亚迪股份有限公司是否有国际合作研发项目受影响或终止;美国Tesla, Inc.研发团队是否分布在多个地区或国家;日本丰田自动车株式会社技术合作主要涉及哪些国家/地区

Pricing: {"unit": "credits", "billing_model": "per_run", "per_run": 30, "unit_description": "optional"}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
company_nameYes企业名称,如「比亚迪股份有限公司」「Tesla, Inc.」。
country_nameYes国家名称,如「中国」「美国」「Japan」「China」。

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesText or Markdown response generated by the agent. Returned for completed results as well as in-progress, failed, cancelled, or waiting-user messages.

TDQS

A4.3/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description does not mention any side effects, permissions, or read-only nature. While it is likely a safe query tool, the lack of explicit behavioral transparency means the description does not fully inform the agent about potential impacts. Annotations provide only openWorldHint, so the description carries the burden and does not fully address it.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficient, but it repeats the indicator list and typical queries, making it slightly redundant. Still, it is not overly verbose and covers essential information clearly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description sets expectations by listing the indicators covered (e.g., affected R&D projects, team distribution). It does not mention output format, but the listed indicators give sufficient context for an agent to infer the nature of results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Both parameters are described with examples in the schema, and the description reinforces their meaning by using them in typical queries. It adds context about the tool's scope but does not significantly go beyond the schema's own examples.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool queries periodic changes in international cooperation for a specific enterprise, covering R&D cooperation, multinational teams, and cooperation countries. It explicitly distinguishes itself from related tools by noting it is not for import/export compliance or foreign policy impact.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides explicit usage scenarios (when to use for international cooperation metrics) and clear exclusions (not for trade compliance or policy impact). Typical queries are given, making the intended use unambiguous.

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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TDQS

B3/5.0
Disambiguation2/5

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。

Naming Consistency3/5

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。

Tool Count1/5

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。

Completeness4/5

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。

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