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SupplyGraph.AI.Daasmart

Enterprise Change Human Resources

enterprise_change_human_resources

基于具体企业名称,按企业查询经营活动方面的周期变化,用于查询新员工与异地招聘,以及研发销售管理层岗位招聘。不用于薪酬福利、离职晋升等雇主品牌类指标。 涉及指标/类型:是否进行了新员工的招聘;是否在其他地区进行过员工招聘;是否招聘了研发或技术类的职位;是否招聘了销售或市场类的职位;是否进行了管理层级别的职位招聘 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进行了新员工的招聘;美国Tesla, Inc.是否在其他地区进行过员工招聘;日本丰田自动车株式会社是否招聘了研发或技术类的职位

Pricing: {"unit": "credits", "billing_model": "per_run", "per_run": 50, "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

A4.4/5.0
Behavior4/5

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

The description uses '查询' (query), indicating a read-only operation with no side effects. However, annotations only include openWorldHint and lack readOnly/destructive hints, so the description partially compensates by implying non-destructive behavior. It does not mention additional behaviors like rate limits or data freshness.

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

Conciseness3/5

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

The description is somewhat repetitive, listing the same HR indicators twice (once in the main sentence and once in the '涉及指标/类型' section). This redundancy adds length without new information, making it less concise than ideal.

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 the large family of enterprise_change_* tools, the description effectively scopes its use case by enumerating covered topics and exclusions. It lacks output schema details, but since no output schema is provided, that is not required. Overall, it provides sufficient context for selection.

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?

The schema already provides descriptions for both parameters, so baseline is 3. The description adds the detail '具体企业名称' (specific enterprise name), clarifying the expected input granularity, which enhances parameter understanding beyond the schema.

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 the tool queries enterprise changes related to human resources, listing specific topics (new hires, remote recruitment, R&D/tech positions, sales/marketing, management). It explicitly excludes unrelated employer brand indicators, providing clear differentiation from sibling tools.

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?

The description provides both positive usage (when to use: for specific HR activities) and negative usage (not for compensation, benefits, etc.). This explicitly guides the agent on when to select this tool over alternatives.

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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