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SupplyGraph.AI.Daasmart

Enterprise Change Employee Protection

enterprise_change_employee_protection

基于具体企业名称,按企业查询雇主品牌方面的周期变化,用于查询劳动合同签订、加班、职业健康与因公伤亡。不用于人均工资福利等待遇指标。 涉及指标/类型:劳动合同签订率;员工平均加班时间;员工职业健康状况;员工因公伤亡人数 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劳动合同签订率;美国Tesla, Inc.员工平均加班时间;日本丰田自动车株式会社员工职业健康状况

Pricing: {"unit": "credits", "billing_model": "per_run", "per_run": 40, "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.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior3/5

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

Annotations only include openWorldHint, which does not indicate side effects or read-only status. The description adds scope by listing included/excluded metrics but does not disclose behavioral traits like whether changes are reversible, rate limits, or output format. It also leaves 'periodic changes' ambiguous. Since annotations provide minimal coverage, the description partially compensates but lacks explicit behavioral clarity, hence a 3.

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 well-structured: first sentence states purpose, then lists included metrics, exclusions, and examples, followed by pricing. It is concise but repeats some information (metrics listed twice). Overall, it is efficient and front-loaded, earning a 4.

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 tool has 2 clearly described parameters, an output schema, and explicit scope, the description is adequate. It provides examples and exclusions, covering most usage scenarios. However, it does not clarify what 'periodic changes' means in terms of time range or frequency, leaving slight ambiguity. Still, it is complete enough for an agent to use correctly, warranting a 4.

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

Parameters3/5

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

Schema description coverage is 100% and both parameters are described with examples. The description adds typical query examples that illustrate parameter usage and mentions country can be in Chinese or English (implicitly). This adds marginal value beyond the schema, qualifying for the baseline 3 without needing to compensate for coverage gaps.

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 it queries employer brand periodic changes related to labor contracts, overtime, occupational health, and work-related deaths, listing specific metrics. It explicitly distinguishes from salary/welfare indicators and batch screening, and provides example queries. This gives a specific verb+resource+scope, clearly separating it from sibling tools like enterprise_change_employee_benefits.

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 explicitly states when not to use the tool (not for per-capita salary/welfare, not for batch screening by park/industry chain) and provides typical question phrasings. This gives clear guidance on appropriate usage and implies alternatives for other metrics, even if not naming specific sibling 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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