SupplyGraph.AI Data

Enterprise Change Public Responsibility

enterprise_change_public_responsibility

基于具体企业名称，按企业查询责任品牌方面的周期变化，用于查询纳税缴费与创造就业岗位。不用于欠税、非正常纳税户等违规违法排查。涉及指标/类型：缴纳税额；缴费数额；创造就业岗位不包含：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缴纳税额；美国Tesla, Inc.缴费数额；日本丰田自动车株式会社创造就业岗位

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

Input Schema

TableJSON Schema

Name	Required	Description	Default
`company_name`	Yes	企业名称，如「比亚迪股份有限公司」「Tesla, Inc.」。
`country_name`	Yes	国家名称，如「中国」「美国」「Japan」「China」。

Output Schema

TableJSON Schema

Name	Required	Description	Default
`text`	Yes	Text 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. Dates show when Glama detected each change.

First observedAug 19, 2026

TDQS

A4/5.0

Behavior3/5

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

描述带有openWorldHint，提示结果可能不完整，但工具说明未对open world的含义进行扩展，也未说明返回周期粒度或精确企业名称匹配等具体行为。不过描述补充了指标范围和典型问法，提供了一些附加值，且与openWorldHint不矛盾。

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

Conciseness5/5

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

描述采用简短的开头+包含列表+不包含列表+典型问法的结构，信息密度高且没有任何冗余。每一句都为工具选择或调用提供实际价值，非常适合代理快速理解。

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?

对于2个参数、有输出schema的工具，描述已覆盖目的、指标范围、排除项、典型问法，并声明定价。虽然未详细描述时间周期或返回形态，但这些可由输出schema承接，整体上下文已足够完整。

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?

输入schema已100%覆盖两个参数的说明，并且给出国家名和公司名示例。描述中的典型问法虽然补充了组合示例，但没有增加schema之外的新语义、格式约定或边界条件，按高覆盖度基线评为3分。

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?

描述明确说明该工具按具体企业名称查询责任品牌相关周期变化，并具体列出缴纳税额、缴费数额、创造就业岗位三类指标。同时通过“不包含”和“不用于”排除违规违法排查、批量筛选等，和同类enterprise_change_*兄弟工具形成清晰区分。

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

Usage Guidelines4/5

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

描述给出了明确的使用场景（纳税缴费、就业岗位）和不使用场景（欠税、非正常纳税户、按园区/产业链批量筛企业名单），让代理能判断何时不调用该工具。但没有明确点出应该改用哪个替代工具名称，因此略低于满分。

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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Most tools have clearly distinct purposes, with consistent scopes (e.g., chain_* vs park_* vs company_* vs gov_data_*). The list/num pairs are clearly differentiated. A few overlapping concepts exist (e.g., company_patent vs enterprise_change_innovation) but descriptions clarify the angle. Some typos (company_randomin_spection) don't cause ambiguity.

Naming Consistency4/5

Naming follows a mostly predictable snake_case pattern with prefixes indicating domain (chain_, park_, company_, enterprise_change_, gov_data_, poi_data_, business_surrounding_, cbd_surrounding_). Most tools use <prefix>_<entity>_<action> or <prefix>_<subject>. A few outliers (sg_chokepoint, tariff_calc, corporate_exception_report) deviate but are few and recognizable.

Tool Count1/5

With 198 tools, this is far beyond any reasonable scope for a single server. It exceeds even the 'extreme mismatch' threshold of 50+ tools. The large number makes selection and discoverability challenging, despite good internal organization.

Completeness4/5

The tool surface covers a vast range of enterprise data, regional macro stats, POI details, supply chain analysis, and tariffs. It appears to cover the primary domain comprehensively, with only minor potential gaps (e.g., no direct tool for company debt ratings or specific product catalogs, but these are addressed via enterprise_change_* and company_* tools).

Resources

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