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Enterprise Change Result Evaluation

enterprise_change_result_evaluation

基于具体企业名称,按企业查询合作品牌方面的周期变化,用于查询应付款项、付款周期、合同违约率与合作年限。不用于履约及时性、供货合格率等合作过程指标。 涉及指标/类型:应付款项;付款周期;合同违约率;合作伙伴年限 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应付款项;美国Tesla, Inc.付款周期;日本丰田自动车株式会社合同违约率

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. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

注解仅提供openWorldHint=true,示意结果为开放世界可能不完全列举。描述在一定程度上补充了行为特征:目的是查询周期变化,但未明确说明是否会返回历史变化序列、数据频率、数据来源或是否需要特定权限。不过对于查询类工具而言,与注解不冲突,且没有提供额外破坏性风险。描述未提及返回格式或当前快照与周期变化的区别,但整体影响不大。

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?

描述有三个段落,第一段说明用途和排除项,第二段列出指标类型和不包含项,第三段给典型问法。信息密度高,没有废话。但整体长度稍长,可适当精简重复部分(如“不用于”与“不包含”有部分重叠)。但结构清晰,先总述后明细再示例,易读性好。

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?

该工具涉及4类指标,且有输出 schema,但描述未说明输出结构的具体细节(schema 部分未被提供,无法评估完整性)。考虑到参数简单、注解仅有比较开放世界的说明,描述已覆盖使用边界和示例,但对于返回的二值可能性(如数据缺失时返回什么)未作说明。整体完整度较高。

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?

schema 覆盖度为100%,两个参数都有中文描述和示例。但 description 中的典型问法进一步补充了参数的实际用法(如“中国比亚迪股份有限公司应付款项”、“美国Tesla, Inc.付款周期”),指出了 country_name 和 company_name 结合使用的示例,也暗示了企业名称可以带或不带国家前缀,因此有额外语义。

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?

描述明确说明工具用途:按企业名称查询合作品牌相关的周期变化指标(应付款项、付款周期、合同违约率、合作年限)。动词“查询”+资源“合作品牌方面的周期变化”具体清晰。与众多企业变更类工具(enterprise_change_*)和其他指标工具区分度高。

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?

描述明确给出使用场景:查询应付款项、付款周期、合同违约率与合作年限。明确指出不用于履约及时性、供货合格率等合作过程指标,也说明不包含非本分类指标和按园区/产业链批量筛企业名单。提供了典型问法示例,包括中文和英文案例,引导清晰。

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

B3.2/5.0
Disambiguation4/5

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