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SupplyGraph.AI.Daasmart

Enterprise Change Credit Debt Risk

enterprise_change_credit_debt_risk

基于具体企业名称,按企业查询企业风险方面的周期变化,用于查询债务违约、负债概况、征信不良与账户冻结等。不用于替代完整征信报告,也不与欠税失信等违规违法记录混用。 涉及指标/类型:企业是否存在未按期偿还的重大债务违约;当前企业负债总额及违约情况如何;企业征信报告中是否有不良信用记录;是否存在被冻结的银行账户 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企业是否存在未按期偿还的重大债务违约;美国Tesla, Inc.当前企业负债总额及违约情况如何;日本丰田自动车株式会社企业征信报告中是否有不良信用记录

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

A4.2/5.0
Behavior3/5

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

The description explains the scope and indicators but does not disclose behavioral traits like read-only nature, response format, or potential side effects. With only openWorldHint annotation, the description carries the burden and could add more about what happens (e.g., that it reports periodic changes). It adds some context but lacks detailed behavioral disclosure.

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 with a clear main statement, bullet-point lists of included and excluded indicators, and example questions. It is slightly lengthy but each part adds value, and the most critical info (purpose) is front-loaded.

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

Completeness5/5

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

Given that an output schema exists, the description need not explain return values. It covers purpose, usage, exclusions, and examples thoroughly for a tool with only two required parameters. It is complete for its complexity.

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 coverage is 100% with both parameters described, but the description enriches semantics by providing typical usage examples (e.g., '中国比亚迪股份有限公司' with country name and company name) and emphasizing that it queries by company name. This goes beyond the basic schema descriptions.

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 enterprise risk periodic changes for specific companies, listing concrete indicators (debt default, liability overview, bad credit, account freeze). It explicitly distinguishes from related tools by stating it is not a substitute for a full credit report and not mixed with tax default or dishonest illegal records, differentiating it from siblings like company_credit_rating and company_tax_violation.

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?

It provides clear context on when to use (by company name for specific risk indicators) and explicit exclusions (not for batch filtering by park/industry chain, not a substitute for full credit report). It includes typical question formats but does not name specific alternative tools, so it is strong but not perfect.

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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