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SupplyGraph.AI.Daasmart

query_company_illegal

company_illegal

基于明确指定的企业名称,查询该企业涉及的严重违法信息,包括列入日期、列入严重违法名录的原因、列入决定机关、移出日期、移出严重违法名录的原因、移出决定机关等。

Pricing: {"unit": "credits", "billing_model": "per_run", "per_run": 0.2}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo指定返回第几页结果,从 1 开始,默认 1;与 limit 配合使用。
limitNo指定单次请求最多返回的记录数,默认 20,最大 100。
company_nameYes企业名称(必填)。用于查询该企业的严重违法。示例:通威股份有限公司

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A3.8/5.0
Behavior3/5

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

The description states the query is based on an explicitly specified company name, implying exact-match behavior. It lists returned fields but does not disclose behaviors like empty-result handling, data freshness, or rate limits. Annotations only include openWorldHint, which is minimal; the description carries some burden but not thoroughly.

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?

The description is one sentence that front-loads the purpose and lists key return fields, followed by pricing in a compact structured format. No wasted words.

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?

For a simple query tool, the description covers the main purpose and field list. Pagination parameters are documented in the schema, and an output schema exists, so return structure is covered. However, it does not note the possibility of empty results or the need for exact name matching, which would make it fully complete.

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?

The input schema already has 100% coverage, with descriptions for company_name, page, and limit. The description reinforces that company_name is the primary key but does not add meaning beyond the schema. Baseline of 3 applies because schema coverage is high.

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 serious illegal information for a specified enterprise, listing specific return fields (inclusion date, reason, decision authority, removal date, etc.). This distinguishes it from sibling tools like company_tax_violation or company_punish by focusing on the serious violation list.

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

Usage Guidelines3/5

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

The description implies the use case: when you need serious illegal records for an exact company name. It states the requirement for an explicitly specified company name but does not mention alternatives or exclusions. This is adequate but lacks explicit when-to-use vs. when-not-to-use guidance.

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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