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SupplyGraph.AI.Daasmart

query_company_randomin_spection

company_randomin_spection

基于明确指定的企业名称,查询该企业涉及的抽查检查信息,包括检查机构、抽查类型、抽查日期、抽查结果等。

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)。用于查询该企业的抽查检查信息。示例:通威股份有限公司

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A3.6/5.0
Behavior3/5

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

Annotations include only openWorldHint, which provides minimal safety context. The description adds that the query requires an explicit company name and lists the fields returned, but it does not explicitly state whether the operation is read-only, nor does it mention pagination behavior beyond implicit schema fields. Overall, the description offers moderate added context beyond what annotations provide.

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 a single, focused sentence that efficiently conveys the tool's purpose. It includes an example and lists core return fields, with no unnecessary elaboration. Pricing information is appended but is not verbose. Structure is clear and front-loaded.

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 query tool with an output schema, the description covers the essential scope (company inspection records) and includes common pagination parameters. It lacks explicit mention of default sorting or filter behavior, but given the existence of an output schema, the description is sufficiently complete for basic invocation. It could benefit from a hint that it returns a list, but it's not critical.

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 covers all three parameters with clear descriptions (company_name, page, limit), achieving 100% coverage. The description reinforces that company_name is required and mentions 'specified company name', but adds no additional parameter semantics. At high coverage, a baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool queries inspection records (抽查检查信息) for a specific company, listing the types of fields returned (inspector, inspection type, date, result). This distinguishes it from other company_* tools such as company_punish or company_illegal, though it doesn't explicitly name alternatives.

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 usage for retrieving inspection data but does not provide explicit guidance on when to use this tool versus other company-related tools or any exclusionary criteria. There is no mention of alternatives, and the context of sibling tools is not leveraged.

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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