Skip to main content
Glama

SupplyGraph.AI.Daasmart

query_company_financing

company_financing

基于明确指定的企业名称,查询该企业的融资信息,包括发布日期、融资轮次、融资金额、投资方等。

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)。用于查询该企业的融资信息。示例:通威股份有限公司

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4/5.0
Behavior3/5

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

The description adds useful context beyond the openWorldHint annotation by disclosing the per-run cost (0.2 credits) and listing the returned data fields. However, it does not explicitly state whether the operation is read-only, whether authentication is required, or how errors are handled, which leaves some behavioral ambiguity.

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, concise sentence that directly conveys the tool's purpose, followed by a compact pricing line. There is no redundancy or unnecessary detail, making it highly scannable.

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?

The tool has moderate complexity with pagination parameters and an output schema. The description sufficiently communicates the data scope and required input, and the openWorldHint annotation adds context about data completeness. It is complete enough for an agent to invoke correctly, though a note on not-found behavior or exact-match expectations could improve it.

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?

All three parameters are fully described in the schema with types, defaults, max values, and an example for company_name. The description itself does not add parameter-specific guidance beyond confirming the company name requirement, so the baseline of 3 for high schema coverage applies.

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 uses the specific verb '查询' (query) with a clearly defined resource '融资信息' (financing information) and enumerates key returned fields (publish date, round, amount, investors). This makes it distinct from sibling tools that focus on other company aspects such as patents, tenders, or subsidies.

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?

The description clearly implies usage when a specific company name is known and financing details are needed. It does not explicitly exclude alternative tools or name siblings like enterprise_change_investment_financing or listed_company_financial_info, but the context is clear enough for an agent to choose this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

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。

Resources