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SupplyGraph.AI.Daasmart

Chain Tech Oriented Company Count

chain_tech_oriented_company_num

基于具体地区(国家,省份,城市,区县)以及具体产业链名称科技型中小型企业数量查询(合并返回总量/生产型/销售型/依赖型文本)。 涉及指标/类型:科技型中小型企业数量;生产型科技型中小型企业数量;销售型科技型中小型企业数量;依赖型科技型中小型企业数量 不包含:其他企业分类的统计;企业名单明细 典型问法:2024年全国集成电路科技型中小型企业有多少;成都市新能源产业链科技型中小型企业数量;海淀区人工智能科技型中小型企业有多少家

Pricing: {"unit": "credits", "billing_model": "per_run", "per_run": 100, "unit_description": "optional"}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNo统计年份,如 2024;可选。
regionYes地区名称,如「全国」「成都」「北京市海淀区」。
chain_nameYes产业链或节点名称,如「集成电路」「新能源」「人工智能」。

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesText or Markdown response. Includes merged results for total / product / sales / dependency company counts. Also used for in-progress, failed, cancelled, or waiting-user messages.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

描述明确说明合并返回总量/生产型/销售型/依赖型文本,披露了返回内容的结构;也说明不包含其他分类统计和企业名单明细。虽然annotations只有openWorldHint=true,未包含readOnlyHint/destructiveHint,但'查询'一词暗示非破坏性操作,且描述对返回内容的说明已超出基础schema,提供了有用的行为上下文。计费信息(Pricing)也提供了成本透明度。

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?

描述结构清晰:首句说明核心功能,然后列出涉及的指标/类型和不包含范围,最后给出典型问法示例,每部分都有实际信息量。虽稍长但无冗余填充,计费信息和描述在合理范围内。

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?

工具参数少(3个)、有输出schema(has output schema: true)、schema覆盖率100%,描述已经足够完整,包含了功能、指标明细、排除范围、典型问法,还补上了计费信息。代理可以正确调用该工具而无需额外猜测,上下文完整性良好。

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描述覆盖率100%(3个参数全部有描述),但描述额外提供了参数的典型示例(如地区'全国''成都''北京市海淀区',产业链'集成电路''新能源''人工智能'),并且解释了region和chain_name在逻辑上的关系(地区限定、产业链限定),这有助于代理构造正确的参数。因此虽未提供语法细节,但示例和场景补充提升了参数语义。

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?

描述明确说明基于地区和产业链名称查询科技型中小型企业数量,并列出合并返回的三种类型(生产型/销售型/依赖型)及典型问法,动词和资源明确,与sibling中的chain_tech_oriented_company_list(列表工具)形成明显区分,同时与chain_company_num等计数工具区分了统计口径(仅限科技型中小企业,不包含其他企业分类)。

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?

描述明确列出使用场景(具体地区+产业链名称查询数量),并通过'不包含'条目排除了统计企业名单明细和其他分类统计,让代理知道该工具不做什么。典型问法示例(2024年全国集成电路等)提供了清晰的调用场景,但未明确提及何时应使用sibling中的list工具而非本num工具,这算轻微不足。

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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