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SupplyGraph.AI.Daasmart

query_company_app

company_app

基于明确指定的企业名称,查询该企业开发的APP信息,包括app名字、APP分类、简介等。

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)。用于查询该企业拥有的APP信息。示例:通威股份有限公司

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

The description clearly indicates a read-style query ('查询') and adds operational context via per-run pricing. However, with only openWorldHint as an annotation, it does not disclose behavior such as empty-result handling, pagination beyond what schema provides, or any limitations.

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 concise and front-loaded, stating the tool's purpose in one clear sentence and then including the necessary pricing detail. There is no redundant or filler content; every sentence earns its place.

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 is simple, has full schema coverage, includes an output schema, and the description covers the core return fields. It could be slightly stronger with explicit guidance on when to choose this tool over siblings, but overall it is sufficiently complete for the agent to use it correctly.

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?

Schema coverage is 100% and the schema already documents company_name, page, and limit with defaults and an example. The description adds little beyond restating that the company name must be explicitly specified, so it meets the baseline but does not meaningfully enhance param understanding.

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 a specific verb ('查询' / query) with a clear resource: APP information developed by a specified company. It enumerates the returned content (app name, category, introduction), and this focus on company-developed apps distinguishes it from the many sibling company_* tools.

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 when to use it: when you have an explicitly specified company name and want the apps developed by that company. However, it does not explicitly state when not to use it or name any alternative tools, so usage guidance remains implied rather than explicit.

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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