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linkedin_company_information

Destructive

当用户需要 LinkedIn 公司信息、领英公司信息、LinkedIn company information、LinkedIn 公司 URL,与采集、抓取、爬取、获取、提取等动词组合时触发。提交 LinkedIn 公司信息采集 Builder 任务,采集器标识固定为 linkedin_company_information_by-url。

Input Schema

NameRequiredDescriptionDefault
urlYes公司URL,该参数用于指定要采集的公司URL。用于 linkedin_company_information_by-url。调用方必须提供非空值,不使用默认值。
file_nameNoBuilder file_name 字段。不传默认为 {{TasksID}}。{{TasksID}}

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare destructiveHint=true, openWorldHint=true and non-idempotent, and the description is consistent with that by disclosing it submits a Builder task (an action, not a read). It does not, however, explain that results are asynchronous and must be retrieved via the scraper_task_* siblings, which is the key behavioral fact for a task-submission tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The trigger sentence is repetitive keyword stuffing in four near-identical phrasings, which crowds out the actual function. The purpose sentence is clean, but roughly half the text is low-value matching boilerplate.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description should close the loop on the async workflow (task submitted here, fetched elsewhere), and it does not. For a 2-param task-submission tool with rich annotations the gaps are moderate rather than severe.

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%, so both parameters (url, file_name) and their defaults are fully documented in the schema. The description adds only the fixed collector identifier and no further parameter meaning or format guidance, so the baseline 3 applies.

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 second sentence states a specific verb+resource: submits a LinkedIn company information collection Builder task, with a fixed collector id. An agent can tell it fetches LinkedIn company data, though it never contrasts itself with neighboring company tools like crunchbase_company or indeed_companies_info.

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 first sentence lists trigger keyword combinations (LinkedIn company info + collect/scrape/get verbs) which implies usage context, but there is no explicit when-not-to-use and no routing to alternatives such as linkedin_job_listings_information or other company-scraping siblings.

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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