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Look up a LinkedIn company

get_company
Read-onlyIdempotent

LinkedIn accounts only. A company page by its id or public name (linkedin.com/company/): description, industry, website, followers and size. Counts as browsing.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "account_id": "<account_id>",
      "company_id": "<company_id>"
    },
    "name": "get_company"
  }
}

Input Schema

NameRequiredDescriptionDefault
account_idYes
company_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description's only added behavioral fact is 'Counts as browsing', which signals quota/usage accounting not present in the annotations. It says nothing about what happens when the company is not found or whether the lookup reaches outside the connected account.

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?

Three short fragments, scope stated first, returned fields listed compactly; nothing is padded. The telegraphic style costs a little readability but no sentence is wasted.

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?

For a two-parameter read with no output schema, listing the returned fields is a reasonable substitute. The gaps are the undocumented required account_id and the absence of any failure behavior, which leave an agent guessing on a required input.

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 0%, so the description must carry parameter meaning, and it partly does by explaining that the company identifier accepts either an internal id or a public name in the linkedin.com/company/<name> form. It never explains account_id, which is required but has no documented meaning in either the schema or the prose.

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?

Names a specific resource (a LinkedIn company page) and enumerates exactly what comes back — description, industry, website, followers, size — which lets an agent match it against a data need. The opening 'LinkedIn accounts only' scopes it away from other networks, though it never distinguishes it from the sibling list_company_pages.

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?

'LinkedIn accounts only' is a real precondition and 'Counts as browsing' hints at how the call is metered, implying it should not be spammed. There is no explicit when-to-use vs when-not framing and no pointer to list_company_pages for enumeration instead of single lookups.

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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