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bhaktatejas922

unipile-linkedin-mcp

get_company_profile

Retrieve a LinkedIn company's profile details including description, industry, size, and specialties by providing its company ID or vanity URL name.

Instructions

Get a company's LinkedIn profile/page details.

Args: company_id: The LinkedIn company ID or vanity URL name

Returns: Company profile data including description, industry, size, specialties, etc.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
company_idYes
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It only states the return data composition (description, industry, etc.) but does not mention that it is a read-only operation, any authentication prerequisites, rate limits, or error behaviors. The description does not add value beyond the obvious 'get' semantics.

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 extremely concise: a single line for purpose, then a clear Args block and Returns block. It is front-loaded with the main action and has no redundant information. Every sentence serves a purpose.

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?

For a simple tool with one parameter and no output schema, the description is mostly complete. It explains the input and gives examples of output fields. However, it could be improved by noting that the output is a JSON object with a defined structure (though no schema exists). Overall, it adequately covers the essential information for an agent to use the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description explicitly explains the only parameter: 'company_id: The LinkedIn company ID or vanity URL name.' This adds critical context about acceptable input types, which is not present in the schema (which only states type: string).

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 clearly states the tool's function: 'Get a company's LinkedIn profile/page details.' This specifies a verb ('Get') and a resource ('company profile'), distinguishing it from sibling tools like 'get_my_profile' (personal profile) and 'search_companies' (search functionality).

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?

Usage is implied (use when you need a company's profile by ID), but no explicit guidance on when to use this tool over siblings, such as 'search_companies' for finding companies by name, or 'get_profile' for people. No when-not-to-use information.

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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