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Get Company Profile

get_company_profile
Read-only

Retrieve a company's LinkedIn profile by name or URL, returning about-page details plus optional posts and jobs sections.

Instructions

Get a specific company's LinkedIn profile.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sectionsNoComma-separated list of extra sections to scrape. The about page is always included. Available sections: posts, jobs Examples: "posts", "posts,jobs" Default (None) scrapes only the about page.
company_nameYesLinkedIn company name (e.g., "docker", "anthropic", "microsoft"). A full company URL is accepted too and is reduced to the slug.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

The annotations already declare readOnlyHint=true and openWorldHint=true, covering the safety and live-data aspects. The description itself adds little behavioral context beyond the schema's mention of 'scrape', and it does not disclose potential scraping limitations, authentication needs, or rate-limit behavior. No contradiction with annotations exists.

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?

The description is a single, direct sentence with no filler or redundancy. It is concise, though it mostly restates the tool name and relies on the schema for substantive detail.

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 read-only tool with two well-documented parameters and an output schema, the definition is mostly complete. The main missing piece is usage guidance around sibling tools, but that gap is already captured in the usage_guidelines dimension.

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 description coverage is 100%, and both parameters are already well documented: company_name accepts a slug or full URL, and sections specifies comma-separated extras with defaults and examples. The description adds no additional parameter meaning beyond what the schema provides.

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 states a specific verb ('Get') and resource ('a specific company's LinkedIn profile'), which clearly distinguishes it from sibling tools like get_person_profile or search_companies. The word 'specific' also signals that this tool targets one known company rather than returning a list.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no explicit guidance on when to use this tool versus alternatives such as search_companies, get_company_posts, or get_company_employees. It does not mention that search_companies should be used when the exact company slug is unknown, nor does it note that get_company_posts is the tool for post-specific data.

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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