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dzigi00

LinkedIn Automation MCP Server

by dzigi00

Get Company Profile

get_company_profile
Read-only

Fetch a company's LinkedIn profile by name. Add optional sections like posts and jobs for more details.

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")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

The description discloses no behavioral traits beyond what annotations already state (readOnlyHint). It does not mention that the tool scrapes data, that the about page is always included, or that sections are optional. The schema provides this information, but the description itself adds no transparency.

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, front-loaded sentence with no redundant words. It is concise and communicates the core purpose efficiently, though it omits useful context that could enhance selection.

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?

The schema is rich with full parameter descriptions and an output schema exists, so the description does not need to explain returns. However, the description lacks usage context, exclusions, or any mention of optional sections, making it minimally complete for an agent's decision-making.

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 the schema already documents both parameters thoroughly, including examples for company_name and detailed format/default for sections. The description adds no extra parameter meaning, but the baseline of 3 applies because the schema does the heavy lifting.

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 description clearly states the action ('Get') and resource ('specific company's LinkedIn profile'), distinguishing it from siblings like get_company_posts or get_company_employees. However, it does not explicitly contrast with those siblings, relying on the tool name for differentiation.

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?

No guidance is provided about when to use this tool versus alternatives. There is no mention of prerequisites, use cases, or exclusions, and sibling tools are not referenced. The agent receives no selection help beyond the tool name.

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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