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Get Company Employees

get_company_employees
Read-only

Retrieve the list of employees at a LinkedIn company using its exact URL slug, with optional keyword filtering by name, title, or skill.

Instructions

List employees at a company from the LinkedIn /people/ page.

Useful for finding who works at a company and discovering mutual connections. The optional keywords filter narrows results by name, title, or skill.

company_name must be the exact LinkedIn URL slug (the path segment after /company/), not the display name. LinkedIn assigns unique slugs and the display name often does not match — for example, the AI lab Anthropic lives at /company/anthropicresearch/, not /company/anthropic/. If you are unsure of the slug, call search_companies first and pick the slug from the returned references.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
company_nameYesLinkedIn company URL slug (e.g., "docker", "anthropicresearch", "microsoft")
keywordsNoOptional filter by name, job title, or skill (e.g., "engineer", "sales")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Discloses it lists employees from /people/ page and mentions keyword filtering. Annotations already indicate read-only and open-world; description adds source and filter behavior, but doesn't detail pagination or mutual connection mechanics.

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?

Six sentences, each necessary. First sentence states purpose. No redundancy. Short and clear.

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

Completeness5/5

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

Provides all needed context for a simple list tool: slug requirement, keyword filter, and sibling search_companies for slug lookup. Output schema exists, so return values not needed.

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

Parameters4/5

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

Schema coverage is 100%, baseline 3. Description adds crucial context: company_name must be exact slug, with example (Anthropic vs. anthropicresearch). Keywords described as optional filter by name/title/skill.

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?

Clearly states the tool lists employees from a LinkedIn company page. Distinguishes from siblings like get_company_profile (company info) and get_person_profile (individual).

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

Usage Guidelines5/5

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

Explicitly explains when to use (finding employees/mutual connections) and provides key prerequisite: company_name must be exact slug, with fallback to search_companies if unsure.

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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