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BACH-AI-Tools

LinkedIn Data API MCP Server

get_company_by_domain

Retrieve detailed company information by providing a domain name. Enrich your data with LinkedIn company profiles, including industry, size, and description. One credit per successful request.

Instructions

Enrich the company data by domain. 1 credit per successful request.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesExample value: apple.com
Behavior2/5

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

With no annotations, the description only adds a credit cost disclosure. It does not confirm whether the operation is read-only, destructive, or requires authentication, leaving behavioral traits unclear beyond the tool name.

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 extremely concise—one sentence plus a credit note. There is no waste, though it could benefit from slight restructuring to front-load the action more explicitly.

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

Completeness2/5

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

No output schema exists, and the description does not explain what company data is returned (e.g., fields, enrichment details). For a tool with one parameter, this is a notable gap in completeness.

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%, so the schema already documents the domain parameter. The description adds no additional meaning or format details beyond what the schema provides (example value). Baseline 3 is appropriate.

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 action ('Enrich the company data') and the method ('by domain'), distinguishing it from sibling tools like get_company_details or get_company_jobs that have different parameters or specific focuses.

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 on when to use this tool versus alternatives (e.g., get_company_details vs. by domain). The description lacks any context for selection criteria.

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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