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bartest5

MCP Server for LinkedIn

by bartest5

Search Companies

search_companies
Read-only

Search LinkedIn companies by keyword to retrieve matching organization profiles for research, hiring leads, or outreach.

Instructions

Search for companies on LinkedIn.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordsYesSearch keywords (e.g., "fintech", "anthropic", "electric vehicles")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

The annotations already declare readOnlyHint=true, so the agent knows this is a safe read operation. The description adds no behavioral context beyond the basic action—it does not mention result limits, pagination, search scope, or any side effects. With no additional disclosure, it contributes minimal value beyond the annotations.

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 a single, clear sentence that states the tool's purpose with zero unnecessary words. It is front-loaded and appropriately sized for a simple search tool, ensuring every word earns its place.

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?

For a simple one-parameter tool with a fully documented schema, an output schema, and read-only annotations, the description is minimally sufficient. However, it lacks contextual guidance on how search results are scoped or when to prefer this tool over siblings like get_company_profile, leaving some ambiguity about its exact role.

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?

The input schema fully documents the sole parameter 'keywords' with a clear description and examples, achieving 100% schema coverage. The tool description adds no extra parameter meaning, but since the schema covers everything, a baseline score of 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 tool searches for companies on LinkedIn, using a specific verb (search) and resource (companies). It distinguishes from sibling search tools like search_people and search_jobs by explicitly naming the target entity, making the purpose unambiguous.

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

Usage Guidelines1/5

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

The description provides no guidance on when to use this tool versus alternatives. There is no mention of appropriate scenarios, exclusions, or comparisons with sibling tools such as get_company_profile or search_people, leaving the agent to infer usage context.

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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