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devag7

LinkedIn MCP

search_companies

Find LinkedIn companies by keywords, returning names and universal slugs to access full details.

Instructions

Search LinkedIn companies by keywords. Returns name + universalName slug (pass that to get_company for full details).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordsYesSearch keywords, e.g. "fintech bangalore"
countNoResults (default 10)
Behavior2/5

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It only states that the tool returns name and universalName, but does not mention side effects, rate limits, authentication, or pagination. For a search tool, more detail on potential limitations would be helpful.

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?

One concise sentence of 15 words, immediately clarifying purpose and providing a key usage hint. No wasted words.

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?

Given the simplicity of the tool (2 parameters, no output schema), the description is mostly complete. It explains what the tool does and what it returns, and how to proceed. It does not cover pagination or error handling, but for a search tool with a maximum count of 25, this may be acceptable.

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 coverage is 100% (both parameters have descriptions in the schema). The description adds minimal additional meaning, only hinting at the relationship between the search result and get_company. The schema already covers the parameters adequately, so the description does not need to add much.

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 uses a specific verb 'Search' and resource 'LinkedIn companies by keywords', clearly differentiating it from sibling tools like get_company (which gets details) and search_people. It also tells the agent to pass the slug to get_company for full details.

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

Usage Guidelines4/5

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

The description states the purpose and hints at the workflow (search then get_company). It does not explicitly state when not to use, but the context is clear given the simple search function.

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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