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LinkedIn Company Search

linkedin_company_search

Search LinkedIn companies. Filter by keywords, industryId, or location. Costs 5 credits per call. Returns a single page of matching companies.

Input Schema

NameRequiredDescriptionDefault
refreshNoBypass the cache and re-run the search live (costs 5 credits). Default false: a previously-fetched result is returned free, with how long ago it was retrieved.
keywordsNoFree-text search (e.g. 'b2b saas analytics')
locationNoLocation filter (e.g. 'San Francisco Bay Area')
industryIdNoLinkedIn industry ID (numeric, comma-separated for several). Not an industry name — IDs are LinkedIn's industry codes (V2), listed at https://learn.microsoft.com/en-us/linkedin/shared/references/reference-tables/industry-codes-v2

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations present, the description must carry the full behavioral burden. It does disclose cost ("5 credits per call") and return shape ("a single page"), which are valuable, but it omits permission requirements, rate limits, page size, and how to retrieve subsequent pages; the cost detail also partially overlaps with the refresh parameter's schema description.

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 three short sentences, front-loaded with the action and resource, followed by filters, cost, and return shape. Every sentence earns its place with no repetition or fluff.

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?

For a simple search tool with fully documented parameters, the description covers purpose, filter dimensions, cost, and return shape. The main remaining gap is pagination behavior beyond "a single page," but the definition is otherwise complete enough to select and call the tool correctly.

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 all four parameters, including the refresh/cache behavior and industryId ID format. The description adds no syntax, format, or default-value guidance beyond what the schema provides, making baseline 3 appropriate.

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 states a specific verb and resource ("Search LinkedIn companies") and names the filter dimensions, so an agent knows exactly what the tool does. It is distinguishable from resource-specific siblings like linkedin_people_search and linkedin_job_search, but it does not explicitly name or contrast any sibling.

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?

There is no guidance on when to use this tool versus alternatives such as linkedin_people_search or linkedin_ad_search, and no exclusions or prerequisites are stated. The filter list implies usage but does not tell the agent when this is the right choice.

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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