LinkedIn MCP Server

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds context about access limitations and potential future requirements, which is useful beyond the basic 'get' operation. However, it lacks details on rate limits, error handling, response format, or what 'basic information' entails, leaving significant gaps for a tool with no annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose. The access note adds necessary context without verbosity. However, the phrase 'in future' could be tightened to 'future' for slightly better conciseness, but overall it earns its place without waste.

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

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

Given no annotations and no output schema, the description is incomplete for a tool that likely returns structured data. It mentions access constraints but omits details on response format, error cases, or what constitutes 'basic information'. For a 'get' tool with one parameter, it's minimally adequate but leaves the agent guessing about the return value and operational limits.

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

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

Schema description coverage is 100%, with the single parameter 'companyId' well-documented in the schema as 'LinkedIn company ID'. The description adds no additional parameter semantics beyond what the schema provides, such as format examples or sourcing tips. Baseline 3 is appropriate since the schema handles the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Get') and resource ('basic company information'), distinguishing it from siblings like 'get_company_profile' by implying a simpler scope. However, it doesn't explicitly differentiate the level of detail or data fields from 'get_company_profile', leaving some ambiguity.

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

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

The description implies usage context with 'limited access' and future partnership requirements, suggesting when this tool might be appropriate versus alternatives. However, it doesn't explicitly state when to use this over 'get_company_profile' or other sibling tools, nor does it provide clear exclusions or prerequisites beyond the vague access note.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.