LinkedIn Intelligence 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 effectively describes the tool's behavior by specifying it returns a list of pending invitations with sender info, mentions the default limit, and includes important warnings about API limitations (LinkedIn API restrictions) and unofficial status. It does not cover rate limits or error handling, but provides substantial context.

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 well-structured and front-loaded with the core purpose, followed by parameter details, return information, and critical notes. Every sentence adds value, with no wasted words, making it efficient and easy to parse.

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 the tool's low complexity (1 parameter, no nested objects) and the presence of an output schema (which handles return values), the description is complete. It covers purpose, usage, parameters, behavioral notes, and warnings, leaving no significant gaps for an AI agent to understand and invoke the tool correctly.

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?

The input schema has 0% description coverage, but the description compensates by explaining the 'limit' parameter's purpose ('Maximum invitations to return') and default value (50). This adds meaningful semantics beyond the schema's type and default, though it could elaborate on constraints like minimum/maximum values.

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 ('pending connection invitations you've received'), distinguishing it from sibling tools that focus on posts, profiles, or analytics. It explicitly notes the scope is limited to received invitations, not sent ones.

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 provides clear context on when to use this tool by specifying it fetches 'pending connection invitations you've received' and noting that 'Sent invitations are not available through this endpoint.' However, it does not explicitly mention when not to use it or name alternative tools for related functions.

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