LinkedIn MCP Server

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the action but doesn't mention important behavioral aspects like rate limits, LinkedIn's connection request policies, whether this requires authentication (implied but not stated), or what happens on success/failure. This leaves significant gaps for an agent to understand the tool's behavior.

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 communicates the core purpose without any wasted words. It's appropriately sized for a tool with two parameters and no complex behavioral nuances to explain.

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?

For a mutation tool (sending connection requests) with no annotations and no output schema, the description is insufficient. It doesn't address behavioral constraints, authentication requirements, LinkedIn's policies, or what the tool returns. Given the complexity of LinkedIn's social interactions and the lack of structured documentation, the description should provide more contextual guidance.

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?

With 100% schema description coverage, the schema already documents both parameters well. The description doesn't add any parameter-specific information beyond what's in the schema, so it meets the baseline for high schema coverage but doesn't provide additional semantic context about parameter usage or constraints.

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 action ('send personalized connection requests') and target resource ('LinkedIn users'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'accept_connection_request' or 'send_message', which prevents a perfect score.

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?

No guidance is provided about when to use this tool versus alternatives like 'send_message' or 'accept_connection_request'. The description only states what the tool does, not when it's appropriate or what prerequisites might exist (such as authentication status).

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