LinkedIn Intelligence MCP Server

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns specific diagnostic information (LinkedIn client status, settings, cookie file, errors), which is useful behavioral context. However, it doesn't mention whether this operation is safe, has side effects, requires authentication, or has rate limits. For a debugging tool with zero annotation coverage, this leaves significant gaps.

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 perfectly concise and well-structured. The first sentence states the purpose, followed by a bulleted list of return information. Every sentence earns its place, with no wasted words or redundancy.

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 that this is a zero-parameter debugging tool with an output schema (implied by 'Returns information about'), the description is reasonably complete. It specifies what diagnostic information is returned, which complements the output schema. However, it lacks context about when and why to use debugging tools, which slightly reduces completeness for an agent.

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 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing instead on what the tool returns. This meets the baseline of 4 for zero-parameter tools.

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: 'Debug tool to check the internal state of the MCP server.' It specifies the verb ('check') and resource ('internal state'), and distinguishes it from all sibling tools which are LinkedIn operations, not debugging tools. It doesn't explicitly contrast with hypothetical other debugging tools, so it's not a perfect 5.

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 no guidance on when to use this tool versus alternatives. It doesn't mention when debugging is appropriate, what symptoms might prompt its use, or whether it should be used proactively. The agent must infer usage from the purpose alone.

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