LinkedIn 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 of behavioral disclosure. It mentions filtering and listing, but lacks details on permissions required, rate limits, pagination behavior, or error handling. For a tool that accesses personal data (LinkedIn connections), this is a significant gap in transparency.

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 concise and front-loaded, stating the core purpose in the first sentence. The second sentence adds optional functionality without redundancy. However, it could be slightly more structured by explicitly separating core and optional features, but overall it's efficient with no wasted words.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain what the return values look like (e.g., format of the list), error conditions, or authentication needs. For a tool that lists personal connections, this leaves significant gaps in understanding how to interpret results or handle failures.

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 description adds minimal value beyond the input schema, which has 100% coverage. It mentions 'Optionally filter by name,' aligning with the 'search' parameter, but doesn't provide additional context like syntax examples or edge cases. With high schema coverage, the baseline score of 3 is appropriate, as the schema does most of the work.

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: 'List your LinkedIn connections with their name, headline, and profile URL.' It specifies the verb ('List'), resource ('LinkedIn connections'), and output fields. However, it doesn't explicitly distinguish this tool from its siblings (like 'get_profile' or 'search_jobs'), which would be needed for a score of 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 minimal usage guidance with 'Optionally filter by name,' but it doesn't specify when to use this tool versus alternatives (e.g., 'get_profile' for individual profiles or 'search_jobs' for job-related queries). There's no explicit context, exclusions, or mention of prerequisites, leaving the agent with little direction on tool selection.

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