LinkedIn Custom MCP Server

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

Annotations only provide a title, so the description carries full burden. It states 'Create a comment' implying a write/mutation operation, but lacks behavioral details such as permissions required, rate limits, whether comments are editable/deletable, or what happens on success/failure. This is inadequate for a mutation 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 front-loaded with the core purpose in the first sentence, followed by a clear 'Args:' section listing parameters. It's efficient with minimal waste, though the structure could be slightly improved by integrating parameter details more seamlessly.

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 has an output schema (which handles return values), 2 parameters with description coverage, and no complex annotations, the description is moderately complete. However, as a mutation tool, it lacks crucial behavioral context (e.g., side effects, error handling), making it incomplete for safe agent use.

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 0%, but the description compensates by explaining both parameters: 'object_urn' as 'The URN of the content to comment on' with an example, and 'text' as 'The text of the comment.' This adds meaningful semantics beyond the bare schema, though it could elaborate on URN formats or text 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 ('Create a comment') and specifies the target resources ('on a LinkedIn share, article, or video'), which distinguishes it from sibling tools like linkedin_create_post or linkedin_delete_comment. However, it doesn't explicitly differentiate from all siblings (e.g., it could mention it's for commenting vs. posting original content).

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 prerequisites (e.g., authentication), exclusions, or compare it to related tools like linkedin_get_post_comments or linkedin_update_post, leaving the agent to infer usage context.

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