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rgthelen

LinkedIn MCP Server

by rgthelen

create_comment

Add a comment to a LinkedIn post. Provide the post URN and comment text to engage with content in your feed.

Instructions

Comment on a LinkedIn post

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
postUrnYesThe URN or ID of the post to comment on
textYesThe comment text
Behavior2/5

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

With no annotations, the description carries the full burden. It does not disclose any behavioral traits such as whether it modifies data, requires authentication, has rate limits, or returns success/failure. Simply stating 'Comment on a LinkedIn post' is minimal for a mutation action.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, concise and to the point. It is not verbose, but missing contextual information. It could be improved with additional structure, but it is not overly short to the point of being useless.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simplicity of the tool (2 required string parameters, no nested objects, no output schema), the description is barely adequate. It lacks information about return values or side effects, but the context from sibling tools and schema partially compensates.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already provides descriptions for both parameters (postUrn and text) with 100% coverage. The description adds no additional meaning beyond the schema, so it meets the baseline of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Comment') and the resource ('a LinkedIn post'), distinguishing it from siblings like create_post, like_post, and share_post. However, it could be more explicit by using 'Create a comment' to emphasize creation, but it is sufficient.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives, such as when to comment versus like or share. There is no mention of prerequisites or context for usage.

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

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