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Iridium: LinkedIn MCP Server

list_comment_drafts

List Comment Drafts

List pending comment drafts awaiting review.

ALWAYS display every draft to the user in full:

Post by [author_name]: [post_text, the complete text, never truncated]

Drafted comment: [comment_text, displayed in full]

Do NOT call approve_comment_draft or schedule anything unless the user explicitly asks.

Responses:

200: Successful Response (Success Response) Content-Type: application/json

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

No schema history has been recorded yet.

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It contributes useful instructions to display every draft in full and not to approve drafts implicitly, but it does not explicitly confirm read-only behavior, pagination, ordering, or other operational traits.

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 purpose is front-loaded and the display instructions are relevant, but the description repeats the title and includes a boilerplate 200 response note that adds little value. Overall it remains appropriately sized.

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?

With no output schema and no annotations, the description should do more to explain the returned draft structure. It mentions author_name, post_text, and comment_text in the display template, but omits identifiers or other fields an agent might need to act on a draft.

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

Parameters4/5

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

The tool has zero parameters, so there is no parameter semantics to explain. The schema coverage is complete and no additional parameter guidance is needed.

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 states a clear verb and resource: it lists pending comment drafts awaiting review. The resource name distinguishes it from reply drafts and content drafts, but the description does not explicitly explain how it differs from the generic sibling list_drafts.

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

Usage Guidelines4/5

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

It establishes the usage context as reviewing pending drafts and explicitly warns not to call approve_comment_draft or schedule anything unless the user asks. However, it does not explain when to choose this tool over list_drafts or list_reply_drafts.

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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