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Iridium: LinkedIn MCP Server

draft_reply

Draft Reply

Generate a reply to a conversation, using the full thread + your voice, for review. Creates a pending reply draft, one per thread. Approve, rewrite, or skip it next.

Args: chat_handle: chat_ handle from list_chats / search_chats / list_replies intent: optional steer for the reply (a goal or tone)

Responses:

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

Input Schema

NameRequiredDescriptionDefault
intentNo
chat_handleYes

Schema Changelog

Changes observed during successful MCP inspections.

No schema history has been recorded yet.

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does disclose the important behavior: this creates a *pending* draft rather than sending anything, uses the full thread plus the user's voice, and is limited to one draft per thread. It omits what happens on a duplicate request (error vs. replace) and any permission or rate-limit constraints.

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

Conciseness3/5

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

The core sentences are tight and front-loaded, but the repeated title "Draft Reply" and the trailing "### Responses: **200**..." OpenAPI boilerplate add text that does not help an agent invoke the tool.

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

Completeness4/5

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

For a two-parameter creation tool with no output schema, the description covers what it makes, what it doesn't do (send), the review path, and both inputs. Missing only the return shape and duplicate-draft handling, which are minor given no output schema exists.

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?

Schema coverage is 0%, so the description must compensate — and it does, documenting both parameters: chat_handle's provenance ("from list_chats / search_chats / list_replies") and intent as an optional goal-or-tone steer. It doesn't describe the handle's format, though that is acceptable given it is an opaque token from sibling tools.

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?

States a specific verb+resource ("Generate a reply to a conversation") and pins the scope ("Creates a pending reply draft, one per thread"), which separates it from rewrite_reply_draft and approve_reply_draft. It does not name those siblings explicitly, so the differentiation is implied rather than stated.

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?

Gives clear usage context: generate a draft "for review" and then "Approve, rewrite, or skip it next," which maps the agent onto the correct follow-up tools. It stops short of explicit exclusions (e.g., when to prefer getting a thread summary first or when a draft already exists).

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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