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Iridium: LinkedIn MCP Server

list_drafts

List Drafts

Connection-note drafts waiting for review. Nothing here has been sent.

Each entry has a draft_ handle, who it is addressed to, a preview of the note, and the time Iridium suggests sending it. Show the notes to the user and let them decide. Approving is a separate step: call approve_draft only when 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

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it declares a read-only surface implicitly (drafts waiting for review, none sent), enumerates the entry fields the caller will see, and warns that approval is a distinct action requiring explicit user consent. It stops short of stating volume, ordering, or whether results are truncated.

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 prose is tightly front-loaded: what it lists, what state the items are in, what each entry contains, then the decision/approval rule. The trailing '### Responses: 200 Successful Response / Content-Type: application/json' block is HTTP boilerplate that adds no decision value for an agent.

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?

With no annotations and no output schema, the description must convey both safety profile and return shape, and it does describe entry fields and the non-destructive nature. Gaps are minor: no guidance on ordering, result size, or how to fetch full note text once a draft handle is chosen.

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 takes zero parameters, so there is no parameter semantics to convey and the schema can carry the full contract. The description usefully redirects that space to describing the shape of each returned entry instead.

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

Purpose5/5

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

The description gives a specific verb and a precise resource subset: connection-note drafts pending review, with the explicit clarification that nothing has been sent. That scoping distinguishes it from the other draft listings (list_reply_drafts, list_comment_drafts, list_content_drafts) without the agent having to open a schema.

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 sets explicit downstream behavior — show entries to the user and let them decide — and states the approval boundary: call approve_draft only when the user explicitly asks. It does not explicitly contrast with get_draft_detail or list_scheduled, so the routing guidance covers one sibling rather than the full field.

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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