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ChimbuezeDavid

Universal LinkedIn MCP Server

list_conversations

Retrieve recent LinkedIn direct message conversations from your authenticated inbox. Specify a limit to control how many conversations to fetch.

Instructions

List recent direct message conversations from your authenticated inbox.

Args: limit: Maximum conversations to retrieve (default: 10, max: 20).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior3/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It conveys that the operation is read-only ('List') and authentication-dependent ('authenticated inbox'), and hints at recency. Still, it does not specify ordering, whether results are paginated, or what happens when the user is not authenticated.

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

Conciseness5/5

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

The description is two concise sentences with the core action front-loaded and the parameter explanation kept in a clear 'Args:' block. There is no redundant or filler content.

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 simple tool with only one optional parameter and an output schema available, the description is largely complete. It could be improved by noting ordering/pagination or pointing to get_conversation_messages for reading a specific conversation's messages, but these are minor gaps for this use case.

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

Parameters5/5

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

Schema description coverage is 0%, but the description fully compensates for the sole parameter 'limit' by defining it as 'Maximum conversations to retrieve' and stating the default and max values. This adds meaningful usage semantics beyond the bare schema definition.

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 states a specific verb and resource: 'List recent direct message conversations from your authenticated inbox.' This clearly identifies what the tool does and differentiates it from sibling tools like get_conversation_messages, which handles individual messages rather than conversation listings.

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

Usage Guidelines3/5

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

The phrase 'from your authenticated inbox' implies the tool is for retrieving the user's own recent DMs, giving some usage context. However, it does not explicitly state when to use this tool versus alternatives such as get_conversation_messages or get_feed, nor does it mention any exclusions.

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