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kaistenberg

MCP Server for LinkedIn

by kaistenberg

Get Inbox

get_inbox
Read-only

Retrieve recent LinkedIn messaging conversations from your inbox. Specify a limit to control how many to load.

Instructions

List recent conversations from the LinkedIn messaging inbox.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of conversations to load (1-50, default 20)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

The annotations already signal read-only and open-world behavior, so the description is not required to repeat that. It adds the 'recent' qualifier, which indicates ordering by recency, but does not provide further behavioral context like pagination, rate limits, or auth requirements. This is a modest addition beyond annotations, so a mid score is appropriate.

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 a single, succinct sentence that immediately states the action and resource. It is front-loaded and contains no filler or redundant information, earning full marks for conciseness.

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

Completeness5/5

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

This is a simple tool with one optional parameter, read-only/open-world annotations, and an output schema. The description clearly conveys the core purpose, and since an output schema exists, there is no need to detail return values. The combination of annotations, schema, and description provides a complete understanding for a straightforward listing operation.

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 fully describes the only parameter `limit` with a clear explanation including range and default (100% coverage). The description does not add any additional meaning about the parameter, so the baseline score of 3 is maintained.

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 uses the specific verb 'List' with the resource 'recent conversations from the LinkedIn messaging inbox.' This clearly defines the tool's scope and differentiates it from siblings like get_conversation (single conversation) or search_conversations (search-based). The mention of 'messaging inbox' distinguishes it from non-inbox tools like get_feed.

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 description implies this is the tool for browsing recent inbox conversations, but it does not explicitly state when to use it versus alternatives such as search_conversations or get_conversation. There is no exclusion or mention of alternative tools, leaving the decision to the agent's inference from the sibling list.

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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