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DarkLvrd

agentic-linkedin

by DarkLvrd

Get conversations

get_conversations

Retrieve recent LinkedIn messaging conversations, including participants and last activity, to review message history and identify active chats.

Instructions

Returns recent messaging conversations with participants and last activity.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
Behavior2/5

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

Since no annotations are provided, the description carries the full burden of behavioral disclosure. It names the returned data categories but does not explain ordering, scope (own conversations vs all), pagination behavior, or what 'recent' means relative to last activity. The effect of the limit parameter is also not described.

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 description is a single efficient sentence with no filler, and the core return value is front-loaded. It is concise, though the conciseness comes at the expense of important semantic and behavioral details captured under other dimensions.

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

Completeness2/5

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 is too thin to fully support correct invocation. It mentions only participants and last activity as return attributes, and omits limit semantics, result ordering, conversation scoping, and distinction from get_conversation_history.

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

Parameters1/5

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

The schema has one parameter, limit, with 0% schema description coverage, and the description does not mention it at all. An agent is left only with the schema's min and max constraints and has no context for what limit controls or what the default behavior is.

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 clearly states it returns recent messaging conversations and specifies the key data included: participants and last activity. However, it does not explicitly differentiate itself from the sibling tool get_conversation_history, so an agent could conflate listing conversations with retrieving the contents of a conversation.

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

Usage Guidelines2/5

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

There is no guidance about when to use this tool versus alternatives such as get_conversation_history or send_message. The description only says what the tool returns, leaving the agent to infer when it should be selected over related tools.

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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