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Linked-API
by Linked-API

nv_get_conversation

Retrieve conversation history with a LinkedIn person using Sales Navigator messaging. Optionally filter messages by date to get updates since a specific timestamp.

Instructions

Allows you to get a conversation with a LinkedIn person using Sales Navigator messaging.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
personUrlYesThe LinkedIn URL of the person whose conversation you want to poll (e.g., 'https://www.linkedin.com/in/john-doe')
sinceNoOptional ISO 8601 timestamp to only retrieve messages since this date (e.g., '2024-01-15T10:30:00Z'). If not provided, the entire conversation history will be returned.
Behavior2/5

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

No annotations provided, so description carries full burden. Only says 'get a conversation' implying read-only, but no mention of rate limits, auth needs, error handling, or whether the conversation is created automatically. Minimal behavioral disclosure.

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?

Single sentence, 14 words, front-loaded with key action. No fluff or redundancy.

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

Completeness3/5

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

No annotations or output schema exist. Description explains what the tool does but does not describe return format, pagination, or error scenarios. Adequate for a simple read operation but lacks completeness.

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?

Schema description coverage is 100%. Both parameters have clear descriptions with examples. The tool description adds no additional parameter info, so baseline 3 is appropriate.

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?

Clearly states the action ('get'), resource ('conversation with a LinkedIn person'), and context ('using Sales Navigator messaging'). Distinguishes from sibling like 'get_conversation' (non-Sales Navigator) and 'nv_send_message' (send vs get).

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?

Implies use for Sales Navigator conversations, but no explicit when-to-use, when-not, or alternatives among siblings. Agent must infer from name and context.

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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