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get_conversation

Legacy. Prefer get_inbox with personUrl. Retrieve a conversation with a LinkedIn person via standard LinkedIn messaging. Returns the conversation immediately if it has already been synced. If the conversation has not been synced yet, this tool starts a syncConversation workflow and returns its ack ({status, workflowId, operationName: "syncConversation", message}); the client should call get_workflow_result with that workflowId until completion, then call get_conversation again to read the synced messages. The result carries syncUntil — the moment syncing of this conversation stops. Once it is in the past the messages are still returned but no longer updated; call sync_conversation again for the same person to resume updates. It also carries personUrn — the permanent LinkedIn member URN (urn:li:member:) of the person, or null when LinkedIn does not expose it.

Linked API actions are queued into a cloud-browser workflow and may take several minutes. The server returns immediately after starting the workflow with {status: 'pending'|'running', pendingReason, workflowId, operationName, message}. To retrieve the final result, call get_workflow_result with the returned workflowId and operationName — it will long-poll until completion or the request budget elapses, then return either the final result or another in-progress snapshot. Do not retry the original tool while a workflow is still running; that creates duplicate queued work.

A pending workflow carries pendingReason: 'queued' means it is waiting its turn behind other work on the same account and will start within minutes. 'outsideWorkingHours' means the account has configured working hours and the workflow is parked until they reopen — possibly the next working day. In that case get_workflow_result returns immediately instead of polling, message states when the window opens, and you should report that to the user rather than looping.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "personUrl": "<personUrl>"
    },
    "name": "get_conversation"
  }
}

Input Schema

NameRequiredDescriptionDefault
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.
personUrlYesThe LinkedIn URL of the person whose conversation you want to poll (e.g., 'https://www.linkedin.com/in/john-doe')

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior5/5

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

Annotations only declare readOnlyHint=false and openWorldHint=true, so the description carries the real behavioral load and does so thoroughly: it explains the cached-vs-unsynced branch, the syncConversation ack shape, the syncUntil cutoff and its consequences, personUrn semantics (null when not exposed), duplicate-work risk on retry, and the meaning of each pendingReason including outsideWorkingHours parking.

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

Conciseness3/5

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

The legacy/deprecation warning and the cached-vs-sync branch are correctly front-loaded, but the final two paragraphs read as generic workflow boilerplate (queued/outsideWorkingHours mechanics) likely duplicated across many sibling tools, and the narrative drifts well past what is needed to call this tool.

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 output schema, the description does the work of explaining return shapes (status/workflowId ack, syncUntil, personUrn) and the multi-step polling protocol, which is what an agent most needs. It stops short of describing the message objects themselves or any pagination/volume limits on the conversation history.

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%, so both personUrl and since are already fully documented in the schema, and the description adds no extra meaning about either parameter's format or constraints. Baseline 3 applies since the schema does the heavy lifting.

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?

Opens with a specific verb+resource ('Retrieve a conversation with a LinkedIn person via standard LinkedIn messaging') and explicitly labels itself 'Legacy. Prefer get_inbox with personUrl,' so an agent can route away from it. It does not, however, distinguish itself from the very similarly named sibling nv_get_conversation, which remains ambiguous.

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?

Gives a concrete alternative (get_inbox with personUrl) and lays out the exact follow-up sequence: call get_workflow_result with the returned workflowId, then call get_conversation again, and call sync_conversation to resume updates. It also warns not to retry while a workflow is running. The only gap is no guidance on choosing between this and nv_get_conversation.

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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