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Import LinkedIn history

import_linkedin_history

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": {
      "window": "<window>"
    },
    "name": "import_linkedin_history"
  }
}

Input Schema

NameRequiredDescriptionDefault
windowYesHow far back from today to import: '30d', '3m', '6m' or '1y'. Only history older than what's stored is new.
on_behalf_ofNoA teammate's email, or an agency client's from list_agency_clients, to run this call in that account: their agents, settings, connected accounts, and credits. Omit it to act on your own account.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / on_behalf_of / description
      Previous value: -"An agency client's email, from list_agency_clients, to run this call in that client's account: their agents, settings, connected accounts, and credits. Omit it to act on your own account."New value: +"A teammate's email, or an agency client's from list_agency_clients, to run this call in that account: their agents, settings, connected accounts, and credits. Omit it to act on your own account."
  2. Changed1 schema field changed
    • addedInput schema / properties / on_behalf_of
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "An agency client's email, from list_agency_clients, to run this call in that client's account: their agents, settings, connected accounts, and credits. Omit it to act on your own account."
+}
  3. Added

TDQS

A4.4/5.0
Behavior5/5

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

Annotations only declare readOnlyHint=false and destructiveHint=false, so the description carries real weight here and delivers: cost (free), async semantics (runs in background, tens of minutes on a large account), a specific cold-start latency (up to an hour after connecting LinkedIn), where live state lives, and the concrete failure modes (LinkedIn not connected, import already running). That is exactly the operational context an agent needs before kicking off a long-running job.

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?

Front-loaded with the action and its product anchor, then timing, then return contract in a labeled block. Dense and largely waste-free, though the summary/returns XML scaffolding is heavier than necessary for a two-parameter tool.

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?

There is no output schema, but the description supplies the return contract itself ({started: true, message_backfill} vs {started: false, error}) along with duration, cost, and the wait-for-indexing caveat. Nothing an agent needs to decide whether and how to call this is missing.

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%, including the enum values and the note that only history older than what's stored is new, plus a full explanation of on_behalf_of. The description adds nothing about either parameter, so the baseline of 3 applies — the schema does all the work.

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?

States a specific verb and resource (import older LinkedIn message history) and anchors it to the exact product surface the user sees: the Messages tab's "Import more message history". This makes it trivially distinguishable from read-side siblings such as search_linkedin_message_history or fetch_linkedin_messages_with_person.

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 clear context for when this applies: importing history older than what's stored, free of charge, and the special case of running it right after connecting LinkedIn (wait up to an hour for indexing). It does not explicitly name alternatives or state when not to call it beyond the implied 'already running' case, so it falls short of full routing guidance.

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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