Get the list of members who recently viewed the account's profile (requires LinkedIn Premium).
| Name | Required | Description | Default |
|---|---|---|---|
| account_id | Yes | Reach id of the LinkedIn account to act on, from list_accounts. |
| Name | Required | Description | Default |
|---|---|---|---|
| total | No | ||
| viewers | No |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only, idempotent, non-destructive behavior. The description adds useful context beyond the annotations: it reveals the premium subscription requirement and that the result is limited to recent viewers. It does not contradict annotations and adds an external dependency the annotations do not capture.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one concise sentence that states both the operation and a critical usage requirement. There is no filler or redundancy, and the main action is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has only one parameter, an informative output schema, and strong annotations, the description is complete enough. It covers the operation outcome and the required product entitlement, so an agent has sufficient information to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents account_id fully, including its type, required status, and source (list_accounts). The description adds no new parameter-level semantics, but because schema coverage is 100%, baseline 3 is appropriate and no compensation is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb ('Get') and resource ('the list of members who recently viewed the account's profile'). This is specific enough to distinguish the tool from siblings like list_connections or list_received_invitations, since it uniquely targets profile viewers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives one practical precondition—LinkedIn Premium—but provides no explicit guidance about when to use this tool versus alternatives or when not to use it. It implies the usage case through the purpose, but does not name sibling tools or exclusion conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.