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LinkedIn: List invitations

linkedin_list_invitations
Read-onlyIdempotent

List pending LinkedIn connection/relation requests sent or received by the account owner. Use before accepting/refusing a received invitation or withdrawing a sent invitation so you have the required request_id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYes
account_idNoOptional Nilyo connection ID (unipile_account_id from list_connected_accounts). Omit when the user has one account for this provider. When several exist, Nilyo never guesses: list them (display name, identifier, provider user ID), choose the one the user named or ask, and pass its ID here.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, covering the safety profile. The description adds the context that the response includes request_id needed for subsequent operations, but does not disclose other behaviors like pagination or response structure. Given the strong annotation coverage, a 3 is appropriate.

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?

Two sentences with no fluff. The main action is front-loaded, and the usage context is concise. Efficient and well-structured.

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?

For a simple list tool with strong annotations, the description is fairly complete. It explains purpose, use case, and implies the response contains request_id. It does not mention pagination or edge cases, but these are minor for this type of operation.

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 50% (account_id has a detailed description, type lacks one). The description partially compensates by mentioning 'sent or received' for the type parameter, but does not add further meaning beyond what the schema provides for account_id. Minimal added value, so a 3.

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?

The description clearly states the tool lists pending LinkedIn connection/relation requests, distinguishing sent vs received. It differentiates from sibling tools like linkedin_send_invitation and linkedin_accept_invitation by focusing on pending requests and the prerequisite role for those actions.

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

Usage Guidelines5/5

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

Explicitly instructs when to use: before accepting/refusing a received invitation or withdrawing a sent invitation, to obtain the required request_id. This provides clear contextual guidance and implies alternatives (accept/refuse/withdraw) that depend on this tool.

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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