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by com.dialogbrain
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linkedin_withdraw_invitation

DestructiveIdempotent

Withdraw PENDING sent connection invitations by invitation_urn (up to 25 per call; call again for more). IRREVERSIBLE: a withdrawn invitation cannot be restored, and LinkedIn does not let you invite the same person again for a while (it says up to 3 weeks). First list with linkedin.list_invitations_sent and pick by sent_at (its invitation_urn values are what this takes). Each withdrawal is spaced 1-4 seconds, so a full batch takes a minute or two. Answers a result per urn: withdrawn, not_found (not pending any more), lookup_incomplete (the sent list could not be read to its end; may still be pending), failed (with LinkedIn's http_status/code) or not_attempted (the batch stopped on an expired session or a rate limit; see stopped; the call then answers an error with the per-urn data), plus totals. Nothing is retried.

Input Schema

NameRequiredDescriptionDefault
in_workspaceNoRun this one call in this workspace id instead of the session's. Nothing is stored; other sessions are not affected.
invitation_urnNoA single invitation_urn, instead of invitation_urns
from_account_idNoWhich of the workspace's LinkedIn accounts to act as (its id from channels.list). Connections, invitations and search results are that person's own network. OMIT to use the default LinkedIn account (in a LinkedIn conversation, the account that conversation belongs to); pass it whenever the workspace has more than one. An account this workspace cannot use is refused, never swapped for another.
invitation_urnsNoinvitation_urn values from linkedin.list_invitations_sent (urn:li:fs_relInvitation:<id>)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior5/5

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

The description reveals crucial behavioral traits beyond the annotations, notably that the action is irreversible and not refundable. It also discloses execution constraints (1-4 second delay) and all possible result codes (not_found, failed, not_attempted, etc.).

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?

The description is highly detailed, which detract from pure conciseness, but it is exceptionally well-structured, following a logical progression from purpose to usage to behavioral constraints.

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?

Given the operational complexity—involving rate limits, multi-step processes, session issues, and permanent data changes—this definition is entirely complete and leaves no critical operational gaps for the user agent.

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?

Since the input schema has 100% coverage, the description does not need to elaborate on parameter meanings. It focuses on the workflow rather than specific parameter values, meeting the baseline score for high schema coverage.

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 and immediately states the tool's purpose: to withdraw pending connection invitations using invitation_urn. It avoids vague language and provides a specific action on a specific resource.

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?

The description provides explicit workflow instructions, dictating that the agent must first use `linkedin.list_invitations_sent` and then process the URNs. It also provides hard limits on call volume (25 per call).

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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