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LinkedIn: Remove connection

linkedin_remove_connection
Destructive

Remove an existing LinkedIn relation/connection. Resolve the exact provider user_id first. This changes the user's network and requires explicit intent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
user_idYesExact provider user ID returned by the relevant profile/contact resolver; never a display name or profile URL. For LinkedIn, use the stable system ID. LinkedIn system user ID: Stable LinkedIn/Unipile user id, commonly ACo... for Classic profiles. Obtain with: linkedin_get_profile_from_url(profile_url) -> result.id; linkedin_get_profile(user_id_or_public_identifier) -> result.id; linkedin_search_people(...) -> selected result.id Never pass: full linkedin.com/in/... URL, person name, company ID.
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
Behavior4/5

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

Annotations already declare destructiveHint=true and readOnlyHint=false. The description adds context beyond this by stating the impact ('changes the user's network') and the requirement of explicit intent. This is useful behavioral context that is not in the annotations.

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?

Three short sentences with no filler. The first sentence states the action, the second gives the key precondition, and the third communicates the impact and intent requirement. Every sentence earns its place and the purpose is front-loaded.

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 tool with two parameters, full schema coverage, and annotations covering safety/destructive behavior, the description provides the essential purpose, precondition, and consequence. No output schema exists, but the description still gives enough operational context for correct invocation.

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 the input schema fully documents both parameters. The main description adds only a sequence hint ('Resolve the exact provider user_id first'), which is minor. Baseline of 3 is appropriate since the schema carries the semantic weight.

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 states a specific verb and resource: 'Remove an existing LinkedIn relation/connection.' This clearly distinguishes it from related sibling tools like linkedin_send_invitation, linkedin_accept_invitation, and linkedin_unfollow_user. The purpose is immediately understandable.

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?

The description gives clear context for use by instructing to 'Resolve the exact provider user_id first' and warning that the action 'changes the user's network and requires explicit intent.' It does not explicitly name alternatives or exclusions, but it sets the appropriate precondition and intent requirement.

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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