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List LinkedIn company pages

list_organizations
Read-only

Lists the LinkedIn company pages (organizations) the user administers in PerfectPost, with the user's rights on each. Call it before creating a draft or reading posts for a company page: the other tools take the returned id, urn or name as their organization parameter. Reading a page's posts is open to everyone (last 28 days without Premium); posting on a page requires PerfectPost Premium.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds real behavioral context on top: returned rights per page, the returned identifiers (id/urn/name), the 28-day non-Premium read window, and that posting requires PerfectPost Premium. It stops short of describing pagination or result ordering.

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?

Three sentences, front-loaded with purpose followed by usage and the access caveat; each sentence carries information. Minor redundancy in 'company pages (organizations)' and the paywall sentence is helpful but slightly tangential.

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?

No output schema exists, so the description must carry the return story, and it does at a high level (id/urn/name, rights). Combined with the dependency guidance and access rules, an agent has enough to call this correctly; only pagination/result-shape details are absent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Zero input parameters, so the baseline is 4. The description usefully characterizes the data the call surfaces (id, urn, name, rights), though that is return-value semantics rather than parameter meaning.

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 (Lists) and resource (LinkedIn company pages/organizations) plus scope (those the user administers) and even the return content (rights per page). An agent can distinguish it from list_posts, list_drafts, and get_linkedin_profile without opening any schema.

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 tells the agent when to call it: before creating a draft or reading posts for a company page, because sibling tools consume the returned id/urn/name as their `organization` parameter. That is a concrete prerequisite and dependency, not an implied one.

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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