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Get post likers

get_post_likers
Read-only

Retrieves the people and organizations who liked a LinkedIn post, with pagination. Works on the personal profile by default; pass organization to target a company page (see list_organizations). For a company page, the post urn must belong to that page.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urnYesLinkedIn URN of the post
limitNoNumber of likers to return
offsetNoNumber of likers to skip
organizationNoLinkedIn company page to act on instead of the personal profile. Pass the page id or urn returned by list_organizations, or the exact page name. Omit to target the personal profile.

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 readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds behavior beyond that: pagination is supported and a company-page target imposes an urn-ownership constraint. It does not cover failure modes (e.g., private posts, hidden likers), keeping it short of a 5.

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 sentences, front-loaded with what is retrieved, followed by target-selection behavior and the constraint. Every clause earns its place with no repetition of schema content.

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 read-only, 4-parameter tool with full schema coverage and annotations but no output schema, the description covers purpose, target selection, and pagination. It could say more about what each liker record contains, though annotations and the absence of an output schema lower that burden.

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 all four parameters are already documented in the schema; the baseline here is 3. The description reinforces the organization parameter's dual-target behavior and names list_organizations as the source of the value, but adds no format or syntax detail beyond what the schema states.

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 and resource ('Retrieves the people and organizations who liked a LinkedIn post') and adds scope ('with pagination'), which cleanly separates it from the adjacent get_post_commenters sibling. An agent can tell exactly what comes back without opening the schema.

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?

Gives clear default behavior ('works on the personal profile by default; pass organization to target a company page'), routes the agent to list_organizations for the id, and adds a prerequisite ('the post urn must belong to that page'). It stops short of explicitly contrasting with the likers-vs-commenters choice, so it is strong but not exhaustive.

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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