ZOOQ - LinkedIn Data for AI Agents

posts_likes

Read-onlyIdempotent

People who reacted to a post + reaction type and total. (Costs 10 Zooq credits.)

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "entityId": "<entityId>"
    },
    "name": "posts_likes"
  }
}

Input Schema

Name	Required	Description	Default
`start`	No	Pagination offset — MUST be a multiple of 10 (0, 10, 20, ...). Upstream pages by page number; the exact start-to-page mapping is still being verified.
`entityId`	Yes	Activity id — bare numeric or urn:li:activity: form, both accepted. Get it from companies_posts — read data.activities[].entityId (person feeds are currently unavailable).

Output Schema

Name	Required	Description
`page`	No	Example value was a number
`reactions`	No	Array in the example
`totalPages`	No	Example value was a number
`totalReactions`	No	Example value was a number

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 1, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered structurally. The description adds valuable non-obvious behavior by warning that the call 'Costs 10 Zooq credits,' which annotations do not convey. No contradiction with 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?

The description is a single tight sentence that delivers the core behavior and the cost caveat with zero filler. It is front-loaded and every part earns its place.

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?

Combining the description, annotations, and fully documented schema parameters, an agent has everything needed to invoke this read-only reactions list correctly: entity source, accepted id formats, pagination constraint, output shape via schema, and cost. There is no material missing context for this tool's complexity.

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% and the parameter descriptions are already detailed (entityId accepts bare or urn:li:activity forms; start must be a multiple of 10). The description adds no parameter-level meaning beyond the schema, so the baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names the exact output ('People who reacted to a post + reaction type and total') and the annotation title adds the 'List' verb, making the operation clear. It is distinguishable from comment-focused siblings like posts_comments and comments_all because it focuses on reactions rather than comments.

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 itself does not name alternative tools, but the schema's entityId description provides strong operational guidance: get the id from companies_posts and use data.activities[].entityId, while noting person feeds are unavailable. The credit-cost warning also signals an important consideration before invoking the 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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