Skip to main content
Glama

ZOOQ - LinkedIn Data for AI Agents

posts_comments

Read-onlyIdempotent

Threaded comments/replies on a post. (Costs 10 Zooq credits.)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoResults per page (default 10).
startNoPagination offset.
sortByNoOrdering. Accepted values: relevance (default), date_posted (newest first).
entityIdYesActivity 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

TableJSON Schema
NameRequiredDescriptionDefault
repliesNoArray in the example

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds meaningful behavioral context beyond annotations: the results are threaded, and the call costs 10 Zooq credits. There is no contradiction with 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?

The description is two short sentences with the core resource front-loaded. The cost warning is neatly parenthesized, and there is no redundant or filler content.

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?

With a full output schema, thoroughly described parameters, and safety annotations, the description is complete enough for an agent to select and invoke the tool correctly. The threaded and cost behaviors are disclosed, and the only small gap—explicit sibling routing—is largely mitigated by the schema guidance.

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 entityId property already explains accepted formats and provenance. The tool description itself adds no additional parameter-level meaning, so the baseline for high schema coverage applies.

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 clearly identifies the resource as 'Threaded comments/replies on a post' and the title 'List post comments' supplies the verb. It is clear enough for an agent to infer this retrieves comments for a specific post, but it does not explicitly contrast with the sibling comments_all.

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 entityId parameter description provides useful workflow context: get the activity id from companies_posts and note that person feeds are currently unavailable. The single-post framing implies when to use the tool, though it does not explicitly name alternatives or state when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.