Skip to main content
Glama
commentkeyword

commentkeyword-mcp

Official

List AI agents

list_agents
Read-only

List AI agents already set up in the workspace and retrieve an agent's publicId to attach it to keyword automations, so it keeps chatting after the first DM.

Instructions

List the AI agents already set up in the workspace (agents are created and edited in the CommentKeyword dashboard). Pass the publicId of a Live agent as aiAgentId to create_keyword or update_keyword so it keeps chatting after the first DM.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true; the description adds the non-obvious constraint that agents cannot be created or edited through this API (dashboard-only) and that only 'Live' agents are usable downstream. It does not cover pagination or failure behavior, so not 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?

Two sentences, purpose front-loaded, second sentence carrying only the chaining instruction. No filler or repetition of the title.

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?

With no parameters and no output schema, the description supplies enough: what it returns (identifiable agents via publicId), which agents matter (Live), and how to use them. It doesn't describe the response shape or ordering, which is a minor gap given no output schema exists.

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?

The tool takes zero parameters, so the baseline is 4. The description instead adds return-semantics value by identifying that results carry a publicId and a Live status that feeds other tools.

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 ('List the AI agents already set up in the workspace') and immediately distinguishes itself from the keyword siblings by noting agents are created and edited in the CommentKeyword dashboard, not here. An agent can tell this is a read-only enumeration of agents versus the keyword CRUD tools.

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 a concrete next step: pass the publicId of a Live agent as aiAgentId to create_keyword or update_keyword so it keeps chatting. That implicitly covers the main reason to call it, but there is no explicit 'do not use this to create/manage agents' exclusion, so it stops short of full 5-level guidance.

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