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ghl-mcp-server-v2

by zackscriven

ghl_conversation_ai_get_agent_actions

Read-onlyIdempotent

Retrieves all actions configured for a Conversation AI agent by agent ID, including custom API call actions.

Instructions

List Actions for an Agent List for actions for an agent, including any customApi ("API Call") actions. Endpoint: GET /conversation-ai/agents/{agentId}/actions (Version header: v3; source: v3/conversation-ai-v3.json) OAuth scopes: conversation-ai.readonly

Input Schema

NameRequiredDescriptionDefault
agentIdYesThe unique identifier of the AI agent

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.1.0

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive, so the bar is lower; the description still adds real value by disclosing the required OAuth scope (`conversation-ai.readonly`), the v3 version header, and the fact that customApi actions are included in results.

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?

Front-loaded with the purpose followed by endpoint and scope metadata; short and mostly waste-free. Minor redundancy in the repeated 'List Actions for an Agent' / 'List for actions for an agent' lines, the latter with a grammatical slip.

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 single-parameter, read-only list operation with full annotation coverage, the description supplies everything needed to invoke it: auth scope, endpoint, version header, and the notable inclusion of customApi actions. Pagination or return-shape details are absent but no output schema exists to compensate.

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?

Only one parameter (agentId) with 100% schema description coverage, so the schema already carries the meaning. The description adds nothing about the parameter beyond the endpoint template showing it is a path variable.

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 a specific verb and resource (list actions for an agent) and clarifies the payload includes `customApi` / API Call actions. It doesn't distinguish this tool from the nearby sibling `ghl_conversation_ai_list_actions`, which appears to overlap, leaving an ambiguity an agent must resolve elsewhere.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description states what it returns but never says when to use it versus `ghl_conversation_ai_list_actions`, `ghl_conversation_ai_get_action_by_id`, or the create/update/delete action siblings. No prerequisites or exclusions are given beyond the endpoint reference.

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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