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ghl-mcp-server-v2

by zackscriven

ghl_conversation_ai_create_action

Create and attach a new action to an AI agent, defining specific tasks like booking appointments, sending follow-ups, or collecting information.

Instructions

Attach Action to Agent Creates and attach a new action for an AI agent. Actions define specific tasks or behaviors that the agent can perform, such as booking appointments, sending follow-ups, or collecting information. Endpoint: POST /conversation-ai/agents/{agentId}/actions (Version header: v3; source: v3/conversation-ai-v3.json) OAuth scopes: conversation-ai.write

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYesRequest body (schema carried verbatim from the official OpenAPI spec).
agentIdYes
Behavior3/5

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

Annotations already indicate this is a write operation (readOnlyHint=false). The description adds OAuth scope information (conversation-ai.write) and endpoint details. However, it does not disclose potential side effects, idempotency, or behavior on duplicate requests. 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.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is moderately lengthy, includes endpoint and OAuth details, but is front-loaded with purpose. Some redundancy (e.g., repeating 'Attach Action to Agent' in both title and description) could be trimmed. Acceptable for the complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite the tool's complexity (7 action types, nested body), the description provides only a high-level overview. It does not explain how to construct the body for each action type, nor does it describe the response (no output schema). The schema carries the burden, but the description lacks sufficient context for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description does not explain the two parameters (agentId and body) beyond referencing the schema. The schema itself has rich descriptions for nested fields, but the tool description adds no extra meaning for parameter usage or construction. Schema coverage is 50%, but the description does not compensate for the gap.

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?

Clearly states it creates/attaches actions for AI agents, lists example action types, and distinguishes from sibling tools like ghl_conversation_ai_create_agent and ghl_conversation_ai_delete_action. The title 'Attach Action to Agent' aligns with the description.

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?

No guidance on when to use this tool vs alternatives (e.g., other conversation AI tools). No conditions, prerequisites, or exclusions are provided. The description only explains what it does, not when to invoke it.

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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