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ghl-mcp-server-v2

by zackscriven

ghl_conversation_ai_create_agent

Create an AI agent for a location with custom name, personality, goal, and instructions. Configure communication channels, mode, and behavior settings like wait time and sleep.

Instructions

Create an Agent Creates a new AI agent for the location. The agent will be created with the specified configuration including name, role, actions, and behavior settings. Endpoint: POST /conversation-ai/agents (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).
Behavior3/5

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

Annotations provide basic non-readOnly, non-idempotent, non-destructive hints. The description adds endpoint and OAuth scopes but lacks details on potential side effects, rate limits, or what happens on conflict (openWorldHint=true is ambiguous). Moderate transparency.

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 concise but includes redundant title line and technical details (endpoint, OAuth) that could be placed elsewhere. It is front-loaded but lacks structure for quick comprehension.

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?

Given the complex nested body with 20+ properties, the description provides no high-level guidance on constructing the request or typical configurations. No output schema is provided, leaving the agent unsure of the response format.

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 coverage is 100% with descriptions and examples, so the description adds minimal value beyond listing 'name, role, actions, behavior settings'. There is a mismatch: 'role' is not in the schema. The description does not compensate for schema gaps.

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 states that the tool creates a new AI agent for a location, distinguishing it from update/delete siblings. The title 'Create an Agent' matches the action. However, the description mentions 'role, actions' which are not in the schema, causing slight confusion.

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 versus alternatives (e.g., updating an existing agent). No prerequisites or context about when creation is appropriate. The agent must be for a specific location, but this is not emphasized.

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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