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create_agent

Create a new AI agent with configurable language, voice, model, and workflow type. Supports single prompt or multi-agent playbooks.

Instructions

Create a new AI agent in your organization. By default the agent is a single_prompt agent with gpt-4.1 model and daniel voice (waves_lightning_v3_1); set workflow_type to multi_agents for a Playbooks agent (an intent router + specialist SOP playbooks — add them via add_playbooks after creation). The STT transcriber defaults to Pulse — change it (e.g. to pulse-legacy) via update_agent_config after creation. Returns the created agent's ID. For single_prompt agents, set the prompt via update_agent_prompt after creation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoName for the new agent
languageNoLanguage configuration. Defaults to English.
slm_modelNoLLM model for the agent. Defaults to gpt-4.1.
descriptionNoShort description of what the agent does
synthesizerNoVoice synthesizer configuration
first_messageNoFirst message the agent says when a call starts (max 500 chars)
global_promptNoGlobal system prompt for the agent (max 4000 chars). For the main prompt, use update_agent_prompt after creation.
workflow_typeNoAgent type. single_prompt (default) = one prompt + tools. multi_agents = Playbooks: an intent router classifies each caller turn and routes to a specialist playbook (SOP) with its own prompt and scoped tools — configure via add_playbooks / configure_playbooks. multi_agents is domain-gated; the API returns 403 if your account isn't allowlisted.
background_soundNoBackground sound during calls
default_variablesNoDefault template variables for the agent prompt (e.g. { company_name: 'Acme' })
knowledge_base_idNoKnowledge base ID to attach to the agent
smart_turn_configNoSmart turn detection configuration
allow_inbound_callNoWhether to allow inbound calls (default true)
enable_style_guideNoEnable conversational style guide (default true)
allow_interruptionsNoWhether to allow user interruptions (default true)
pronunciation_dictsNoCustom pronunciation dictionary
voicemail_detectionNoVoicemail detection configuration
wait_for_user_to_speak_firstNoWait for user to speak before agent starts (default false)
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses defaults (model, voice, STT), the return value (agent ID), and post-creation steps (set prompt, change STT, add playbooks). It also mentions the gating for multi_agents. It lacks details on authorization or destructive behavior, but these are not critical for a creation tool.

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?

The description is a single paragraph but is information-dense and well-organized. It starts with the primary purpose, then details defaults, then alternative types and post-creation steps. No wasted words, though it could be slightly restructured for easier scanning.

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?

Despite 18 parameters and no output schema or annotations, the description is remarkably complete. It covers default behavior, post-creation steps required for certain configurations, and a critical domain-gating warning. It provides enough context for an agent to use this tool effectively.

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?

Schema coverage is 100%, so baseline is 3. The description adds value by explaining default values for several parameters (e.g., slm_model defaults to gpt-4.1, synthesizer voice defaults to daniel, STT defaults to Pulse). It also clarifies the workflow_type enum and the need for post-creation configuration for prompts and playbooks.

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?

The description clearly states 'Create a new AI agent in your organization' and specifies the default type (single_prompt) with an alternative (multi_agents). It distinguishes from sibling tools like update_agent_prompt, add_playbooks, etc. The verb 'Create' and resource 'AI agent' are specific and unambiguous.

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 description tells when to use multi_agents (set workflow_type to multi_agents) and warns that it is domain-gated. It also explains that for single_prompt agents, the prompt must be set via update_agent_prompt after creation. While it doesn't explicitly list all alternatives or when not to use, it provides clear context for distinguishing between agent types.

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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