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update_agent_config

Modify an agent's configuration fields (name, language, voice, model, variables, etc.) with partial updates. For versioned agents, changes are saved as a draft.

Instructions

Update an agent's configuration (name, language, first message, voice settings, model, variables, etc.). Only provided fields are updated. To update the agent's prompt/instructions, use update_agent_prompt instead. For versioned agents, changes are saved as a draft — use publish_draft to make them live, or test the draft first via make_call with the draft's version_id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoNew agent name
agent_idYesThe agent ID to update
languageNoLanguage configuration
slm_modelNoInference LLM model for the agent
descriptionNoAgent description
synthesizerNoVoice synthesizer configuration
first_messageNoFirst message when call starts (max 500 chars)
global_promptNoGlobal system prompt for the agent (max 4000 chars). This is separate from the workflow prompt updated via update_agent_prompt.
background_soundNoBackground sound option
denoising_configNoAudio denoising configuration
redaction_configNoRedaction configuration
transcriber_typeNoSpeech-to-text (STT) transcriber. 'pulse' is the current default and recommended option (widest language support). 'pulse-legacy' is the older model, deprecated and only available to allowlisted organizations — prefer 'pulse'. Note: 'gpt-realtime'/'gpt-realtime-mini' transcribers are set automatically when using a speech-to-speech LLM model and should not be set here.
default_variablesNoDefault variables for the agent prompt. Example: { prospect_name: 'Default', company: 'Acme' }
knowledge_base_idNoKnowledge base ID to attach to the agent
smart_turn_configNoSmart turn detection configuration
speech_formattingNoEnable speech formatting
allow_inbound_callNoWhether to allow inbound calls
enable_style_guideNoEnable conversational style guide
allow_interruptionsNoWhether to allow user interruptions
pronunciation_dictsNoCustom pronunciation dictionary
voicemail_detectionNoVoicemail detection configuration
telephony_product_idsNoTelephony product IDs (see get_phone_numbers) to assign to this agent. Takes effect IMMEDIATELY — number assignment is agent metadata, not versioned config, so no draft/publish is involved. Replaces the agent's current numbers; assigning a number already attached to another agent moves it. Pass [] to unassign all.
session_timeout_configNoSession timeout configuration
voice_detection_configNoVoice activity detection configuration
call_disposition_configNoCall disposition configuration prompt
llm_idle_timeout_configNoLLM idle timeout configuration per call type
interruption_backoff_timerNoDelay in seconds before agent resumes after interruption (0-10)
wait_for_user_to_speak_firstNoWait for user to speak before agent starts
mute_user_until_first_bot_responseNoMute user audio until the bot sends its first response
Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses partial update behavior, draft semantics, immediate effect of phone number assignment, and character limits. It could additionally mention behavior for non-versioned agents.

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?

The description is three sentences, front-loaded with purpose and followed by usage guidelines and behavioral notes. Every sentence adds value, no redundancy.

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?

Given the tool's complexity (29 params, nested objects, no output schema), the description covers the main aspects: what fields can be updated, key exceptions, and workflow. It could be slightly more explicit about non-versioned agent behavior.

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%, but the description adds meaningful context for key parameters: telephony_product_ids (immediate effect), global_prompt (separate from update_agent_prompt), and transcriber_type (note about gpt-realtime). This goes beyond the schema's descriptions.

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 the verb 'Update' and the resource 'agent's configuration', listing the main categories of fields. It explicitly distinguishes from the sibling tool update_agent_prompt, making the purpose unambiguous.

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

Usage Guidelines5/5

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

The description provides explicit usage guidance: when to use update_agent_prompt instead for prompt updates, and explains the draft/publish workflow for versioned agents. It also notes the immediate effect of telephony_product_ids.

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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