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Create or Update Target

create_or_update_target
Idempotent

Create or update an AI Target for evaluation simulations. Supports generation models, custom endpoints, and voice agents with templates, tools, and HTTP settings.

Instructions

Create or update a Target — the AI system you want to evaluate in a simulation.

    Calling create_or_update_target with the same name as an existing Target will
    **fully replace** its configuration — caller must re-specify all desired fields.
    Supported types: 'generation' (foundation model), 'custom_endpoint' (your own
    REST API), and 'voice' (voice-based targets reached by phone via Twilio or
    over SIP).

    **Cloning workflow**: this tool accepts the same key structure that `get_target`
    returns, so you can read an existing Target, change `name`, swap in real values
    for any field whose value is `"***REDACTED***"`, and pass the result here as
    kwargs. Calls that still contain the redaction sentinel are rejected with an
    error naming each offending path; the sentinel is never forwarded to the backend.

    Args:
        name: Unique name for this target.
        type: Target type — 'generation', 'custom_endpoint', or 'voice'.

        model_id: (generation targets) Foundation model ID, e.g. 'gpt-4o-mini'.
        temperature: (generation targets) Response randomness, default 0.
        system_prompt_template: (generation targets) System instructions; mustache
            syntax supported, e.g. '{scenario_input}'.
        user_prompt_template: (generation targets) User prompt template.
        dialog_template: (generation targets) Dialog formatting template.
        tools: (generation targets) Tool definitions for function calling.

        next_message_params: (custom_endpoint) Nested HTTP config for each
            conversation turn. Required keys: 'url', 'method'. Optional:
            'headers', 'body', 'status_code', 'response_message_path',
            'response_session_id_path', 'response_tool_calls_path'.
            All response path values MUST use dot-path notation starting with
            'response.' — e.g., 'response.message', 'response.choices[0].message.content',
            'response.choices[0].tool_calls'. Never use bare property names.
            For SSE/streaming endpoints, include a 'streaming' object with:
              - 'stop': array of stop conditions (OR semantics — any match ends
                the stream). Each has 'value' (required) and optional 'path'
                (dot-path into JSON chunk). Without 'path', matches raw SSE data.
              - 'select': array of select conditions (AND semantics — all must
                match for a chunk's content to be extracted). Each requires
                'path' and 'value'.
            When streaming, set response_message_path to the chunk field
            (e.g., 'response.choices[0].delta.content').
        start_session_params: (custom_endpoint, optional) Nested HTTP config to
            initialise a session. Required key: 'url'. Optional: 'method',
            'headers', 'body', 'status_code', 'response_session_id_path'
            (dot-path starting with 'response.', e.g. 'response.id'),
            'response_message_path'. Supports 'streaming' object (same
            structure as next_message_params.streaming).
        end_session_params: (custom_endpoint, optional) Nested HTTP config to
            close a session after the last turn.
        auth_params: (custom_endpoint, optional) Token-based authorization config.
            Required keys when provided: 'url', 'method', 'response_access_token_path'
            (dot-path starting with 'response.', e.g. 'response.access_token').
            Optional: 'headers', 'body', 'status_code'.
        sensitive_fields: (custom_endpoint, optional) List of dot-path strings for
            secret fields within auth_params (e.g., 'auth_params.body.client_id').
            The MCP auto-generates entries for top-level auth_params keys; use this
            for deeper paths. To remove auth from an existing target, call
            create_or_update_target again without auth_params.
        max_parallel_requests: (custom_endpoint, twilio) Concurrency limit. This is
            the same setting the Okareo web UI labels "max concurrency".

        edge_type: (voice targets) How Okareo reaches the voice agent —
            'twilio' (dial a phone number) or 'sip' (call a SIP URI).

        to_phone_number: (voice twilio) Destination phone number (required).
        account_sid: (voice twilio, custom only) Twilio account SID. If provided,
            auth_token and from_phone_number are also required (all-or-nothing).
            Omit for generic Twilio targets using Okareo's managed integration.
        auth_token: (voice twilio, custom only) Twilio auth token. Required with
            account_sid and from_phone_number.
        from_phone_number: (voice twilio, custom only) Caller phone number. Required
            with account_sid and auth_token.

        sip_uri: (voice sip) Destination SIP URI (required), e.g.
            "sip:agent@your-domain.example.com". Use this to test any voice
            agent reachable over SIP — for example one fronted by Daily,
            Vapi, LiveKit, or a SIP trunk.
        sip_username: (voice sip, optional) SIP authentication username.
        sip_password: (voice sip, optional) SIP authentication password
            (stored as a sensitive field).
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
typeYes
toolsNo
sip_uriNo
model_idNo
edge_typeNo
auth_tokenNo
account_sidNo
auth_paramsNo
temperatureNo
sip_passwordNo
sip_usernameNo
dialog_templateNo
to_phone_numberNo
sensitive_fieldsNo
from_phone_numberNo
end_session_paramsNo
next_message_paramsNo
start_session_paramsNo
user_prompt_templateNo
max_parallel_requestsNo
system_prompt_templateNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Beyond the annotations (idempotentHint=true, destructiveHint=false), the description discloses critical behaviors: 'fully replace its configuration — caller must re-specify all desired fields', redaction sentinel rejection, auto-generation of sensitive fields, and the all-or-nothing rule for Twilio auth. These details significantly exceed what the annotations alone convey.

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 long but justified by the tool's complexity (22 parameters, three target types). It uses clear sectioning (type-specific parameter groups) and front-loads the core purpose and replacement warning. A few sentences, like the streaming stop/select details, are dense but necessary. Very little is wasted.

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?

For a tool with 22 parameters, 0% schema descriptions, and a rich output schema, the description is fully complete. It covers all parameter categories, type-specific configurations, redaction handling, replacement semantics, and auth removal. The presence of an output schema means return-value documentation is unnecessary, and the description fills all other gaps.

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

Parameters5/5

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

With 0% schema coverage, the description carries the full burden and excels: every one of the 22 parameters is documented with type-specific context, requiredness, defaults, examples, and nested structures (e.g., next_message_params with dot-path rules and streaming stop/select semantics). This adds enormous meaning beyond the bare schema property names.

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 opens with a specific verb+resource: 'Create or update a Target — the AI system you want to evaluate in a simulation.' It clearly distinguishes from sibling tools like get_target, list_targets, and delete_target by covering both creation and update in one operation. The title and description align perfectly.

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 provides clear usage context, including the cloning workflow ('this tool accepts the same key structure that `get_target` returns') and the replacement behavior when reusing a name. It also explains type-specific requirements (generation, custom_endpoint, voice) and how to remove auth. However, it does not explicitly state when to use an alternative tool, instead relying on the context of the cloning workflow.

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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