Your API key for authentication.
Body
The ID of the historical call to generate a scenario from. The call transcript will be analyzed by AI to extract a realistic test scenario.
The pathway to bind the generated scenario to. Either pathway_id or persona_id is required.
The persona to bind the generated scenario to. Either pathway_id or persona_id is required.
Response
The response contains the generated scenario data. This data is not yet saved — it is returned so you can review and use it to create a scenario.
Sensitive data such as phone numbers, webhook URLs, and API keys is automatically stripped from the generated request_data.
An AI-generated name summarizing the scenario.
An AI-generated description of what the scenario tests based on the call transcript.
The inferred category for the scenario (e.g., HAPPY_PATH, EDGE_CASE, ANGRY_CALLER).
An AI-generated prompt that instructs the simulated caller to replicate the behavior observed in the original call.
A name for the simulated caller persona derived from the call.
The pathway the scenario is bound to (if provided).
The persona the scenario is bound to (if provided).
Request data extracted from the call with sensitive fields automatically removed.
{
"name": "Inbound Appointment Booking - Returning Customer",
"description": "Simulates a returning customer calling to book a follow-up appointment. The caller provides their name and preferred time slot, and expects confirmation.",
"category": "HAPPY_PATH",
"tester_persona_prompt": "You are Sarah Chen, a returning customer. You previously visited for a consultation and want to book a follow-up appointment. You prefer afternoons, ideally next Thursday at 2 PM. Be polite but firm about your preferred time. If that slot is unavailable, accept an alternative within the same week.",
"tester_persona_name": "Sarah Chen",
"pathway_id": "pw_abc123",
"persona_id": null,
"request_data": {
"customer_name": "Sarah Chen",
"account_id": "cust_92841",
"appointment_type": "follow_up"
}
}