| name | design-persona |
| description | Design and create a simulation persona for testing an AI agent. Guides through use case selection, voice and language configuration, behavior prompt crafting, and interruption calibration. Use when user says "create a persona", "design a persona", "set up a test persona", "configure simulation persona", or "build a caller profile". |
| argument-hint | [use-case-or-agent-name] |
Design Persona
Guide the user through designing and creating a simulation persona using the coval CLI. Follow the phases below in order, asking questions at each step.
If $ARGUMENTS contains a use case (e.g. "insurance_claims", "customer_support") or agent name, use it to skip or pre-fill relevant questions.
Phase 0: Preflight + Inventory
Step 1: Check authentication
coval whoami
If not authenticated, guide the user:
coval login
This prompts for an API key. Get one at https://app.coval.dev/settings (Organization > Manage > API Keys).
If the user doesn't have a Coval account, direct them to https://coval.dev to sign up.
Step 2: Inventory existing resources
Run these in parallel:
coval personas list --format json
coval agents list --format json
Decision matrix:
- Has personas → present them as a numbered list: "You already have these personas. Want to reuse one, duplicate and modify, or create new?"
- No personas → proceed to Phase 1
- If
$ARGUMENTS matches an existing agent name, pre-select that agent for Phase 1
Phase 1: Agent Context
Ask: "Which agent will this persona test?"
- If agents exist, present them as a numbered list to pick from
- If no agents exist, say: "No agents found. You can still create a persona — just tell me what type of agent it will test (voice, outbound-voice, chat, sms, websocket)."
If the user selects an agent, fetch its details:
coval agents get <agent_id> --format json
Extract from the response:
- Agent type (
model_type) — determines whether voice settings are relevant and conversation initiator direction
- Agent name — for context in prompts
- Agent prompt (if available) — helps craft a better persona
Key type mappings:
MODEL_TYPE_VOICE / MODEL_TYPE_OUTBOUND_VOICE → voice settings matter, conversation initiator depends on direction
MODEL_TYPE_CHAT / MODEL_TYPE_WEBSOCKET / MODEL_TYPE_API / MODEL_TYPE_ENDPOINT → voice settings are defaults only (won't affect simulation)
Phase 2: Use Case Detection
Ask: "What does your agent do?"
Present the options:
- customer_support — Customer Support
- scheduling_booking — Scheduling & Booking
- sales — Sales
- insurance_claims — Insurance Claims
- healthcare_intake — Healthcare Intake
- restaurant_orders — Restaurant Orders
- debt_collection — Debt Collection
- it_helpdesk — IT Helpdesk
- other — Other (describe it)
Load references/persona-templates.md and select the template matching the chosen use case.
Present the template as a starting point:
Here's a starting persona for <use case>:
Name: <template name>
Voice: <voice>
Language: en-US
Background: <background>
Wait: <wait seconds>s
Prompt: "<template description>"
Ask: "Use this as a starting point? (yes / customize name / start from scratch)"
Phase 3: Voice + Language
Load references/voice-options.md for available options.
Ask these questions:
-
"What language should the persona speak?"
- en-US — English (US)
- es-ES — Spanish (Spain)
- fr-FR — French (France)
- de-DE — German
- pt-BR — Portuguese (Brazil)
- ja-JP — Japanese
-
"Voice preference?"
- Female: aria (clear, professional)
- Male: callum (clear, professional)
For non-voice agents (chat, websocket, API), explain: "Since your agent is text-based, voice and language are stored as defaults but won't affect the simulation."
Phase 4: Environment + Behavior
Background Sound
Present options with recommendations based on the use case:
| Value | Description | Recommended For |
|---|
| quiet | No background noise | Medical, legal, financial calls |
| office | Office ambient noise | Corporate, business, IT support |
| cafe | Restaurant/cafe noise | Casual, restaurant scenarios |
| airport | Airport/travel noise | Travel-related agents |
Say: "Based on your use case, I'd recommend . Use that or pick another?"
Wait Seconds
How long the persona waits before speaking after connection:
| Value | Style | Best For |
|---|
| 0.3 | Fast responder | Restaurant orders, fast-paced interactions |
| 0.5 | Standard | Most inbound call scenarios |
| 1.0 | Slow / deliberate | Outbound calls, debt collection, elderly callers |
Say: "The template uses