What problem does it solve? Voice agent tests often fail silently because voice-layer behaviors like accents, interruptions, background noise, and idle timing are written into evaluator instructions where they have no effect. This Skill routes each request to the correct layer and guides choosing, forking, creating, and patching Cekura personalities so the simulated caller actually sounds and behaves as intended. ## Core Features & Use Cases - Personality vs. Evaluator Routing: Classifies each request by duration — call-wide traits go to the personality, one-moment behaviors go to evaluator instructions, and post-call judgements go to metrics. - Accent and Voice Resolution: Resolves accent requests to concrete voice selections using the ElevenLabs and Cartesia voice catalogs, since accent is a read-only label derived from voice_id and provider. - Choose, Fork, Create Workflow: Prefers existing personalities, forks shared predefined ones before patching, and creates from scratch only when nothing fits, with read-back verification of derived accent and gender. - Use Case: A user says the testing agent keeps asking "are you still there?" mid-test. The Skill identifies the default 10-second idle timeout as the cause and raises message_plan.idle_timeout_seconds on an org-owned personality. ## Quick Start Ask the assistant to create a Cekura personality with an Indian-accented caller who interrupts frequently for your voice agent test suite.