Cekura Metric Design

Purpose

Guide the creation of effective Cekura metrics that accurately evaluate AI voice agent call quality. Metrics measure call quality after the fact by evaluating transcripts against defined criteria. Each metric targets a specific workflow or KPI that needs tracking per call.

Performing Platform Actions

When this skill suggests creating, listing, updating, or evaluating something on Cekura, prefer using available platform tools over describing API calls or dashboard steps. In Claude Code with the Cekura plugin installed, these tools are auto-configured and handle authentication, parameter validation, and error handling for you. Fall back to direct API endpoints or dashboard guidance only when no tools are available in the current session.

Core Terminology

• Main agent: The client's AI voice agent being tested
• Testing agent: Cekura's simulated caller that exercises the main agent
• Metric: A post-call evaluation that scores a transcript
• Evaluator/Scenario: A test case that simulates a caller (separate concept — see cekura-eval-design skill)

The Metric Creation Workflow