Use when the user asks to "create an evaluator", "create evals", "create a scenario", "write a test scenario", "design a test case", "test my agent", "build eval coverage", "plan a test suite", "create red team tests", "set up test profiles", "configure conditional actions", "write a conditional action evaluator", "build a deterministic test", "design an IVR test", "IVR navigation test", "write a unit test for a voice agent", "build a regression test", "scripted scenario", "scripted voice test", "structured evaluator", "exact flow test", "sequential conditions", "fixed sequence test", or "run evals". Covers individual evaluator design, suite coverage strategy, test profiles, mock-tool data design, conditional actions (deterministic / unit test / regression / IVR navigation flows), and best practices for workflow / red-team / edge-case / deterministic test types.
Use when the user asks to "create a main agent", "set up a main agent", "add my main agent to Cekura", "configure my main agent", "connect my main agent", "set up mock tools", "add tools to my agent", "upload knowledge base", "configure integration", "connect VAPI", "connect Retell", "connect LiveKit", "connect ElevenLabs", "add dynamic variables", or needs to onboard a voice AI agent onto the Cekura platform. Covers the full agent setup flow: project selection, provider selection, basics and connection type, description, main agent creation, mock tools, knowledge base, dynamic variables, and advanced configuration.
Use to close the loop on agent quality — turn a failure signal into a verified fix. Triggers: "improve my agent", "self-improving agent", "auto-tune / iterate on my prompt", "fix my agent from test results", "optimize my prompt based on failures", "rewrite my prompt". ALSO for production-call bug fixing: "fix this prod call issue", "debug and fix call ID", "reproduce this production bug", "regression test before a PR", "fix the bug from this call and open a PR". Works across VAPI, ElevenLabs, and self-hosted agents, and across three fix surfaces — prompt, tool config, and (self-hosted) owned source code, including infra-flavored / forked-SDK bugs, which are reproduced and validated on Cekura (never a code test) and, for source edits, shipped as a PR.
Use when the user says "get started with Cekura", "set up Cekura", "onboard to Cekura", "I'm new to Cekura", "help me set up my agent", "how do I use Cekura", "walk me through Cekura", "configure my project", "first time using Cekura", or needs guidance on initial platform setup. Covers two onboarding paths: **testing** (default — build evaluators and run simulated calls) and **observability** (ingest production call logs and evaluate them).
Use when the user asks to "create a metric", "write a metric", "design a metric", "build a metric for", "evaluate agent performance", "measure call quality", "track a KPI", "add a workflow metric", "improve my metric", "fix a metric", "debug metric results", "set up quality scoring", or "what metrics do I need". Also relevant when discussing LLM judge prompts, custom code metrics, evaluation triggers, VALID_SKIP patterns, section extraction, or metric best practices for Cekura voice AI agents. Covers both creating new metrics and reviewing, iterating on, or troubleshooting existing ones.
Use when the user asks to "improve a metric", "run labs", "leave feedback on a metric", "add to labs", "fix metric accuracy", "review metric results", "find misaligned metrics", or "iterate on metric quality". Covers the metric improvement cycle, the feedback workflow, and the labs pipeline used to refine metric accuracy over time.
Use when the user asks "what predefined metrics are available", "which built-in metrics should I use", "what does CSAT measure", "how does hallucination detection work", "what's the difference between Interruption Score and AI Interrupting User", "which metrics are free", "which metrics need audio", "configure silence threshold", "set up sentiment metric", or any question about Cekura's out-of-the-box metrics. Covers the full catalog of predefined metrics — what each does, costs, constraints, configuration options, and when to use each one.
Turn a set of flagged production call logs into evaluator scenarios for a Cekura agent — cluster the failures into reproducible modes and create one scenario per cluster. Use when the user says "create scenarios from failed calls", "build evaluators for prod failures", "turn call logs into scenarios", "simulate the failures we saw in prod", "replay these bad calls as tests", "regression-test the agent on prod issues", or hands over a set of flagged call IDs to harden the agent against. The flagged set normally comes from `cekura-internal:flag-call-log-failures` (which triages recent calls against specified issues/goals and applies attribution rules); if the user hasn't triaged yet, run that skill first. This skill takes the flagged calls as given — it does NOT re-mine or re-triage — clusters by failure mode, drafts one scenario per cluster, and optionally creates them via the scenarios API (or the dedicated call-logs → scenarios endpoint). Also supports a single-call fast path: given one specific call log ID