Launch a specific Coval evaluation with explicit cases and execution bounds. Use when resources are already selected; for result analysis use quick-eval.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Use quick-eval when installed; it covers planning, bounded execution and the
result audit. Do not bypass its session budget when invoked from that workflow.
If this skill is installed alone, follow the same minimum launch contract:
options.test_case_ids,
iteration count, concurrency, metric IDs and a verified per-call duration
limit. Count cases × iterations × (1 + mutation count), per persona, including
any prior runs in the session. Concurrency does not reduce total cost.coval --agent runs launch --input-json @run.json. Check ok and
exit status. Save the returned run ID. If the response is ambiguous, inspect
matching runs before retrying; never blindly retry a launch.quick-eval; for launch-only, hand back the run without claiming quality.Use the current runs schema. Do not use
/eval/*, invent command flags, add schedules, change agent defaults, or rerun
unattended. A local plan is not a server-enforced spending cap.
아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
Analyze a Coval accent testing report from runs across different speaker accents. Use when a user provides a Coval report URL, report export, run IDs, screenshots, or metric summary and wants evidence-backed next steps such as prompt changes, STT/confirmation adjustments, accent-robust routing, or expanded accent coverage.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Analyze a Coval adversarial / red-team testing report and turn it into an agent-hardening plan. Use when a user provides a Coval report URL, report export, run IDs, screenshots, or a per-scenario scorecard from an adversarial sweep and wants evidence-backed next steps such as prompt/guardrail changes, refusal hardening, verification fixes, escalation routing, or expanded attack coverage.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Analyze a Coval audio-quality testing report from runs across different voice, speaking-style, volume, interruption, and background-noise scenarios. Use when a user provides a Coval report URL, report export, run IDs, screenshots, or metric summary and wants evidence-backed next steps such as prompt changes, tool handling fixes, STT/TTS adjustments, trace setup, or expanded audio-scenario coverage.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build or improve a Coval dashboard with metric visualizations backed by real data. Creates new dashboards from scratch or rebuilds existing ones by analyzing usage patterns, metric frequency, and data density. Use when user says "create a dashboard", "build a dashboard", "improve my dashboard", "add widgets", "visualize my metrics", "make a performance dashboard", or "dashboard for my runs".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build a compact Coval test set from product requirements, observed conversation failures or a coverage gap. Design realistic scenarios with separate expected behaviors, provenance and controlled voice/persona variation.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Select and configure a Coval metric for a concrete product criterion, choosing transcript, audio, trace or deterministic evidence and testing the result. Use for metric creation or scoring design, not for final human calibration.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.