Coval
Official@coval-ai
Offers comprehensive evaluation, observability, and adversarial testing infrastructure for voice and text-based conversational systems.
Agent Skills by Coval
Showing 28 vetted skills indexed across 1 GitHub repositories.
coval-aiconfigure-metrics
Configure and attach evaluation metrics to AI agents in Coval.
coval-aidebug-traces
Diagnose OpenTelemetry trace ingestion failures and correlation errors in Coval workflows.
coval-aiconfigure-trace-metrics
Configure trace-based metrics and LLM judges from OpenTelemetry spans.
coval-aioptimize-trace-observability
Add missing STT, LLM, TTS, and tool spans to OpenTelemetry traces.
coval-aisetup-tracing
Configure OpenTelemetry tracing for AI agents in the Coval platform.
coval-aidistill-test-set
Distill large datasets into compact, failure-weighted test suites for AI evaluation.
coval-aihuggingface-import
Import HuggingFace datasets into structured CSV files for Coval.
coval-aibuild-test-suite
Create test sets and test cases for AI agent evaluation via the Coval CLI.
coval-aimigrate-bluejay
Migrate agents, personas, metrics, and test schedules from Bluejay to Coval.
coval-aisetup-agent
Configure and connect AI agents to the Coval evaluation platform.
coval-aipersonas-from-artifacts
Derive simulation personas from backend payloads, UI screenshots, and user transcripts.
coval-aidesign-persona
Create simulation personas for AI agent testing via the Coval CLI.
coval-aibuild-dashboard
Construct Coval evaluation dashboards from recent run data and metric frequency.
coval-aiget-results
Retrieves and parses simulation results from Coval evaluation platform via CLI.
coval-aidownload-audio
Download individual or bulk audio files from Coval voice simulations via the Coval CLI.
coval-aicoval-resources
Reference Coval platform data models, resource hierarchies, and API interaction patterns.
coval-aiwatch-run
Monitors Coval evaluation runs via CLI and API polling for live progress and final results.
coval-airun-accent-testing
Create accent-specific personas and launch synchronized voice agent evaluation runs.
coval-airun-audio-quality-testing
Automate multi-persona audio-quality evaluation runs for voice agents.
coval-airun-adversarial-testing
Run adversarial red-team testing sweeps against AI agents using the Coval CLI.
coval-aiquick-eval
Orchestrate AI agent evaluation runs and aggregate results via the Coval CLI.
coval-ailaunch-run
Orchestrate AI agent evaluation runs via the Coval CLI.
coval-aionboard
Configure and execute AI evaluation workflows on the Coval platform.
coval-aiconsult-sofia
Delegate read-only diagnostic tasks to the Coval Sofia expert system.
Frequently Asked Questions About Coval
FAQPage SchemaWhat specific tasks can engineers perform using Coval?▼
Engineers can configure OpenTelemetry tracing, distill large datasets into failure-weighted test suites, execute adversarial red-team sweeps, and analyze performance reports for voice and text-based systems. The platform enables granular evaluation of accent-specific personas and audio quality metrics to identify regressions.
Which technical personas benefit most from this platform?▼
Coval is designed for machine learning engineers, quality assurance specialists, and voice interaction designers. These professionals use the platform to validate conversational performance, monitor trace-based metrics, and refine evaluation prompts based on discrepancies between human and judge annotations.
What are the prerequisites for integrating Coval?▼
Integration requires an existing OpenTelemetry-compliant environment to capture spans and traces. Users must configure their agents to emit telemetry data, which is then ingested by the platform to enable metric correlation, test suite execution, and diagnostic reporting.