Orchestrate AI agent evaluation runs and aggregate results via the Coval CLI.
npx skills add https://github.com/coval-ai/coval-external-skills --skill quick-eval
Please help me install this Agent Skill. Skill: quick-eval Source: https://github.com/coval-ai/coval-external-skills/tree/main/skills/runs/quick-eval Command: npx skills add https://github.com/coval-ai/coval-external-skills --skill quick-eval
This skill removes the friction from the evaluation lifecycle by automating the orchestration of agent runs, progress monitoring, and result summarization.
Use the quick-eval skill to launch an evaluation for the current agent and test set and provide a summary of the results.
High-intent search queries and answers about installing and using this skill.
You can automate AI agent evaluation by launching runs that coordinate agents, personas, and test sets in a single workflow, tracking progress, and retrieving simulation results automatically upon completion.
End-to-end agent testing works by automating the execution of evaluation runs, monitoring their progress in real-time, and aggregating the simulation results into a summary report.
Yes, you need the Coval CLI installed to interface with the Coval API for managing evaluation runs and retrieving simulation data.
Yes, the evaluation workflow tracks run progress in real-time and retrieves simulation results automatically upon completion to summarize pass/fail metrics.
After launching an evaluation run and waiting for completion, the workflow automatically retrieves simulation results and generates a summary report of pass/fail metrics.
The best way is to launch an evaluation run for the new agent version, wait for the simulation results, and generate a summary report of pass/fail metrics.
coval-aiOrchestrate AI agent evaluation runs via the Coval CLI.
eusouwillnunesValidate agent-produced checklists against predefined QA criteria with pass/fail results.
jonnabioAutomate CI/CD pipeline design and configuration for software workflows.
bugrabilgeDesign benchmark test suites for evaluating LLM agent reliability.
