build-test-suite

To build an AI agent test suite, use guided test design to select test set types and create scenarios based on vertical-specific templates. This structures expected behaviors into observable, binary-verifiable criteria for accurate metric scoring.

Creating test cases for customer support agents involves generating scenarios that cover happy paths, edge cases, and compliance requirements like escalation requests. Structured expected behaviors ensure consistent evaluation across various use cases.

Yes, you can automate the creation of multiple test cases and test sets. Bulk creation is facilitated through the Coval CLI or API, which manages the test case lifecycle and automates agent evaluation resources.

Designing expected behaviors for AI agent test scoring involves crafting observable, binary-verifiable criteria. This ensures the agent's performance is consistently measured against structured requirements during evaluation.

The Coval CLI is used to manage agent evaluation resources and the test case lifecycle. It facilitates the bulk creation of test sets and automates the creation of expected behaviors for metric scoring.

Structured test cases are needed when manually designing and organizing evaluations for AI agents. They ensure consistent evaluation across various use cases and compliance requirements, solving the challenge of unstructured manual testing.