Validate AI agent prompts and workflows with unit, scenario, and evaluation tests.
npx skills add https://github.com/JNZader/javi-ai --skill agent-testing
Please help me install this Agent Skill. Skill: agent-testing Source: https://github.com/JNZader/javi-ai/tree/main/own/skills/agent-testing Command: npx skills add https://github.com/JNZader/javi-ai --skill agent-testing
Automates robust testing of AI agents by providing a pyramid of tests (unit, scenario, and evaluation) to catch prompts and workflow issues early.
Install and run tests locally with the provided CLI, then integrate into your CI pipeline.
High-intent search queries and answers about installing and using this skill.
You can test AI agent prompts and workflows by applying a pyramid of tests, including unit tests with mocked LLMs, scenario tests for state transitions, and evaluation suites to catch regressions early and ensure safe deployments.
Automating AI agent testing in a CI/CD pipeline is best handled by integrating cost-aware evaluation suites and scenario fixtures, enabling automated checks across local development, pull requests, and nightly CI runs.
Scenario tests verify end-to-end agent workflows by checking state transitions and handoffs using predefined fixtures, ensuring the complete execution path behaves as expected during local development and CI checks.
Yes, you need mocked LLMs for unit testing AI agents to validate prompt rendering and tool usage quickly and cost-effectively without making actual API calls, forming the base of the testing pyramid.
Yes, you can run cost-aware evaluation suites for nightly CI checks to score outputs, detect regressions, and ensure safe deployments while monitoring the expenses associated with live LLM interactions.
Using a testing pyramid for AI agent validation enforces a scalable structure of mock-based unit tests, scenario fixtures, and evaluation suites, catching prompt and workflow issues early while balancing speed and cost.
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