---
title: "Regression test LLM apps and agents with metrics, traces, and eval suites using DeepEval"
description: "Run repeatable eval suites against prompts, RAG pipelines, and agents so regressions surface before release."
verification: "listed"
source: "https://github.com/confident-ai/deepeval"
author: "Confident AI"
publisher_type: "organization"
category:
  - "Code Quality & Review"
framework:
  - "Multi-Framework"
tool_ecosystem:
  github_repo: "confident-ai/deepeval"
  github_stars: 14815
  npm_package: "deepeval"
  npm_weekly_downloads: 1263
---

# Regression test LLM apps and agents with metrics, traces, and eval suites using DeepEval

Run repeatable eval suites against prompts, RAG pipelines, and agents so regressions surface before release.

## Prerequisites

Python or Node.js, API access to an LLM judge or compatible local models, CI optional

## Installation

Choose whichever fits your setup:

1. Copy this skill folder into your local skills directory.
2. Clone the repo and symlink or copy the skill into your agent workspace.
3. Add the repo as a git submodule if you manage shared skills centrally.
4. Install it through your internal provisioning or packaging workflow.
5. Download the folder directly from GitHub and place it in your skills collection.

Install command or upstream instructions:

```
Install with `pip install -U deepeval` for the primary Python workflow, or use the official `deepeval` npm package when you need the JavaScript path. Then define eval cases and metrics in code and run the suite locally or in CI.
```

## Documentation

- https://docs.confident-ai.com/docs/getting-started

## Source

- [Agent Skill Exchange](https://agentskillexchange.com/skills/regression-test-llm-apps-and-agents-with-metrics-traces-and-eval-suites-using-deepeval/)