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arize-experiment

Manage Arize AI experiments with CRUD operations and run analysis via the `ax` CLI.

42|7|Updated Mar 5, 2026
Search Tags:#mlops#llm evaluation#data analysis#a/b testing#experiment management#arize
One-click install
npx skills add https://github.com/Arize-ai/arize-skills --skill arize-experiment
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: arize-experiment
Source: https://github.com/Arize-ai/arize-skills/tree/main/skills/arize-experiment
Command: npx skills add https://github.com/Arize-ai/arize-skills --skill arize-experiment

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill streamlines the creation, execution, and analysis of machine learning experiments within the Arize platform, simplifying complex A/B testing and model evaluation workflows.

Core Features & Use Cases

  • Experiment Management: Create, list, get, and delete experiments.
  • Data Export/Import: Export experiment runs for analysis or import runs to create new experiments.
  • Workflow Automation: Automate the process of running experiments against datasets and comparing results.
  • Use Case: After deploying a new version of your LLM, use this skill to create an experiment comparing its performance against the previous version on a benchmark dataset, then analyze the results to identify regressions.

Quick Start

Use the arize-experiment skill to list all available experiments.

Frequently Asked Questions about arize-experiment

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I manage Arize AI experiments using the command line?▼

You can manage Arize AI experiments by using the `ax` CLI to perform CRUD operations, create runs against versioned datasets, and analyze results for your machine learning models.

Can I automate A/B testing workflows for LLM evaluation in Arize?▼

Yes, you can automate A/B testing workflows by creating experiments that run new LLM versions against benchmark datasets, then comparing results to identify regressions.

Do I need API credentials to run experiment management tasks?▼

Yes, you need the `ax` CLI installed and valid Arize API credentials to interact with the platform and execute experiment management tasks.

How do I export experiment runs for data analysis?▼

You can export experiment runs for data analysis or import existing runs to create new experiments, streamlining the evaluation of your machine learning models.

What is the best way to compare model performance against versioned datasets?▼

The best way to compare model performance is to create an experiment using the `ax` CLI, run it against versioned datasets, and analyze the exported results to detect regressions.

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