# arize-experiment

> Claude/Codex skill by [@arize-ai](https://omgskills.com/library/arize-ai/index.md) · 65 stars · Updated 2026-10-16

Creates, runs, and analyzes Arize experiments for evaluating and comparing model performance. Covers experiment CRUD, exporting runs, comparing results, and evaluation workflows using the ax CLI. Use when the user mentions create experiment, run experiment, compare models, model performance, evaluate AI, experiment results, benchmark, A/B test models, or measure accuracy.

Tags: agent-skills, ai-agents, ai-observability, arize, claude-code, codex, cursor, datasets, experiments, llmops, tracing

## Install

```sh
git clone https://github.com/Arize-ai/arize-skills /tmp/arize-skills && ln -s /tmp/arize-skills/skills/arize-experiment ~/.claude/skills/arize-experiment
```

## From README

Arize Experiment Skill SPACE — --space flags accept a space name (e.g., my-workspace) or a base64 space ID (e.g., U3BhY2U6...). Find yours with ax spaces list. Concepts Experiment = a named evaluation run against a specific dataset version, containing one run per example Experiment Run = the result of processing one dataset example -- includes the model output, optional evaluations, and optional metadata Dataset = a versioned collection of examples; every experiment is tied to a dataset and a specific dataset version Evaluation = a named metric attached to a run (e.g., correctness, relevance), with optional label, score, and explanation The typical flow: export a dataset → process each example → collect outputs and evaluations → create an experiment with the runs. Prerequisites Proceed directly with the task — run the ax command you need. Do NOT check versions, env vars, or profiles upfront.

## Links

- HTML page: https://omgskills.com/skills/arize-ai/arize-skills/arize-experiment/
- GitHub: https://github.com/Arize-ai/arize-skills
- Author: [@arize-ai](https://omgskills.com/library/arize-ai/index.md)

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