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arize-experiment

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.

skills/arize-experiment/SKILL.md

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# Arize Experiment Skill

> **`SPACE`** — All `--space` flags and the `ARIZE_SPACE` env var 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