智能体工作流

arize-experiment

arize-ai/arize-skills

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.

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安装命令

npx skills add https://github.com/arize-ai/arize-skills --skill arize-experiment

SKILL.md

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.