phoenix-evals

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Build and run evaluators for AI/LLM applications using Phoenix.

Arize-ai By Arize-ai schedule Updated 2/26/2026

name: phoenix-evals description: Build and run evaluators for AI/LLM applications using Phoenix. license: Apache-2.0 metadata: author: oss@arize.com version: "1.0.0" languages: Python, TypeScript

Phoenix Evals

Build evaluators for AI/LLM applications. Code first, LLM for nuance, validate against humans.

Quick Reference

Task Files
Setup setup-python, setup-typescript
Build code evaluator evaluators-code-{python|typescript}
Build LLM evaluator evaluators-llm-{python|typescript}, evaluators-custom-templates
Batch evaluate DataFrame evaluate-dataframe-python
Run experiment experiments-running-{python|typescript}
Create dataset experiments-datasets-{python|typescript}
Validate evaluator validation, validation-calibration-{python|typescript}
Analyze errors error-analysis, axial-coding
RAG evals evaluators-rag
Avoid common mistakes common-mistakes-python
Production production-overview, production-guardrails

Workflows

Starting Fresh: observe-tracing-setuperror-analysisaxial-codingevaluators-overview

Building Evaluator: fundamentalscommon-mistakes-pythonevaluators-{code\|llm}-{python\|typescript}validation-calibration-{python\|typescript}

RAG Systems: evaluators-ragevaluators-code-* (retrieval) → evaluators-llm-* (faithfulness)

Production: production-overviewproduction-guardrailsproduction-continuous

Rule Categories

Prefix Description
fundamentals-* Types, scores, anti-patterns
observe-* Tracing, sampling
error-analysis-* Finding failures
axial-coding-* Categorizing failures
evaluators-* Code, LLM, RAG evaluators
experiments-* Datasets, running experiments
validation-* Calibrating judges
production-* CI/CD, monitoring

Key Principles

Principle Action
Error analysis first Can't automate what you haven't observed
Custom > generic Build from your failures
Code first Deterministic before LLM
Validate judges >80% TPR/TNR
Binary > Likert Pass/fail, not 1-5
Install via CLI
npx skills add https://github.com/Arize-ai/twitter-to-newsletter --skill phoenix-evals
Repository Details
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article Path SKILL.md
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