# Phoenix Arize Setup

> Phoenix Arize Setup is an Agent Skill for devops & security published in the a5c-ai/babysitter repository on GitHub: a SKILL.md instruction file an AI agent can load to do this task.

Arize Phoenix observability platform setup for LLM debugging and evaluation

- Skill name: `phoenix-arize-setup`
- Category: [DevOps & Security](https://www.openparable.com/skill/devops-security/1)
- Source: https://github.com/a5c-ai/babysitter/blob/HEAD/library/specializations/ai-agents-conversational/skills/phoenix-arize-setup/SKILL.md
- Repository: a5c-ai/babysitter (1,548 GitHub stars when collected)

## SKILL.md

# Phoenix Arize Setup Skill

## Capabilities

- Set up Phoenix local server
- Configure tracing instrumentation
- Design evaluation experiments
- Implement embedding visualizations
- Set up retrieval analysis
- Create custom evaluations with LLM-as-judge

## Target Processes

- llm-observability-monitoring
- agent-evaluation-framework

## Implementation Details

### Core Features

1. **Tracing**: OpenTelemetry-based LLM traces
2. **Evals**: LLM-as-judge evaluations
3. **Embeddings**: Visualization and drift detection
4. **Retrieval**: RAG quality analysis
5. **Datasets**: Experiment management

### Instrumentation

- OpenAI auto-instrumentation
- LangChain instrumentation
- LlamaIndex instrumentation
- Custom span creation

### Configuration Options

- Phoenix server setup
- Trace sampling
- Evaluation metrics
- Embedding models
- Export settings

### Best Practices

- Comprehensive instrumentation
- Regular evaluation runs
- Monitor embedding drift
- Analyze retrieval quality

### Dependencies

- arize-phoenix
- openinference-instrumentation-openai

---

Source: https://www.openparable.com/skill/devops-security/phoenix-arize-setup (OpenParable). Cite the canonical URL above.