phoenix-arize-setup
// Arize Phoenix observability platform setup for LLM debugging and evaluation
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updated:March 4, 2026
SKILL.mdreadonly
SKILL.md Frontmatter
namephoenix-arize-setup
descriptionArize Phoenix observability platform setup for LLM debugging and evaluation
allowed-toolsRead,Write,Edit,Bash,Glob,Grep
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
- Tracing: OpenTelemetry-based LLM traces
- Evals: LLM-as-judge evaluations
- Embeddings: Visualization and drift detection
- Retrieval: RAG quality analysis
- 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