Phoenix arize setup

Skill a5c-ai/babysitter/library/specializations/ai-agents-conversational/skills/phoenix-arize-setup

Babysitter enforces obedience on agentic workforces and enables them to manage extremely complex tasks and workflows through deterministic, hallucination-free self-orchestration

Install

npx -y skills add a5c-ai/babysitter --skill phoenix-arize-setup

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What its author says it does

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Arize Phoenix observability platform setup for LLM debugging and evaluation

SKILL.md

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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