phoenix-observability
CommunityAI Observability & Evaluation
AuthorDoanNgocCuong
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill streamlines the debugging, evaluation, and monitoring of AI and LLM applications by providing detailed tracing and performance insights.
Core Features & Use Cases
- LLM Tracing: Visualize the execution flow of LLM calls, including prompts, responses, and intermediate steps.
- Model Evaluation: Run systematic evaluations on datasets to assess model performance against various metrics.
- Real-time Monitoring: Track production AI systems for performance degradation and anomalies.
- Use Case: When a user reports an unexpected response from your chatbot, use this Skill to trace the specific conversation, identify the problematic LLM call, and analyze the prompt and parameters that led to the issue.
Quick Start
Use the phoenix observability skill to launch the Phoenix UI server.
Dependency Matrix
Required Modules
arize-phoenix
Components
references
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: phoenix-observability Download link: https://github.com/DoanNgocCuong/continuous-training-pipeline_T3_2026/archive/main.zip#phoenix-observability Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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