Langfuse Instrumentation Setup

What problem does it solve?

This Skill helps developers correctly add Langfuse tracing to their Python applications, ensuring robust observability for LLM calls, tool usage, and overall pipeline execution.

Core Features & Use Cases

• Guided Setup: Validates your Langfuse environment and SDK installation.
• Code Instrumentation: Provides step-by-step instructions and templates for instrumenting various pipeline types (Simple, RAG, Agentic, Multi-model).
• Best Practices: Educates on common pitfalls like incorrect trace nesting and missing observation types.
• Use Case: You've built an agent that uses multiple LLM calls and tools. Use this Skill to ensure each LLM call is traced as a generation, each tool call as a tool, and the entire agent run is a single trace.

Quick Start

Use the instrumentation setup skill to add Langfuse tracing to your Python code.