How do I trigger this skill in Claude Code?

You can trigger it using phrases like 'langfuse hello world', 'langfuse quick start', or 'first langfuse trace'.

Why is my trace not appearing in the Langfuse dashboard?

Common causes include missing API credentials or failing to flush the data. Ensure you call sdk.shutdown() in v4+ or langfuse.flushAsync() in v3 before the process exits.

What is the primary purpose of the Langfuse Hello World skill?

It provides a minimal, working implementation of Langfuse tracing to help developers test their setup and learn basic observability patterns for LLM applications.

Does this skill support both TypeScript and Python?

Yes, the skill includes code examples for the latest Langfuse TypeScript SDK (including OpenTelemetry support) and Python decorator-based instrumentation.

Langfuse Quick Start

Name: Langfuse Quick Start
Author: jeremylongshore

byjeremylongshore

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1,909

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Analíticas y Monitorización

Implements minimal Langfuse tracing examples to monitor LLM applications and establish observability workflows.

This skill provides a comprehensive entry point for integrating Langfuse into your applications, enabling developers to quickly generate their first traces, spans, and generations. It covers multiple implementation patterns, including the Modular v4 SDK with OpenTelemetry, the 'observe' wrapper for clean instrumentation, legacy v3 SDK support, and Python decorators. By using this skill, developers can validate their environment setup, verify API credentials, and master the core hierarchy of LLM observability within their Claude Code environment.

Características Principales

01Built-in troubleshooting guide for authentication and data flushing issues

02Demonstration of trace, span, and generation hierarchies

03Modular OpenTelemetry (OTel) integration patterns

04Functional 'observe' wrapper patterns for non-invasive instrumentation

051,909 GitHub stars

06Multi-SDK support including TypeScript (v3/v4) and Python

Casos de Uso

01Setting up initial LLM observability for a new project

02Testing Langfuse API credentials and connectivity in a dev environment

03Learning the structural difference between traces, spans, and generations

Características Principales

01Built-in troubleshooting guide for authentication and data flushing issues

02Demonstration of trace, span, and generation hierarchies

03Modular OpenTelemetry (OTel) integration patterns

04Functional 'observe' wrapper patterns for non-invasive instrumentation

051,909 GitHub stars

06Multi-SDK support including TypeScript (v3/v4) and Python

Casos de Uso

01Setting up initial LLM observability for a new project

02Testing Langfuse API credentials and connectivity in a dev environment

03Learning the structural difference between traces, spans, and generations