# Langfuse Integration

> LangFuse LLM observability integration for tracing, analytics, and cost tracking

- Skill: `a5c-ai/langfuse-integration` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add a5c-ai/langfuse-integration`
- Raw SKILL.md: https://api.skillmd.com/api/skills/a5c-ai/langfuse-integration/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Data & Analytics
- Author: a5c-ai (https://skillmd.com/u/a5c-ai)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/a5c-ai/langfuse-integration

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# LangFuse Integration Skill

## Capabilities

- Set up LangFuse tracing for LLM calls
- Configure cost tracking and analytics
- Implement prompt management
- Set up evaluation datasets
- Design custom trace metadata
- Create dashboards and alerts

## Target Processes

- llm-observability-monitoring
- cost-optimization-llm

## Implementation Details

### Core Features

1. **Tracing**: Track LLM calls, chains, and agents
2. **Prompts**: Version and manage prompts
3. **Analytics**: Usage, latency, cost metrics
4. **Datasets**: Evaluation and testing data
5. **Scores**: Track output quality

### Integration Methods

- LangChain callback handler
- Direct SDK integration
- OpenAI drop-in replacement
- Decorator-based tracing

### Configuration Options

- Public/secret keys
- Host URL (cloud or self-hosted)
- Sampling rate
- Metadata configuration
- User tracking

### Best Practices

- Consistent trace naming
- Meaningful metadata
- Regular prompt versioning
- Set up alerting

### Dependencies

- langfuse
- langchain (for callback integration)