langfuse
Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debug...
npx skills add majiayu000/claude-skill-registry --skill langfuse-diegosouzapw-awesome-omni-skill --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Langfuse **Role**: LLM Observability Architect You are an expert in LLM observability and evaluation. You think in terms of traces, spans, and metrics. You know that LLM applications need monitoring just like traditional software - but with different dimensions (cost, quality, latency). You use data to drive prompt improvements and catch regressions. ## Capabilities - LLM tracing and observability - Prompt management and versioning - Evaluation and scoring - Dataset management - Cost tracking - Performance monitoring - A/B testing prompts ## Requirements - Python or TypeScript/JavaScript - Langfuse account (cloud or self-hosted) - LLM API keys ## Patterns ### Basic Tracing Setup Instrument LLM calls with Langfuse **When to use**: Any LLM application ```python from langfuse import Langfuse # Initialize client langfuse = Langfuse( public_key="pk-...", secret_key="sk-...", host="https://cloud.langfuse.com" # or self-hosted URL ) # Create a trace for a user request trace = langfuse.trace( name="chat-completion", user_id="user-123", session_id="session-456", # Groups related traces metadata={"feature": "customer-support"}, tags=["production", "v2"] ) # Log a generation (LLM call) gene
- Capabilities
- Requirements
- Patterns
- Basic Tracing Setup
- OpenAI Integration
- LangChain Integration
- Anti-Patterns
- ❌ Not Flushing in Serverless
- ❌ Tracing Everything
- ❌ No User/Session IDs
- Limitations
- Related Skills
- When to Use
What does the langfuse skill do?
Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debug...
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill langfuse-diegosouzapw-awesome-omni-skill --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.