langfuse-integration
LangFuse LLM observability integration for tracing, analytics, and cost tracking
npx skills add a5c-ai/babysitter --skill langfuse-integration --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 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)
- Capabilities
- Target Processes
- Implementation Details
- Core Features
- Integration Methods
- Configuration Options
- Best Practices
- Dependencies
What does the langfuse-integration skill do?
LangFuse LLM observability integration for tracing, analytics, and cost tracking
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill langfuse-integration --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 a5c-ai/babysitter, a repository with 1,642 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.