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LLM Observability Tracing

sickn33/antigravity-awesome-skills

Instrument Langfuse into LLM workflows to capture traces, metrics, prompt versions, and A/B test results, so you can monitor cost, latency, and quality alongside prompt-driven fixes.

Langfuse CI Integration

langfuse-ci-integration

jeremylongshore/claude-code-plugins-plus-skills

Configure Langfuse observability and prompt management across CI/CD workflows, covering automated trace validation, prompt regression suites, prompt deployment, and quality score monitoring via GitHub Actions.

Langfuse LLM Tracing Workflow

langfuse-core-workflow-a

jeremylongshore/claude-code-plugins-plus-skills

Guides setup of Langfuse tracing for LLM pipelines, covering automatic OpenAI wrapping, manual spans, streaming responses, and parent-child trace linking for end-to-end observability.

Langfuse Evaluation Workflow

langfuse-core-workflow-b

jeremylongshore/claude-code-plugins-plus-skills

Use Langfuse Core Workflow B to collect manual feedback, run automated evaluation functions, operate LLM-as-judge scoring, and compare prompts for AI quality scoring.

Langfuse Cost Optimization

langfuse-cost-tuning

jeremylongshore/claude-code-plugins-plus-skills

Monitor Langfuse telemetry to record LLM token usage, aggregate spend by model and time, alert on budget breaches, and steer requests toward cheaper models while caching responses and trimming prompts.

Langfuse Trace Starter

langfuse-hello-world

jeremylongshore/claude-code-plugins-plus-skills

Provides a minimal Langfuse trace example that initializes the client, records spans and generations, flushes data, and logs a trace URL—ideal when starting integrations, validating setup, or learning trace patterns.

Langfuse Auth Setup

langfuse-install-auth

jeremylongshore/claude-code-plugins-plus-skills

Guides through installing the Langfuse SDK and configuring public/secret keys plus host settings so you can authenticate tracing for new LLM observability projects in Node.js or Python.

Langfuse Observability Setup

langfuse-observability

jeremylongshore/claude-code-plugins-plus-skills

Set up comprehensive Langfuse observability with Prometheus metrics, Grafana dashboards, and AlertManager rules to monitor LLM operations, track latency, costs, and errors, and ensure integration health.

Langfuse SDK Patterns

langfuse-sdk-patterns

jeremylongshore/claude-code-plugins-plus-skills

Guides Langfuse SDK best practices—singleton clients, trace lifecycle updates, nested spans, Python decorators, session tracking, and scoring—for reliable LLM observability.

LangGraph Agent Architecture

sickn33/antigravity-awesome-skills

Guides architects in building production-grade AI agents with LangGraph, emphasizing explicit graph structures, reducer-based state management, persistence, and tool-supported workflows.

LangSmith Trace Debugger

langsmith-fetch

ComposioHQ/awesome-claude-skills

Fetch execution traces from LangSmith Studio to inspect LangChain/LangGraph agent runs, analyze errors, tool calls, memory usage, and performance, and export sessions for deeper diagnostics using the langsmith-fetch CLI.

LangSmith Observability Platform

langsmith-observability

Orchestra-Research/AI-Research-SKILLs

LangSmith is an observability platform for debugging, evaluating, and monitoring LLM applications, combining tracing, dataset-backed evaluation, and production metrics to streamline AI testing and incident response.

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