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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 LLM Evaluation And Benchmarking

langfuse-core-workflow-b

jeremylongshore/claude-code-plugins-plus-skills

A comprehensive workflow for implementing robust LLM evaluation using Langfuse. This skill guides users through key processes including scoring traces (numeric, categorical, boolean), collecting user feedback, managing versioned prompts, creating structured datasets, running automated experiments, and implementing LLM-as-a-Judge patterns for advanced quality assurance and system benchmarking.

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 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.

Learning Rate Scheduler

learning-rate-scheduler

jeremylongshore/claude-code-plugins-plus-skills

Provides automated guidance for configuring learning rate schedulers during ML training, covering best practices, setup patterns, and framework-ready code snippets for PyTorch, TensorFlow, and Scikit-learn while validating against common standards.

Troubleshooting Lindy AI Agent Errors

lindy-common-errors

jeremylongshore/claude-code-plugins-plus-skills

A comprehensive guide to diagnose and resolve common errors in Lindy AI agent workflows. Covers troubleshooting issues related to trigger failures (webhooks, email, schedule), action execution errors (Slack, Gmail, HTTP requests, code), and advanced agent step logic problems, ensuring reliable automation.

Lindy AI Agent Workflow

lindy-core-workflow-a

jeremylongshore/claude-code-plugins-plus-skills

Guided workflow for creating, configuring, testing, and deploying Lindy AI agents, covering specification, tool setup, and validation steps that you trigger when building new agent personas.

Lindy Data Handling

lindy-data-handling

jeremylongshore/claude-code-plugins-plus-skills

Guides teams through Lindy AI data classification, PII redaction, secure pipelines, and retention policies so sensitive information stays compliant across privacy regimes.

Lindy Debug Toolkit

lindy-debug-bundle

jeremylongshore/claude-code-plugins-plus-skills

Provides Lindy AI agents with a step-by-step diagnostics suite for environment info, API checks, agent state, run history, and support bundle generation when investigating issues.

Lindy Hello World

lindy-hello-world

jeremylongshore/claude-code-plugins-plus-skills

Provides a minimal Lindy AI agent example for starting a new integration, testing your setup, or learning core API patterns, guiding you through file creation, client initialization, and first agent execution.

Lindy Incident Runbook

lindy-incident-runbook

jeremylongshore/claude-code-plugins-plus-skills

Structured incident response runbook for Lindy AI integrations, guiding teams through diagnostics, severity tiers, escalation, and post-mortem steps during outages.

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