Claude Skills by jeremylongshore

"Build reliable dev / staging / prod isolation for LangChain 1.0 services\

"Wire LangSmith tracing and custom metric callbacks into a LangChain\

'Wire LangChain 1.0 / LangGraph 1.0 traces into an OpenTelemetry-native

"Tune LangChain 1.0 / LangGraph 1.0 Python chains and agents for throughput,\n\

"Manage LangChain 1.0 prompts like code \u2014 LangSmith prompt hub versioning,\n\

"Rate-limit LangChain 1.0 calls correctly across multi-worker deployments\

"A reference layered architecture for production LangChain 1.0 / LangGraph\

'Compose LangChain 1.0 Python runnables with the production defaults

"Harden a LangChain 1.0 chain or LangGraph agent against prompt injection,\

"Migrate a LangChain 0.3.x Python codebase to LangChain 1.0 / LangGraph\

"Dispatch LangChain 1.0 chain/agent events to external systems \u2014\

'Configure Langfuse CI/CD integration with GitHub Actions and automated

'Diagnose and fix common Langfuse errors and exceptions.

'Execute Langfuse primary workflow: Tracing LLM calls and spans.

'Monitor and optimize LLM costs using Langfuse analytics and dashboards.

'Manage Langfuse data export, retention, and compliance requirements.

'Collect Langfuse debug evidence for support tickets and troubleshooting.

'Configure Langfuse enterprise organization management and access control.

'Create a minimal working Langfuse trace example.

'Troubleshoot and respond to Langfuse-related incidents and outages.

'Install and configure Langfuse SDK authentication for LLM observability.

'Set up Langfuse local development workflow with hot reload and debugging.

'Execute complex Langfuse migrations including data migration and platform

'Configure Langfuse across development, staging, and production environments.

'Set up comprehensive observability for Langfuse with metrics, dashboards,

'Optimize Langfuse tracing performance for high-throughput applications.

'Langfuse production readiness checklist and verification.

'Implement Langfuse rate limiting, batching, and backoff patterns.

'Production-grade Langfuse architecture patterns and best practices.

'Langfuse SDK best practices, patterns, and idiomatic usage.

'Upgrade Langfuse SDK versions and migrate between API changes.

'Configure Langfuse webhooks for prompt change notifications and event-driven

'Configure CI/CD pipelines for testing Lindy AI agent integrations.

'Troubleshoot common Lindy AI agent errors and workflow failures.

'Build and configure multi-step Lindy AI agent workflows.

'Configure Lindy triggers, scheduling, multi-agent delegation, and automation.

'Optimize Lindy AI costs through credit management, model selection,

'Data handling best practices for Lindy AI agents.

'Comprehensive debugging toolkit for Lindy AI agents.

'Deploy applications that integrate with Lindy AI agents.

'Configure enterprise role-based access control for Lindy AI workspaces.

'Create your first Lindy AI agent with a real trigger and action.

'Incident response procedures for Lindy AI agent failures and outages.

'Set up a Lindy account and authenticated webhook trigger.

'Set up local development workflow for testing Lindy AI agent integrations.

'Advanced migration strategies for moving to Lindy AI from other platforms.

'Configure Lindy AI across development, staging, and production environments.

'Monitor Lindy AI agent health, task success rates, and credit consumption.

'Optimize Lindy AI agent execution speed, reliability, and cost efficiency.

'Production readiness checklist for Lindy AI agent deployments.