Skill UI

This guide details how to set up and execute large-scale, distributed GPU training jobs on the CoreWeave platform. It covers both single-node multi-GPU setups and multi-node training utilizing PyTorch DDP and Kubernetes resources (A100/H100). This workflow is ideal for fine-tuning large language models (LLMs) or running complex deep learning models that require high-performance, shared-storage compute clusters.

This bundle is designed to collect comprehensive diagnostics for CoreWeave clusters, including GPU node status, Kubernetes Pod logs, event history, and API connectivity. It aggregates critical cluster-level resource allocation and failure data into a single, actionable archive. Use it when preparing a support ticket to expedite the diagnosis of complex infrastructure issues like stuck pods, OOM errors, or resource bottlenecks.

This guide demonstrates how to deploy GPU workloads on the CoreWeave platform using Kubernetes (kubectl). It covers deploying vLLM inference services for large language model (LLM) testing and running batch CUDA jobs for benchmarking. This is ideal for users running their first GPU workloads, testing inference pipelines, or verifying cluster access on bare-metal GPU nodes (A100, H100).

This runbook provides structured steps for responding to critical production incidents on the CoreWeave platform. Use it when dealing with GPU workload failures, inference service outages, or general Kubernetes resource issues. It guides users through checking pod status, node health, and diagnosing common model loading errors to ensure rapid service recovery.

This guide provides step-by-step instructions to configure access to the CoreWeave Kubernetes Service (CKS). It covers downloading the kubeconfig file, setting API tokens, and verifying GPU node access using standard `kubectl` commands. This is essential for deploying AI/ML workloads on bare-metal GPU infrastructure.

A comprehensive solution for monitoring CoreWeave cluster events and GPU workload status using webhooks. It tracks critical lifecycle events such as pod readiness, job completion, volume attachment, and node health. Essential for building automated scaling, alerting, and recovery pipelines for large-scale GPU-accelerated inference and training workloads.

This comprehensive guide details how to install and properly configure the ElevenLabs SDK for both Node.js and Python environments. It covers setting up the required API keys using environment variables, initializing the client connection, and verifying the setup by listing available voices. Use this skill when starting a new project that requires advanced text-to-speech (TTS) or voice synthesis capabilities.

This guide provides a comprehensive walk-through of making the first REST API calls to Figma. Users learn how to fetch core file metadata (name, version, pages) and traverse the complex document structure (nodes, frames, components). It's ideal for developers starting a new Figma integration, setting up API connectivity tests, or understanding the fundamental relationships between design elements within a Figma file.

This skill guides you through installing and setting up the official Klaviyo SDK for both Node.js and Python. It covers essential steps including authenticating with a private API key, managing environment variables for secure credential storage, and initializing resource-specific API clients (e.g., Profiles, Events). Use this when building integrations that require programmatic access to Klaviyo's marketing data, such as tracking user events or managing contact profiles.

This guide provides a comprehensive strategy for configuring Klaviyo across development, staging, and production environments. It covers best practices for using separate API keys, implementing robust environment detection logic (like reading NODE_ENV), and utilizing secret management solutions (AWS/GCP/Vault). Crucially, it teaches how to implement 'guards' to prevent accidental real-world actions, such as sending live emails or deleting data, in non-production environments, ensuring data integrity and smooth CI/CD deployment.

A comprehensive guide to implementing production-ready patterns for interacting with the Klaviyo API via the Node.js SDK. This includes best practices for handling singleton sessions, creating type-safe API wrappers, implementing robust retry logic for rate limits, managing cursor-based pagination, and supporting multi-tenant environments. This ensures reliable and maintainable Klaviyo integrations.

This skill provides a comprehensive guide to building robust LangGraph 1.0 StateGraphs in Python. It covers defining typed TypedDict states with reducers, writing deterministic nodes, and defensively wiring conditional edges. It addresses common pitfalls such as silent graph termination, incorrect state updates using reducers, proper management of recursion limits, and handling evolving checkpoint schemas for reliable LLM workflow orchestration.