Skill UI

This guide details how to use Google Distroless images to drastically reduce the attack surface of containerized applications. By eliminating shells, package managers, and unnecessary OS utilities, these minimal base images enhance security, align with compliance standards, and improve supply chain security in Kubernetes and Docker deployments. It provides multi-stage build patterns for various languages (Go, Java, Python, Node.js).

Hono is a minimal and ultrafast web framework built entirely on Web Standards (Request/Response/fetch). It allows developers to build high-performance APIs and full-stack applications that run seamlessly across multiple environments, including Cloudflare Workers, Deno, Bun, and Node.js. It is ideal for edge deployment, Backend for Frontend (BFF) layers, and type-safe backend services.

Transformers.js allows developers to run state-of-the-art machine learning models directly within JavaScript/TypeScript environments (browser, Node.js). It supports a comprehensive range of tasks including NLP (text generation, summarization, translation), Computer Vision (image classification, object detection), and Audio processing. This capability enables building fully client-side, multimodal AI applications without requiring a dedicated Python backend or server infrastructure.

Complex Skill CLI wraps multi-line metadata and coordinates lark-cli plus Node.js binaries to expose a predictable helper for complex automation or deployment tasks within CLI-driven workflows.

Automate the deployment of CAST AI across various multi-cloud Kubernetes clusters, including EKS, GKE, and AKS. This module uses Terraform Infrastructure as Code (IaC) patterns to reliably configure necessary components like IAM roles, node autoscaling policies, and cluster resources, ensuring standardized onboarding across different cloud environments.

A comprehensive guide to optimizing CAST AI's core performance metrics, including node provisioning speed, autoscaler responsiveness, and API call efficiency. This skill covers techniques like configuring headroom, selecting optimal instance families, tuning evictors, and implementing caching for multi-cluster dashboards to ensure high availability and cost efficiency in cloud environments.

A comprehensive guide to optimizing performance when integrating with the Figma REST API. Techniques cover aggressive response caching (LRU), reducing payload size using depth parameters, batching multiple node fetches, and implementing webhook-driven cache invalidation. Essential for handling large, complex Figma files efficiently.

Provides a comprehensive, production-ready reference architecture for building advanced analytics platforms powered by ClickHouse. It details everything from project layout (TypeScript/Node.js structure) and data ingestion pipelines (Kafka, Webhooks) to the optimal 3-layer schema design (Raw, Hourly, Daily) and multi-tenancy patterns, ensuring scalable and efficient OLAP query performance.

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 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.

Master advanced patterns for composing LangGraph subgraphs, which is essential for building robust, multi-agent systems like planner-executors or hierarchical teams. This skill addresses critical issues such as shared state contract propagation (P21) and callback scoping (P28). Learn to manage state across independent graph components using sophisticated dispatch patterns: compiled nodes, Send fan-out, and Command bubble-up.