Skill UI

This skill guides the implementation of Mobile Application Management (MAM) policies, enabling robust data protection for corporate assets on both managed and unmanaged mobile devices (BYOD). It covers configuring app-level controls such as Data Loss Prevention (DLP), selective wiping, and containerization using platforms like Microsoft Intune and Azure AD. Use this when enforcing data separation between personal and work environments without requiring full device enrollment.

This comprehensive template and guide facilitate the containerization of ASP.NET Core applications. It provides a structured prompt and checklist to ensure that the resulting Dockerfile adheres to industry best practices for performance, security, and maintainability when running on Linux containers. It covers all necessary aspects, including dependency management, port exposure, build stages, and custom configuration.

Helps produce Dockerfiles and a detailed containerization plan for ASP.NET .NET Framework projects running in Windows containers, covering configuration settings, IIS, dependencies, and deployment steps.

This skill provides comprehensive guidance for deploying and managing GPU-accelerated AI inference services on CoreWeave Kubernetes (CKS). It covers best practices including containerization using NVIDIA CUDA base images, configuring specific GPU resource limits (A100/H100), setting up robust health checks, and executing controlled rolling updates. Ideal for managing multi-model inference and scaling demanding AI workloads in a cloud environment.

This guide provides a deep dive into migrating machine learning workloads, including inference services and training pipelines, from major hyperscalers (AWS, GCP, Azure) to the CoreWeave GPU cloud. It covers cost comparisons, containerization, Kubernetes YAML adaptation, and a phased deployment strategy, helping users ensure a smooth, cost-effective, and optimized transition.

This skill provides a comprehensive guide for deploying Palantir Foundry integrated applications to major cloud platforms, such as GCP Cloud Run, AWS Lambda, and Docker. It covers best practices including containerization using Docker, implementing robust secrets management via cloud secret managers, establishing health check endpoints, and configuring environment-specific scopes. This process ensures applications are production-ready, secure, and highly available.

Dep handles the entire journey from local code to production deployment. This skill automates containerization using Docker and docker-compose, establishes robust CI/CD pipelines (linting, testing, security scanning, deployment), manages environment variables and secrets, and generates Infrastructure as Code (Terraform/Pulumi) configurations. It ensures observability and provides rollback procedures.

This guide provides comprehensive instructions for creating a robust, reproducible artifact package for database systems research. It details best practices including containerization, pinning workloads, generating a permanent DOI-archived record, and designing the package to be successfully built and demonstrated on a reviewer's clean machine within a tight time budget. The goal is to strengthen scientific rigor and ensure permanent, open-access citation.

This guide provides authors with comprehensive best practices for submitting research artifacts (e.g., compilers, benchmarks, proofs) for post-acceptance evaluation at PLDI. It details how to structure the submission, ensuring reproducibility, containerization, and clear documentation to achieve Functional, Reusable, or Available badges.

This comprehensive guide outlines the requirements for submitting computational artifacts for post-acceptance evaluation at PPoPP. It details PPoPP's unique badge policy (Functional, Reusable, Results Reproduced), addresses the challenges of ensuring results reproduce across different hardware architectures, and provides a detailed packaging plan, including containerization, README structure, and provenance documentation for maximizing reproducibility.

Build and manage OCI/Linux containers on Apple Silicon macOS using Apple's open-source container CLI without Docker daemon. Each container runs in its own lightweight VM backed by Containerization framework and Virtualization API. Supports standard OCI artifacts, Docker-like workflows with build/run/exec/logs commands. Requires macOS 26 (Tahoe) officially, works on macOS 15 with limited networking.