Skill UI

Utilizes the Azure AI Projects SDK's ImageBasedHostedAgentDefinition to build robust, container-based AI agents deployed in Azure AI Foundry. This workflow is essential for creating production-grade agents that require custom logic, precise resource allocation (CPU/Memory), and integration of advanced tools like code interpreters.

Guides React Server Components workflows, streaming SSR, code splitting, bundle/image/font optimizations, and Core Web Vitals monitoring to keep Next.js frontends fast and responsive.

This comprehensive guide provides a multi-platform deployment solution for Ideogram-powered image generation APIs. It includes detailed code and setup steps for Vercel, Google Cloud Run, and self-hosted Docker containers. The solution addresses key production concerns, including secure secret management (API keys), handling generation timeouts, and ensuring generated images are persisted to durable cloud storage (like S3) with CDN integration for reliable service operation. Use this when migrating Ideogram prototypes to a production environment.

A comprehensive guide to setting up and authenticating the Ideogram API for AI image generation. This skill covers obtaining the necessary API key, configuring environment variables, and providing verifiable code snippets (Python/TypeScript) to establish a successful connection. It is essential for integrating image generation, editing, and remixing capabilities into any development project.

This guide provides a comprehensive technical deep dive for developers migrating image generation workflows from services like DALL-E, Midjourney, and Stable Diffusion to Ideogram. It covers API parameter mapping, architectural patterns (like the Adapter pattern), and provides code examples to ensure a stable, gradual, and feature-rich transition to Ideogram's platform.

Automated assistant for frontend image optimization walks you through best practices, generates production-ready code and config, and validates results whenever you ask about image optimization patterns or helper workflows.

This guide provides a comprehensive reference for diagnosing and resolving common errors encountered when interacting with the Kling AI API. It covers various HTTP status codes (e.g., 400, 401, 429), task-level failures (e.g., content policy violations, low image quality), proper JWT token management, and implementing rate limit handling with exponential backoff. Use this resource when troubleshooting failed video generation or API integration issues.

Helps manage container registries like AWS ECR, Google GCR, and Harbor by generating configuration code, guiding access controls, and advising best practices for secure, production-ready image storage and deployment automation.

A comprehensive guide and methodology for identifying, measuring, and fixing performance bottlenecks across the entire stack. This skill covers optimizing database queries (e.g., N+1 problems, missing indexes), improving API efficiency (caching, parallel processing), and enhancing frontend performance (memoization, code splitting, image optimization). It emphasizes the critical 'Measure First' principle to ensure all optimizations are data-driven and effective.

Learn how to implement robust container security by integrating the open-source Trivy scanner (from Aqua Security) into your CI/CD pipelines. This guide covers scanning container images, Kubernetes manifests, IaC files, and code repositories to detect critical vulnerabilities, misconfigurations, secrets, and generating Software Bill of Materials (SBOM) for comprehensive supply chain security.

Accelerates CPU-bound Python workflows by translating NumPy, pandas, ML, graph, image, simulation, and IO code into NVIDIA GPU kernels using CuPy, Numba CUDA, Warp, cuDF/cuML/cuGraph, KvikIO, cuSpatial, and RAFT for dramatic speedups.

A powerful tool that converts complex Unified Modeling Language (UML) diagrams—such as Sequence, Class, Activity, and State diagrams—into plain text ASCII art. This is crucial for documentation in environments that do not support image embedding, such as terminal sessions, README files, or Git commit messages. Supports both standard ASCII and enhanced Unicode ASCII formats for better visual fidelity.