Skill UI

Generates and iterates high-performing ad creative—headlines, descriptions, primary text, and full variations—for any platform, using performance data to discover winning angles, stay within platform specs, and scale creative production.

This comprehensive Python SDK serves as a client library for managing the full lifecycle of Machine Learning resources on Azure Machine Learning. It allows users to programmatically handle workspaces, register data and models, provision compute clusters, define complex training jobs, and build reproducible, end-to-end MLOps pipelines.

This comprehensive Python SDK serves as a client library for managing the full lifecycle of Machine Learning resources on Azure Machine Learning. It allows users to programmatically handle workspaces, register data and models, provision compute clusters, define complex training jobs, and build reproducible, end-to-end MLOps pipelines.

A comprehensive Python SDK for interacting with Azure Container Registry (ACR). This tool allows developers to manage the full container lifecycle, including listing repositories, handling tags, manipulating manifests, downloading artifacts, and managing container images within Azure's cloud environment. Ideal for implementing robust CI/CD pipelines and container automation.

A comprehensive Python SDK for interacting with Azure Container Registry (ACR). This tool allows developers to manage the full container lifecycle, including listing repositories, handling tags, manipulating manifests, downloading artifacts, and managing container images within Azure's cloud environment. Ideal for implementing robust CI/CD pipelines and container automation.

This Python SDK provides comprehensive management capabilities for Azure API Center. It allows developers to programmatically handle the entire API lifecycle, including API registration, version control, metadata definition, definition import, and deployment management across an organization's API estate, ensuring robust governance and centralized control.

This expert guides users through advanced, data-driven content marketing strategies. It covers AI-powered content creation, comprehensive SEO optimization, omnichannel distribution, social media management, email automation, and performance analytics. Use it when developing comprehensive content plans, maximizing online reach, or optimizing conversion funnels across various digital platforms.

A comprehensive guide for integrating and managing VS Code extensions within the Cursor IDE environment. This resource details the transition from the Microsoft Marketplace to the Open VSX Registry, covering installation methods (in-app, VSIX, CLI), conflict resolution with advanced AI features (e.g., Copilot, TabNine), and best practices for ensuring optimal performance and recommended extension stacks for various languages like Python, JavaScript, and Go.

This guide outlines the complete MLOps workflow on Databricks. It covers feature engineering using Feature Store, tracking experiments with MLflow, managing model versions in the Model Registry, and deploying real-time inference endpoints via Mosaic AI Model Serving. Ideal for building robust, production-grade ML pipelines.

Generates end-to-end tests for web workflows using Playwright, Cypress, or Selenium, automating browser steps and assertions so QA teams can validate registration, login, shopping cart, and other multi-step flows across browsers and devices.

Provides a workflow for automating GitHub Gist operations by discovering Rube MCP tool schemas, ensuring active connections, and invoking Composio toolkit calls consistently with session reuse and schema compliance.

This blueprint provides a scalable, production-grade reference architecture for advanced LLM applications using LangChain. It guides the implementation of layered design, provider abstraction (allowing seamless switching between LLMs like OpenAI and Anthropic), dynamic chain registry, robust RAG pipelines, and complex multi-agent orchestration. Ideal for building enterprise-level, maintainable, and highly flexible AI systems.