Skill UI

This skill implements comprehensive SERP (Search Engine Results Page) monitoring using SerpApi. It covers asynchronous search result retrieval via polling and builds robust pipelines for tracking keyword rankings over time. Ideal for SEO tools, competitive intelligence, and automated performance monitoring.

This guide provides production-ready, idiomatic patterns for interacting with Snowflake using official SDKs (Node.js and Python). It covers essential patterns like implementing robust connection pooling, handling asynchronous query wrappers, efficiently streaming large result sets, and utilizing context managers for reliable resource cleanup. Use this when establishing team coding standards or optimizing data access performance.

This comprehensive guide provides step-by-step instructions for upgrading Snowflake drivers (Node.js and Python) and managing complex data warehouse migrations. It covers prerequisite checks, reviewing release notes, handling common API breaking changes (e.g., cursor types, async connections), and performing post-migration validation to ensure application stability during platform or edition upgrades.

A comprehensive reference architecture for building scalable, cost-effective, and robust AI services. This system manages the full AI lifecycle, including intelligent model routing (for quality/cost trade-offs), response caching (using Redis), asynchronous batch processing, and fine-tuning pipeline management via Together AI's OpenAI-compatible API. Ideal for enterprise applications requiring high availability across multiple open-source models.

This utility handles asynchronous webhook events from Together AI, enabling developers to build robust, event-driven Machine Learning pipelines. Instead of constantly polling the API for status updates (e.g., fine-tuning completion, batch job status, model deprecation), you can subscribe to these webhooks. It includes logic for signature verification, event routing, and idempotency, making it ideal for mission-critical AI workflows.

Comprehensive guide for designing robust backend APIs within the Webiny framework. It details best practices for structuring features, distinguishing between Services (multi-method, singleton) and UseCases (single-method orchestrators, transient), managing dependencies via the DI container, and implementing advanced patterns like ServiceProviders for asynchronous bootstrapping. Essential for all backend API development.

This API module provides comprehensive tools and abstractions for managing scheduled actions within the webiny ecosystem. It covers the entire lifecycle of asynchronous tasks, including scheduling actions for future execution, retrieving details, listing existing tasks, executing them immediately, and canceling them. Key components include dedicated Use Cases and a core SchedulerService, enabling robust background processing and reliable task management for enterprise applications.

This module provides core abstractions for handling long-running, asynchronous background tasks within an API context. It introduces `TaskDefinition` to define the complete lifecycle and hooks for a background task, and `TaskService` to programmatically trigger and manage these operations. It is essential for backend development requiring robust, non-instantaneous processing.

This guide demonstrates how to integrate Wispr Flow for robust voice-to-text transcription. It covers two primary methods: asynchronous REST calls for transcribing audio files, and real-time WebSocket streaming for live microphone input. Wispr specializes in developer-context-aware dictation, making it ideal for building complex voice-powered applications, especially those involving code or technical jargon.

This guide outlines architectural patterns and best practices for building scalable, production-ready APIs with FastAPI. It covers proper project structure, separating concerns using routers, services, and CRUD layers, implementing dependency injection for database sessions and authentication, defining Pydantic schemas for request/response, handling asynchronous operations, and managing custom error responses.

The CommunityToolkit.Mvvm Messenger provides a robust Publish/Subscribe messaging system for ViewModels and other objects. It allows multiple components to communicate asynchronously without holding direct references, effectively eliminating tight coupling. Supports various messaging patterns, including simple value broadcasts, request/reply (sync/async), and collection requests, making it ideal for complex applications using WPF, WinUI 3, .NET MAUI, or Avalonia.

A powerful solution for handling background jobs and asynchronous tasks within Django applications using Celery. It facilitates task queuing, reliable worker management, scheduled execution (cron jobs), and robust error handling. Ideal for sending emails, processing heavy data loads, or managing complex, multi-step workflows without blocking the main thread.