Skill UI

This SDK provides comprehensive Python support for Azure Data Lake Storage Gen2. It enables developers to interact with hierarchical file systems, performing essential big data operations such as creating, listing, uploading, downloading, and managing metadata for files and directories. Ideal for building data analytics pipelines and cloud-based data processing workflows.

This SDK provides comprehensive Python support for managing Azure File Shares, which function as SMB file shares in the cloud. It allows users to perform core operations including creating, listing, and deleting shares, managing nested directories, uploading, downloading, and copying files, and utilizing advanced features like snapshots and partial range operations. Ideal for cloud-native development and lift-and-shift migrations.

A comprehensive Python SDK for interacting with Azure Queue Storage. This tool enables reliable, asynchronous communication patterns by managing message queuing, task distribution, and data processing workflows. It supports core operations including sending, receiving, peeking, updating, and deleting messages, making it ideal for building resilient, decoupled backend systems on Azure.

This guide provides production-ready patterns for building robust integrations with the Clay platform. It covers interacting with Clay via webhooks (inbound data), HTTP API enrichment columns (outbound data), and the Enterprise API. Implementation examples are provided in TypeScript and Python, ensuring reliable, reusable, and scalable data pipeline construction.

The official SDK for building applications that programmatically interact with GitHub Copilot. It provides comprehensive features including session management, custom tool definition (function calling), real-time streaming, and lifecycle hooks. Supports multiple languages, including Node.js, Python, Go, and .NET, making AI integration seamless across your tech stack.

A comprehensive guide detailing the setup process for Databricks CLI v2 and Python SDK. It covers essential steps for connecting to various Databricks workspaces, including configuring Personal Access Tokens (PAT), interactive OAuth U2M flows, and secure OAuth M2M service principals for CI/CD pipelines. Essential for developers integrating Databricks into their projects.

A comprehensive guide to production-ready patterns for the Databricks Python SDK. This skill covers essential best practices including singleton client initialization, structured error handling with typed exceptions, context-managed cluster lifecycle control (ensuring cleanup), and implementing type-safe job definitions. It is essential for building robust, maintainable, and idiomatic integrations with the Databricks platform.

Provides production-ready coding patterns for integrating Deepgram using TypeScript and Python. This guide covers essential best practices, including implementing singleton client management, performing text-to-speech synthesis with Aura, and setting up advanced audio intelligence pipelines (e.g., summarization, topic detection, sentiment analysis). Use this when establishing robust Deepgram integration standards, refactoring existing SDK usage, or migrating to newer SDK versions.

This guide provides comprehensive instructions for setting up and authenticating the Documenso SDK and API. Users will learn how to install the SDKs (TypeScript and Python), generate secure API keys, and initialize the client connection for both v1 (legacy) and v2 (recommended) API versions. It covers best practices for secure credential management within development projects.

A comprehensive set of production-ready design patterns for integrating with the Documenso SDK. It covers best practices for managing singleton clients, building typed service wrappers, robust API error handling (including status code analysis), and automatically implementing retry logic with exponential backoff. Ideal for establishing stable, scalable, and maintainable coding standards in TypeScript and Python.

A comprehensive guide for migrating from Documenso's legacy v1 API (document-centric) to the modern, recommended v2 API (envelope-based). This resource covers SDK upgrades for TypeScript and Python, providing code migration examples, best practices for implementing feature flags for gradual rollout, and steps for self-hosted container version upgrades.

This guide provides a comprehensive walkthrough for setting up the Evernote SDK and implementing OAuth 1.0a authentication. It details the entire process, from acquiring API keys via the developer portal, installing the SDK (for Node.js or Python), configuring environment variables, to initializing the client. Use this skill when starting a new Evernote integration or needing to verify secure API connectivity to the Evernote Cloud.