Skill UI

This SDK provides a comprehensive Java client for interacting with Azure Monitor. It allows developers to execute powerful Kusto Query Language (KQL) queries against Log Analytics workspaces to retrieve detailed operational logs, and to query time-series metrics from various Azure resources. It supports both synchronous and asynchronous operations, making it ideal for building monitoring, auditing, and analytics features in Java applications.

A comprehensive Python SDK for interacting with Azure Monitor services. It enables developers to execute complex Kusto Query Language (KQL) queries against Log Analytics workspaces and retrieve various resource metrics (CPU usage, network traffic, etc.). Ideal for building robust monitoring dashboards, automated alerting systems, and custom data analysis pipelines in cloud environments.

The official SDK for interacting with Azure AI Search service using Python. It provides comprehensive functionality for advanced search retrieval, including full-text search, vector similarity search (HNSW), hybrid search, and semantic ranking. Use this tool to build sophisticated enterprise search applications that require deep content understanding and precise information retrieval.

This SDK provides a comprehensive Python interface for interacting with Azure Blob Storage, Microsoft's scalable object storage service. It enables users to perform core object storage operations, including uploading, downloading, listing, deleting blobs, managing containers, and setting custom metadata. The library supports both synchronous and asynchronous workflows, making it ideal for building robust data pipelines, data lakes, or cloud-native applications that require reliable, scalable file storage.

This is a comprehensive client library for interacting with Azure Blob Storage, Microsoft's scalable object storage solution for the cloud. It allows developers to perform core operations in Rust, such as uploading, downloading, listing, creating, and managing blobs and containers. Ideal for building cloud-native applications that require persistent, scalable data storage.

This SDK provides a full set of tools for interacting with Azure Blob Storage using JavaScript or TypeScript. It enables developers to perform essential object storage operations, including uploading, downloading, listing, creating, and managing both blobs and containers. Supports various authentication methods like DefaultAzureCredential and Connection Strings, making it ideal for building robust, cloud-native applications.

A comprehensive JavaScript/TypeScript SDK for interacting with Azure File Shares. This library facilitates full lifecycle management of SMB file shares, including creating, listing, and deleting shares, managing quotas, and performing robust file and directory operations (uploading via stream, buffer, or file paths; downloading streamed content). Ideal for modern cloud-native applications requiring persistent file storage.

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 SDK provides comprehensive JavaScript/TypeScript functionality for interacting with Azure Queue Storage. It allows developers to implement robust asynchronous message queue patterns, including sending, receiving, peeking, and deleting messages. It supports various authentication methods (DefaultAzureCredential, connection string, SAS token) for secure and scalable deployment in enterprise cloud applications.

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.

This guide details security best practices for integrating with Clay. It covers securing API keys, validating webhook signatures, isolating provider credentials, and redacting sensitive PII data. Essential for maintaining compliance and data integrity in production environments.

This guide provides comprehensive strategies for managing rate limits and quotas when interacting with the Clerk API. It covers implementing robust retry logic using exponential backoff for 429 errors, optimizing bulk operations through batching, establishing multi-level caching (in-memory/Redis) to reduce API calls, and monitoring usage to ensure stability in high-traffic production environments.