Skill UI

This is a low-level SDK for Java designed to create and manage persistent AI agents within Azure AI. It provides comprehensive tools for handling the entire agent lifecycle, including creating agents, managing conversation threads, sending messages, running agent processes, and cleaning up resources. Ideal for building robust, stateful AI applications requiring fine-grained control over agent interactions.

This is a low-level SDK for Java designed to create and manage persistent AI agents within Azure AI. It provides comprehensive tools for handling the entire agent lifecycle, including creating agents, managing conversation threads, sending messages, running agent processes, and cleaning up resources. Ideal for building robust, stateful AI applications requiring fine-grained control over agent interactions.

A comprehensive SDK for building real-time, bidirectional voice AI applications using Azure AI services within the .NET framework. This library facilitates seamless voice interactions, supporting WebSocket communication, advanced features like function calling, and handling audio/text streaming events for developing sophisticated virtual assistants.

This library provides essential common utilities for Azure Communication Services (ACS) development in Java. It handles robust authentication mechanisms, including token credential management (supporting static, proactive refresh, and Azure AD/Entra ID integration), and standardized identification for various communication endpoints. Use it to ensure reliable, secure, and cohesive communication interactions across your applications.

This library provides essential common utilities for Azure Communication Services (ACS) development in Java. It handles robust authentication mechanisms, including token credential management (supporting static, proactive refresh, and Azure AD/Entra ID integration), and standardized identification for various communication endpoints. Use it to ensure reliable, secure, and cohesive communication interactions across your applications.

Automate Clickmeeting interactions through Composio’s Rube MCP toolkit by always discovering up-to-date tools, checking active connections, and executing RUBE_MULTI_EXECUTE_TOOL with schema-compliant arguments.

Provides comprehensive guidance for developing robust, cross-platform Command Line Interface (CLI) applications. Covers the entire workflow from initial UX analysis and command design to implementation using popular frameworks (e.g., commander, click, cobra). Key features include advanced argument parsing, handling shell completions, displaying progress bars, and ensuring reliable terminal interactions across Windows, macOS, and Linux.

A comprehensive guide for treating project context as a managed, first-class artifact alongside code. It establishes systematic documentation (e.g., product vision, tech stack, workflow) to ensure consistent requirements, maintain team alignment, and optimize AI interactions throughout the entire development lifecycle. Essential for greenfield and brownfield projects.

This skill set provides advanced, structured strategies for optimizing Large Language Model (LLM) interactions. It covers techniques such as intelligent context summarization, dynamic trimming, context routing, and precise token budget allocation to prevent 'context rot'. It is essential for building robust, long-running, multi-turn conversational AI systems.

This advanced system transforms session interactions into reusable, atomic knowledge units called "Instincts." By hooking into tool usage and session activity, it observes patterns (like preferred coding styles, error fixes, or repeated workflows). These instincts are then clustered and "evolved" into structured Skills, Commands, or specialized Agents, capturing deep contextual knowledge with weighted confidence scoring to enhance development productivity.

A robust solution for implementing and handling real-time webhooks from Customer.io. This tool processes critical marketing events, including delivery status, opens, clicks, bounces, and unsubscribes. Key features include HMAC signature verification for security, reliable asynchronous event processing, and structured routing to manage various customer interactions, allowing data to be streamed efficiently to a data warehouse or CRM.

Feature Engineering Toolkit automates creating, selecting, and transforming dataset features to improve machine learning models; use it whenever you need new interactions, automatic selection, scaling, or encoding to boost accuracy and interpretability.