Skill UI

This SDK allows developers to build persistent, sophisticated AI agents directly on Azure AI Foundry. It supports complex conversational workflows by integrating external functions (tools), enabling code execution, web search, and maintaining conversation history through dedicated thread management. Ideal for developing enterprise-grade, production-ready AI applications.

A comprehensive, low-level Software Development Kit (SDK) for building and managing stateful AI Agents within the Azure AI ecosystem using .NET. This SDK provides core clients for managing agent lifecycles, persistent conversation threads, message history, complex run execution, tool/function calling, and integrating file search through vector stores. It is essential for developing enterprise-grade, multi-turn conversational AI applications.

A comprehensive, low-level Software Development Kit (SDK) for building and managing stateful AI Agents within the Azure AI ecosystem using .NET. This SDK provides core clients for managing agent lifecycles, persistent conversation threads, message history, complex run execution, tool/function calling, and integrating file search through vector stores. It is essential for developing enterprise-grade, multi-turn conversational AI applications.

This guide provides comprehensive examples for developing real-time chat applications using the Azure Communication Services Chat SDK in Java. It covers essential features including creating chat threads, sending diverse message types (text, HTML), listing message history, managing participants, and handling advanced functionalities like read receipts, message updates, and participant management. Ideal for building robust, enterprise-grade messaging systems.

This guide provides comprehensive examples for developing real-time chat applications using the Azure Communication Services Chat SDK in Java. It covers essential features including creating chat threads, sending diverse message types (text, HTML), listing message history, managing participants, and handling advanced functionalities like read receipts, message updates, and participant management. Ideal for building robust, enterprise-grade messaging systems.

This powerful tool calculates detailed cryptocurrency tax obligations by processing transaction history from multiple exchanges. It supports various cost basis methods (FIFO, LIFO, HIFO) to accurately determine capital gains and losses. Key features include identifying staking, airdrop, and mining income, and generating comprehensive reports compatible with Form 8949, simplifying complex tax filing processes.

This skill automates the generation of comprehensive changelogs and release notes directly from commit history, Pull Requests (PRs), and release tags. It ensures that documentation adheres to industry-standard formats, such as Keep a Changelog, streamlining release workflows and standardizing version management practices.

Transforms git commits into polished, customer-ready changelog entries by analyzing history, categorizing features/bug fixes, filtering noise, and applying consistent brand voice so releases are ready in minutes.

Automate Clockify time tracking via Claude Code, letting you log entries, query history, manage workspaces, and handle running timers through natural language commands for streamlined billing, reporting, and team audits.

Collects comprehensive diagnostic evidence for troubleshooting CodeRabbit integration issues. This bundle checks the App installation status, validates the `.coderabbit.yaml` configuration, reviews recent PR history, and verifies GitHub webhook deliveries. Essential for preparing support tickets and diagnosing complex SaaS integration failures.

This skill generates commit messages strictly following Sentry's conventions and the Conventional Commit format. It mandates a structured commit message including a type, scope, subject, body (explaining what and why), and a footer for issue references. Use this whenever committing code changes to ensure a highly readable, traceable, and standardized version history.

A comprehensive guide to understanding the complete state (context) available to Large Language Models during inference. Covers core components like System Prompts, Tool Definitions, Message History, and Retrieval Augmented Generation (RAG). Learning to engineer context is crucial for building robust, efficient, and reliable AI agent systems by managing the attention budget and ensuring high-signal information delivery.