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Combine tools for research, reference management, notes, document creation, and publishing. Agents check available software and credentials, then choose suitable tools based on output requirements, costs, and offline needs to build a complete workflow.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Review literature and organize references
• Research, write, and publish a blog post
• Turn competitor research into a presentation

Plan game development workflows by matching engines, art and audio tools, automated playtests, packaging, publishing, and analytics to available tools and credentials. Compare options by cost, quality requirements, and offline availability.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Plan a small Godot game for a game jam
• Combine AI-generated art with a simple game loop
• Choose tools for automated agent playtesting

Plan video production and combine tools for footage search, capture, generation, audio, analysis, and captions. Select tools for each task based on quality, budget, available credentials, and offline needs, with guidance for source rights and review.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Turning a video concept into a script and storyboard
• Finding footage and music while recording usage rights
• Planning narration, music, and sound effects

Send prompts to Novita AI models such as DeepSeek and GLM from the command line. Retrieve answers as readable text or structured JSON, stream responses as they arrive, and check available models and API connectivity.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Send questions to DeepSeek or GLM
• Display responses as they arrive
• Retrieve AI responses as JSON

Design how an AI agent trims long conversations and large tool outputs while retaining decisions, constraints, failed approaches, and sources. Compare summarization strategies, choose compression triggers, and consider separate subagents to keep intermediate information out of the main conversation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Managing large search results and tool outputs
• Preserving decisions and constraints during summarization
• Choosing compression triggers and batch processing

Gather scholarly evidence for a scientific manuscript or research brief. Organize supporting and conflicting findings into references, study comparison tables, and claim-to-source maps, with search records and coverage reports that help identify gaps requiring further review.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Gather background literature for a manuscript
• Compare supporting, conflicting, and null findings
• Build study comparison tables and claim-to-source maps

Organize research sources in self-hosted Open Notebook, then search them, ask questions with citations, create notes, transform text, or generate podcasts with multiple speakers. Supports REST API automation and configuration of local or cloud AI providers.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Collect PDFs and web sources in a research notebook
• Ask questions about selected sources with citations
• Apply custom summaries and text transformations

Plan and audit HypoGeniC workflows that use language models to propose patterns from labeled text. Check configurations, dataset splits, cost limits, and saved predictions while keeping candidate hypotheses separate from scientific confirmation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing task settings before a HypoGeniC run
• Checking duplicates across training and test data
• Estimating token and cost limits before model calls

Convert PDF, Office, and other documents into Markdown that preserves useful text structure. Use batch conversion and literature organization to prepare files for search, text analysis, or AI systems that retrieve information from documents.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Convert PDF and Office files to Markdown
• Batch-convert a document folder
• Organize research papers with source metadata

Generate photos, illustrations, logos, and presentation visuals through the OpenRouter Image API. Edit or combine reference images, choose among supported models, and check available settings such as resolution, output format, and transparency before generation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating illustrations and visuals for slides or posters
• Editing colors or styles in existing images
• Combining multiple reference images

Plan how an AI application should use Hindsight memory. Identify useful information to retain, define user-scoping tags and memory bank settings, and specify how retrieved facts and synthesized knowledge should reach the model.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Plan memory that carries conversation context across sessions
• Design tags that separate each user's memories
• Plan summaries of customer preferences and recurring issues

Review changed code against project rules and report missing tests, unused code, typing problems, and style violations. It also checks API design and data isolation, helping developers identify issues after implementation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing changes after implementation
• Finding missing tests and unused code
• Checking Python types and API design

Retrieve academic full texts and supporting files through open access, publisher APIs, or authorized institutional access. The skill selects a route for each paper, checks downloaded files, and records sources, formats, and download outcomes.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Download papers from a confirmed DOI list
• Find legally available open-access full texts
• Retrieve Chinese papers through institutional CNKI access

Summarize web articles, YouTube videos, podcasts, and local files with the summarize command-line tool. Extract available text or transcripts from URLs, choose a summary length, and request JSON output for use in other workflows.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Get the main points of a web article
• Summarize a YouTube video
• Extract an available video transcript

Build real-time voice assistants in .NET with Azure AI. Covers two-way audio communication, text and audio responses, detecting when a speaker finishes, and calling functions to connect conversations with external services.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build a real-time voice assistant in .NET
• Configure voices and detect when speakers finish
• Connect voice conversations to external services

Prepare and verify application deployments to Azure Container Apps using azd and Bicep. Review environment settings, remote builds, identity permissions, and deployment changes, then check running revisions, service health, and frontend-to-backend connections.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing azure.yaml and Bicep before deployment
• Checking remote builds and image architecture
• Configuring managed identity and resource permissions

Implement .NET workflows for Azure AI Foundry projects, including agent creation, resource connections, dataset uploads, model deployment inspection, search index management, and evaluations. Examples also cover authentication, asynchronous operations, and resource cleanup.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating and running agents from a .NET application
• Inspecting resource connections and model deployments
• Uploading datasets and managing search indexes

Build Java applications that exchange live audio with AI assistants using Azure AI VoiceLive. The skill covers authentication, streaming sessions, speech detection, voice selection, transcription, and handling responses over WebSocket, a persistent two-way connection.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Implementing a real-time voice assistant in Java
• Configuring speech detection and interruptions
• Adding transcription and noise reduction

Build TypeScript code for Azure AI Foundry projects using its SDK, a library for accessing project services. Create and run agents, inspect connections and deployed models, and manage datasets and search indexes.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating and running agents in TypeScript
• Adding file search or external tools to agents
• Inspecting project connections and deployed models

Help implement Azure OpenAI features in C# and .NET applications using SDK examples. Cover authentication, chat, document-backed answers, image generation, and audio processing, including transcription and speech generation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Adding streaming chat to a .NET application
• Generating JSON responses in a defined format
• Building answers backed by Azure AI Search

Build real-time voice assistants in JavaScript or TypeScript using Azure AI Voice Live. Covers two-way audio streaming, authentication, speech turn detection, transcription events, and calling application functions during conversations in Node.js or browsers.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build a voice assistant in Node.js
• Stream microphone audio from a browser
• Configure speech boundaries and transcription events

Build real-time voice applications in Python with Azure AI Voice Live. Covers two-way audio streaming, transcripts, conversation history, and handling interruptions, with examples for authentication and configuring when the assistant responds.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build a voice assistant in Python
• Display transcripts during voice conversations
• Stop an audio response when the user interrupts

Implement Java workflows for Azure AI Foundry projects using SDK examples for authentication, connected resources, datasets, search indexes, and model evaluations. The skill also covers client setup, paginated resource lists, and error handling.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• List connected Azure resources
• Create or update search indexes
• Implement access to model evaluations

Build Python AI applications on Microsoft Foundry with azure-ai-projects. Provides examples for creating agents, connecting tools, managing conversations and project resources, and running evaluations through Foundry and OpenAI-compatible clients.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build an agent that searches uploaded documents
• Implement conversation threads and response handling
• List model deployments and project connections