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Use for voice assistants, conversational AI, real-time speech-to-speech, and voice-enabled chatbots. Triggers: \"voice live\", \"real-time voice\", \"VoiceLiveClient\", \"VoiceLiveSession\", \"voice assistant .NET\", \"bidirectional audio\", \"speech-to-speech\".","microsoft\u002Fskills","microsoft","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F6154722?v=4","01M698VYDXZ6JW5WH3CRV650R8","Microsoft","01M69AJYYW4E1RMSYCQDJ4FJSH",3195,"MIT","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fskills\u002Fblob\u002Fmain\u002F.github\u002Fplugins\u002Fazure-sdk-dotnet\u002Fskills\u002Fazure-ai-voicelive-dotnet\u002FSKILL.md",[18,23],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000016","图像与多媒体","SCENARIO","使用场景",{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",[27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,9,47],"dotnet","azure ai","azure","azure ai voicelive dotnet","applications","for","speech-to-speech","with","Conversational AI","triggers","live","time","build","use","Audio","assistant","real-time","websocket","speech","communication","sdk","2026-11-10 10:12:30",false,"---\nname: azure-ai-voicelive-dotnet\ndescription: |\n  Azure AI Voice Live SDK for .NET. Build real-time voice AI applications with bidirectional WebSocket communication. Use for voice assistants, conversational AI, real-time speech-to-speech, and voice-enabled chatbots. Triggers: \"voice live\", \"real-time voice\", \"VoiceLiveClient\", \"VoiceLiveSession\", \"voice assistant .NET\", \"bidirectional audio\", \"speech-to-speech\".\nlicense: MIT\nmetadata:\n  author: Microsoft\n  version: \"1.0.0\"\n  package: Azure.AI.VoiceLive\n---\n\n# Azure.AI.VoiceLive (.NET)\n\nReal-time voice AI SDK for building bidirectional voice assistants with Azure AI.\n\n## Installation\n\n```bash\ndotnet add package Azure.AI.VoiceLive\ndotnet add package Azure.Identity\ndotnet add package NAudio                    # For audio capture\u002Fplayback\n```\n\n**Current Versions**: Stable v1.0.0, Preview v1.1.0-beta.1\n\n## Environment Variables\n\n```bash\nAZURE_VOICELIVE_ENDPOINT=https:\u002F\u002F\u003Cresource>.services.ai.azure.com\u002F  # Required: Voice Live endpoint\nAZURE_VOICELIVE_MODEL=gpt-4o-realtime-preview  # Required: model deployment name\nAZURE_VOICELIVE_VOICE=en-US-AvaNeural  # Optional: Voice Live voice name\nAZURE_VOICELIVE_API_KEY=\u003Cyour-api-key>  # Only required for AzureKeyCredential auth\nAZURE_TOKEN_CREDENTIALS=prod  # Required only if DefaultAzureCredential is used in production\n```\n\n## Authentication\n\n### Microsoft Entra Token Credential\n\n```csharp\nusing Azure.Identity;\nusing Azure.AI.VoiceLive;\n\nUri endpoint = new Uri(\"https:\u002F\u002Fyour-resource.cognitiveservices.azure.com\");\n\u002F\u002F Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=\u003Cspecific_credential>\nvar credential = new DefaultAzureCredential(\n    DefaultAzureCredential.DefaultEnvironmentVariableName\n);\n\u002F\u002F Or use a specific credential directly in production:\n\u002F\u002F See https:\u002F\u002Flearn.microsoft.com\u002Fdotnet\u002Fapi\u002Foverview\u002Fazure\u002Fidentity-readme?view=azure-dotnet#credential-classes\n\u002F\u002F var credential = new ManagedIdentityCredential();\nVoiceLiveClient client = new VoiceLiveClient(endpoint, credential);\n```\n\n**Required Role**: `Cognitive Services User` (assign in Azure Portal → Access control)\n\n### API Key\n\n```csharp\nUri endpoint = new Uri(\"https:\u002F\u002Fyour-resource.cognitiveservices.azure.com\");\nAzureKeyCredential credential = new AzureKeyCredential(\"your-api-key\");\nVoiceLiveClient client = new VoiceLiveClient(endpoint, credential);\n```\n\n## Client Hierarchy\n\n```\nVoiceLiveClient\n└── VoiceLiveSession (WebSocket connection)\n    ├── ConfigureSessionAsync()\n    ├── GetUpdatesAsync() → SessionUpdate events\n    ├── AddItemAsync() → UserMessageItem, FunctionCallOutputItem\n    ├── SendAudioAsync()\n    └── StartResponseAsync()\n```\n\n## Core Workflow\n\n### 1. Start Session and Configure\n\n```csharp\nusing Azure.Identity;\nusing Azure.AI.VoiceLive;\n\nvar endpoint = new Uri(Environment.GetEnvironmentVariable(\"AZURE_VOICELIVE_ENDPOINT\"));\nvar client = new VoiceLiveClient(endpoint, new DefaultAzureCredential());\n\nvar model = \"gpt-4o-mini-realtime-preview\";\n\n\u002F\u002F Start session\nusing VoiceLiveSession session = await client.StartSessionAsync(model);\n\n\u002F\u002F Configure session\nVoiceLiveSessionOptions sessionOptions = new()\n{\n    Model = model,\n    Instructions = \"You are a helpful AI assistant. Respond naturally.\",\n    Voice = new AzureStandardVoice(\"en-US-AvaNeural\"),\n    TurnDetection = new AzureSemanticVadTurnDetection()\n    {\n        Threshold = 0.5f,\n        PrefixPadding = TimeSpan.FromMilliseconds(300),\n        SilenceDuration = TimeSpan.FromMilliseconds(500)\n    },\n    InputAudioFormat = InputAudioFormat.Pcm16,\n    OutputAudioFormat = OutputAudioFormat.Pcm16\n};\n\n\u002F\u002F Set modalities (both text and audio for voice assistants)\nsessionOptions.Modalities.Clear();\nsessionOptions.Modalities.Add(InteractionModality.Text);\nsessionOptions.Modalities.Add(InteractionModality.Audio);\n\nawait session.ConfigureSessionAsync(sessionOptions);\n```\n\n### 2. Process Events\n\n```csharp\nawait foreach (SessionUpdate serverEvent in session.GetUpdatesAsync())\n{\n    switch (serverEvent)\n    {\n        case SessionUpdateResponseAudioDelta audioDelta:\n            byte[] audioData = audioDelta.Delta.ToArray();\n            \u002F\u002F Play audio via NAudio or other audio library\n            break;\n            \n        case SessionUpdateResponseTextDelta textDelta:\n            Console.Write(textDelta.Delta);\n            break;\n            \n        case SessionUpdateResponseFunctionCallArgumentsDone functionCall:\n            \u002F\u002F Handle function call (see Function Calling section)\n            break;\n            \n        case SessionUpdateError error:\n            Console.WriteLine($\"Error: {error.Error.Message}\");\n            break;\n            \n        case SessionUpdateResponseDone:\n            Console.WriteLine(\"\\n--- Response complete ---\");\n            break;\n    }\n}\n```\n\n### 3. Send User Message\n\n```csharp\nawait session.AddItemAsync(new UserMessageItem(\"Hello, can you help me?\"));\nawait session.StartResponseAsync();\n```\n\n### 4. Function Calling\n\n```csharp\n\u002F\u002F Define function\nvar weatherFunction = new VoiceLiveFunctionDefinition(\"get_current_weather\")\n{\n    Description = \"Get the current weather for a given location\",\n    Parameters = BinaryData.FromString(\"\"\"\n        {\n            \"type\": \"object\",\n            \"properties\": {\n                \"location\": {\n                    \"type\": \"string\",\n                    \"description\": \"The city and state or country\"\n                }\n            },\n            \"required\": [\"location\"]\n        }\n        \"\"\")\n};\n\n\u002F\u002F Add to session options\nsessionOptions.Tools.Add(weatherFunction);\n\n\u002F\u002F Handle function call in event loop\nif (serverEvent is SessionUpdateResponseFunctionCallArgumentsDone functionCall)\n{\n    if (functionCall.Name == \"get_current_weather\")\n    {\n        var parameters = JsonSerializer.Deserialize\u003CDictionary\u003Cstring, string>>(functionCall.Arguments);\n        string location = parameters?[\"location\"] ?? \"\";\n        \n        \u002F\u002F Call external service\n        string weatherInfo = $\"The weather in {location} is sunny, 75°F.\";\n        \n        \u002F\u002F Send response\n        await session.AddItemAsync(new FunctionCallOutputItem(functionCall.CallId, weatherInfo));\n        await session.StartResponseAsync();\n    }\n}\n```\n\n## Voice Options\n\n| Voice Type | Class | Example |\n|------------|-------|---------|\n| Azure Standard | `AzureStandardVoice` | `\"en-US-AvaNeural\"` |\n| Azure HD | `AzureStandardVoice` | `\"en-US-Ava:DragonHDLatestNeural\"` |\n| Azure Custom | `AzureCustomVoice` | Custom voice with endpoint ID |\n\n## Supported Models\n\n| Model | Description |\n|-------|-------------|\n| `gpt-4o-realtime-preview` | GPT-4o with real-time audio |\n| `gpt-4o-mini-realtime-preview` | Lightweight, fast interactions |\n| `phi4-mm-realtime` | Cost-effective multimodal |\n\n## Key Types Reference\n\n| Type | Purpose |\n|------|---------|\n| `VoiceLiveClient` | Main client for creating sessions |\n| `VoiceLiveSession` | Active WebSocket session |\n| `VoiceLiveSessionOptions` | Session configuration |\n| `AzureStandardVoice` | Standard Azure voice provider |\n| `AzureSemanticVadTurnDetection` | Voice activity detection |\n| `VoiceLiveFunctionDefinition` | Function tool definition |\n| `UserMessageItem` | User text message |\n| `FunctionCallOutputItem` | Function call response |\n| `SessionUpdateResponseAudioDelta` | Audio chunk event |\n| `SessionUpdateResponseTextDelta` | Text chunk event |\n\n## Best Practices\n\n1. **Always set both modalities** — Include `Text` and `Audio` for voice assistants\n2. **Use `AzureSemanticVadTurnDetection`** — Provides natural conversation flow\n3. **Configure appropriate silence duration** — 500ms typical to avoid premature cutoffs\n4. **Use `using` statement** — Ensures proper session disposal\n5. **Handle all event types** — Check for errors, audio, text, and function calls\n6. **Use DefaultAzureCredential** — Never hardcode API keys\n\n## Error Handling\n\n```csharp\nif (serverEvent is SessionUpdateError error)\n{\n    if (error.Error.Message.Contains(\"Cancellation failed: no active response\"))\n    {\n        \u002F\u002F Benign error, can ignore\n    }\n    else\n    {\n        Console.WriteLine($\"Error: {error.Error.Message}\");\n    }\n}\n```\n\n## Audio Configuration\n\n- **Input Format**: `InputAudioFormat.Pcm16` (16-bit PCM)\n- **Output Format**: `OutputAudioFormat.Pcm16`\n- **Sample Rate**: 24kHz recommended\n- **Channels**: Mono\n\n## Related SDKs\n\n| SDK | Purpose | Install |\n|-----|---------|---------|\n| `Azure.AI.VoiceLive` | Real-time voice (this SDK) | `dotnet add package Azure.AI.VoiceLive` |\n| `Microsoft.CognitiveServices.Speech` | Speech-to-text, text-to-speech | `dotnet add package Microsoft.CognitiveServices.Speech` |\n| `NAudio` | Audio capture\u002Fplayback | `dotnet add package NAudio` |\n\n## Reference Links\n\n| Resource | URL |\n|----------|-----|\n| NuGet Package | https:\u002F\u002Fwww.nuget.org\u002Fpackages\u002FAzure.AI.VoiceLive |\n| API Reference | https:\u002F\u002Flearn.microsoft.com\u002Fdotnet\u002Fapi\u002Fazure.ai.voicelive |\n| GitHub Source | https:\u002F\u002Fgithub.com\u002FAzure\u002Fazure-sdk-for-net\u002Ftree\u002Fmain\u002Fsdk\u002Fai\u002FAzure.AI.VoiceLive |\n| Quickstart | https:\u002F\u002Flearn.microsoft.com\u002Fazure\u002Fai-services\u002Fspeech-service\u002Fvoice-live-quickstart |\n","# Azure.AI.VoiceLive (.NET)\n\nReal-time voice AI SDK for building bidirectional voice assistants with Azure AI.\n\n## Installation\n\n```bash\ndotnet add package Azure.AI.VoiceLive\ndotnet add package Azure.Identity\ndotnet add package NAudio                    # For audio capture\u002Fplayback\n```\n\n**Current Versions**: Stable v1.0.0, Preview v1.1.0-beta.1\n\n## Environment Variables\n\n```bash\nAZURE_VOICELIVE_ENDPOINT=https:\u002F\u002F\u003Cresource>.services.ai.azure.com\u002F  # Required: Voice Live endpoint\nAZURE_VOICELIVE_MODEL=gpt-4o-realtime-preview  # Required: model deployment name\nAZURE_VOICELIVE_VOICE=en-US-AvaNeural  # Optional: Voice Live voice name\nAZURE_VOICELIVE_API_KEY=\u003Cyour-api-key>  # Only required for AzureKeyCredential auth\nAZURE_TOKEN_CREDENTIALS=prod  # Required only if DefaultAzureCredential is used in production\n```\n\n## Authentication\n\n### Microsoft Entra Token Credential\n\n```csharp\nusing Azure.Identity;\nusing Azure.AI.VoiceLive;\n\nUri endpoint = new Uri(\"https:\u002F\u002Fyour-resource.cognitiveservices.azure.com\");\n\u002F\u002F Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=\u003Cspecific_credential>\nvar credential = new DefaultAzureCredential(\n    DefaultAzureCredential.DefaultEnvironmentVariableName\n);\n\u002F\u002F Or use a specific credential directly in production:\n\u002F\u002F See https:\u002F\u002Flearn.microsoft.com\u002Fdotnet\u002Fapi\u002Foverview\u002Fazure\u002Fidentity-readme?view=azure-dotnet#credential-classes\n\u002F\u002F var credential = new ManagedIdentityCredential();\nVoiceLiveClient client = new VoiceLiveClient(endpoint, credential);\n```\n\n**Required Role**: `Cognitive Services User` (assign in Azure Portal → Access control)\n\n### API Key\n\n```csharp\nUri endpoint = new Uri(\"https:\u002F\u002Fyour-resource.cognitiveservices.azure.com\");\nAzureKeyCredential credential = new AzureKeyCredential(\"your-api-key\");\nVoiceLiveClient client = new VoiceLiveClient(endpoint, credential);\n```\n\n## Client Hierarchy\n\n```\nVoiceLiveClient\n└── VoiceLiveSession (WebSocket connection)\n    ├── ConfigureSessionAsync()\n    ├── GetUpdatesAsync() → SessionUpdate events\n    ├── AddItemAsync() → UserMessageItem, FunctionCallOutputItem\n    ├── SendAudioAsync()\n    └── StartResponseAsync()\n```\n\n## Core Workflow\n\n### 1. Start Session and Configure\n\n```csharp\nusing Azure.Identity;\nusing Azure.AI.VoiceLive;\n\nvar endpoint = new Uri(Environment.GetEnvironmentVariable(\"AZURE_VOICELIVE_ENDPOINT\"));\nvar client = new VoiceLiveClient(endpoint, new DefaultAzureCredential());\n\nvar model = \"gpt-4o-mini-realtime-preview\";\n\n\u002F\u002F Start session\nusing VoiceLiveSession session = await client.StartSessionAsync(model);\n\n\u002F\u002F Configure session\nVoiceLiveSessionOptions sessionOptions = new()\n{\n    Model = model,\n    Instructions = \"You are a helpful AI assistant. Respond naturally.\",\n    Voice = new AzureStandardVoice(\"en-US-AvaNeural\"),\n    TurnDetection = new AzureSemanticVadTurnDetection()\n    {\n        Threshold = 0.5f,\n        PrefixPadding = TimeSpan.FromMilliseconds(300),\n        SilenceDuration = TimeSpan.FromMilliseconds(500)\n    },\n    InputAudioFormat = InputAudioFormat.Pcm16,\n    OutputAudioFormat = OutputAudioFormat.Pcm16\n};\n\n\u002F\u002F Set modalities (both text and audio for voice assistants)\nsessionOptions.Modalities.Clear();\nsessionOptions.Modalities.Add(InteractionModality.Text);\nsessionOptions.Modalities.Add(InteractionModality.Audio);\n\nawait session.ConfigureSessionAsync(sessionOptions);\n```\n\n### 2. Process Events\n\n```csharp\nawait foreach (SessionUpdate serverEvent in session.GetUpdatesAsync())\n{\n    switch (serverEvent)\n    {\n        case SessionUpdateResponseAudioDelta audioDelta:\n            byte[] audioData = audioDelta.Delta.ToArray();\n            \u002F\u002F Play audio via NAudio or other audio library\n            break;\n            \n        case SessionUpdateResponseTextDelta textDelta:\n            Console.Write(textDelta.Delta);\n            break;\n            \n        case SessionUpdateResponseFunctionCallArgumentsDone functionCall:\n            \u002F\u002F Handle function call (see Function Calling section)\n            break;\n            \n        case SessionUpdateError error:\n            Console.WriteLine($\"Error: {error.Error.Message}\");\n            break;\n            \n        case SessionUpdateResponseDone:\n            Console.WriteLine(\"\\n--- Response complete ---\");\n            break;\n    }\n}\n```\n\n### 3. Send User Message\n\n```csharp\nawait session.AddItemAsync(new UserMessageItem(\"Hello, can you help me?\"));\nawait session.StartResponseAsync();\n```\n\n### 4. Function Calling\n\n```csharp\n\u002F\u002F Define function\nvar weatherFunction = new VoiceLiveFunctionDefinition(\"get_current_weather\")\n{\n    Description = \"Get the current weather for a given location\",\n    Parameters = BinaryData.FromString(\"\"\"\n        {\n            \"type\": \"object\",\n            \"properties\": {\n                \"location\": {\n                    \"type\": \"string\",\n                    \"description\": \"The city and state or country\"\n                }\n            },\n            \"required\": [\"location\"]\n        }\n        \"\"\")\n};\n\n\u002F\u002F Add to session options\nsessionOptions.Tools.Add(weatherFunction);\n\n\u002F\u002F Handle function call in event loop\nif (serverEvent is SessionUpdateResponseFunctionCallArgumentsDone functionCall)\n{\n    if (functionCall.Name == \"get_current_weather\")\n    {\n        var parameters = JsonSerializer.Deserialize\u003CDictionary\u003Cstring, string>>(functionCall.Arguments);\n        string location = parameters?[\"location\"] ?? \"\";\n        \n        \u002F\u002F Call external service\n        string weatherInfo = $\"The weather in {location} is sunny, 75°F.\";\n        \n        \u002F\u002F Send response\n        await session.AddItemAsync(new FunctionCallOutputItem(functionCall.CallId, weatherInfo));\n        await session.StartResponseAsync();\n    }\n}\n```\n\n## Voice Options\n\n| Voice Type | Class | Example |\n|------------|-------|---------|\n| Azure Standard | `AzureStandardVoice` | `\"en-US-AvaNeural\"` |\n| Azure HD | `AzureStandardVoice` | `\"en-US-Ava:DragonHDLatestNeural\"` |\n| Azure Custom | `AzureCustomVoice` | Custom voice with endpoint ID |\n\n## Supported Models\n\n| Model | Description |\n|-------|-------------|\n| `gpt-4o-realtime-preview` | GPT-4o with real-time audio |\n| `gpt-4o-mini-realtime-preview` | Lightweight, fast interactions |\n| `phi4-mm-realtime` | Cost-effective multimodal |\n\n## Key Types Reference\n\n| Type | Purpose |\n|------|---------|\n| `VoiceLiveClient` | Main client for creating sessions |\n| `VoiceLiveSession` | Active WebSocket session |\n| `VoiceLiveSessionOptions` | Session configuration |\n| `AzureStandardVoice` | Standard Azure voice provider |\n| `AzureSemanticVadTurnDetection` | Voice activity detection |\n| `VoiceLiveFunctionDefinition` | Function tool definition |\n| `UserMessageItem` | User text message |\n| `FunctionCallOutputItem` | Function call response |\n| `SessionUpdateResponseAudioDelta` | Audio chunk event |\n| `SessionUpdateResponseTextDelta` | Text chunk event |\n\n## Best Practices\n\n1. **Always set both modalities** — Include `Text` and `Audio` for voice assistants\n2. **Use `AzureSemanticVadTurnDetection`** — Provides natural conversation flow\n3. **Configure appropriate silence duration** — 500ms typical to avoid premature cutoffs\n4. **Use `using` statement** — Ensures proper session disposal\n5. **Handle all event types** — Check for errors, audio, text, and function calls\n6. **Use DefaultAzureCredential** — Never hardcode API keys\n\n## Error Handling\n\n```csharp\nif (serverEvent is SessionUpdateError error)\n{\n    if (error.Error.Message.Contains(\"Cancellation failed: no active response\"))\n    {\n        \u002F\u002F Benign error, can ignore\n    }\n    else\n    {\n        Console.WriteLine($\"Error: {error.Error.Message}\");\n    }\n}\n```\n\n## Audio Configuration\n\n- **Input Format**: `InputAudioFormat.Pcm16` (16-bit PCM)\n- **Output Format**: `OutputAudioFormat.Pcm16`\n- **Sample Rate**: 24kHz recommended\n- **Channels**: Mono\n\n## Related SDKs\n\n| SDK | Purpose | Install |\n|-----|---------|---------|\n| `Azure.AI.VoiceLive` | Real-time voice (this SDK) | `dotnet add package Azure.AI.VoiceLive` |\n| `Microsoft.CognitiveServices.Speech` | Speech-to-text, text-to-speech | `dotnet add package Microsoft.CognitiveServices.Speech` |\n| `NAudio` | Audio capture\u002Fplayback | `dotnet add package NAudio` |\n\n## Reference Links\n\n| Resource | URL |\n|----------|-----|\n| NuGet Package | https:\u002F\u002Fwww.nuget.org\u002Fpackages\u002FAzure.AI.VoiceLive |\n| API Reference | https:\u002F\u002Flearn.microsoft.com\u002Fdotnet\u002Fapi\u002Fazure.ai.voicelive |\n| GitHub Source | https:\u002F\u002Fgithub.com\u002FAzure\u002Fazure-sdk-for-net\u002Ftree\u002Fmain\u002Fsdk\u002Fai\u002FAzure.AI.VoiceLive |\n| Quickstart | https:\u002F\u002Flearn.microsoft.com\u002Fazure\u002Fai-services\u002Fspeech-service\u002Fvoice-live-quickstart |\n",{"name":5,"license":15,"metadata":53,"description":56},{"author":12,"package":54,"version":55},"Azure.AI.VoiceLive","1.0.0","Azure AI Voice Live SDK for .NET. 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Use when creating new skills or updating existing skills.","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fskills\u002Fblob\u002Fmain\u002F.github\u002Fskills\u002Fskill-creator\u002FSKILL.md",[88],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[90,91,92,9,93,94,95,29,96,97,98,40,99,34,100,32,101,102,103],"skill creator","creator","coding agents","foundry","microsoft foundry","ai coding agents","services","coding","guide","ai coding","sdks","Existing","when","new",{"skillNo":105,"name":106,"nameZh":6,"description":107,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":108,"categories":109,"keywords":118,"publishedAt":48},"01M69B4FD57V1MYKRWAJJECTZ7","podcast-generation","Generate AI-powered podcast-style audio narratives using Azure OpenAI's GPT Realtime Mini model via WebSocket. Use when building text-to-speech features, audio narrative generation, podcast creation from content, or integrating with Azure OpenAI Realtime API for real audio output. Covers full-stack implementation from React frontend to Python FastAPI backend with WebSocket streaming.","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fskills\u002Fblob\u002Fmain\u002F.github\u002Fskills\u002Fpodcast-generation\u002FSKILL.md",[110,113,116,117],{"categoryNo":111,"categoryName":112,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000009","前端开发",{"categoryNo":114,"categoryName":115,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000010","后端与接口",{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[119,120,121,122,123,124,125,29,126,127,128,129,41,130,131,132,133,134,135,136,137,102,138],"podcast generation","podcast","generation","frontend","python","react","realtime","azure openai","generate","streaming","api","stack","text","model","fastapi","creation","python fastapi","narrative","features","fastapi backend",{"skillNo":140,"name":141,"nameZh":6,"description":142,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":143,"categories":144,"keywords":146,"publishedAt":48},"01M69B4CYPM5SESY5ZWEFDXEQZ","microsoft-docs","Understand Microsoft technologies by querying official documentation. Use whenever the user asks how something works, wants tutorials, needs configuration options, limits, quotas, or best practices for any Microsoft technology (Azure, .NET, M365, Windows, Power Platform, etc.)—even if they don't mention \"docs.\" If the question is about understanding a concept rather than writing code, this is the right skill.","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fskills\u002Fblob\u002Fmain\u002F.github\u002Fskills\u002Fmicrosoft-docs\u002FSKILL.md",[145],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[147,9,148,149,150,151,152,153,154,155,156,29,157,158,159,40,160,70,161,162,163,164,165,32],"docs","microsoft docs","MCP","writing","cli","mcp server","windows","power platform","official","documentation","learn","best practices","question","power","back","technology","platform","learn mcp","concept",{"skillNo":167,"name":168,"nameZh":6,"description":169,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":170,"categories":171,"keywords":173,"publishedAt":48},"01M69B49C3YPD1ZJ3NC0HPCY58","mcp-builder","Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP), Node\u002FTypeScript (MCP SDK), or C#\u002F.NET (Microsoft MCP SDK).","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fskills\u002Fblob\u002Fmain\u002F.github\u002Fskills\u002Fmcp-builder\u002FSKILL.md",[172],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[149,174,175,176,123,177,47,178,9,179,180,132,181,182,98,40,183,184,185,34,32,102],"mcp builder","builder","typescript","llms","model context protocol","fastmcp","Tools","node","context","integrate","mcp sdk","building mcp servers",{"skillNo":187,"name":188,"nameZh":6,"description":189,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":190,"categories":191,"keywords":204,"publishedAt":48},"01M69B467A7CDMFQ0T6Q0ZA12Q","kql","KQL language expertise for writing correct, efficient Kusto Query Language queries. Covers syntax gotchas, join patterns, dynamic types, datetime pitfalls, regex patterns, serialization, memory management, result-size discipline, and advanced functions (geo, vector, graph). USE THIS SKILL whenever writing, debugging, or reviewing KQL queries — even simple ones — because the gotchas section prevents the most common errors that waste tool calls and cause expensive retry cascades. Trigger on: KQL, Kusto, ADX, Azure Data Explorer, Fabric Real-Time Intelligence, EventHouse, Log Analytics, log analysis, data exploration, time series, anomaly detection, summarize, where clause, join, extend, project, let statement, parse operator, extract function, any mention of pipe-forward query syntax.","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fskills\u002Fblob\u002Fmain\u002F.github\u002Fskills\u002Fkql\u002FSKILL.md",[192,195,196,201],{"categoryNo":193,"categoryName":194,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":197,"categoryName":198,"taxonomyType":199,"taxonomyTypeDesc":200},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",{"categoryNo":202,"categoryName":203,"taxonomyType":199,"taxonomyTypeDesc":200},"01JBSEEDCAT000000000000036","内容创作者",[188,150,205,206,207,29,208,209,210,211,212,213,214,215,38,216,217,218,219,32,220,221,222],"summarize","memory","analytics","vector","time series","tool","discipline","log","geo","exploration","pipe","project","regex","join","datetime","section","anomaly","parse",{"skillNo":224,"name":225,"nameZh":6,"description":226,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":227,"categories":228,"keywords":229,"publishedAt":48},"01M69B44HJQ7897EZ7NE7DWQX3","github-issue-creator","Convert raw notes, error logs, voice dictation, or screenshots into crisp GitHub-flavored markdown issue reports. Use when the user pastes bug info, error messages, or informal descriptions and wants a structured GitHub issue. Supports images\u002FGIFs for visual evidence.","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fskills\u002Fblob\u002Fmain\u002F.github\u002Fskills\u002Fgithub-issue-creator\u002FSKILL.md",[],[230,231,232,233,91,234,235,236,237,238,239,240,40,241,242,243,244,245,246,32,102],"github","github issue creator","github issue","issue","issue creator","screenshots","notes","logs","error messages","messages","convert","evidence","reports","images","info","visual","error"]