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Real-time bidirectional voice conversations with AI assistants using WebSocket.\n  Triggers: \"VoiceLiveClient java\", \"voice assistant java\", \"real-time voice java\", \"audio streaming java\", \"voice activity detection java\".\nlicense: MIT\nmetadata:\n  author: Microsoft\n  version: \"1.0.0\"\n  package: com.azure:azure-ai-voicelive\n---\n\n# Azure AI VoiceLive SDK for Java\n\nReal-time, bidirectional voice conversations with AI assistants using WebSocket technology.\n\n## Installation\n\n```xml\n\u003Cdependency>\n    \u003CgroupId>com.azure\u003C\u002FgroupId>\n    \u003CartifactId>azure-ai-voicelive\u003C\u002FartifactId>\n    \u003Cversion>1.0.0-beta.2\u003C\u002Fversion>\n\u003C\u002Fdependency>\n```\n\n## Environment Variables\n\n```bash\nAZURE_VOICELIVE_ENDPOINT=https:\u002F\u002F\u003Cresource>.openai.azure.com\u002F # Required for all auth methods\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### API Key\n\n```java\nimport com.azure.ai.voicelive.VoiceLiveAsyncClient;\nimport com.azure.ai.voicelive.VoiceLiveClientBuilder;\nimport com.azure.core.credential.AzureKeyCredential;\n\nVoiceLiveAsyncClient client = new VoiceLiveClientBuilder()\n    .endpoint(System.getenv(\"AZURE_VOICELIVE_ENDPOINT\"))\n    .credential(new AzureKeyCredential(System.getenv(\"AZURE_VOICELIVE_API_KEY\")))\n    .buildAsyncClient();\n```\n\n### DefaultAzureCredential (Recommended)\n\n```java\nimport com.azure.core.credential.TokenCredential;\nimport com.azure.identity.AzureIdentityEnvVars;\nimport com.azure.identity.DefaultAzureCredentialBuilder;\nimport com.azure.identity.ManagedIdentityCredentialBuilder;\n\nTokenCredential credential = new DefaultAzureCredentialBuilder()\n    .requireEnvVars(AzureIdentityEnvVars.AZURE_TOKEN_CREDENTIALS)\n    .build();\n\u002F\u002F Or use a specific credential directly in production:\n\u002F\u002F See https:\u002F\u002Flearn.microsoft.com\u002Fjava\u002Fapi\u002Foverview\u002Fazure\u002Fidentity-readme?view=azure-java-stable#credential-classes\n\u002F\u002F TokenCredential credential = new ManagedIdentityCredentialBuilder().build();\n\nVoiceLiveAsyncClient client = new VoiceLiveClientBuilder()\n    .endpoint(System.getenv(\"AZURE_VOICELIVE_ENDPOINT\"))\n    .credential(credential)\n    .buildAsyncClient();\n```\n\n## Key Concepts\n\n| Concept | Description |\n|---------|-------------|\n| `VoiceLiveAsyncClient` | Main entry point for voice sessions |\n| `VoiceLiveSessionAsyncClient` | Active WebSocket connection for streaming |\n| `VoiceLiveSessionOptions` | Configuration for session behavior |\n\n### Audio Requirements\n\n- **Sample Rate**: 24kHz (24000 Hz)\n- **Bit Depth**: 16-bit PCM\n- **Channels**: Mono (1 channel)\n- **Format**: Signed PCM, little-endian\n\n## Core Workflow\n\n### 1. Start Session\n\n```java\nimport reactor.core.publisher.Mono;\n\nclient.startSession(\"gpt-4o-realtime-preview\")\n    .flatMap(session -> {\n        System.out.println(\"Session started\");\n        \n        \u002F\u002F Subscribe to events\n        session.receiveEvents()\n            .subscribe(\n                event -> System.out.println(\"Event: \" + event.getType()),\n                error -> System.err.println(\"Error: \" + error.getMessage())\n            );\n        \n        return Mono.just(session);\n    })\n    .block();\n```\n\n### 2. Configure Session Options\n\n```java\nimport com.azure.ai.voicelive.models.*;\nimport java.util.Arrays;\n\nServerVadTurnDetection turnDetection = new ServerVadTurnDetection()\n    .setThreshold(0.5)                    \u002F\u002F Sensitivity (0.0-1.0)\n    .setPrefixPaddingMs(300)              \u002F\u002F Audio before speech\n    .setSilenceDurationMs(500)            \u002F\u002F Silence to end turn\n    .setInterruptResponse(true)           \u002F\u002F Allow interruptions\n    .setAutoTruncate(true)\n    .setCreateResponse(true);\n\nAudioInputTranscriptionOptions transcription = new AudioInputTranscriptionOptions(\n    AudioInputTranscriptionOptionsModel.WHISPER_1);\n\nVoiceLiveSessionOptions options = new VoiceLiveSessionOptions()\n    .setInstructions(\"You are a helpful AI voice assistant.\")\n    .setVoice(BinaryData.fromObject(new OpenAIVoice(OpenAIVoiceName.ALLOY)))\n    .setModalities(Arrays.asList(InteractionModality.TEXT, InteractionModality.AUDIO))\n    .setInputAudioFormat(InputAudioFormat.PCM16)\n    .setOutputAudioFormat(OutputAudioFormat.PCM16)\n    .setInputAudioSamplingRate(24000)\n    .setInputAudioNoiseReduction(new AudioNoiseReduction(AudioNoiseReductionType.NEAR_FIELD))\n    .setInputAudioEchoCancellation(new AudioEchoCancellation())\n    .setInputAudioTranscription(transcription)\n    .setTurnDetection(turnDetection);\n\n\u002F\u002F Send configuration\nClientEventSessionUpdate updateEvent = new ClientEventSessionUpdate(options);\nsession.sendEvent(updateEvent).subscribe();\n```\n\n### 3. Send Audio Input\n\n```java\nbyte[] audioData = readAudioChunk(); \u002F\u002F Your PCM16 audio data\nsession.sendInputAudio(BinaryData.fromBytes(audioData)).subscribe();\n```\n\n### 4. Handle Events\n\n```java\nsession.receiveEvents().subscribe(event -> {\n    ServerEventType eventType = event.getType();\n    \n    if (ServerEventType.SESSION_CREATED.equals(eventType)) {\n        System.out.println(\"Session created\");\n    } else if (ServerEventType.INPUT_AUDIO_BUFFER_SPEECH_STARTED.equals(eventType)) {\n        System.out.println(\"User started speaking\");\n    } else if (ServerEventType.INPUT_AUDIO_BUFFER_SPEECH_STOPPED.equals(eventType)) {\n        System.out.println(\"User stopped speaking\");\n    } else if (ServerEventType.RESPONSE_AUDIO_DELTA.equals(eventType)) {\n        if (event instanceof SessionUpdateResponseAudioDelta) {\n            SessionUpdateResponseAudioDelta audioEvent = (SessionUpdateResponseAudioDelta) event;\n            playAudioChunk(audioEvent.getDelta());\n        }\n    } else if (ServerEventType.RESPONSE_DONE.equals(eventType)) {\n        System.out.println(\"Response complete\");\n    } else if (ServerEventType.ERROR.equals(eventType)) {\n        if (event instanceof SessionUpdateError) {\n            SessionUpdateError errorEvent = (SessionUpdateError) event;\n            System.err.println(\"Error: \" + errorEvent.getError().getMessage());\n        }\n    }\n});\n```\n\n## Voice Configuration\n\n### OpenAI Voices\n\n```java\n\u002F\u002F Available: ALLOY, ASH, BALLAD, CORAL, ECHO, SAGE, SHIMMER, VERSE\nVoiceLiveSessionOptions options = new VoiceLiveSessionOptions()\n    .setVoice(BinaryData.fromObject(new OpenAIVoice(OpenAIVoiceName.ALLOY)));\n```\n\n### Azure Voices\n\n```java\n\u002F\u002F Azure Standard Voice\noptions.setVoice(BinaryData.fromObject(new AzureStandardVoice(\"en-US-JennyNeural\")));\n\n\u002F\u002F Azure Custom Voice\noptions.setVoice(BinaryData.fromObject(new AzureCustomVoice(\"myVoice\", \"endpointId\")));\n\n\u002F\u002F Azure Personal Voice\noptions.setVoice(BinaryData.fromObject(\n    new AzurePersonalVoice(\"speakerProfileId\", PersonalVoiceModels.PHOENIX_LATEST_NEURAL)));\n```\n\n## Function Calling\n\n```java\nVoiceLiveFunctionDefinition weatherFunction = new VoiceLiveFunctionDefinition(\"get_weather\")\n    .setDescription(\"Get current weather for a location\")\n    .setParameters(BinaryData.fromObject(parametersSchema));\n\nVoiceLiveSessionOptions options = new VoiceLiveSessionOptions()\n    .setTools(Arrays.asList(weatherFunction))\n    .setInstructions(\"You have access to weather information.\");\n```\n\n## Best Practices\n\n1. **Use async client** — VoiceLive requires reactive patterns\n2. **Configure turn detection** for natural conversation flow\n3. **Enable noise reduction** for better speech recognition\n4. **Handle interruptions** gracefully with `setInterruptResponse(true)`\n5. **Use Whisper transcription** for input audio transcription\n6. **Close sessions** properly when conversation ends\n\n## Error Handling\n\n```java\nsession.receiveEvents()\n    .doOnError(error -> System.err.println(\"Connection error: \" + error.getMessage()))\n    .onErrorResume(error -> {\n        \u002F\u002F Attempt reconnection or cleanup\n        return Flux.empty();\n    })\n    .subscribe();\n```\n\n## Reference Links\n\n| Resource | URL |\n|----------|-----|\n| GitHub Source | https:\u002F\u002Fgithub.com\u002FAzure\u002Fazure-sdk-for-java\u002Ftree\u002Fmain\u002Fsdk\u002Fai\u002Fazure-ai-voicelive |\n| Samples | https:\u002F\u002Fgithub.com\u002FAzure\u002Fazure-sdk-for-java\u002Ftree\u002Fmain\u002Fsdk\u002Fai\u002Fazure-ai-voicelive\u002Fsrc\u002Fsamples |\n","# Azure AI VoiceLive SDK for Java\n\nReal-time, bidirectional voice conversations with AI assistants using WebSocket technology.\n\n## Installation\n\n```xml\n\u003Cdependency>\n    \u003CgroupId>com.azure\u003C\u002FgroupId>\n    \u003CartifactId>azure-ai-voicelive\u003C\u002FartifactId>\n    \u003Cversion>1.0.0-beta.2\u003C\u002Fversion>\n\u003C\u002Fdependency>\n```\n\n## Environment Variables\n\n```bash\nAZURE_VOICELIVE_ENDPOINT=https:\u002F\u002F\u003Cresource>.openai.azure.com\u002F # Required for all auth methods\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### API Key\n\n```java\nimport com.azure.ai.voicelive.VoiceLiveAsyncClient;\nimport com.azure.ai.voicelive.VoiceLiveClientBuilder;\nimport com.azure.core.credential.AzureKeyCredential;\n\nVoiceLiveAsyncClient client = new VoiceLiveClientBuilder()\n    .endpoint(System.getenv(\"AZURE_VOICELIVE_ENDPOINT\"))\n    .credential(new AzureKeyCredential(System.getenv(\"AZURE_VOICELIVE_API_KEY\")))\n    .buildAsyncClient();\n```\n\n### DefaultAzureCredential (Recommended)\n\n```java\nimport com.azure.core.credential.TokenCredential;\nimport com.azure.identity.AzureIdentityEnvVars;\nimport com.azure.identity.DefaultAzureCredentialBuilder;\nimport com.azure.identity.ManagedIdentityCredentialBuilder;\n\nTokenCredential credential = new DefaultAzureCredentialBuilder()\n    .requireEnvVars(AzureIdentityEnvVars.AZURE_TOKEN_CREDENTIALS)\n    .build();\n\u002F\u002F Or use a specific credential directly in production:\n\u002F\u002F See https:\u002F\u002Flearn.microsoft.com\u002Fjava\u002Fapi\u002Foverview\u002Fazure\u002Fidentity-readme?view=azure-java-stable#credential-classes\n\u002F\u002F TokenCredential credential = new ManagedIdentityCredentialBuilder().build();\n\nVoiceLiveAsyncClient client = new VoiceLiveClientBuilder()\n    .endpoint(System.getenv(\"AZURE_VOICELIVE_ENDPOINT\"))\n    .credential(credential)\n    .buildAsyncClient();\n```\n\n## Key Concepts\n\n| Concept | Description |\n|---------|-------------|\n| `VoiceLiveAsyncClient` | Main entry point for voice sessions |\n| `VoiceLiveSessionAsyncClient` | Active WebSocket connection for streaming |\n| `VoiceLiveSessionOptions` | Configuration for session behavior |\n\n### Audio Requirements\n\n- **Sample Rate**: 24kHz (24000 Hz)\n- **Bit Depth**: 16-bit PCM\n- **Channels**: Mono (1 channel)\n- **Format**: Signed PCM, little-endian\n\n## Core Workflow\n\n### 1. Start Session\n\n```java\nimport reactor.core.publisher.Mono;\n\nclient.startSession(\"gpt-4o-realtime-preview\")\n    .flatMap(session -> {\n        System.out.println(\"Session started\");\n        \n        \u002F\u002F Subscribe to events\n        session.receiveEvents()\n            .subscribe(\n                event -> System.out.println(\"Event: \" + event.getType()),\n                error -> System.err.println(\"Error: \" + error.getMessage())\n            );\n        \n        return Mono.just(session);\n    })\n    .block();\n```\n\n### 2. Configure Session Options\n\n```java\nimport com.azure.ai.voicelive.models.*;\nimport java.util.Arrays;\n\nServerVadTurnDetection turnDetection = new ServerVadTurnDetection()\n    .setThreshold(0.5)                    \u002F\u002F Sensitivity (0.0-1.0)\n    .setPrefixPaddingMs(300)              \u002F\u002F Audio before speech\n    .setSilenceDurationMs(500)            \u002F\u002F Silence to end turn\n    .setInterruptResponse(true)           \u002F\u002F Allow interruptions\n    .setAutoTruncate(true)\n    .setCreateResponse(true);\n\nAudioInputTranscriptionOptions transcription = new AudioInputTranscriptionOptions(\n    AudioInputTranscriptionOptionsModel.WHISPER_1);\n\nVoiceLiveSessionOptions options = new VoiceLiveSessionOptions()\n    .setInstructions(\"You are a helpful AI voice assistant.\")\n    .setVoice(BinaryData.fromObject(new OpenAIVoice(OpenAIVoiceName.ALLOY)))\n    .setModalities(Arrays.asList(InteractionModality.TEXT, InteractionModality.AUDIO))\n    .setInputAudioFormat(InputAudioFormat.PCM16)\n    .setOutputAudioFormat(OutputAudioFormat.PCM16)\n    .setInputAudioSamplingRate(24000)\n    .setInputAudioNoiseReduction(new AudioNoiseReduction(AudioNoiseReductionType.NEAR_FIELD))\n    .setInputAudioEchoCancellation(new AudioEchoCancellation())\n    .setInputAudioTranscription(transcription)\n    .setTurnDetection(turnDetection);\n\n\u002F\u002F Send configuration\nClientEventSessionUpdate updateEvent = new ClientEventSessionUpdate(options);\nsession.sendEvent(updateEvent).subscribe();\n```\n\n### 3. Send Audio Input\n\n```java\nbyte[] audioData = readAudioChunk(); \u002F\u002F Your PCM16 audio data\nsession.sendInputAudio(BinaryData.fromBytes(audioData)).subscribe();\n```\n\n### 4. Handle Events\n\n```java\nsession.receiveEvents().subscribe(event -> {\n    ServerEventType eventType = event.getType();\n    \n    if (ServerEventType.SESSION_CREATED.equals(eventType)) {\n        System.out.println(\"Session created\");\n    } else if (ServerEventType.INPUT_AUDIO_BUFFER_SPEECH_STARTED.equals(eventType)) {\n        System.out.println(\"User started speaking\");\n    } else if (ServerEventType.INPUT_AUDIO_BUFFER_SPEECH_STOPPED.equals(eventType)) {\n        System.out.println(\"User stopped speaking\");\n    } else if (ServerEventType.RESPONSE_AUDIO_DELTA.equals(eventType)) {\n        if (event instanceof SessionUpdateResponseAudioDelta) {\n            SessionUpdateResponseAudioDelta audioEvent = (SessionUpdateResponseAudioDelta) event;\n            playAudioChunk(audioEvent.getDelta());\n        }\n    } else if (ServerEventType.RESPONSE_DONE.equals(eventType)) {\n        System.out.println(\"Response complete\");\n    } else if (ServerEventType.ERROR.equals(eventType)) {\n        if (event instanceof SessionUpdateError) {\n            SessionUpdateError errorEvent = (SessionUpdateError) event;\n            System.err.println(\"Error: \" + errorEvent.getError().getMessage());\n        }\n    }\n});\n```\n\n## Voice Configuration\n\n### OpenAI Voices\n\n```java\n\u002F\u002F Available: ALLOY, ASH, BALLAD, CORAL, ECHO, SAGE, SHIMMER, VERSE\nVoiceLiveSessionOptions options = new VoiceLiveSessionOptions()\n    .setVoice(BinaryData.fromObject(new OpenAIVoice(OpenAIVoiceName.ALLOY)));\n```\n\n### Azure Voices\n\n```java\n\u002F\u002F Azure Standard Voice\noptions.setVoice(BinaryData.fromObject(new AzureStandardVoice(\"en-US-JennyNeural\")));\n\n\u002F\u002F Azure Custom Voice\noptions.setVoice(BinaryData.fromObject(new AzureCustomVoice(\"myVoice\", \"endpointId\")));\n\n\u002F\u002F Azure Personal Voice\noptions.setVoice(BinaryData.fromObject(\n    new AzurePersonalVoice(\"speakerProfileId\", PersonalVoiceModels.PHOENIX_LATEST_NEURAL)));\n```\n\n## Function Calling\n\n```java\nVoiceLiveFunctionDefinition weatherFunction = new VoiceLiveFunctionDefinition(\"get_weather\")\n    .setDescription(\"Get current weather for a location\")\n    .setParameters(BinaryData.fromObject(parametersSchema));\n\nVoiceLiveSessionOptions options = new VoiceLiveSessionOptions()\n    .setTools(Arrays.asList(weatherFunction))\n    .setInstructions(\"You have access to weather information.\");\n```\n\n## Best Practices\n\n1. **Use async client** — VoiceLive requires reactive patterns\n2. **Configure turn detection** for natural conversation flow\n3. **Enable noise reduction** for better speech recognition\n4. **Handle interruptions** gracefully with `setInterruptResponse(true)`\n5. **Use Whisper transcription** for input audio transcription\n6. **Close sessions** properly when conversation ends\n\n## Error Handling\n\n```java\nsession.receiveEvents()\n    .doOnError(error -> System.err.println(\"Connection error: \" + error.getMessage()))\n    .onErrorResume(error -> {\n        \u002F\u002F Attempt reconnection or cleanup\n        return Flux.empty();\n    })\n    .subscribe();\n```\n\n## Reference Links\n\n| Resource | URL |\n|----------|-----|\n| GitHub Source | https:\u002F\u002Fgithub.com\u002FAzure\u002Fazure-sdk-for-java\u002Ftree\u002Fmain\u002Fsdk\u002Fai\u002Fazure-ai-voicelive |\n| Samples | https:\u002F\u002Fgithub.com\u002FAzure\u002Fazure-sdk-for-java\u002Ftree\u002Fmain\u002Fsdk\u002Fai\u002Fazure-ai-voicelive\u002Fsrc\u002Fsamples |\n",{"name":5,"license":15,"metadata":51,"description":54},{"author":12,"package":52,"version":53},"com.azure:azure-ai-voicelive","1.0.0","Azure AI VoiceLive SDK for Java. 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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",[121,124,127,128],{"categoryNo":122,"categoryName":123,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000009","前端开发",{"categoryNo":125,"categoryName":126,"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},[130,131,132,133,134,135,136,28,137,138,44,139,40,140,141,142,143,144,145,146,147,113,148],"podcast generation","podcast","generation","frontend","python","react","realtime","azure openai","generate","api","stack","text","model","fastapi","creation","python fastapi","narrative","features","fastapi backend",{"skillNo":150,"name":151,"nameZh":6,"description":152,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":153,"categories":154,"keywords":156,"publishedAt":46},"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",[155],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[157,9,158,159,160,161,162,163,164,165,166,28,167,168,169,109,170,68,171,172,173,174,175,32],"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":177,"name":178,"nameZh":6,"description":179,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":180,"categories":181,"keywords":183,"publishedAt":46},"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",[182],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[159,184,185,186,134,187,45,188,9,189,190,142,191,192,108,109,193,194,195,34,32,113],"mcp builder","builder","typescript","llms","model context protocol","fastmcp","Tools","node","context","integrate","mcp sdk","building mcp servers",{"skillNo":197,"name":198,"nameZh":6,"description":199,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":200,"categories":201,"keywords":214,"publishedAt":46},"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",[202,205,206,211],{"categoryNo":203,"categoryName":204,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":207,"categoryName":208,"taxonomyType":209,"taxonomyTypeDesc":210},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",{"categoryNo":212,"categoryName":213,"taxonomyType":209,"taxonomyTypeDesc":210},"01JBSEEDCAT000000000000036","内容创作者",[198,160,215,216,217,28,218,219,220,221,222,223,224,225,37,226,227,228,229,32,230,231,232],"summarize","memory","analytics","vector","time series","tool","discipline","log","geo","exploration","pipe","project","regex","join","datetime","section","anomaly","parse",{"skillNo":234,"name":235,"nameZh":6,"description":236,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":237,"categories":238,"keywords":239,"publishedAt":46},"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",[],[240,241,242,243,101,244,245,246,247,248,249,250,109,251,252,253,254,255,256,32,113],"github","github issue creator","github issue","issue","issue creator","screenshots","notes","logs","error messages","messages","convert","evidence","reports","images","info","visual","error"]