[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71B6287DV42XS9DN51XM280":3,"skill-same:01M71B6287DV42XS9DN51XM280":81},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":23,"publishedAt":44,"linkOnly":45,"markdownContent":46,"markdownBody":47,"frontMatter":48,"refName":54,"commitSha":55,"skillDirectory":56,"forksCount":57,"repositoryHtmlUrl":58,"repositoryHomepageUrl":6,"ownerHtmlUrl":59,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":60,"install":61,"resources":74},"01M71B6287DV42XS9DN51XM280","azure-ai-agents-persistent-dotnet",null,"Azure AI Agents Persistent SDK for .NET. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools. Use for agent CRUD, conversation threads, streaming responses, function calling, file search, and code interpreter. Triggers: \"PersistentAgentsClient\", \"persistent agents\", \"agent threads\", \"agent runs\", \"streaming agents\", \"function calling agents .NET\".","strmt7\u002Fai_skills_collection_benchmarked","strmt7","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F28989754?v=4","01M71929P914SWKQ7QJV24NBBY","Stratos","01M71929Q9VGKQ7PWYR95VSQQQ",1,"MIT","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fcloud-azure-microsoft-sdks\u002Fofficial-vendor-reference\u002Fazure-ai-agents-persistent-dotnet\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43],"ai agents","azure ai agents persistent dotnet","azure","azure ai","dotnet","function calling","use","calling","triggers","for","Tools","file search","threads","streaming","code","crud","messages","search","conversation","interpreter","2026-11-10 10:12:30",false,"---\nname: azure-ai-agents-persistent-dotnet\ndescription: |\n  Azure AI Agents Persistent SDK for .NET. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools. Use for agent CRUD, conversation threads, streaming responses, function calling, file search, and code interpreter. Triggers: \"PersistentAgentsClient\", \"persistent agents\", \"agent threads\", \"agent runs\", \"streaming agents\", \"function calling agents .NET\".\nlicense: MIT\nmetadata:\n  author: Microsoft\n  version: \"1.0.0\"\n  package: Azure.AI.Agents.Persistent\n---\n\n# Azure.AI.Agents.Persistent (.NET)\n\nLow-level SDK for creating and managing persistent AI agents with threads, messages, runs, and tools.\n\n## Installation\n\n```bash\ndotnet add package Azure.AI.Agents.Persistent --prerelease\ndotnet add package Azure.Identity\n```\n\n**Current Versions**: Stable v1.1.0, Preview v1.2.0-beta.8\n\n## Environment Variables\n\n```bash\nPROJECT_ENDPOINT=https:\u002F\u002F\u003Cresource>.services.ai.azure.com\u002Fapi\u002Fprojects\u002F\u003Cproject>\nMODEL_DEPLOYMENT_NAME=gpt-4o-mini\nAZURE_BING_CONNECTION_ID=\u003Cbing-connection-resource-id>\nAZURE_AI_SEARCH_CONNECTION_ID=\u003Csearch-connection-resource-id>\n```\n\n## Authentication\n\n```csharp\nusing Azure.AI.Agents.Persistent;\nusing Azure.Identity;\n\nvar projectEndpoint = Environment.GetEnvironmentVariable(\"PROJECT_ENDPOINT\");\nPersistentAgentsClient client = new(projectEndpoint, new DefaultAzureCredential());\n```\n\n## Client Hierarchy\n\n```\nPersistentAgentsClient\n├── Administration  → Agent CRUD operations\n├── Threads         → Thread management\n├── Messages        → Message operations\n├── Runs            → Run execution and streaming\n├── Files           → File upload\u002Fdownload\n└── VectorStores    → Vector store management\n```\n\n## Core Workflow\n\n### 1. Create Agent\n\n```csharp\nvar modelDeploymentName = Environment.GetEnvironmentVariable(\"MODEL_DEPLOYMENT_NAME\");\n\nPersistentAgent agent = await client.Administration.CreateAgentAsync(\n    model: modelDeploymentName,\n    name: \"Math Tutor\",\n    instructions: \"You are a personal math tutor. Write and run code to answer math questions.\",\n    tools: [new CodeInterpreterToolDefinition()]\n);\n```\n\n### 2. Create Thread and Message\n\n```csharp\n\u002F\u002F Create thread\nPersistentAgentThread thread = await client.Threads.CreateThreadAsync();\n\n\u002F\u002F Create message\nawait client.Messages.CreateMessageAsync(\n    thread.Id,\n    MessageRole.User,\n    \"I need to solve the equation `3x + 11 = 14`. Can you help me?\"\n);\n```\n\n### 3. Run Agent (Polling)\n\n```csharp\n\u002F\u002F Create run\nThreadRun run = await client.Runs.CreateRunAsync(\n    thread.Id,\n    agent.Id,\n    additionalInstructions: \"Please address the user as Jane Doe.\"\n);\n\n\u002F\u002F Poll for completion\ndo\n{\n    await Task.Delay(TimeSpan.FromMilliseconds(500));\n    run = await client.Runs.GetRunAsync(thread.Id, run.Id);\n}\nwhile (run.Status == RunStatus.Queued || run.Status == RunStatus.InProgress);\n\n\u002F\u002F Retrieve messages\nawait foreach (PersistentThreadMessage message in client.Messages.GetMessagesAsync(\n    threadId: thread.Id,\n    order: ListSortOrder.Ascending))\n{\n    Console.Write($\"{message.Role}: \");\n    foreach (MessageContent content in message.ContentItems)\n    {\n        if (content is MessageTextContent textContent)\n            Console.WriteLine(textContent.Text);\n    }\n}\n```\n\n### 4. Streaming Response\n\n```csharp\nAsyncCollectionResult\u003CStreamingUpdate> stream = client.Runs.CreateRunStreamingAsync(\n    thread.Id,\n    agent.Id\n);\n\nawait foreach (StreamingUpdate update in stream)\n{\n    if (update.UpdateKind == StreamingUpdateReason.RunCreated)\n    {\n        Console.WriteLine(\"--- Run started! ---\");\n    }\n    else if (update is MessageContentUpdate contentUpdate)\n    {\n        Console.Write(contentUpdate.Text);\n    }\n    else if (update.UpdateKind == StreamingUpdateReason.RunCompleted)\n    {\n        Console.WriteLine(\"\\n--- Run completed! ---\");\n    }\n}\n```\n\n### 5. Function Calling\n\n```csharp\n\u002F\u002F Define function tool\nFunctionToolDefinition weatherTool = new(\n    name: \"getCurrentWeather\",\n    description: \"Gets the current weather at a location.\",\n    parameters: BinaryData.FromObjectAsJson(new\n    {\n        Type = \"object\",\n        Properties = new\n        {\n            Location = new { Type = \"string\", Description = \"City and state, e.g. San Francisco, CA\" },\n            Unit = new { Type = \"string\", Enum = new[] { \"c\", \"f\" } }\n        },\n        Required = new[] { \"location\" }\n    }, new JsonSerializerOptions { PropertyNamingPolicy = JsonNamingPolicy.CamelCase })\n);\n\n\u002F\u002F Create agent with function\nPersistentAgent agent = await client.Administration.CreateAgentAsync(\n    model: modelDeploymentName,\n    name: \"Weather Bot\",\n    instructions: \"You are a weather bot.\",\n    tools: [weatherTool]\n);\n\n\u002F\u002F Handle function calls during polling\ndo\n{\n    await Task.Delay(500);\n    run = await client.Runs.GetRunAsync(thread.Id, run.Id);\n\n    if (run.Status == RunStatus.RequiresAction\n        && run.RequiredAction is SubmitToolOutputsAction submitAction)\n    {\n        List\u003CToolOutput> outputs = [];\n        foreach (RequiredToolCall toolCall in submitAction.ToolCalls)\n        {\n            if (toolCall is RequiredFunctionToolCall funcCall)\n            {\n                \u002F\u002F Execute function and get result\n                string result = ExecuteFunction(funcCall.Name, funcCall.Arguments);\n                outputs.Add(new ToolOutput(toolCall, result));\n            }\n        }\n        run = await client.Runs.SubmitToolOutputsToRunAsync(run, outputs, toolApprovals: null);\n    }\n}\nwhile (run.Status == RunStatus.Queued || run.Status == RunStatus.InProgress);\n```\n\n### 6. File Search with Vector Store\n\n```csharp\n\u002F\u002F Upload file\nPersistentAgentFileInfo file = await client.Files.UploadFileAsync(\n    filePath: \"document.txt\",\n    purpose: PersistentAgentFilePurpose.Agents\n);\n\n\u002F\u002F Create vector store\nPersistentAgentsVectorStore vectorStore = await client.VectorStores.CreateVectorStoreAsync(\n    fileIds: [file.Id],\n    name: \"my_vector_store\"\n);\n\n\u002F\u002F Create file search resource\nFileSearchToolResource fileSearchResource = new();\nfileSearchResource.VectorStoreIds.Add(vectorStore.Id);\n\n\u002F\u002F Create agent with file search\nPersistentAgent agent = await client.Administration.CreateAgentAsync(\n    model: modelDeploymentName,\n    name: \"Document Assistant\",\n    instructions: \"You help users find information in documents.\",\n    tools: [new FileSearchToolDefinition()],\n    toolResources: new ToolResources { FileSearch = fileSearchResource }\n);\n```\n\n### 7. Bing Grounding\n\n```csharp\nvar bingConnectionId = Environment.GetEnvironmentVariable(\"AZURE_BING_CONNECTION_ID\");\n\nBingGroundingToolDefinition bingTool = new(\n    new BingGroundingSearchToolParameters(\n        [new BingGroundingSearchConfiguration(bingConnectionId)]\n    )\n);\n\nPersistentAgent agent = await client.Administration.CreateAgentAsync(\n    model: modelDeploymentName,\n    name: \"Search Agent\",\n    instructions: \"Use Bing to answer questions about current events.\",\n    tools: [bingTool]\n);\n```\n\n### 8. Azure AI Search\n\n```csharp\nAzureAISearchToolResource searchResource = new(\n    connectionId: searchConnectionId,\n    indexName: \"my_index\",\n    topK: 5,\n    filter: \"category eq 'documentation'\",\n    queryType: AzureAISearchQueryType.Simple\n);\n\nPersistentAgent agent = await client.Administration.CreateAgentAsync(\n    model: modelDeploymentName,\n    name: \"Search Agent\",\n    instructions: \"Search the documentation index to answer questions.\",\n    tools: [new AzureAISearchToolDefinition()],\n    toolResources: new ToolResources { AzureAISearch = searchResource }\n);\n```\n\n### 9. Cleanup\n\n```csharp\nawait client.Threads.DeleteThreadAsync(thread.Id);\nawait client.Administration.DeleteAgentAsync(agent.Id);\nawait client.VectorStores.DeleteVectorStoreAsync(vectorStore.Id);\nawait client.Files.DeleteFileAsync(file.Id);\n```\n\n## Available Tools\n\n| Tool | Class | Purpose |\n|------|-------|---------|\n| Code Interpreter | `CodeInterpreterToolDefinition` | Execute Python code, generate visualizations |\n| File Search | `FileSearchToolDefinition` | Search uploaded files via vector stores |\n| Function Calling | `FunctionToolDefinition` | Call custom functions |\n| Bing Grounding | `BingGroundingToolDefinition` | Web search via Bing |\n| Azure AI Search | `AzureAISearchToolDefinition` | Search Azure AI Search indexes |\n| OpenAPI | `OpenApiToolDefinition` | Call external APIs via OpenAPI spec |\n| Azure Functions | `AzureFunctionToolDefinition` | Invoke Azure Functions |\n| MCP | `MCPToolDefinition` | Model Context Protocol tools |\n| SharePoint | `SharepointToolDefinition` | Access SharePoint content |\n| Microsoft Fabric | `MicrosoftFabricToolDefinition` | Access Fabric data |\n\n## Streaming Update Types\n\n| Update Type | Description |\n|-------------|-------------|\n| `StreamingUpdateReason.RunCreated` | Run started |\n| `StreamingUpdateReason.RunInProgress` | Run processing |\n| `StreamingUpdateReason.RunCompleted` | Run finished |\n| `StreamingUpdateReason.RunFailed` | Run errored |\n| `MessageContentUpdate` | Text content chunk |\n| `RunStepUpdate` | Step status change |\n\n## Key Types Reference\n\n| Type | Purpose |\n|------|---------|\n| `PersistentAgentsClient` | Main entry point |\n| `PersistentAgent` | Agent with model, instructions, tools |\n| `PersistentAgentThread` | Conversation thread |\n| `PersistentThreadMessage` | Message in thread |\n| `ThreadRun` | Execution of agent against thread |\n| `RunStatus` | Queued, InProgress, RequiresAction, Completed, Failed |\n| `ToolResources` | Combined tool resources |\n| `ToolOutput` | Function call response |\n\n## Best Practices\n\n1. **Always dispose clients** — Use `using` statements or explicit disposal\n2. **Poll with appropriate delays** — 500ms recommended between status checks\n3. **Clean up resources** — Delete threads and agents when done\n4. **Handle all run statuses** — Check for `RequiresAction`, `Failed`, `Cancelled`\n5. **Use streaming for real-time UX** — Better user experience than polling\n6. **Store IDs not objects** — Reference agents\u002Fthreads by ID\n7. **Use async methods** — All operations should be async\n\n## Error Handling\n\n```csharp\nusing Azure;\n\ntry\n{\n    var agent = await client.Administration.CreateAgentAsync(...);\n}\ncatch (RequestFailedException ex) when (ex.Status == 404)\n{\n    Console.WriteLine(\"Resource not found\");\n}\ncatch (RequestFailedException ex)\n{\n    Console.WriteLine($\"Error: {ex.Status} - {ex.ErrorCode}: {ex.Message}\");\n}\n```\n\n## Related SDKs\n\n| SDK | Purpose | Install |\n|-----|---------|---------|\n| `Azure.AI.Agents.Persistent` | Low-level agents (this SDK) | `dotnet add package Azure.AI.Agents.Persistent` |\n| `Azure.AI.Projects` | High-level project client | `dotnet add package Azure.AI.Projects` |\n\n## Reference Links\n\n| Resource | URL |\n|----------|-----|\n| NuGet Package | https:\u002F\u002Fwww.nuget.org\u002Fpackages\u002FAzure.AI.Agents.Persistent |\n| API Reference | https:\u002F\u002Flearn.microsoft.com\u002Fdotnet\u002Fapi\u002Fazure.ai.agents.persistent |\n| GitHub Source | https:\u002F\u002Fgithub.com\u002FAzure\u002Fazure-sdk-for-net\u002Ftree\u002Fmain\u002Fsdk\u002Fai\u002FAzure.AI.Agents.Persistent |\n| Samples | https:\u002F\u002Fgithub.com\u002FAzure\u002Fazure-sdk-for-net\u002Ftree\u002Fmain\u002Fsdk\u002Fai\u002FAzure.AI.Agents.Persistent\u002Fsamples |\n","# Azure.AI.Agents.Persistent (.NET)\n\nLow-level SDK for creating and managing persistent AI agents with threads, messages, runs, and tools.\n\n## Installation\n\n```bash\ndotnet add package Azure.AI.Agents.Persistent --prerelease\ndotnet add package Azure.Identity\n```\n\n**Current Versions**: Stable v1.1.0, Preview v1.2.0-beta.8\n\n## Environment Variables\n\n```bash\nPROJECT_ENDPOINT=https:\u002F\u002F\u003Cresource>.services.ai.azure.com\u002Fapi\u002Fprojects\u002F\u003Cproject>\nMODEL_DEPLOYMENT_NAME=gpt-4o-mini\nAZURE_BING_CONNECTION_ID=\u003Cbing-connection-resource-id>\nAZURE_AI_SEARCH_CONNECTION_ID=\u003Csearch-connection-resource-id>\n```\n\n## Authentication\n\n```csharp\nusing Azure.AI.Agents.Persistent;\nusing Azure.Identity;\n\nvar projectEndpoint = Environment.GetEnvironmentVariable(\"PROJECT_ENDPOINT\");\nPersistentAgentsClient client = new(projectEndpoint, new DefaultAzureCredential());\n```\n\n## Client Hierarchy\n\n```\nPersistentAgentsClient\n├── Administration  → Agent CRUD operations\n├── Threads         → Thread management\n├── Messages        → Message operations\n├── Runs            → Run execution and streaming\n├── Files           → File upload\u002Fdownload\n└── VectorStores    → Vector store management\n```\n\n## Core Workflow\n\n### 1. Create Agent\n\n```csharp\nvar modelDeploymentName = Environment.GetEnvironmentVariable(\"MODEL_DEPLOYMENT_NAME\");\n\nPersistentAgent agent = await client.Administration.CreateAgentAsync(\n    model: modelDeploymentName,\n    name: \"Math Tutor\",\n    instructions: \"You are a personal math tutor. Write and run code to answer math questions.\",\n    tools: [new CodeInterpreterToolDefinition()]\n);\n```\n\n### 2. Create Thread and Message\n\n```csharp\n\u002F\u002F Create thread\nPersistentAgentThread thread = await client.Threads.CreateThreadAsync();\n\n\u002F\u002F Create message\nawait client.Messages.CreateMessageAsync(\n    thread.Id,\n    MessageRole.User,\n    \"I need to solve the equation `3x + 11 = 14`. Can you help me?\"\n);\n```\n\n### 3. Run Agent (Polling)\n\n```csharp\n\u002F\u002F Create run\nThreadRun run = await client.Runs.CreateRunAsync(\n    thread.Id,\n    agent.Id,\n    additionalInstructions: \"Please address the user as Jane Doe.\"\n);\n\n\u002F\u002F Poll for completion\ndo\n{\n    await Task.Delay(TimeSpan.FromMilliseconds(500));\n    run = await client.Runs.GetRunAsync(thread.Id, run.Id);\n}\nwhile (run.Status == RunStatus.Queued || run.Status == RunStatus.InProgress);\n\n\u002F\u002F Retrieve messages\nawait foreach (PersistentThreadMessage message in client.Messages.GetMessagesAsync(\n    threadId: thread.Id,\n    order: ListSortOrder.Ascending))\n{\n    Console.Write($\"{message.Role}: \");\n    foreach (MessageContent content in message.ContentItems)\n    {\n        if (content is MessageTextContent textContent)\n            Console.WriteLine(textContent.Text);\n    }\n}\n```\n\n### 4. Streaming Response\n\n```csharp\nAsyncCollectionResult\u003CStreamingUpdate> stream = client.Runs.CreateRunStreamingAsync(\n    thread.Id,\n    agent.Id\n);\n\nawait foreach (StreamingUpdate update in stream)\n{\n    if (update.UpdateKind == StreamingUpdateReason.RunCreated)\n    {\n        Console.WriteLine(\"--- Run started! ---\");\n    }\n    else if (update is MessageContentUpdate contentUpdate)\n    {\n        Console.Write(contentUpdate.Text);\n    }\n    else if (update.UpdateKind == StreamingUpdateReason.RunCompleted)\n    {\n        Console.WriteLine(\"\\n--- Run completed! ---\");\n    }\n}\n```\n\n### 5. Function Calling\n\n```csharp\n\u002F\u002F Define function tool\nFunctionToolDefinition weatherTool = new(\n    name: \"getCurrentWeather\",\n    description: \"Gets the current weather at a location.\",\n    parameters: BinaryData.FromObjectAsJson(new\n    {\n        Type = \"object\",\n        Properties = new\n        {\n            Location = new { Type = \"string\", Description = \"City and state, e.g. San Francisco, CA\" },\n            Unit = new { Type = \"string\", Enum = new[] { \"c\", \"f\" } }\n        },\n        Required = new[] { \"location\" }\n    }, new JsonSerializerOptions { PropertyNamingPolicy = JsonNamingPolicy.CamelCase })\n);\n\n\u002F\u002F Create agent with function\nPersistentAgent agent = await client.Administration.CreateAgentAsync(\n    model: modelDeploymentName,\n    name: \"Weather Bot\",\n    instructions: \"You are a weather bot.\",\n    tools: [weatherTool]\n);\n\n\u002F\u002F Handle function calls during polling\ndo\n{\n    await Task.Delay(500);\n    run = await client.Runs.GetRunAsync(thread.Id, run.Id);\n\n    if (run.Status == RunStatus.RequiresAction\n        && run.RequiredAction is SubmitToolOutputsAction submitAction)\n    {\n        List\u003CToolOutput> outputs = [];\n        foreach (RequiredToolCall toolCall in submitAction.ToolCalls)\n        {\n            if (toolCall is RequiredFunctionToolCall funcCall)\n            {\n                \u002F\u002F Execute function and get result\n                string result = ExecuteFunction(funcCall.Name, funcCall.Arguments);\n                outputs.Add(new ToolOutput(toolCall, result));\n            }\n        }\n        run = await client.Runs.SubmitToolOutputsToRunAsync(run, outputs, toolApprovals: null);\n    }\n}\nwhile (run.Status == RunStatus.Queued || run.Status == RunStatus.InProgress);\n```\n\n### 6. File Search with Vector Store\n\n```csharp\n\u002F\u002F Upload file\nPersistentAgentFileInfo file = await client.Files.UploadFileAsync(\n    filePath: \"document.txt\",\n    purpose: PersistentAgentFilePurpose.Agents\n);\n\n\u002F\u002F Create vector store\nPersistentAgentsVectorStore vectorStore = await client.VectorStores.CreateVectorStoreAsync(\n    fileIds: [file.Id],\n    name: \"my_vector_store\"\n);\n\n\u002F\u002F Create file search resource\nFileSearchToolResource fileSearchResource = new();\nfileSearchResource.VectorStoreIds.Add(vectorStore.Id);\n\n\u002F\u002F Create agent with file search\nPersistentAgent agent = await client.Administration.CreateAgentAsync(\n    model: modelDeploymentName,\n    name: \"Document Assistant\",\n    instructions: \"You help users find information in documents.\",\n    tools: [new FileSearchToolDefinition()],\n    toolResources: new ToolResources { FileSearch = fileSearchResource }\n);\n```\n\n### 7. Bing Grounding\n\n```csharp\nvar bingConnectionId = Environment.GetEnvironmentVariable(\"AZURE_BING_CONNECTION_ID\");\n\nBingGroundingToolDefinition bingTool = new(\n    new BingGroundingSearchToolParameters(\n        [new BingGroundingSearchConfiguration(bingConnectionId)]\n    )\n);\n\nPersistentAgent agent = await client.Administration.CreateAgentAsync(\n    model: modelDeploymentName,\n    name: \"Search Agent\",\n    instructions: \"Use Bing to answer questions about current events.\",\n    tools: [bingTool]\n);\n```\n\n### 8. Azure AI Search\n\n```csharp\nAzureAISearchToolResource searchResource = new(\n    connectionId: searchConnectionId,\n    indexName: \"my_index\",\n    topK: 5,\n    filter: \"category eq 'documentation'\",\n    queryType: AzureAISearchQueryType.Simple\n);\n\nPersistentAgent agent = await client.Administration.CreateAgentAsync(\n    model: modelDeploymentName,\n    name: \"Search Agent\",\n    instructions: \"Search the documentation index to answer questions.\",\n    tools: [new AzureAISearchToolDefinition()],\n    toolResources: new ToolResources { AzureAISearch = searchResource }\n);\n```\n\n### 9. Cleanup\n\n```csharp\nawait client.Threads.DeleteThreadAsync(thread.Id);\nawait client.Administration.DeleteAgentAsync(agent.Id);\nawait client.VectorStores.DeleteVectorStoreAsync(vectorStore.Id);\nawait client.Files.DeleteFileAsync(file.Id);\n```\n\n## Available Tools\n\n| Tool | Class | Purpose |\n|------|-------|---------|\n| Code Interpreter | `CodeInterpreterToolDefinition` | Execute Python code, generate visualizations |\n| File Search | `FileSearchToolDefinition` | Search uploaded files via vector stores |\n| Function Calling | `FunctionToolDefinition` | Call custom functions |\n| Bing Grounding | `BingGroundingToolDefinition` | Web search via Bing |\n| Azure AI Search | `AzureAISearchToolDefinition` | Search Azure AI Search indexes |\n| OpenAPI | `OpenApiToolDefinition` | Call external APIs via OpenAPI spec |\n| Azure Functions | `AzureFunctionToolDefinition` | Invoke Azure Functions |\n| MCP | `MCPToolDefinition` | Model Context Protocol tools |\n| SharePoint | `SharepointToolDefinition` | Access SharePoint content |\n| Microsoft Fabric | `MicrosoftFabricToolDefinition` | Access Fabric data |\n\n## Streaming Update Types\n\n| Update Type | Description |\n|-------------|-------------|\n| `StreamingUpdateReason.RunCreated` | Run started |\n| `StreamingUpdateReason.RunInProgress` | Run processing |\n| `StreamingUpdateReason.RunCompleted` | Run finished |\n| `StreamingUpdateReason.RunFailed` | Run errored |\n| `MessageContentUpdate` | Text content chunk |\n| `RunStepUpdate` | Step status change |\n\n## Key Types Reference\n\n| Type | Purpose |\n|------|---------|\n| `PersistentAgentsClient` | Main entry point |\n| `PersistentAgent` | Agent with model, instructions, tools |\n| `PersistentAgentThread` | Conversation thread |\n| `PersistentThreadMessage` | Message in thread |\n| `ThreadRun` | Execution of agent against thread |\n| `RunStatus` | Queued, InProgress, RequiresAction, Completed, Failed |\n| `ToolResources` | Combined tool resources |\n| `ToolOutput` | Function call response |\n\n## Best Practices\n\n1. **Always dispose clients** — Use `using` statements or explicit disposal\n2. **Poll with appropriate delays** — 500ms recommended between status checks\n3. **Clean up resources** — Delete threads and agents when done\n4. **Handle all run statuses** — Check for `RequiresAction`, `Failed`, `Cancelled`\n5. **Use streaming for real-time UX** — Better user experience than polling\n6. **Store IDs not objects** — Reference agents\u002Fthreads by ID\n7. **Use async methods** — All operations should be async\n\n## Error Handling\n\n```csharp\nusing Azure;\n\ntry\n{\n    var agent = await client.Administration.CreateAgentAsync(...);\n}\ncatch (RequestFailedException ex) when (ex.Status == 404)\n{\n    Console.WriteLine(\"Resource not found\");\n}\ncatch (RequestFailedException ex)\n{\n    Console.WriteLine($\"Error: {ex.Status} - {ex.ErrorCode}: {ex.Message}\");\n}\n```\n\n## Related SDKs\n\n| SDK | Purpose | Install |\n|-----|---------|---------|\n| `Azure.AI.Agents.Persistent` | Low-level agents (this SDK) | `dotnet add package Azure.AI.Agents.Persistent` |\n| `Azure.AI.Projects` | High-level project client | `dotnet add package Azure.AI.Projects` |\n\n## Reference Links\n\n| Resource | URL |\n|----------|-----|\n| NuGet Package | https:\u002F\u002Fwww.nuget.org\u002Fpackages\u002FAzure.AI.Agents.Persistent |\n| API Reference | https:\u002F\u002Flearn.microsoft.com\u002Fdotnet\u002Fapi\u002Fazure.ai.agents.persistent |\n| GitHub Source | https:\u002F\u002Fgithub.com\u002FAzure\u002Fazure-sdk-for-net\u002Ftree\u002Fmain\u002Fsdk\u002Fai\u002FAzure.AI.Agents.Persistent |\n| Samples | https:\u002F\u002Fgithub.com\u002FAzure\u002Fazure-sdk-for-net\u002Ftree\u002Fmain\u002Fsdk\u002Fai\u002FAzure.AI.Agents.Persistent\u002Fsamples |\n",{"name":5,"license":15,"metadata":49,"description":53},{"author":50,"package":51,"version":52},"Microsoft","Azure.AI.Agents.Persistent","1.0.0","Azure AI Agents Persistent SDK for .NET. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools. Use for agent CRUD, conversation threads, streaming responses, function calling, file search, and code interpreter. Triggers: \"PersistentAgentsClient\", \"persistent agents\", \"agent threads\", \"agent runs\", \"streaming agents\", \"function calling agents .NET\".\n","main","5c95bcac4646c5aed06bd9aed5235cfc7985aafc","included\u002Fskills\u002Fby-category\u002Fcloud-azure-microsoft-sdks\u002Fofficial-vendor-reference\u002Fazure-ai-agents-persistent-dotnet",0,"https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked","https:\u002F\u002Fgithub.com\u002Fstrmt7","2026-11-11 04:18:12",{"source":8,"skillName":5,"commands":62,"prompt":72,"zipAvailable":73},[63,66,69],{"tool":64,"command":65},"npx","npx skills add strmt7\u002Fai_skills_collection_benchmarked --skill azure-ai-agents-persistent-dotnet",{"tool":67,"command":68},"bunx","bunx skills add strmt7\u002Fai_skills_collection_benchmarked --skill azure-ai-agents-persistent-dotnet",{"tool":70,"command":71},"pnpm","pnpm dlx skills add strmt7\u002Fai_skills_collection_benchmarked --skill azure-ai-agents-persistent-dotnet","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fcloud-azure-microsoft-sdks\u002Fofficial-vendor-reference\u002Fazure-ai-agents-persistent-dotnet\u002FSKILL.md",true,[75],{"path":76,"resourceType":77,"resourceTypeDesc":78,"sizeBytes":79,"sourceHtmlUrl":80},"references\u002Facceptance-criteria.md","REFERENCE","参考文档",18848,"https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fcloud-azure-microsoft-sdks\u002Fofficial-vendor-reference\u002Fazure-ai-agents-persistent-dotnet\u002Freferences\u002Facceptance-criteria.md",[82,113,141,166,191,218],{"skillNo":83,"name":84,"nameZh":6,"description":85,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":86,"licenseFileUrl":87,"sourceHtmlUrl":88,"categories":89,"keywords":96,"publishedAt":44},"01M71D4H3T6M57DFKN8HENAWRV","webapp-testing","Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.","Apache-2.0","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Ftesting-qa-benchmarking\u002Fofficial-reference\u002Fwebapp-testing\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Ftesting-qa-benchmarking\u002Fofficial-reference\u002Fwebapp-testing\u002FSKILL.md",[90,93],{"categoryNo":91,"categoryName":92,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":94,"categoryName":95,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000009","前端开发",[97,98,99,33,100,101,102,103,104,105,106,107,108,109,110,111,112],"webapp","testing","webapp testing","applications","local","frontend","debugging","toolkit","logs","browser","with","playwright","web","behavior","ui","screenshots",{"skillNo":114,"name":115,"nameZh":6,"description":116,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":86,"licenseFileUrl":117,"sourceHtmlUrl":118,"categories":119,"keywords":121,"publishedAt":44},"01M71D4CQR2A2TB7GASCR5ZBG3","skill-creator","Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Ftesting-qa-benchmarking\u002Fofficial-reference\u002Fskill-creator-anthropics\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Ftesting-qa-benchmarking\u002Fofficial-reference\u002Fskill-creator-anthropics\u002FSKILL.md",[120],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,33,140],"skill creator","creator","performance","improve","run evals","new","when","analysis","create","optimize","variance analysis","run","edit","benchmark","a skill","existing skill","evals","modify","accuracy",{"skillNo":142,"name":143,"nameZh":6,"description":144,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":145,"categories":146,"keywords":149,"publishedAt":44},"01M71D488XHEZVXXSXFYP8ENMH","playwright-skill","Complete browser automation with Playwright. Auto-detects dev servers, writes reusable test scripts, and supports screenshots, responsive checks, UX validation, login flows, link checks, and arbitrary browser automation. Use when the user wants to test a website, automate browser interactions, validate web functionality, or perform browser-based testing.","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Ftesting-qa-benchmarking\u002Flatest-release-browser-automation\u002Fplaywright-skill\u002FSKILL.md",[147,148],{"categoryNo":91,"categoryName":92,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[108,150,151,152,98,153,154,128,155,106,156,157,158,159,160,161,162,163,164,165],"playwright skill","browser automation","flows","auto","access","Bash","website","ux","login","scripts","read","write","node","install","network","responsive",{"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":86,"licenseFileUrl":170,"sourceHtmlUrl":171,"categories":172,"keywords":174,"publishedAt":44},"01M71CY25GM939M6RES91QSG3T","web-artifacts-builder","Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn\u002Fui). Use for complex artifacts requiring state management, routing, or shadcn\u002Fui components - not for simple single-file HTML\u002FJSX artifacts.","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fsearch-retrieval-web-automation\u002Fofficial-reference\u002Fweb-artifacts-builder\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fsearch-retrieval-web-automation\u002Fofficial-reference\u002Fweb-artifacts-builder\u002FSKILL.md",[173],{"categoryNo":94,"categoryName":95,"taxonomyType":21,"taxonomyTypeDesc":22},[175,176,177,109,178,179,180,33,181,182,102,183,30,184,185,186,187,188,189,190],"builder","artifacts builder","artifacts","web artifacts builder","single-file","css","Tailwind","ui components","single","file","components","react","multi","state","routing","state management",{"skillNo":192,"name":193,"nameZh":6,"description":194,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":86,"licenseFileUrl":195,"sourceHtmlUrl":196,"categories":197,"keywords":207,"publishedAt":44},"01M71CXZB60QJJ1H4S3NN94WMZ","frontend-design","Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML\u002FCSS layouts, or when styling\u002Fbeautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fsearch-retrieval-web-automation\u002Fofficial-reference\u002Ffrontend-design\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fsearch-retrieval-web-automation\u002Fofficial-reference\u002Ffrontend-design\u002FSKILL.md",[198,199,202],{"categoryNo":94,"categoryName":95,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":200,"categoryName":201,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":203,"categoryName":204,"taxonomyType":205,"taxonomyTypeDesc":206},"01JBSEEDCAT000000000000032","设计师","PROFESSION","适用职业",[102,208,209,180,210,211,212,100,213,214,30,128,177,38,185,215,186,216,217,107],"design","frontend design","ui design","generic","aesthetics","landing","pages","web ui","react components","examples",{"skillNo":219,"name":220,"nameZh":6,"description":221,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":222,"categories":223,"keywords":224,"publishedAt":44},"01M71CVZ54WFBTVA7R16PFY1ZE","zarr-python","Chunked N-D arrays for cloud storage. Compressed arrays, parallel I\u002FO, S3\u002FGCS integration, NumPy\u002FDask\u002FXarray compatible, for large-scale scientific computing pipelines.","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fscience-research-data-analysis\u002Flatest-release-community\u002Fzarr-python\u002FSKILL.md",[],[225,226,227,228,229,230,231,232,233,33,234,235,236,237,238,239,240,241],"zarr python","python","zarr","arrays","Cloud Storage","scientific","storage","parallel","dask","numpy","gcs","s3","integration","scientific computing","cloud","scale","pipelines"]