[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71B77P9VVFQKP7D3HPGFNK5":3,"skill-same:01M71B77P9VVFQKP7D3HPGFNK5":76},{"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":18,"publishedAt":39,"linkOnly":40,"markdownContent":41,"markdownBody":42,"frontMatter":43,"refName":49,"commitSha":50,"skillDirectory":51,"forksCount":52,"repositoryHtmlUrl":53,"repositoryHomepageUrl":6,"ownerHtmlUrl":54,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":55,"install":56,"resources":69},"01M71B77P9VVFQKP7D3HPGFNK5","azure-ai-projects-dotnet",null,"Azure AI Projects SDK for .NET. High-level client for Azure AI Foundry projects including agents, connections, datasets, deployments, evaluations, and indexes. Use for AI Foundry project management, versioned agents, and orchestration. Triggers: \"AI Projects\", \"AIProjectClient\", \"Foundry project\", \"versioned agents\", \"evaluations\", \"datasets\", \"connections\", \"deployments .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-projects-dotnet\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"azure ai projects dotnet","azure","dotnet","azure ai","azure ai projects","projects","client","indexes","microsoft","datasets","sdk","high","orchestration","use","connections","deployments","triggers","project","for","azure ai foundry","2026-11-10 10:12:30",false,"---\nname: azure-ai-projects-dotnet\ndescription: |\n  Azure AI Projects SDK for .NET. High-level client for Azure AI Foundry projects including agents, connections, datasets, deployments, evaluations, and indexes. Use for AI Foundry project management, versioned agents, and orchestration. Triggers: \"AI Projects\", \"AIProjectClient\", \"Foundry project\", \"versioned agents\", \"evaluations\", \"datasets\", \"connections\", \"deployments .NET\".\nlicense: MIT\nmetadata:\n  author: Microsoft\n  version: \"1.0.0\"\n  package: Azure.AI.Projects\n---\n\n# Azure.AI.Projects (.NET)\n\nHigh-level SDK for Azure AI Foundry project operations including agents, connections, datasets, deployments, evaluations, and indexes.\n\n## Installation\n\n```bash\ndotnet add package Azure.AI.Projects\ndotnet add package Azure.Identity\n\n# Optional: For versioned agents with OpenAI extensions\ndotnet add package Azure.AI.Projects.OpenAI --prerelease\n\n# Optional: For low-level agent operations\ndotnet add package Azure.AI.Agents.Persistent --prerelease\n```\n\n**Current Versions**: GA v1.1.0, Preview v1.2.0-beta.5\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\nCONNECTION_NAME=\u003Cyour-connection-name>\nAI_SEARCH_CONNECTION_NAME=\u003Cai-search-connection>\n```\n\n## Authentication\n\n```csharp\nusing Azure.Identity;\nusing Azure.AI.Projects;\n\nvar endpoint = Environment.GetEnvironmentVariable(\"PROJECT_ENDPOINT\");\nAIProjectClient projectClient = new AIProjectClient(\n    new Uri(endpoint),\n    new DefaultAzureCredential());\n```\n\n## Client Hierarchy\n\n```\nAIProjectClient\n├── Agents          → AIProjectAgentsOperations (versioned agents)\n├── Connections     → ConnectionsClient\n├── Datasets        → DatasetsClient\n├── Deployments     → DeploymentsClient\n├── Evaluations     → EvaluationsClient\n├── Evaluators      → EvaluatorsClient\n├── Indexes         → IndexesClient\n├── Telemetry       → AIProjectTelemetry\n├── OpenAI          → ProjectOpenAIClient (preview)\n└── GetPersistentAgentsClient() → PersistentAgentsClient\n```\n\n## Core Workflows\n\n### 1. Get Persistent Agents Client\n\n```csharp\n\u002F\u002F Get low-level agents client from project client\nPersistentAgentsClient agentsClient = projectClient.GetPersistentAgentsClient();\n\n\u002F\u002F Create agent\nPersistentAgent agent = await agentsClient.Administration.CreateAgentAsync(\n    model: \"gpt-4o-mini\",\n    name: \"Math Tutor\",\n    instructions: \"You are a personal math tutor.\");\n\n\u002F\u002F Create thread and run\nPersistentAgentThread thread = await agentsClient.Threads.CreateThreadAsync();\nawait agentsClient.Messages.CreateMessageAsync(thread.Id, MessageRole.User, \"Solve 3x + 11 = 14\");\nThreadRun run = await agentsClient.Runs.CreateRunAsync(thread.Id, agent.Id);\n\n\u002F\u002F Poll for completion\ndo\n{\n    await Task.Delay(500);\n    run = await agentsClient.Runs.GetRunAsync(thread.Id, run.Id);\n}\nwhile (run.Status == RunStatus.Queued || run.Status == RunStatus.InProgress);\n\n\u002F\u002F Get messages\nawait foreach (var msg in agentsClient.Messages.GetMessagesAsync(thread.Id))\n{\n    foreach (var content in msg.ContentItems)\n    {\n        if (content is MessageTextContent textContent)\n            Console.WriteLine(textContent.Text);\n    }\n}\n\n\u002F\u002F Cleanup\nawait agentsClient.Threads.DeleteThreadAsync(thread.Id);\nawait agentsClient.Administration.DeleteAgentAsync(agent.Id);\n```\n\n### 2. Versioned Agents with Tools (Preview)\n\n```csharp\nusing Azure.AI.Projects.OpenAI;\n\n\u002F\u002F Create agent with web search tool\nPromptAgentDefinition agentDefinition = new(model: \"gpt-4o-mini\")\n{\n    Instructions = \"You are a helpful assistant that can search the web\",\n    Tools = {\n        ResponseTool.CreateWebSearchTool(\n            userLocation: WebSearchToolLocation.CreateApproximateLocation(\n                country: \"US\",\n                city: \"Seattle\",\n                region: \"Washington\"\n            )\n        ),\n    }\n};\n\nAgentVersion agentVersion = await projectClient.Agents.CreateAgentVersionAsync(\n    agentName: \"myAgent\",\n    options: new(agentDefinition));\n\n\u002F\u002F Get response client\nProjectResponsesClient responseClient = projectClient.OpenAI.GetProjectResponsesClientForAgent(agentVersion.Name);\n\n\u002F\u002F Create response\nResponseResult response = responseClient.CreateResponse(\"What's the weather in Seattle?\");\nConsole.WriteLine(response.GetOutputText());\n\n\u002F\u002F Cleanup\nprojectClient.Agents.DeleteAgentVersion(agentName: agentVersion.Name, agentVersion: agentVersion.Version);\n```\n\n### 3. Connections\n\n```csharp\n\u002F\u002F List all connections\nforeach (AIProjectConnection connection in projectClient.Connections.GetConnections())\n{\n    Console.WriteLine($\"{connection.Name}: {connection.ConnectionType}\");\n}\n\n\u002F\u002F Get specific connection\nAIProjectConnection conn = projectClient.Connections.GetConnection(\n    connectionName,\n    includeCredentials: true);\n\n\u002F\u002F Get default connection\nAIProjectConnection defaultConn = projectClient.Connections.GetDefaultConnection(\n    includeCredentials: false);\n```\n\n### 4. Deployments\n\n```csharp\n\u002F\u002F List all deployments\nforeach (AIProjectDeployment deployment in projectClient.Deployments.GetDeployments())\n{\n    Console.WriteLine($\"{deployment.Name}: {deployment.ModelName}\");\n}\n\n\u002F\u002F Filter by publisher\nforeach (var deployment in projectClient.Deployments.GetDeployments(modelPublisher: \"Microsoft\"))\n{\n    Console.WriteLine(deployment.Name);\n}\n\n\u002F\u002F Get specific deployment\nModelDeployment details = (ModelDeployment)projectClient.Deployments.GetDeployment(\"gpt-4o-mini\");\n```\n\n### 5. Datasets\n\n```csharp\n\u002F\u002F Upload single file\nFileDataset fileDataset = projectClient.Datasets.UploadFile(\n    name: \"my-dataset\",\n    version: \"1.0\",\n    filePath: \"data\u002Ftraining.txt\",\n    connectionName: connectionName);\n\n\u002F\u002F Upload folder\nFolderDataset folderDataset = projectClient.Datasets.UploadFolder(\n    name: \"my-dataset\",\n    version: \"2.0\",\n    folderPath: \"data\u002Ftraining\",\n    connectionName: connectionName,\n    filePattern: new Regex(\".*\\\\.txt\"));\n\n\u002F\u002F Get dataset\nAIProjectDataset dataset = projectClient.Datasets.GetDataset(\"my-dataset\", \"1.0\");\n\n\u002F\u002F Delete dataset\nprojectClient.Datasets.Delete(\"my-dataset\", \"1.0\");\n```\n\n### 6. Indexes\n\n```csharp\n\u002F\u002F Create Azure AI Search index\nAzureAISearchIndex searchIndex = new(aiSearchConnectionName, aiSearchIndexName)\n{\n    Description = \"Sample Index\"\n};\n\nsearchIndex = (AzureAISearchIndex)projectClient.Indexes.CreateOrUpdate(\n    name: \"my-index\",\n    version: \"1.0\",\n    index: searchIndex);\n\n\u002F\u002F List indexes\nforeach (AIProjectIndex index in projectClient.Indexes.GetIndexes())\n{\n    Console.WriteLine(index.Name);\n}\n\n\u002F\u002F Delete index\nprojectClient.Indexes.Delete(name: \"my-index\", version: \"1.0\");\n```\n\n### 7. Evaluations\n\n```csharp\n\u002F\u002F Create evaluation configuration\nvar evaluatorConfig = new EvaluatorConfiguration(id: EvaluatorIDs.Relevance);\nevaluatorConfig.InitParams.Add(\"deployment_name\", BinaryData.FromObjectAsJson(\"gpt-4o\"));\n\n\u002F\u002F Create evaluation\nEvaluation evaluation = new Evaluation(\n    data: new InputDataset(\"\u003Cdataset_id>\"),\n    evaluators: new Dictionary\u003Cstring, EvaluatorConfiguration>\n    {\n        { \"relevance\", evaluatorConfig }\n    }\n)\n{\n    DisplayName = \"Sample Evaluation\"\n};\n\n\u002F\u002F Run evaluation\nEvaluation result = projectClient.Evaluations.Create(evaluation: evaluation);\n\n\u002F\u002F Get evaluation\nEvaluation getResult = projectClient.Evaluations.Get(result.Name);\n\n\u002F\u002F List evaluations\nforeach (var eval in projectClient.Evaluations.GetAll())\n{\n    Console.WriteLine($\"{eval.DisplayName}: {eval.Status}\");\n}\n```\n\n### 8. Get Azure OpenAI Chat Client\n\n```csharp\nusing Azure.AI.OpenAI;\nusing OpenAI.Chat;\n\nClientConnection connection = projectClient.GetConnection(typeof(AzureOpenAIClient).FullName!);\n\nif (!connection.TryGetLocatorAsUri(out Uri uri) || uri is null)\n    throw new InvalidOperationException(\"Invalid URI.\");\n\nuri = new Uri($\"https:\u002F\u002F{uri.Host}\");\n\nAzureOpenAIClient azureOpenAIClient = new AzureOpenAIClient(uri, new DefaultAzureCredential());\nChatClient chatClient = azureOpenAIClient.GetChatClient(\"gpt-4o-mini\");\n\nChatCompletion result = chatClient.CompleteChat(\"List all rainbow colors\");\nConsole.WriteLine(result.Content[0].Text);\n```\n\n## Available Agent Tools\n\n| Tool | Class | Purpose |\n|------|-------|---------|\n| Code Interpreter | `CodeInterpreterToolDefinition` | Execute Python code |\n| File Search | `FileSearchToolDefinition` | Search uploaded files |\n| Function Calling | `FunctionToolDefinition` | Call custom functions |\n| Bing Grounding | `BingGroundingToolDefinition` | Web search via Bing |\n| Azure AI Search | `AzureAISearchToolDefinition` | Search Azure AI indexes |\n| OpenAPI | `OpenApiToolDefinition` | Call external APIs |\n| Azure Functions | `AzureFunctionToolDefinition` | Invoke Azure Functions |\n| MCP | `MCPToolDefinition` | Model Context Protocol tools |\n\n## Key Types Reference\n\n| Type | Purpose |\n|------|---------|\n| `AIProjectClient` | Main entry point |\n| `PersistentAgentsClient` | Low-level agent operations |\n| `PromptAgentDefinition` | Versioned agent definition |\n| `AgentVersion` | Versioned agent instance |\n| `AIProjectConnection` | Connection to Azure resource |\n| `AIProjectDeployment` | Model deployment info |\n| `AIProjectDataset` | Dataset metadata |\n| `AIProjectIndex` | Search index metadata |\n| `Evaluation` | Evaluation configuration and results |\n\n## Best Practices\n\n1. **Use `DefaultAzureCredential`** for production authentication\n2. **Use async methods** (`*Async`) for all I\u002FO operations\n3. **Poll with appropriate delays** (500ms recommended) when waiting for runs\n4. **Clean up resources** — delete threads, agents, and files when done\n5. **Use versioned agents** (via `Azure.AI.Projects.OpenAI`) for production scenarios\n6. **Store connection IDs** rather than names for tool configurations\n7. **Use `includeCredentials: true`** only when credentials are needed\n8. **Handle pagination** — use `AsyncPageable\u003CT>` for listing operations\n\n## Error Handling\n\n```csharp\nusing Azure;\n\ntry\n{\n    var result = await projectClient.Evaluations.CreateAsync(evaluation);\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.Projects` | High-level project client (this SDK) | `dotnet add package Azure.AI.Projects` |\n| `Azure.AI.Agents.Persistent` | Low-level agent operations | `dotnet add package Azure.AI.Agents.Persistent` |\n| `Azure.AI.Projects.OpenAI` | Versioned agents with OpenAI | `dotnet add package Azure.AI.Projects.OpenAI` |\n\n## Reference Links\n\n| Resource | URL |\n|----------|-----|\n| NuGet Package | https:\u002F\u002Fwww.nuget.org\u002Fpackages\u002FAzure.AI.Projects |\n| API Reference | https:\u002F\u002Flearn.microsoft.com\u002Fdotnet\u002Fapi\u002Fazure.ai.projects |\n| GitHub Source | https:\u002F\u002Fgithub.com\u002FAzure\u002Fazure-sdk-for-net\u002Ftree\u002Fmain\u002Fsdk\u002Fai\u002FAzure.AI.Projects |\n| Samples | https:\u002F\u002Fgithub.com\u002FAzure\u002Fazure-sdk-for-net\u002Ftree\u002Fmain\u002Fsdk\u002Fai\u002FAzure.AI.Projects\u002Fsamples |\n","# Azure.AI.Projects (.NET)\n\nHigh-level SDK for Azure AI Foundry project operations including agents, connections, datasets, deployments, evaluations, and indexes.\n\n## Installation\n\n```bash\ndotnet add package Azure.AI.Projects\ndotnet add package Azure.Identity\n\n# Optional: For versioned agents with OpenAI extensions\ndotnet add package Azure.AI.Projects.OpenAI --prerelease\n\n# Optional: For low-level agent operations\ndotnet add package Azure.AI.Agents.Persistent --prerelease\n```\n\n**Current Versions**: GA v1.1.0, Preview v1.2.0-beta.5\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\nCONNECTION_NAME=\u003Cyour-connection-name>\nAI_SEARCH_CONNECTION_NAME=\u003Cai-search-connection>\n```\n\n## Authentication\n\n```csharp\nusing Azure.Identity;\nusing Azure.AI.Projects;\n\nvar endpoint = Environment.GetEnvironmentVariable(\"PROJECT_ENDPOINT\");\nAIProjectClient projectClient = new AIProjectClient(\n    new Uri(endpoint),\n    new DefaultAzureCredential());\n```\n\n## Client Hierarchy\n\n```\nAIProjectClient\n├── Agents          → AIProjectAgentsOperations (versioned agents)\n├── Connections     → ConnectionsClient\n├── Datasets        → DatasetsClient\n├── Deployments     → DeploymentsClient\n├── Evaluations     → EvaluationsClient\n├── Evaluators      → EvaluatorsClient\n├── Indexes         → IndexesClient\n├── Telemetry       → AIProjectTelemetry\n├── OpenAI          → ProjectOpenAIClient (preview)\n└── GetPersistentAgentsClient() → PersistentAgentsClient\n```\n\n## Core Workflows\n\n### 1. Get Persistent Agents Client\n\n```csharp\n\u002F\u002F Get low-level agents client from project client\nPersistentAgentsClient agentsClient = projectClient.GetPersistentAgentsClient();\n\n\u002F\u002F Create agent\nPersistentAgent agent = await agentsClient.Administration.CreateAgentAsync(\n    model: \"gpt-4o-mini\",\n    name: \"Math Tutor\",\n    instructions: \"You are a personal math tutor.\");\n\n\u002F\u002F Create thread and run\nPersistentAgentThread thread = await agentsClient.Threads.CreateThreadAsync();\nawait agentsClient.Messages.CreateMessageAsync(thread.Id, MessageRole.User, \"Solve 3x + 11 = 14\");\nThreadRun run = await agentsClient.Runs.CreateRunAsync(thread.Id, agent.Id);\n\n\u002F\u002F Poll for completion\ndo\n{\n    await Task.Delay(500);\n    run = await agentsClient.Runs.GetRunAsync(thread.Id, run.Id);\n}\nwhile (run.Status == RunStatus.Queued || run.Status == RunStatus.InProgress);\n\n\u002F\u002F Get messages\nawait foreach (var msg in agentsClient.Messages.GetMessagesAsync(thread.Id))\n{\n    foreach (var content in msg.ContentItems)\n    {\n        if (content is MessageTextContent textContent)\n            Console.WriteLine(textContent.Text);\n    }\n}\n\n\u002F\u002F Cleanup\nawait agentsClient.Threads.DeleteThreadAsync(thread.Id);\nawait agentsClient.Administration.DeleteAgentAsync(agent.Id);\n```\n\n### 2. Versioned Agents with Tools (Preview)\n\n```csharp\nusing Azure.AI.Projects.OpenAI;\n\n\u002F\u002F Create agent with web search tool\nPromptAgentDefinition agentDefinition = new(model: \"gpt-4o-mini\")\n{\n    Instructions = \"You are a helpful assistant that can search the web\",\n    Tools = {\n        ResponseTool.CreateWebSearchTool(\n            userLocation: WebSearchToolLocation.CreateApproximateLocation(\n                country: \"US\",\n                city: \"Seattle\",\n                region: \"Washington\"\n            )\n        ),\n    }\n};\n\nAgentVersion agentVersion = await projectClient.Agents.CreateAgentVersionAsync(\n    agentName: \"myAgent\",\n    options: new(agentDefinition));\n\n\u002F\u002F Get response client\nProjectResponsesClient responseClient = projectClient.OpenAI.GetProjectResponsesClientForAgent(agentVersion.Name);\n\n\u002F\u002F Create response\nResponseResult response = responseClient.CreateResponse(\"What's the weather in Seattle?\");\nConsole.WriteLine(response.GetOutputText());\n\n\u002F\u002F Cleanup\nprojectClient.Agents.DeleteAgentVersion(agentName: agentVersion.Name, agentVersion: agentVersion.Version);\n```\n\n### 3. Connections\n\n```csharp\n\u002F\u002F List all connections\nforeach (AIProjectConnection connection in projectClient.Connections.GetConnections())\n{\n    Console.WriteLine($\"{connection.Name}: {connection.ConnectionType}\");\n}\n\n\u002F\u002F Get specific connection\nAIProjectConnection conn = projectClient.Connections.GetConnection(\n    connectionName,\n    includeCredentials: true);\n\n\u002F\u002F Get default connection\nAIProjectConnection defaultConn = projectClient.Connections.GetDefaultConnection(\n    includeCredentials: false);\n```\n\n### 4. Deployments\n\n```csharp\n\u002F\u002F List all deployments\nforeach (AIProjectDeployment deployment in projectClient.Deployments.GetDeployments())\n{\n    Console.WriteLine($\"{deployment.Name}: {deployment.ModelName}\");\n}\n\n\u002F\u002F Filter by publisher\nforeach (var deployment in projectClient.Deployments.GetDeployments(modelPublisher: \"Microsoft\"))\n{\n    Console.WriteLine(deployment.Name);\n}\n\n\u002F\u002F Get specific deployment\nModelDeployment details = (ModelDeployment)projectClient.Deployments.GetDeployment(\"gpt-4o-mini\");\n```\n\n### 5. Datasets\n\n```csharp\n\u002F\u002F Upload single file\nFileDataset fileDataset = projectClient.Datasets.UploadFile(\n    name: \"my-dataset\",\n    version: \"1.0\",\n    filePath: \"data\u002Ftraining.txt\",\n    connectionName: connectionName);\n\n\u002F\u002F Upload folder\nFolderDataset folderDataset = projectClient.Datasets.UploadFolder(\n    name: \"my-dataset\",\n    version: \"2.0\",\n    folderPath: \"data\u002Ftraining\",\n    connectionName: connectionName,\n    filePattern: new Regex(\".*\\\\.txt\"));\n\n\u002F\u002F Get dataset\nAIProjectDataset dataset = projectClient.Datasets.GetDataset(\"my-dataset\", \"1.0\");\n\n\u002F\u002F Delete dataset\nprojectClient.Datasets.Delete(\"my-dataset\", \"1.0\");\n```\n\n### 6. Indexes\n\n```csharp\n\u002F\u002F Create Azure AI Search index\nAzureAISearchIndex searchIndex = new(aiSearchConnectionName, aiSearchIndexName)\n{\n    Description = \"Sample Index\"\n};\n\nsearchIndex = (AzureAISearchIndex)projectClient.Indexes.CreateOrUpdate(\n    name: \"my-index\",\n    version: \"1.0\",\n    index: searchIndex);\n\n\u002F\u002F List indexes\nforeach (AIProjectIndex index in projectClient.Indexes.GetIndexes())\n{\n    Console.WriteLine(index.Name);\n}\n\n\u002F\u002F Delete index\nprojectClient.Indexes.Delete(name: \"my-index\", version: \"1.0\");\n```\n\n### 7. Evaluations\n\n```csharp\n\u002F\u002F Create evaluation configuration\nvar evaluatorConfig = new EvaluatorConfiguration(id: EvaluatorIDs.Relevance);\nevaluatorConfig.InitParams.Add(\"deployment_name\", BinaryData.FromObjectAsJson(\"gpt-4o\"));\n\n\u002F\u002F Create evaluation\nEvaluation evaluation = new Evaluation(\n    data: new InputDataset(\"\u003Cdataset_id>\"),\n    evaluators: new Dictionary\u003Cstring, EvaluatorConfiguration>\n    {\n        { \"relevance\", evaluatorConfig }\n    }\n)\n{\n    DisplayName = \"Sample Evaluation\"\n};\n\n\u002F\u002F Run evaluation\nEvaluation result = projectClient.Evaluations.Create(evaluation: evaluation);\n\n\u002F\u002F Get evaluation\nEvaluation getResult = projectClient.Evaluations.Get(result.Name);\n\n\u002F\u002F List evaluations\nforeach (var eval in projectClient.Evaluations.GetAll())\n{\n    Console.WriteLine($\"{eval.DisplayName}: {eval.Status}\");\n}\n```\n\n### 8. Get Azure OpenAI Chat Client\n\n```csharp\nusing Azure.AI.OpenAI;\nusing OpenAI.Chat;\n\nClientConnection connection = projectClient.GetConnection(typeof(AzureOpenAIClient).FullName!);\n\nif (!connection.TryGetLocatorAsUri(out Uri uri) || uri is null)\n    throw new InvalidOperationException(\"Invalid URI.\");\n\nuri = new Uri($\"https:\u002F\u002F{uri.Host}\");\n\nAzureOpenAIClient azureOpenAIClient = new AzureOpenAIClient(uri, new DefaultAzureCredential());\nChatClient chatClient = azureOpenAIClient.GetChatClient(\"gpt-4o-mini\");\n\nChatCompletion result = chatClient.CompleteChat(\"List all rainbow colors\");\nConsole.WriteLine(result.Content[0].Text);\n```\n\n## Available Agent Tools\n\n| Tool | Class | Purpose |\n|------|-------|---------|\n| Code Interpreter | `CodeInterpreterToolDefinition` | Execute Python code |\n| File Search | `FileSearchToolDefinition` | Search uploaded files |\n| Function Calling | `FunctionToolDefinition` | Call custom functions |\n| Bing Grounding | `BingGroundingToolDefinition` | Web search via Bing |\n| Azure AI Search | `AzureAISearchToolDefinition` | Search Azure AI indexes |\n| OpenAPI | `OpenApiToolDefinition` | Call external APIs |\n| Azure Functions | `AzureFunctionToolDefinition` | Invoke Azure Functions |\n| MCP | `MCPToolDefinition` | Model Context Protocol tools |\n\n## Key Types Reference\n\n| Type | Purpose |\n|------|---------|\n| `AIProjectClient` | Main entry point |\n| `PersistentAgentsClient` | Low-level agent operations |\n| `PromptAgentDefinition` | Versioned agent definition |\n| `AgentVersion` | Versioned agent instance |\n| `AIProjectConnection` | Connection to Azure resource |\n| `AIProjectDeployment` | Model deployment info |\n| `AIProjectDataset` | Dataset metadata |\n| `AIProjectIndex` | Search index metadata |\n| `Evaluation` | Evaluation configuration and results |\n\n## Best Practices\n\n1. **Use `DefaultAzureCredential`** for production authentication\n2. **Use async methods** (`*Async`) for all I\u002FO operations\n3. **Poll with appropriate delays** (500ms recommended) when waiting for runs\n4. **Clean up resources** — delete threads, agents, and files when done\n5. **Use versioned agents** (via `Azure.AI.Projects.OpenAI`) for production scenarios\n6. **Store connection IDs** rather than names for tool configurations\n7. **Use `includeCredentials: true`** only when credentials are needed\n8. **Handle pagination** — use `AsyncPageable\u003CT>` for listing operations\n\n## Error Handling\n\n```csharp\nusing Azure;\n\ntry\n{\n    var result = await projectClient.Evaluations.CreateAsync(evaluation);\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.Projects` | High-level project client (this SDK) | `dotnet add package Azure.AI.Projects` |\n| `Azure.AI.Agents.Persistent` | Low-level agent operations | `dotnet add package Azure.AI.Agents.Persistent` |\n| `Azure.AI.Projects.OpenAI` | Versioned agents with OpenAI | `dotnet add package Azure.AI.Projects.OpenAI` |\n\n## Reference Links\n\n| Resource | URL |\n|----------|-----|\n| NuGet Package | https:\u002F\u002Fwww.nuget.org\u002Fpackages\u002FAzure.AI.Projects |\n| API Reference | https:\u002F\u002Flearn.microsoft.com\u002Fdotnet\u002Fapi\u002Fazure.ai.projects |\n| GitHub Source | https:\u002F\u002Fgithub.com\u002FAzure\u002Fazure-sdk-for-net\u002Ftree\u002Fmain\u002Fsdk\u002Fai\u002FAzure.AI.Projects |\n| Samples | https:\u002F\u002Fgithub.com\u002FAzure\u002Fazure-sdk-for-net\u002Ftree\u002Fmain\u002Fsdk\u002Fai\u002FAzure.AI.Projects\u002Fsamples |\n",{"name":5,"license":15,"metadata":44,"description":48},{"author":45,"package":46,"version":47},"Microsoft","Azure.AI.Projects","1.0.0","Azure AI Projects SDK for .NET. High-level client for Azure AI Foundry projects including agents, connections, datasets, deployments, evaluations, and indexes. Use for AI Foundry project management, versioned agents, and orchestration. Triggers: \"AI Projects\", \"AIProjectClient\", \"Foundry project\", \"versioned agents\", \"evaluations\", \"datasets\", \"connections\", \"deployments .NET\".\n","main","5c95bcac4646c5aed06bd9aed5235cfc7985aafc","included\u002Fskills\u002Fby-category\u002Fcloud-azure-microsoft-sdks\u002Fofficial-vendor-reference\u002Fazure-ai-projects-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":57,"prompt":67,"zipAvailable":68},[58,61,64],{"tool":59,"command":60},"npx","npx skills add strmt7\u002Fai_skills_collection_benchmarked --skill azure-ai-projects-dotnet",{"tool":62,"command":63},"bunx","bunx skills add strmt7\u002Fai_skills_collection_benchmarked --skill azure-ai-projects-dotnet",{"tool":65,"command":66},"pnpm","pnpm dlx skills add strmt7\u002Fai_skills_collection_benchmarked --skill azure-ai-projects-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-projects-dotnet\u002FSKILL.md",true,[70],{"path":71,"resourceType":72,"resourceTypeDesc":73,"sizeBytes":74,"sourceHtmlUrl":75},"references\u002Facceptance-criteria.md","REFERENCE","参考文档",15727,"https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fcloud-azure-microsoft-sdks\u002Fofficial-vendor-reference\u002Fazure-ai-projects-dotnet\u002Freferences\u002Facceptance-criteria.md",[77,110,140,165,190,218],{"skillNo":78,"name":79,"nameZh":6,"description":80,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":81,"licenseFileUrl":82,"sourceHtmlUrl":83,"categories":84,"keywords":93,"publishedAt":39},"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",[85,90],{"categoryNo":86,"categoryName":87,"taxonomyType":88,"taxonomyTypeDesc":89},"01JBSEEDCAT000000000000008","测试与质量","SCENARIO","使用场景",{"categoryNo":91,"categoryName":92,"taxonomyType":88,"taxonomyTypeDesc":89},"01JBSEEDCAT000000000000009","前端开发",[94,95,96,37,97,98,99,100,101,102,103,104,105,106,107,108,109],"webapp","testing","webapp testing","applications","local","frontend","debugging","toolkit","logs","browser","with","playwright","web","behavior","ui","screenshots",{"skillNo":111,"name":112,"nameZh":6,"description":113,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":81,"licenseFileUrl":114,"sourceHtmlUrl":115,"categories":116,"keywords":120,"publishedAt":39},"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",[117],{"categoryNo":118,"categoryName":119,"taxonomyType":88,"taxonomyTypeDesc":89},"01JBSEEDCAT000000000000023","Skill与智能体开发",[121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,37,139],"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":141,"name":142,"nameZh":6,"description":143,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":144,"categories":145,"keywords":148,"publishedAt":39},"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",[146,147],{"categoryNo":86,"categoryName":87,"taxonomyType":88,"taxonomyTypeDesc":89},{"categoryNo":118,"categoryName":119,"taxonomyType":88,"taxonomyTypeDesc":89},[105,149,150,151,95,152,153,127,154,103,155,156,157,158,159,160,161,162,163,164],"playwright skill","browser automation","flows","auto","access","Bash","website","ux","login","scripts","read","write","node","install","network","responsive",{"skillNo":166,"name":167,"nameZh":6,"description":168,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":81,"licenseFileUrl":169,"sourceHtmlUrl":170,"categories":171,"keywords":173,"publishedAt":39},"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",[172],{"categoryNo":91,"categoryName":92,"taxonomyType":88,"taxonomyTypeDesc":89},[174,175,176,106,177,178,179,37,180,181,99,182,32,183,184,185,186,187,188,189],"builder","artifacts builder","artifacts","web artifacts builder","single-file","css","Tailwind","ui components","single","file","components","react","multi","state","routing","state management",{"skillNo":191,"name":192,"nameZh":6,"description":193,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":81,"licenseFileUrl":194,"sourceHtmlUrl":195,"categories":196,"keywords":206,"publishedAt":39},"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",[197,198,201],{"categoryNo":91,"categoryName":92,"taxonomyType":88,"taxonomyTypeDesc":89},{"categoryNo":199,"categoryName":200,"taxonomyType":88,"taxonomyTypeDesc":89},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":202,"categoryName":203,"taxonomyType":204,"taxonomyTypeDesc":205},"01JBSEEDCAT000000000000032","设计师","PROFESSION","适用职业",[99,207,208,179,209,210,211,97,212,213,32,127,176,214,184,215,185,216,217,104],"design","frontend design","ui design","generic","aesthetics","landing","pages","code","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":39},"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",[],[225,226,227,228,229,230,231,232,233,37,234,235,236,237,238,239,240,241],"zarr python","python","zarr","arrays","Cloud Storage","scientific","storage","parallel","dask","numpy","gcs","s3","integration","scientific computing","cloud","scale","pipelines"]