# SkillPatch skill: azure-ai-projects-dotnet

This skill provides comprehensive guidance for using the Azure AI Projects SDK for .NET (Azure.AI.Projects). It covers installation, authentication, client hierarchy, and core workflows for managing Azure AI Foundry projects including agents, connections, datasets, deployments, evaluations, and indexes. It includes detailed C# code examples for creating and managing persistent agents, threads, and runs.

You (the agent) were given this URL and asked to use this skill. This is a **public** skill — no SkillPatch account, API key, or prior setup is required. Two ways to use it:

**1. Use it right now** — the skill's complete file tree (SKILL.md + all reference files) is inlined below; read `SKILL.md` first, then follow it, consulting the other files as it directs.

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```bash
mkdir -p .claude/skills/azure-ai-projects-dotnet
curl -sSL https://skillpatch.dev/install_skill/azure-ai-projects-dotnet | tar -xz -C .claude/skills/
```

(`.claude/skills/` is Claude Code's convention; use whatever directory your agent loads skills from.)


---

## Skill files (1)

- `SKILL.md`


### `SKILL.md`

````markdown
---
name: azure-ai-projects-dotnet
description: |
  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".
license: MIT
metadata:
  author: Microsoft
  version: "1.0.0"
  package: Azure.AI.Projects
---

# Azure.AI.Projects (.NET)

High-level SDK for Azure AI Foundry project operations including agents, connections, datasets, deployments, evaluations, and indexes.

## Installation

```bash
dotnet add package Azure.AI.Projects
dotnet add package Azure.Identity

# Optional: For versioned agents with OpenAI extensions
dotnet add package Azure.AI.Projects.OpenAI --prerelease

# Optional: For low-level agent operations
dotnet add package Azure.AI.Agents.Persistent --prerelease
```

**Current Versions**: GA v1.1.0, Preview v1.2.0-beta.5

## Environment Variables

```bash
PROJECT_ENDPOINT=https://<resource>.services.ai.azure.com/api/projects/<project>  # Required: Azure AI project endpoint
MODEL_DEPLOYMENT_NAME=gpt-4o-mini  # Required: model deployment name
CONNECTION_NAME=<your-connection-name>  # Optional: project connection name
AI_SEARCH_CONNECTION_NAME=<ai-search-connection>  # Optional: Azure AI Search connection name
AZURE_TOKEN_CREDENTIALS=prod  # Required only if DefaultAzureCredential is used in production
```

## Authentication

```csharp
using Azure.Identity;
using Azure.AI.Projects;

var endpoint = Environment.GetEnvironmentVariable("PROJECT_ENDPOINT");
// Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=<specific_credential>
var credential = new DefaultAzureCredential(
    DefaultAzureCredential.DefaultEnvironmentVariableName
);
// Or use a specific credential directly in production:
// See https://learn.microsoft.com/dotnet/api/overview/azure/identity-readme?view=azure-dotnet#credential-classes
// var credential = new ManagedIdentityCredential();
AIProjectClient projectClient = new AIProjectClient(
    new Uri(endpoint), 
    credential);
```

## Client Hierarchy

```
AIProjectClient
├── Agents          → AIProjectAgentsOperations (versioned agents)
├── Connections     → ConnectionsClient
├── Datasets        → DatasetsClient
├── Deployments     → DeploymentsClient
├── Evaluations     → EvaluationsClient
├── Evaluators      → EvaluatorsClient
├── Indexes         → IndexesClient
├── Telemetry       → AIProjectTelemetry
├── OpenAI          → ProjectOpenAIClient (preview)
└── GetPersistentAgentsClient() → PersistentAgentsClient
```

## Core Workflows

### 1. Get Persistent Agents Client

```csharp
// Get low-level agents client from project client
PersistentAgentsClient agentsClient = projectClient.GetPersistentAgentsClient();

// Create agent
PersistentAgent agent = await agentsClient.Administration.CreateAgentAsync(
    model: "gpt-4o-mini",
    name: "Math Tutor",
    instructions: "You are a personal math tutor.");

// Create thread and run
PersistentAgentThread thread = await agentsClient.Threads.CreateThreadAsync();
await agentsClient.Messages.CreateMessageAsync(thread.Id, MessageRole.User, "Solve 3x + 11 = 14");
ThreadRun run = await agentsClient.Runs.CreateRunAsync(thread.Id, agent.Id);

// Poll for completion
do
{
    await Task.Delay(500);
    run = await agentsClient.Runs.GetRunAsync(thread.Id, run.Id);
}
while (run.Status == RunStatus.Queued || run.Status == RunStatus.InProgress);

// Get messages
await foreach (var msg in agentsClient.Messages.GetMessagesAsync(thread.Id))
{
    foreach (var content in msg.ContentItems)
    {
        if (content is MessageTextContent textContent)
            Console.WriteLine(textContent.Text);
    }
}

// Cleanup
await agentsClient.Threads.DeleteThreadAsync(thread.Id);
await agentsClient.Administration.DeleteAgentAsync(agent.Id);
```

### 2. Versioned Agents with Tools (Preview)

```csharp
using Azure.AI.Projects.OpenAI;

// Create agent with web search tool
PromptAgentDefinition agentDefinition = new(model: "gpt-4o-mini")
{
    Instructions = "You are a helpful assistant that can search the web",
    Tools = {
        ResponseTool.CreateWebSearchTool(
            userLocation: WebSearchToolLocation.CreateApproximateLocation(
                country: "US",
                city: "Seattle",
                region: "Washington"
            )
        ),
    }
};

AgentVersion agentVersion = await projectClient.Agents.CreateAgentVersionAsync(
    agentName: "myAgent",
    options: new(agentDefinition));

// Get response client
ProjectResponsesClient responseClient = projectClient.OpenAI.GetProjectResponsesClientForAgent(agentVersion.Name);

// Create response
ResponseResult response = responseClient.CreateResponse("What's the weather in Seattle?");
Console.WriteLine(response.GetOutputText());

// Cleanup
projectClient.Agents.DeleteAgentVersion(agentName: agentVersion.Name, agentVersion: agentVersion.Version);
```

### 3. Connections

```csharp
// List all connections
foreach (AIProjectConnection connection in projectClient.Connections.GetConnections())
{
    Console.WriteLine($"{connection.Name}: {connection.ConnectionType}");
}

// Get specific connection
AIProjectConnection conn = projectClient.Connections.GetConnection(
    connectionName, 
    includeCredentials: true);

// Get default connection
AIProjectConnection defaultConn = projectClient.Connections.GetDefaultConnection(
    includeCredentials: false);
```

### 4. Deployments

```csharp
// List all deployments
foreach (AIProjectDeployment deployment in projectClient.Deployments.GetDeployments())
{
    Console.WriteLine($"{deployment.Name}: {deployment.ModelName}");
}

// Filter by publisher
foreach (var deployment in projectClient.Deployments.GetDeployments(modelPublisher: "Microsoft"))
{
    Console.WriteLine(deployment.Name);
}

// Get specific deployment
ModelDeployment details = (ModelDeployment)projectClient.Deployments.GetDeployment("gpt-4o-mini");
```

### 5. Datasets

```csharp
// Upload single file
FileDataset fileDataset = projectClient.Datasets.UploadFile(
    name: "my-dataset",
    version: "1.0",
    filePath: "data/training.txt",
    connectionName: connectionName);

// Upload folder
FolderDataset folderDataset = projectClient.Datasets.UploadFolder(
    name: "my-dataset",
    version: "2.0",
    folderPath: "data/training",
    connectionName: connectionName,
    filePattern: new Regex(".*\\.txt"));

// Get dataset
AIProjectDataset dataset = projectClient.Datasets.GetDataset("my-dataset", "1.0");

// Delete dataset
projectClient.Datasets.Delete("my-dataset", "1.0");
```

### 6. Indexes

```csharp
// Create Azure AI Search index
AzureAISearchIndex searchIndex = new(aiSearchConnectionName, aiSearchIndexName)
{
    Description = "Sample Index"
};

searchIndex = (AzureAISearchIndex)projectClient.Indexes.CreateOrUpdate(
    name: "my-index",
    version: "1.0",
    index: searchIndex);

// List indexes
foreach (AIProjectIndex index in projectClient.Indexes.GetIndexes())
{
    Console.WriteLine(index.Name);
}

// Delete index
projectClient.Indexes.Delete(name: "my-index", version: "1.0");
```

### 7. Evaluations

```csharp
// Create evaluation configuration
var evaluatorConfig = new EvaluatorConfiguration(id: EvaluatorIDs.Relevance);
evaluatorConfig.InitParams.Add("deployment_name", BinaryData.FromObjectAsJson("gpt-4o"));

// Create evaluation
Evaluation evaluation = new Evaluation(
    data: new InputDataset("<dataset_id>"),
    evaluators: new Dictionary<string, EvaluatorConfiguration> 
    { 
        { "relevance", evaluatorConfig } 
    }
)
{
    DisplayName = "Sample Evaluation"
};

// Run evaluation
Evaluation result = projectClient.Evaluations.Create(evaluation: evaluation);

// Get evaluation
Evaluation getResult = projectClient.Evaluations.Get(result.Name);

// List evaluations
foreach (var eval in projectClient.Evaluations.GetAll())
{
    Console.WriteLine($"{eval.DisplayName}: {eval.Status}");
}
```

### 8. Get Azure OpenAI Chat Client

```csharp
using Azure.AI.OpenAI;
using OpenAI.Chat;

ClientConnection connection = projectClient.GetConnection(typeof(AzureOpenAIClient).FullName!);

if (!connection.TryGetLocatorAsUri(out Uri uri) || uri is null)
    throw new InvalidOperationException("Invalid URI.");

uri = new Uri($"https://{uri.Host}");

AzureOpenAIClient azureOpenAIClient = new AzureOpenAIClient(uri, new DefaultAzureCredential());
ChatClient chatClient = azureOpenAIClient.GetChatClient("gpt-4o-mini");

ChatCompletion result = chatClient.CompleteChat("List all rainbow colors");
Console.WriteLine(result.Content[0].Text);
```

## Available Agent Tools

| Tool | Class | Purpose |
|------|-------|---------|
| Code Interpreter | `CodeInterpreterToolDefinition` | Execute Python code |
| File Search | `FileSearchToolDefinition` | Search uploaded files |
| Function Calling | `FunctionToolDefinition` | Call custom functions |
| Bing Grounding | `BingGroundingToolDefinition` | Web search via Bing |
| Azure AI Search | `AzureAISearchToolDefinition` | Search Azure AI indexes |
| OpenAPI | `OpenApiToolDefinition` | Call external APIs |
| Azure Functions | `AzureFunctionToolDefinition` | Invoke Azure Functions |
| MCP | `MCPToolDefinition` | Model Context Protocol tools |

## Key Types Reference

| Type | Purpose |
|------|---------|
| `AIProjectClient` | Main entry point |
| `PersistentAgentsClient` | Low-level agent operations |
| `PromptAgentDefinition` | Versioned agent definition |
| `AgentVersion` | Versioned agent instance |
| `AIProjectConnection` | Connection to Azure resource |
| `AIProjectDeployment` | Model deployment info |
| `AIProjectDataset` | Dataset metadata |
| `AIProjectIndex` | Search index metadata |
| `Evaluation` | Evaluation configuration and results |

## Best Practices

1. **Use `DefaultAzureCredential`** for production authentication
2. **Use async methods** (`*Async`) for all I/O operations
3. **Poll with appropriate delays** (500ms recommended) when waiting for runs
4. **Clean up resources** — delete threads, agents, and files when done
5. **Use versioned agents** (via `Azure.AI.Projects.OpenAI`) for production scenarios
6. **Store connection IDs** rather than names for tool configurations
7. **Use `includeCredentials: true`** only when credentials are needed
8. **Handle pagination** — use `AsyncPageable<T>` for listing operations

## Error Handling

```csharp
using Azure;

try
{
    var result = await projectClient.Evaluations.CreateAsync(evaluation);
}
catch (RequestFailedException ex)
{
    Console.WriteLine($"Error: {ex.Status} - {ex.ErrorCode}: {ex.Message}");
}
```

## Related SDKs

| SDK | Purpose | Install |
|-----|---------|---------|
| `Azure.AI.Projects` | High-level project client (this SDK) | `dotnet add package Azure.AI.Projects` |
| `Azure.AI.Agents.Persistent` | Low-level agent operations | `dotnet add package Azure.AI.Agents.Persistent` |
| `Azure.AI.Projects.OpenAI` | Versioned agents with OpenAI | `dotnet add package Azure.AI.Projects.OpenAI` |

## Reference Links

| Resource | URL |
|----------|-----|
| NuGet Package | https://www.nuget.org/packages/Azure.AI.Projects |
| API Reference | https://learn.microsoft.com/dotnet/api/azure.ai.projects |
| GitHub Source | https://github.com/Azure/azure-sdk-for-net/tree/main/sdk/ai/Azure.AI.Projects |
| Samples | https://github.com/Azure/azure-sdk-for-net/tree/main/sdk/ai/Azure.AI.Projects/samples |

````