Files
antigravity-skills-reference/skills/azure-ai-agents-persistent-dotnet/SKILL.md
Ares 4a5f1234bb fix: harden registry tooling, make tests hermetic, and restore metadata consistency (#168)
* chore: upgrade maintenance scripts to robust PyYAML parsing

- Replaces fragile regex frontmatter parsing with PyYAML/yaml library
- Ensures multi-line descriptions and complex characters are handled safely
- Normalizes quoting and field ordering across all maintenance scripts
- Updates validator to strictly enforce description quality

* fix: restore and refine truncated skill descriptions

- Recovered 223+ truncated descriptions from git history (6.5.0 regression)
- Refined long descriptions into concise, complete sentences (<200 chars)
- Added missing descriptions for brainstorming and orchestration skills
- Manually fixed imagen skill description
- Resolved dangling links in competitor-alternatives skill

* chore: sync generated registry files and document fixes

- Regenerated skills index with normalized forward-slash paths
- Updated README and CATALOG to reflect restored descriptions
- Documented restoration and script improvements in CHANGELOG.md

* fix: restore missing skill and align metadata for full 955 count

- Renamed SKILL.MD to SKILL.md in andruia-skill-smith to ensure indexing
- Fixed risk level and missing section in andruia-skill-smith
- Synchronized all registry files for final 955 skill count

* chore(scripts): add cross-platform runners and hermetic test orchestration

* fix(scripts): harden utf-8 output and clone target writeability

* fix(skills): add missing date metadata for strict validation

* chore(index): sync generated metadata dates

* fix(catalog): normalize skill paths to prevent CI drift

* chore: sync generated registry files

* fix: enforce LF line endings for generated registry files
2026-03-01 09:38:25 +01:00

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Markdown

---
name: azure-ai-agents-persistent-dotnet
description: Azure AI Agents Persistent SDK for .NET. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools.
risk: unknown
source: community
date_added: '2026-02-27'
---
# Azure.AI.Agents.Persistent (.NET)
Low-level SDK for creating and managing persistent AI agents with threads, messages, runs, and tools.
## Installation
```bash
dotnet add package Azure.AI.Agents.Persistent --prerelease
dotnet add package Azure.Identity
```
**Current Versions**: Stable v1.1.0, Preview v1.2.0-beta.8
## Environment Variables
```bash
PROJECT_ENDPOINT=https://<resource>.services.ai.azure.com/api/projects/<project>
MODEL_DEPLOYMENT_NAME=gpt-4o-mini
AZURE_BING_CONNECTION_ID=<bing-connection-resource-id>
AZURE_AI_SEARCH_CONNECTION_ID=<search-connection-resource-id>
```
## Authentication
```csharp
using Azure.AI.Agents.Persistent;
using Azure.Identity;
var projectEndpoint = Environment.GetEnvironmentVariable("PROJECT_ENDPOINT");
PersistentAgentsClient client = new(projectEndpoint, new DefaultAzureCredential());
```
## Client Hierarchy
```
PersistentAgentsClient
├── Administration → Agent CRUD operations
├── Threads → Thread management
├── Messages → Message operations
├── Runs → Run execution and streaming
├── Files → File upload/download
└── VectorStores → Vector store management
```
## Core Workflow
### 1. Create Agent
```csharp
var modelDeploymentName = Environment.GetEnvironmentVariable("MODEL_DEPLOYMENT_NAME");
PersistentAgent agent = await client.Administration.CreateAgentAsync(
model: modelDeploymentName,
name: "Math Tutor",
instructions: "You are a personal math tutor. Write and run code to answer math questions.",
tools: [new CodeInterpreterToolDefinition()]
);
```
### 2. Create Thread and Message
```csharp
// Create thread
PersistentAgentThread thread = await client.Threads.CreateThreadAsync();
// Create message
await client.Messages.CreateMessageAsync(
thread.Id,
MessageRole.User,
"I need to solve the equation `3x + 11 = 14`. Can you help me?"
);
```
### 3. Run Agent (Polling)
```csharp
// Create run
ThreadRun run = await client.Runs.CreateRunAsync(
thread.Id,
agent.Id,
additionalInstructions: "Please address the user as Jane Doe."
);
// Poll for completion
do
{
await Task.Delay(TimeSpan.FromMilliseconds(500));
run = await client.Runs.GetRunAsync(thread.Id, run.Id);
}
while (run.Status == RunStatus.Queued || run.Status == RunStatus.InProgress);
// Retrieve messages
await foreach (PersistentThreadMessage message in client.Messages.GetMessagesAsync(
threadId: thread.Id,
order: ListSortOrder.Ascending))
{
Console.Write($"{message.Role}: ");
foreach (MessageContent content in message.ContentItems)
{
if (content is MessageTextContent textContent)
Console.WriteLine(textContent.Text);
}
}
```
### 4. Streaming Response
```csharp
AsyncCollectionResult<StreamingUpdate> stream = client.Runs.CreateRunStreamingAsync(
thread.Id,
agent.Id
);
await foreach (StreamingUpdate update in stream)
{
if (update.UpdateKind == StreamingUpdateReason.RunCreated)
{
Console.WriteLine("--- Run started! ---");
}
else if (update is MessageContentUpdate contentUpdate)
{
Console.Write(contentUpdate.Text);
}
else if (update.UpdateKind == StreamingUpdateReason.RunCompleted)
{
Console.WriteLine("\n--- Run completed! ---");
}
}
```
### 5. Function Calling
```csharp
// Define function tool
FunctionToolDefinition weatherTool = new(
name: "getCurrentWeather",
description: "Gets the current weather at a location.",
parameters: BinaryData.FromObjectAsJson(new
{
Type = "object",
Properties = new
{
Location = new { Type = "string", Description = "City and state, e.g. San Francisco, CA" },
Unit = new { Type = "string", Enum = new[] { "c", "f" } }
},
Required = new[] { "location" }
}, new JsonSerializerOptions { PropertyNamingPolicy = JsonNamingPolicy.CamelCase })
);
// Create agent with function
PersistentAgent agent = await client.Administration.CreateAgentAsync(
model: modelDeploymentName,
name: "Weather Bot",
instructions: "You are a weather bot.",
tools: [weatherTool]
);
// Handle function calls during polling
do
{
await Task.Delay(500);
run = await client.Runs.GetRunAsync(thread.Id, run.Id);
if (run.Status == RunStatus.RequiresAction
&& run.RequiredAction is SubmitToolOutputsAction submitAction)
{
List<ToolOutput> outputs = [];
foreach (RequiredToolCall toolCall in submitAction.ToolCalls)
{
if (toolCall is RequiredFunctionToolCall funcCall)
{
// Execute function and get result
string result = ExecuteFunction(funcCall.Name, funcCall.Arguments);
outputs.Add(new ToolOutput(toolCall, result));
}
}
run = await client.Runs.SubmitToolOutputsToRunAsync(run, outputs, toolApprovals: null);
}
}
while (run.Status == RunStatus.Queued || run.Status == RunStatus.InProgress);
```
### 6. File Search with Vector Store
```csharp
// Upload file
PersistentAgentFileInfo file = await client.Files.UploadFileAsync(
filePath: "document.txt",
purpose: PersistentAgentFilePurpose.Agents
);
// Create vector store
PersistentAgentsVectorStore vectorStore = await client.VectorStores.CreateVectorStoreAsync(
fileIds: [file.Id],
name: "my_vector_store"
);
// Create file search resource
FileSearchToolResource fileSearchResource = new();
fileSearchResource.VectorStoreIds.Add(vectorStore.Id);
// Create agent with file search
PersistentAgent agent = await client.Administration.CreateAgentAsync(
model: modelDeploymentName,
name: "Document Assistant",
instructions: "You help users find information in documents.",
tools: [new FileSearchToolDefinition()],
toolResources: new ToolResources { FileSearch = fileSearchResource }
);
```
### 7. Bing Grounding
```csharp
var bingConnectionId = Environment.GetEnvironmentVariable("AZURE_BING_CONNECTION_ID");
BingGroundingToolDefinition bingTool = new(
new BingGroundingSearchToolParameters(
[new BingGroundingSearchConfiguration(bingConnectionId)]
)
);
PersistentAgent agent = await client.Administration.CreateAgentAsync(
model: modelDeploymentName,
name: "Search Agent",
instructions: "Use Bing to answer questions about current events.",
tools: [bingTool]
);
```
### 8. Azure AI Search
```csharp
AzureAISearchToolResource searchResource = new(
connectionId: searchConnectionId,
indexName: "my_index",
topK: 5,
filter: "category eq 'documentation'",
queryType: AzureAISearchQueryType.Simple
);
PersistentAgent agent = await client.Administration.CreateAgentAsync(
model: modelDeploymentName,
name: "Search Agent",
instructions: "Search the documentation index to answer questions.",
tools: [new AzureAISearchToolDefinition()],
toolResources: new ToolResources { AzureAISearch = searchResource }
);
```
### 9. Cleanup
```csharp
await client.Threads.DeleteThreadAsync(thread.Id);
await client.Administration.DeleteAgentAsync(agent.Id);
await client.VectorStores.DeleteVectorStoreAsync(vectorStore.Id);
await client.Files.DeleteFileAsync(file.Id);
```
## Available Tools
| Tool | Class | Purpose |
|------|-------|---------|
| Code Interpreter | `CodeInterpreterToolDefinition` | Execute Python code, generate visualizations |
| File Search | `FileSearchToolDefinition` | Search uploaded files via vector stores |
| Function Calling | `FunctionToolDefinition` | Call custom functions |
| Bing Grounding | `BingGroundingToolDefinition` | Web search via Bing |
| Azure AI Search | `AzureAISearchToolDefinition` | Search Azure AI Search indexes |
| OpenAPI | `OpenApiToolDefinition` | Call external APIs via OpenAPI spec |
| Azure Functions | `AzureFunctionToolDefinition` | Invoke Azure Functions |
| MCP | `MCPToolDefinition` | Model Context Protocol tools |
| SharePoint | `SharepointToolDefinition` | Access SharePoint content |
| Microsoft Fabric | `MicrosoftFabricToolDefinition` | Access Fabric data |
## Streaming Update Types
| Update Type | Description |
|-------------|-------------|
| `StreamingUpdateReason.RunCreated` | Run started |
| `StreamingUpdateReason.RunInProgress` | Run processing |
| `StreamingUpdateReason.RunCompleted` | Run finished |
| `StreamingUpdateReason.RunFailed` | Run errored |
| `MessageContentUpdate` | Text content chunk |
| `RunStepUpdate` | Step status change |
## Key Types Reference
| Type | Purpose |
|------|---------|
| `PersistentAgentsClient` | Main entry point |
| `PersistentAgent` | Agent with model, instructions, tools |
| `PersistentAgentThread` | Conversation thread |
| `PersistentThreadMessage` | Message in thread |
| `ThreadRun` | Execution of agent against thread |
| `RunStatus` | Queued, InProgress, RequiresAction, Completed, Failed |
| `ToolResources` | Combined tool resources |
| `ToolOutput` | Function call response |
## Best Practices
1. **Always dispose clients** — Use `using` statements or explicit disposal
2. **Poll with appropriate delays** — 500ms recommended between status checks
3. **Clean up resources** — Delete threads and agents when done
4. **Handle all run statuses** — Check for `RequiresAction`, `Failed`, `Cancelled`
5. **Use streaming for real-time UX** — Better user experience than polling
6. **Store IDs not objects** — Reference agents/threads by ID
7. **Use async methods** — All operations should be async
## Error Handling
```csharp
using Azure;
try
{
var agent = await client.Administration.CreateAgentAsync(...);
}
catch (RequestFailedException ex) when (ex.Status == 404)
{
Console.WriteLine("Resource not found");
}
catch (RequestFailedException ex)
{
Console.WriteLine($"Error: {ex.Status} - {ex.ErrorCode}: {ex.Message}");
}
```
## Related SDKs
| SDK | Purpose | Install |
|-----|---------|---------|
| `Azure.AI.Agents.Persistent` | Low-level agents (this SDK) | `dotnet add package Azure.AI.Agents.Persistent` |
| `Azure.AI.Projects` | High-level project client | `dotnet add package Azure.AI.Projects` |
## Reference Links
| Resource | URL |
|----------|-----|
| NuGet Package | https://www.nuget.org/packages/Azure.AI.Agents.Persistent |
| API Reference | https://learn.microsoft.com/dotnet/api/azure.ai.agents.persistent |
| GitHub Source | https://github.com/Azure/azure-sdk-for-net/tree/main/sdk/ai/Azure.AI.Agents.Persistent |
| Samples | https://github.com/Azure/azure-sdk-for-net/tree/main/sdk/ai/Azure.AI.Agents.Persistent/samples |
## When to Use
This skill is applicable to execute the workflow or actions described in the overview.