agentleFS
MicrosoftKnown publishermicrosoft-foundry/foundry-agent-webapp/.github/skills/researching-azure-ai-sdk/SKILL.md

researching-azure-ai-sdk

Skill124 starsChanged 7 months agoMITView on GitHub

Provides research patterns for Foundry Agent Service SDK. Use when implementing agent features, looking up SDK methods, finding code samples, or troubleshooting Azure.AI.Projects API usage.

The file

We split this skill into the rules it gives an agent

8 rules. About 0 are common, 6 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈6

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    CRITICAL: Don't guess SDK usage. Follow this research workflow.

    line 8
  2. Distinctive:

    When implementing new UI features, check these sources in order:

    line 149
  3. Distinctive:

    Use GitHub search to find usage examples:

    line 172
  4. Very specific:

    Note: Check WebApp.Api.csproj for current versions.

    line 193
  5. Very specific:

    Agent Framework (Microsoft.Agents.AI.AzureAI): Not referenced. As of rc5, incompatible with Azure.AI.Projects 2.0.0 GA.

    line 200
  6. Distinctive:

    Start here: when researching agent capabilities, limits, or new features:

    line 212
  7. Distinctive:

    Search across all .NET codebases for real-world usage:

    line 356
  8. Distinctive:

    Use when SDK docs are outdated or incomplete — the DLLs are the ground truth.

    line 367

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Researching Azure AI SDK

CRITICAL: Don't guess SDK usage. Follow this research workflow.

Subagent Delegation for Research

Multi-repo research blows up context (1000+ tokens per file). Delegate to subagent for:

  • Searching across 3+ repositories
  • Reading 5+ files for patterns
  • Comprehensive API surface exploration
  • Finding all usages of a method/type

Delegation Pattern

runSubagent(
  prompt: "RESEARCH task - do NOT write code.
    
    **Question**: [specific SDK question]
    
    **Search these sources in order**:
    1. Azure.AI.Projects SDK: github.com/Azure/azure-sdk-for-net/tree/main/sdk/ai/Azure.AI.Projects
    2. Azure.AI.Agents.Persistent samples: .../Azure.AI.Agents.Persistent/samples
    3. Microsoft Foundry Samples: github.com/microsoft-foundry/foundry-samples
    
    **Find**:
    - Method signatures for [specific API]
    - Usage examples (pseudocode only)
    - Any gotchas or edge cases
    
    **Return** (max 20 lines):
    - Key method name and signature
    - Code pattern (pseudocode)
    - File path where found (for later reference)
    
    Do NOT include full file contents.",
  description: "SDK research: [topic]"
)

When to Delegate vs Inline

Delegate to SubagentKeep Inline
Multi-repo code searchLocal codebase grep
Finding all usagesKnown method lookup
API surface explorationSingle file read
Pattern comparisonQuick signature check
Sample discoveryUsing known pattern

SDK Architecture Overview

The Foundry Agent Service SDK has two API surfaces for agents:

APIEndpointID FormatSDK Access
v2 Agents API/agents/Human-readable (e.g., dadjokes)AIProjectClient.AgentAdministrationClient
OpenAI Assistants API/assistants/OpenAI format (e.g., asst_xxx)PersistentAgentsClient

This project uses v2 Agents API for human-readable agent IDs.

Azure.AI.Projects (Main Entry Point)
├── AIProjectClient
│   ├── .AgentAdministrationClient.GetAgentVersionAsync() → ProjectsAgentVersion (v2 Agents API)
│   ├── .GetPersistentAgentsClient() → PersistentAgentsClient (Assistants API)
│   └── .ProjectOpenAIClient.GetProjectResponsesClientForAgent() → ProjectResponsesClient (Responses API)
└── Companion packages:
    ├── Azure.AI.Projects.Agents (ProjectsAgentVersion, DeclarativeAgentDefinition, …)
    ├── Azure.AI.Extensions.OpenAI (ProjectConversationsClient, ProjectOpenAIClient, …)
    └── OpenAI.Responses (streaming types)

1. Primary SDK Repository (Start Here)

Azure.AI.Projects SDK: https://github.com/Azure/azure-sdk-for-net/tree/main/sdk/ai/Azure.AI.Projects

  • README: Core client patterns, authentication, basic operations
  • Samples: tests/Samples/ folder with full examples

Azure.AI.Agents.Persistent SDK: https://github.com/Azure/azure-sdk-for-net/tree/main/sdk/ai/Azure.AI.Agents.Persistent

  • 33+ samples covering streaming, file search, Bing grounding, MCP, Azure Functions
  • Key samples:
    • Sample9_PersistentAgents_Streaming.md - Basic streaming pattern
    • Sample8_PersistentAgents_FunctionsWithStreaming.md - Tool calls with streaming
    • Sample27_PersistentAgents_MCP_Streaming.md - MCP server integration

2. Official Quickstart Samples

Microsoft Foundry Samples: https://github.com/microsoft-foundry/foundry-samples

  • samples/csharp/quickstart/quickstart-chat-with-agent.cs - Responses API pattern
  • samples/csharp/quickstart/ - Multiple quickstart examples

Key pattern from official quickstart:

AIProjectClient projectClient = new(new Uri(projectEndpoint), new AzureCliCredential());
ProjectConversation conversation = projectClient.ProjectOpenAIClient.GetProjectConversationsClient().CreateProjectConversation();
ProjectResponsesClient responsesClient = projectClient.ProjectOpenAIClient.GetProjectResponsesClientForAgent(
    defaultAgent: agentName,
    defaultConversationId: conversation.Id);
ResponseResult response = responsesClient.CreateResponse("Your prompt");

3. Azure Architecture Center Samples

Baseline Chat App: https://github.com/Azure-Samples/microsoft-foundry-baseline

  • Full production architecture with Entra ID auth
  • website/chatui/Controllers/ChatController.cs - SSE streaming pattern

Basic Chat Example: https://github.com/Azure-Samples/microsoft-foundry-basic

  • Simpler example of Foundry agent chat integration

Semantic Kernel + Foundry: https://github.com/Azure-Samples/app-service-agentic-semantic-kernel-ai-foundry-agent

  • Integration pattern for Semantic Kernel with Foundry Agents

4. UI Reference Samples (React Patterns)

Primary UI Reference

Azure AI Agents React Sample: https://github.com/Azure-Samples/get-started-with-ai-agents

This is the primary UI reference for this project. Many UI patterns were borrowed from here:

  • Chat interface components
  • Message rendering with citations/annotations
  • Streaming text display
  • Responsive layout patterns

Agent Framework DevUI (Python)

Agent Framework DevUI: https://github.com/microsoft/agent-framework/tree/main/python/packages/devui

Alternative UI patterns for agent development:

  • Development-focused chat interface
  • Multi-agent visualization
  • Tool call debugging UI

UI Component Inspiration

When implementing new UI features, check these sources in order:

  1. get-started-with-ai-agents - React + TypeScript patterns for chat UI
  2. agent-framework/devui - Development UI patterns
  3. Fluent UI Copilot Components - Base component library (already used)

5. Semantic Kernel Integration

Repository: https://github.com/microsoft/semantic-kernel

Relevant paths:

  • dotnet/src/Agents/OpenAI/ - OpenAI Responses API integration
  • dotnet/samples/GettingStartedWithAgents/AzureAIAgent/
  • dotnet/samples/Concepts/Agents/ (Step##_*.cs files)

6. OpenAI .NET SDK (Streaming Types)

Repository: https://github.com/openai/openai-dotnet

  • docs/guides/streaming-responses/ - Streaming patterns
  • Source of StreamingResponseOutputTextDeltaUpdate and related types

7. GitHub Code Search (For Specific Patterns)

Use GitHub search to find usage examples:

# Find streaming patterns
"StreamingResponseOutputTextDeltaUpdate language:csharp"

# Find Responses API usage
"ProjectResponsesClient CreateResponseStreamingAsync language:csharp"

# Find conversation patterns
"ProjectConversation GetProjectResponsesClientForAgent language:csharp"

Current SDK Packages

PackagePurpose
Azure.AI.ProjectsMain entry point, AIProjectClient, v2 Agents API, Responses API
Azure.IdentityAuthentication (AzureDeveloperCliCredential, ManagedIdentityCredential)
Microsoft.Identity.WebJWT Bearer authentication for API

Note: Check WebApp.Api.csproj for current versions. This project requires Azure.AI.Projects GA with v2 Agents API support (AIProjectClient.AgentAdministrationClient).

Companion packages used:

  • Azure.AI.Projects.Agents — ProjectsAgentVersion, ProjectsAgentRecord, DeclarativeAgentDefinition / HostedAgentDefinition / WorkflowAgentDefinition, AgentAdministrationClient
  • Azure.AI.Extensions.OpenAI — ProjectOpenAIClient, ProjectConversationsClient, ProjectResponsesClient, ProjectConversation
  • OpenAI.Responses — streaming types

Agent Framework (Microsoft.Agents.AI.AzureAI): Not referenced. As of rc5, incompatible with Azure.AI.Projects 2.0.0 GA. See "Compatibility blocker" below.

Key Resources:

Official Azure AI Foundry Agent Service Documentation

Start here when researching agent capabilities, limits, or new features:

Agent Framework (Microsoft.Agents) docs:

Annotation Types in Responses

The SDK provides several annotation types for citations (from OpenAI.Responses namespace):

TypeClassUse CaseKey Properties
URI CitationUriCitationMessageAnnotationBing, Azure AI Search, SharePointUri, Title, StartIndex, EndIndex
File CitationFileCitationMessageAnnotationFile search (vector stores)FileId, Filename, Index
File PathFilePathMessageAnnotationCode interpreter outputFileId, Index
Container CitationContainerFileCitationMessageAnnotationContainer file citationsFileId, Filename, ContainerId, StartIndex, EndIndex

Note: FileCitationMessageAnnotation uses Index (not StartIndex/EndIndex) per the SDK. See ExtractAnnotations() in AgentFrameworkService.cs for mapping to AnnotationInfo.

Container File Download

The C# SDK does not yet have a typed client for container file downloads. Use the REST API directly with a bearer token scoped to https://ai.azure.com/.default:

GET {projectEndpoint}/openai/v1/containers/{containerId}/files/{fileId}/content
Authorization: Bearer {token}

For standard (non-container) files (cfile_ prefix absent), use OpenAI.Files.FileClient instead. The backend endpoint GET /api/files/{fileId}?containerId={id} abstracts this: it routes cfile_-prefixed files through the REST API and standard files through FileClient.

Streaming Response Types (from OpenAI.Responses namespace)

TypePurpose
StreamingResponseOutputTextDeltaUpdateText content delta chunks
StreamingResponseOutputItemDoneUpdateItem completion signals
StreamingResponseCompletedUpdateResponse completion with usage
ResponseItemBase type for response items

Pattern used in this project:

await foreach (var update in responsesClient.CreateResponseStreamingAsync(...))
{
    if (update is StreamingResponseOutputTextDeltaUpdate textUpdate)
        yield return new StreamChunk { Text = textUpdate.Delta };
    if (update is StreamingResponseOutputItemDoneUpdate itemDone)
        // Extract annotations from itemDone.Item
}

Microsoft Agent Framework (NOT used — see rationale)

Package: Microsoft.Agents.AI.AzureAI (prerelease, not referenced)

Status: ❌ Not installed. Blocked on compatibility with Azure.AI.Projects 2.0.0 GA.

Compatibility blocker (as of rc5)

Microsoft.Agents.AI.AzureAI 1.0.0-rc5 pins Azure.AI.Projects 2.0.0-beta.2 and references types removed in the GA release. Attempting to use rc5 with Azure.AI.Projects 2.0.0 throws TypeLoadException at runtime. Re-evaluate when rc6+ ships.

Why we use the direct SDK anyway

Even when the compat blocker is lifted, this project's streaming path needs direct access to ProjectResponsesClient and typed response items that are not surfaced by the IChatClient abstraction:

  • McpToolCallApprovalRequestItem for MCP approval flows
  • FileSearchCallResponseItem for file search quotes
  • MessageResponseItem.OutputTextAnnotations for citations
  • ResponseItem.CreateMcpApprovalResponseItem() to respond to MCP approvals

Routing through ChatClientAgent.RunStreamingAsync() would require casting RawRepresentation for each of these, which defeats the abstraction benefit.

Current pattern (direct SDK only)

// Agent metadata — no "latest" keyword in the REST spec; enumerate versions descending.
ProjectsAgentVersion? agentVersion = null;
await foreach (var v in projectClient.AgentAdministrationClient.GetAgentVersionsAsync(
    agentName: agentName,
    limit: 1,
    order: AgentListOrder.Descending,
    after: null,
    before: null,
    cancellationToken: ct))
{
    agentVersion = v;
    break;
}
var definition = agentVersion?.Definition as DeclarativeAgentDefinition;
string model = definition?.Model ?? "";
string instructions = definition?.Instructions ?? "";

// Streaming — pin the resolved version so streaming hits the same version as metadata.
ProjectResponsesClient responsesClient = projectClient.ProjectOpenAIClient
    .GetProjectResponsesClientForAgent(
        new AgentReference(agentId, agentVersion?.Version),
        conversationId);
await foreach (var update in responsesClient.CreateResponseStreamingAsync(...)) { }

Migration Notes

AIProjectClient requires a project endpoint URI (not a connection string):

var projectClient = new AIProjectClient(new Uri(projectEndpoint), new DefaultAzureCredential());

Connection-string constructors are deprecated. See: https://github.com/Azure/azure-sdk-for-net/blob/main/sdk/ai/Azure.AI.Projects/AGENTS_MIGRATION_GUIDE.md

Additional SDK Resources

Fetch SDK Source from GitHub (Authoritative)

Type definitions live in these repos—read them directly:

GitHub Code Search

Search across all .NET codebases for real-world usage:

"ProjectResponsesClient CreateResponseStreamingAsync" language:csharp
"StreamingResponseOutputTextDeltaUpdate" language:csharp

This finds how other projects use these APIs, revealing patterns and edge cases.

PowerShell Reflection (When Docs Lag Behind)

Use when SDK docs are outdated or incomplete — the DLLs are the ground truth.

Works even when dotnet build fails (loads from NuGet cache):

cd backend/WebApp.Api; dotnet restore

# Option A: Load from build output (requires successful build)
$asm = [Reflection.Assembly]::LoadFrom((Resolve-Path "bin/Debug/net10.0/Azure.AI.Projects.dll"))

# Option B: Load from NuGet cache (works even if build fails — use for pre-release migrations)
$dll = Get-ChildItem "$env:USERPROFILE\.nuget\packages\azure.ai.projects" -Recurse -Filter "Azure.AI.Projects.dll" | Select-Object -Last 1
$asm = [Reflection.Assembly]::LoadFrom($dll.FullName)

# Find types matching a pattern
$asm.GetExportedTypes() | Where-Object { $_.Name -like "*Streaming*" } | ForEach-Object { $_.FullName }

# Get method signatures with parameter details
$type = $asm.GetType("Azure.AI.Extensions.OpenAI.ProjectResponsesClient")
$type.GetMethods() | Where-Object { $_.Name -like "*Async*" } | Select-Object Name, ReturnType, @{N='Params';E={($_.GetParameters() | ForEach-Object { "$($_.ParameterType.Name) $($_.Name)" }) -join ', '}}

Agent Framework assemblies (for Microsoft.Agents.AI.AzureAI migrations):

# Load Agent Framework DLL from NuGet cache
$pkg = Get-ChildItem "$env:USERPROFILE\.nuget\packages\microsoft.agents.ai.azureai" -Recurse -Filter "Microsoft.Agents.AI.AzureAI.dll" | Select-Object -Last 1
$asm = [Reflection.Assembly]::LoadFrom($pkg.FullName)

# Dump all exported types to see what changed between versions
$asm.GetExportedTypes() | ForEach-Object { $_.FullName } | Sort-Object

# Check if types you depend on still exist
@("ChatClientAgent", "AgentVersion", "PromptAgentDefinition", "AgentReference") | ForEach-Object {
    $match = $asm.GetExportedTypes() | Where-Object { $_.Name -eq $_ }
    if ($match) { Write-Host "FOUND: $($match.FullName)" } else { Write-Host "MISSING: $_" -ForegroundColor Red }
}

# Inspect extension methods (GetAIAgentAsync, etc.)
$asm.GetExportedTypes() | Where-Object { $_.GetMethods([Reflection.BindingFlags]::Static -bor [Reflection.BindingFlags]::Public) | Where-Object { $_.IsDefined([Runtime.CompilerServices.ExtensionAttribute], $false) } } | ForEach-Object {
    $_.GetMethods() | Where-Object { $_.IsDefined([Runtime.CompilerServices.ExtensionAttribute], $false) } | ForEach-Object { Write-Host "$($_.DeclaringType.Name).$($_.Name)" }
}

When to use: SDK upgrade with breaking changes, pre-release packages where docs lag, verifying actual API surface before writing migration code.

Key insight: Load from NuGet cache ($env:USERPROFILE\.nuget\packages\) to inspect the new version's types even when the build is broken.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.