Agent skill

Researching Azure AI SDK

by microsoft-foundry in microsoft-foundry/foundry-agent-webapp

Provides research patterns for Foundry Agent Service SDK. An agent skill from microsoft-foundry/foundry-agent-webapp.

MITAuto-check passedDevOps & Cloud

Install Researching Azure AI SDK

skills CLI
$ npx skills add microsoft-foundry/foundry-agent-webapp --skill researching-azure-ai-sdk -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install microsoft-foundry/foundry-agent-webapp researching-azure-ai-sdk --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/microsoft-foundry/foundry-agent-webapp.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.github/skills/researching-azure-ai-sdk .claude/skills/researching-azure-ai-sdk && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
researching-azure-ai-sdk
GitHub stars
127
Token cost
~4.7k tokens
SKILL.md length
1,039 words
Files
1
Skills in repo
19
Repo updated
First seen
Licence
MIT

At a glance

Provides research patterns for Foundry Agent Service SDK. An agent skill from microsoft-foundry/foundry-agent-webapp.

  • Works in 7 steps: Primary SDK Repository (Start Here) → Official Quickstart Samples → Azure Architecture Center Samples → …
  • Implementing agent features
  • SKILL.md covers Subagent Delegation for Research, SDK Architecture Overview, 1. Primary SDK Repository… and 2. Official Quickstart Samples, plus 12 more sections
  • Calls dotnet; reaches ai.azure.com

What it does

Researching Azure AI SDK is an agent skill from microsoft-foundry/foundry-agent-webapp. 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.

Its SKILL.md is about 4.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in DevOps & Cloud. It works with Vercel AI SDK, Microsoft Azure, Azure AI Foundry and OpenAI. The repository describes itself as: GitHub Copilot enabled repo for building and deploying a web application with Entra ID authentication and integrated with Azure AI Foundry Agents. The licence is MIT.

When your agent uses it

  • Implementing agent features
  • Looking up SDK methods
  • Finding code samples
  • Troubleshooting Azure.AI.Projects API usage

Example prompts

  • “Use the researching-azure-ai-sdk skill to provide research patterns for Foundry Agent Service SDK. An agent skill from…”
  • “/researching-azure-ai-sdk”

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Primary SDK Repository (Start Here)
  2. Official Quickstart Samples
  3. Azure Architecture Center Samples
  4. UI Reference Samples (React Patterns)
  5. Semantic Kernel Integration
  6. OpenAI .NET SDK (Streaming Types)
  7. GitHub Code Search (For Specific Patterns)

What it can do on your machine

Read from SKILL.md and the folder at commit f6cb362. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • dotnet

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • ai.azure.com

    Also links to:

    • learn.microsoft.com
    • github.com
    • nuget.org

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Researching Azure AI SDK loads about 4.7k tokens when it runs. Until then it costs about 54 tokens; SKILL.md has 1,039 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~54
When it runs · the whole SKILL.md, loaded when a task matches
~4.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from microsoft-foundry/foundry-agent-webapp at commit f6cb362, republished under its MIT licence (© microsoft-foundry). 1,039 words, ~4,671 tokens.

Download SKILL.mdSave it as .claude/skills/researching-azure-ai-sdk/SKILL.md (or your agent's skills folder).
name
researching-azure-ai-sdk
description
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.

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
text
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.

text
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:

csharp
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:

text
# 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:

Show full SKILL.md (445 more words)Show less

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:

csharp
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)
csharp
// 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):

csharp
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:

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

text
"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):

powershell
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):

powershell
# 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.

© microsoft-foundry, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .github/skills/researching-azure-ai-sdk of microsoft-foundry/foundry-agent-webapp.

Open the folder on GitHubat commit f6cb362

Compare with similar skills

Researching Azure AI SDK next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Researching Azure AI SDK compared with similar skills
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Openai Docsaafqaq/codex-lb-enhanced1032 repos~861Automated safety check: PassApache-2.0
Deploynoskillish/bankmcp277—~744Automated safety check: PassMIT
Neurolink Guidejuspay/neurolink145—~1.4kAutomated safety check: PassMIT
Go Spec Reviewerinference-gateway/inference-gateway214—~1.2kAutomated safety check: PassApache-2.0

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Questions about Researching Azure AI SDK

What does Researching Azure AI SDK do?

Provides research patterns for Foundry Agent Service SDK. An agent skill from microsoft-foundry/foundry-agent-webapp. Researching Azure AI SDK is an agent skill from microsoft-foundry/foundry-agent-webapp. Provides research patterns for Foundry Agent Service SDK.

When should I use Researching Azure AI SDK?

Researching Azure AI SDK fits situations like: implementing agent features; looking up SDK methods; finding code samples; troubleshooting Azure.AI.Projects API usage.

How do I install Researching Azure AI SDK in Claude Code?

Run `npx skills add microsoft-foundry/foundry-agent-webapp --skill researching-azure-ai-sdk -a claude-code`. Or copy the skill folder (.github/skills/researching-azure-ai-sdk in microsoft-foundry/foundry-agent-webapp) into .claude/skills/researching-azure-ai-sdk in your project. Claude Code loads it when a task matches its description.

How do I install Researching Azure AI SDK in Codex?

Run `npx skills add microsoft-foundry/foundry-agent-webapp --skill researching-azure-ai-sdk -a codex`. Or copy the skill folder (.github/skills/researching-azure-ai-sdk in microsoft-foundry/foundry-agent-webapp) into .agents/skills/researching-azure-ai-sdk in your project. Codex loads it when a task matches its description.

Can I use Researching Azure AI SDK in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add microsoft-foundry/foundry-agent-webapp --skill researching-azure-ai-sdk -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/researching-azure-ai-sdk, .gemini/skills/researching-azure-ai-sdk, .github/skills/researching-azure-ai-sdk and .opencode/skills/researching-azure-ai-sdk in your project.

What does Researching Azure AI SDK need to run?

Going by SKILL.md and its folder, Researching Azure AI SDK needs the command-line tools its instructions call (dotnet).

Does Researching Azure AI SDK access the network?

SKILL.md names 4 domains. In commands or code: ai.azure.com; the agent is likely to contact it when it follows the instructions. As links in the text: learn.microsoft.com, github.com and nuget.org. This is read from the text; nothing was executed.

Is Researching Azure AI SDK safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Researching Azure AI SDK use?

Researching Azure AI SDK is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Researching Azure AI SDK use?

About 4.7k tokens (SKILL.md is roughly 19k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Researching Azure AI SDK?

Skills that share tags, products or a category with Researching Azure AI SDK: Azure AI Projects TS (microsoft/skills, 3.1k stars), Openai Docs (aafqaq/codex-lb-enhanced, 103 stars), Deploy (noskillish/bankmcp, 277 stars) and Neurolink Guide (juspay/neurolink, 145 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Researching Azure AI SDK?

microsoft-foundry (a GitHub organization) maintains it in microsoft-foundry/foundry-agent-webapp, which has 127 GitHub stars. The repository holds 19 skills in this directory. The repository was last updated on April 21, 2026.

Source: microsoft-foundry/foundry-agent-webapp on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.