Fix sample

Fix failing tests
fix tests
2026-06-16 21:04:09 +08:00 · 2026-06-05 09:24:17 -07:00 · 2026-06-04 11:26:53 -07:00 · 2026-06-03 17:18:23 -07:00 · 2026-06-03 17:09:11 -07:00 · 2026-06-03 15:22:42 -07:00
117 changed files with 2410 additions and 4847 deletions
@@ -8,7 +8,6 @@ function getPullRequest(context) {

  return {
    author: pullRequest.user.login,
-    authorType: pullRequest.user.type,
    labels: pullRequest.labels?.map((label) => label.name).filter(Boolean) ?? [],
    number: pullRequest.number,
  };
@@ -50,10 +49,6 @@ function hasLabel(labels, labelName) {
  return labels.some((label) => label.toLowerCase() === labelName.toLowerCase());
 }

-function isDependabotAuthor({ author, authorType }) {
-  return authorType === 'Bot' && author.toLowerCase() === 'dependabot[bot]';
-}
-
 function buildLimitMessage({ author, exemptLabelName, maxOpenPrs, openPrCount }) {
  return [
    `Thank you for your contribution, @${author}.`,
@@ -88,17 +83,7 @@ async function getOpenPrCount({ github, owner, repo, author, pullRequestNumber }

 async function enforcePrLimit({ github, context, core, exemptLabelName, maxOpenPrs, labelName }) {
  const { owner, repo } = context.repo;
-  const { author, authorType, labels, number } = getPullRequest(context);
-
-  if (isDependabotAuthor({ author, authorType })) {
-    core.info(`Author ${author} is Dependabot; skipping open PR limit enforcement.`);
-    return {
-      author,
-      closed: false,
-      dependabotExempt: true,
-      openPrCount: null,
-    };
-  }
+  const { author, labels, number } = getPullRequest(context);

  if (hasLabel(labels, exemptLabelName)) {
    core.info(`PR #${number} has the ${exemptLabelName} label; skipping open PR limit enforcement.`);
@@ -16,7 +16,7 @@ const { enforcePrLimit } = require('../scripts/pr_limit_moderation.js');
 // Helpers
 // ---------------------------------------------------------------------------

-function createContext({ author = 'community-user', authorType = 'User', labels = [], number = 123 } = {}) {
+function createContext({ author = 'community-user', labels = [], number = 123 } = {}) {
  return {
    repo: {
      owner: 'microsoft',
@@ -28,7 +28,6 @@ function createContext({ author = 'community-user', authorType = 'User', labels
        labels: labels.map((name) => ({ name })),
        user: {
          login: author,
-          type: authorType,
        },
      },
    },
@@ -297,30 +296,6 @@ describe('PR limit enforcement', () => {
    assert.deepEqual(github.calls, []);
  });

-  it('does not close Dependabot PRs', async () => {
-    const github = createGithub({
-      itemNumbers: [123, ...Array.from({ length: 25 }, (_, index) => index + 1)],
-      pullRequests: createPullRequestPage({
-        author: 'dependabot[bot]',
-        numbers: [123, ...Array.from({ length: 25 }, (_, index) => index + 1)],
-      }),
-    });
-
-    const result = await enforcePrLimit({
-      github,
-      context: createContext({ author: 'dependabot[bot]', authorType: 'Bot' }),
-      core: createCore(),
-      exemptLabelName: 'pr-limit-exempt',
-      maxOpenPrs: 10,
-      labelName: 'too-many-prs',
-    });
-
-    assert.equal(result.closed, false);
-    assert.equal(result.dependabotExempt, true);
-    assert.equal(result.openPrCount, null);
-    assert.deepEqual(github.calls, []);
-  });
-
  it('counts the current PR when the author has more than one page of open PRs', async () => {
    const github = createGithub({
      itemNumbers: [123, ...Array.from({ length: 100 }, (_, index) => index + 1)],
@@ -474,45 +474,6 @@ jobs:
          path: ./python/pytest.xml
          if-no-files-found: ignore

-  # GitHub Copilot integration tests
-  python-tests-github-copilot:
-    name: Python Integration Tests - GitHub Copilot
-    runs-on: ubuntu-latest
-    environment: integration
-    timeout-minutes: 60
-    env:
-      COPILOT_GITHUB_TOKEN: ${{ secrets.COPILOT_GITHUB_TOKEN }}
-      GITHUB_COPILOT_TIMEOUT: "120"
-    defaults:
-      run:
-        working-directory: python
-    steps:
-      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
-        with:
-          ref: ${{ inputs.checkout-ref }}
-          persist-credentials: false
-      - name: Set up python and install the project
-        id: python-setup
-        uses: ./.github/actions/python-setup
-        with:
-          python-version: ${{ env.UV_PYTHON }}
-          os: ${{ runner.os }}
-      - name: Test with pytest (GitHub Copilot integration)
-        run: >
-          uv run pytest --import-mode=importlib
-          packages/github_copilot/tests
-          -m integration
-          --timeout=120 --session-timeout=900 --timeout_method thread
-          --retries 2 --retry-delay 5
-          --junitxml=pytest.xml
-      - name: Upload test results
-        if: always()
-        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
-        with:
-          name: test-results-github-copilot
-          path: ./python/pytest.xml
-          if-no-files-found: ignore
-
  # Integration test trend report (aggregates per-job JUnit XML results)
  python-integration-test-report:
    name: Integration Test Report
@@ -529,7 +490,6 @@ jobs:
        python-tests-foundry,
        python-tests-foundry-hosting,
        python-tests-cosmos,
-        python-tests-github-copilot,
      ]
    runs-on: ubuntu-latest
    defaults:
@@ -593,8 +553,7 @@ jobs:
        python-tests-functions,
        python-tests-foundry,
        python-tests-foundry-hosting,
-        python-tests-cosmos,
-        python-tests-github-copilot
+        python-tests-cosmos
      ]
    steps:
      - name: Fail workflow if tests failed
@@ -40,7 +40,6 @@ jobs:
      foundryChanged: ${{ steps.filter.outputs.foundry }}
      foundryHostingChanged: ${{ steps.filter.outputs.foundry_hosting }}
      cosmosChanged: ${{ steps.filter.outputs.cosmos }}
-      githubCopilotChanged: ${{ steps.filter.outputs.github_copilot }}
    steps:
      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
      - uses: dorny/paths-filter@d1c1ffe0248fe513906c8e24db8ea791d46f8590 # v3
@@ -86,8 +85,6 @@ jobs:
              - 'python/packages/foundry_hosting/**'
            cosmos:
              - 'python/packages/azure-cosmos/**'
-            github_copilot:
-              - 'python/packages/github_copilot/**'
      # run only if 'python' files were changed
      - name: python tests
        if: steps.filter.outputs.python == 'true'
@@ -661,58 +658,6 @@ jobs:
          path: ./python/pytest.xml
          if-no-files-found: ignore

-  # GitHub Copilot integration tests
-  python-tests-github-copilot:
-    name: Python Tests - GitHub Copilot Integration
-    needs: paths-filter
-    if: >
-      github.event_name != 'pull_request' &&
-      needs.paths-filter.outputs.pythonChanges == 'true' &&
-      (github.event_name != 'merge_group' ||
-       needs.paths-filter.outputs.githubCopilotChanged == 'true' ||
-       needs.paths-filter.outputs.coreChanged == 'true')
-    runs-on: ubuntu-latest
-    environment: integration
-    timeout-minutes: 60
-    env:
-      COPILOT_GITHUB_TOKEN: ${{ secrets.COPILOT_GITHUB_TOKEN }}
-      GITHUB_COPILOT_TIMEOUT: "120"
-    defaults:
-      run:
-        working-directory: python
-    steps:
-      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
-      - name: Set up python and install the project
-        id: python-setup
-        uses: ./.github/actions/python-setup
-        with:
-          python-version: ${{ env.UV_PYTHON }}
-          os: ${{ runner.os }}
-      - name: Test with pytest (GitHub Copilot integration)
-        run: >
-          uv run pytest --import-mode=importlib
-          packages/github_copilot/tests
-          -m integration
-          --timeout=120 --session-timeout=900 --timeout_method thread
-          --retries 2 --retry-delay 5
-          --junitxml=pytest.xml
-      - name: Surface failing tests
-        if: always()
-        uses: pmeier/pytest-results-action@20b595761ba9bf89e115e875f8bc863f913bc8ad # v0.7.2
-        with:
-          path: ./python/pytest.xml
-          summary: true
-          display-options: fEX
-          fail-on-empty: false
-          title: GitHub Copilot integration test results
-      - name: Upload test results
-        if: always()
-        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
-        with:
-          name: test-results-github-copilot
-          path: ./python/pytest.xml
-          if-no-files-found: ignore
-
  # Integration test trend report (aggregates per-job JUnit XML results)
  python-integration-test-report:
    name: Integration Test Report
@@ -729,7 +674,6 @@ jobs:
        python-tests-foundry,
        python-tests-foundry-hosting,
        python-tests-cosmos,
-        python-tests-github-copilot,
      ]
    runs-on: ubuntu-latest
    defaults:
@@ -791,7 +735,6 @@ jobs:
        python-tests-foundry,
        python-tests-foundry-hosting,
        python-tests-cosmos,
-        python-tests-github-copilot,
      ]
    steps:
      - name: Fail workflow if tests failed
@@ -109,7 +109,7 @@
    <PackageVersion Include="A2A" Version="1.0.0-preview2" />
    <PackageVersion Include="A2A.AspNetCore" Version="1.0.0-preview2" />
    <!-- MCP -->
-    <PackageVersion Include="ModelContextProtocol" Version="1.2.0" />
+    <PackageVersion Include="ModelContextProtocol" Version="1.1.0" />
    <!-- Hyperlight -->
    <PackageVersion Include="Hyperlight.HyperlightSandbox.Api" Version="0.4.0" />
    <PackageVersion Include="Hyperlight.HyperlightSandbox.Guest.Python" Version="0.4.0" />
@@ -1,14 +1,14 @@
 <Project>
  <PropertyGroup>
    <!-- Central version prefix - applies to all nuget packages. -->
-    <VersionPrefix>1.9.0</VersionPrefix>
+    <VersionPrefix>1.8.0</VersionPrefix>
    <RCNumber>1</RCNumber>
-    <DateSuffix>260603</DateSuffix>
+    <DateSuffix>260528</DateSuffix>
    <PackageVersion Condition="'$(IsReleaseCandidate)' == 'true'">$(VersionPrefix)-rc$(RCNumber)</PackageVersion>
    <PackageVersion Condition="'$(IsReleaseCandidate)' != 'true' AND '$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).$(DateSuffix).1</PackageVersion>
    <PackageVersion Condition="'$(IsReleaseCandidate)' != 'true' AND '$(VersionSuffix)' == ''">$(VersionPrefix)-preview.$(DateSuffix).1</PackageVersion>
    <PackageVersion Condition="'$(IsReleased)' == 'true'">$(VersionPrefix)</PackageVersion>
-    <GitTag>1.9.0</GitTag>
+    <GitTag>1.8.0</GitTag>

    <Configurations>Debug;Release;Publish</Configurations>
    <IsPackable>true</IsPackable>
@@ -10,11 +10,6 @@ WebApplicationBuilder builder = WebApplication.CreateBuilder(args);
 builder.Services.AddHttpClient().AddLogging();
 builder.Services.AddAGUI();

-// WARNING: When adding session persistence (e.g., WithInMemorySessionStore), or running in production,
-// make sure to also register a SessionIsolationKeyProvider to scope sessions by principal in multi-user
-// deployments, e.g.:
-// builder.Services.UseClaimsBasedSessionIsolation(new() { ClaimType = ClaimTypes.NameIdentifier });
-
 WebApplication app = builder.Build();

 string endpoint = builder.Configuration["AZURE_OPENAI_ENDPOINT"]
@@ -14,7 +14,6 @@

  <ItemGroup>
    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.Hosting.AGUI.AspNetCore\Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.csproj" />
-    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.Hosting.AspNetCore\Microsoft.Agents.AI.Hosting.AspNetCore.csproj" />
    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
  </ItemGroup>

@@ -16,11 +16,6 @@ builder.Services.ConfigureHttpJsonOptions(options =>
    options.SerializerOptions.TypeInfoResolverChain.Add(SampleJsonSerializerContext.Default));
 builder.Services.AddAGUI();

-// WARNING: When adding session persistence (e.g., WithInMemorySessionStore), or running in production,
-// make sure to also register a SessionIsolationKeyProvider to scope sessions by principal in multi-user
-// deployments, e.g.:
-// builder.Services.UseClaimsBasedSessionIsolation(new() { ClaimType = ClaimTypes.NameIdentifier });
-
 WebApplication app = builder.Build();

 string endpoint = builder.Configuration["AZURE_OPENAI_ENDPOINT"]
@@ -14,7 +14,6 @@

  <ItemGroup>
    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.Hosting.AGUI.AspNetCore\Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.csproj" />
-    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.Hosting.AspNetCore\Microsoft.Agents.AI.Hosting.AspNetCore.csproj" />
    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
  </ItemGroup>

@@ -10,11 +10,6 @@ WebApplicationBuilder builder = WebApplication.CreateBuilder(args);
 builder.Services.AddHttpClient().AddLogging();
 builder.Services.AddAGUI();

-// WARNING: When adding session persistence (e.g., WithInMemorySessionStore), or running in production,
-// make sure to also register a SessionIsolationKeyProvider to scope sessions by principal in multi-user
-// deployments, e.g.:
-// builder.Services.UseClaimsBasedSessionIsolation(new() { ClaimType = ClaimTypes.NameIdentifier });
-
 WebApplication app = builder.Build();

 string endpoint = builder.Configuration["AZURE_OPENAI_ENDPOINT"]
@@ -14,7 +14,6 @@

  <ItemGroup>
    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.Hosting.AGUI.AspNetCore\Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.csproj" />
-    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.Hosting.AspNetCore\Microsoft.Agents.AI.Hosting.AspNetCore.csproj" />
    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
  </ItemGroup>

@@ -27,11 +27,6 @@ builder.Services.ConfigureHttpJsonOptions(options =>
    options.SerializerOptions.TypeInfoResolverChain.Add(ApprovalJsonContext.Default));
 builder.Services.AddAGUI();

-// WARNING: When adding session persistence (e.g., WithInMemorySessionStore), or running in production,
-// make sure to also register a SessionIsolationKeyProvider to scope sessions by principal in multi-user
-// deployments, e.g.:
-// builder.Services.UseClaimsBasedSessionIsolation(new() { ClaimType = ClaimTypes.NameIdentifier });
-
 WebApplication app = builder.Build();

 app.UseHttpLogging();
@@ -14,7 +14,6 @@

  <ItemGroup>
    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.Hosting.AGUI.AspNetCore\Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.csproj" />
-    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.Hosting.AspNetCore\Microsoft.Agents.AI.Hosting.AspNetCore.csproj" />
    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
  </ItemGroup>

@@ -17,11 +17,6 @@ builder.Services.AddAGUI();
 // Configure to listen on port 8888
 builder.WebHost.UseUrls("http://localhost:8888");

-// WARNING: When adding session persistence (e.g., WithInMemorySessionStore), or running in production,
-// make sure to also register a SessionIsolationKeyProvider to scope sessions by principal in multi-user
-// deployments, e.g.:
-// builder.Services.UseClaimsBasedSessionIsolation(new() { ClaimType = ClaimTypes.NameIdentifier });
-
 WebApplication app = builder.Build();

 string endpoint = builder.Configuration["AZURE_OPENAI_ENDPOINT"]
@@ -14,7 +14,6 @@

  <ItemGroup>
    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.Hosting.AGUI.AspNetCore\Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.csproj" />
-    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.Hosting.AspNetCore\Microsoft.Agents.AI.Hosting.AspNetCore.csproj" />
    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
  </ItemGroup>

@@ -50,16 +50,12 @@ internal static partial class WorkflowHelper
    /// <summary>
    /// Executor that starts the concurrent processing by sending messages to the agents.
    /// </summary>
-    [SendsMessage(typeof(List<ChatMessage>))]
-    [SendsMessage(typeof(TurnToken))]
-    private sealed partial class ConcurrentStartExecutor()
-        : Executor("ConcurrentStartExecutor", declareCrossRunShareable: true), IResettableExecutor
+    private sealed partial class ConcurrentStartExecutor() : Executor("ConcurrentStartExecutor")
    {
        [MessageHandler]
-        internal ValueTask RouteMessages(IEnumerable<ChatMessage> messages, IWorkflowContext context, CancellationToken cancellationToken)
+        internal ValueTask RouteMessages(List<ChatMessage> messages, IWorkflowContext context, CancellationToken cancellationToken)
        {
-            List<ChatMessage> payload = messages as List<ChatMessage> ?? messages.ToList();
-            return context.SendMessageAsync(payload, cancellationToken: cancellationToken);
+            return context.SendMessageAsync(messages, cancellationToken: cancellationToken);
        }

        [MessageHandler]
@@ -67,16 +63,13 @@ internal static partial class WorkflowHelper
        {
            return context.SendMessageAsync(token, cancellationToken: cancellationToken);
        }
-
-        public ValueTask ResetAsync() => default;
    }

    /// <summary>
    /// Executor that aggregates the results from the concurrent agents.
    /// </summary>
-    [YieldsOutput(typeof(string))]
-    private sealed partial class ConcurrentAggregationExecutor() :
-        Executor<List<ChatMessage>>("ConcurrentAggregationExecutor"), IResettableExecutor
+    [YieldsOutput(typeof(List<ChatMessage>))]
+    private sealed partial class ConcurrentAggregationExecutor() : Executor<List<ChatMessage>>("ConcurrentAggregationExecutor")
    {
        private readonly List<ChatMessage> _messages = [];

@@ -97,11 +90,5 @@ internal static partial class WorkflowHelper
                await context.YieldOutputAsync(formattedMessages, cancellationToken);
            }
        }
-
-        public ValueTask ResetAsync()
-        {
-            this._messages.Clear();
-            return default;
-        }
    }
 }
@@ -13,7 +13,7 @@
  <ItemGroup>
    <PackageReference Include="Azure.AI.Projects" />
    <PackageReference Include="Azure.Identity" />
-    <PackageReference Include="ModelContextProtocol" />
+    <PackageReference Include="ModelContextProtocol" VersionOverride="1.2.0" />
    <PackageReference Include="DotNetEnv" />
  </ItemGroup>

@@ -15,7 +15,6 @@

  <ItemGroup>
    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.Hosting.AGUI.AspNetCore\Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.csproj" />
-    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.Hosting.AspNetCore\Microsoft.Agents.AI.Hosting.AspNetCore.csproj" />
    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
  </ItemGroup>

@@ -19,11 +19,6 @@ builder.Services.AddHttpClient().AddLogging();
 builder.Services.ConfigureHttpJsonOptions(options => options.SerializerOptions.TypeInfoResolverChain.Add(AGUIDojoServerSerializerContext.Default));
 builder.Services.AddAGUI();

-// WARNING: When adding session persistence (e.g., WithInMemorySessionStore), or running in production,
-// make sure to also register a SessionIsolationKeyProvider to scope sessions by principal in multi-user
-// deployments, e.g.:
-// builder.Services.UseClaimsBasedSessionIsolation(new() { ClaimType = ClaimTypes.NameIdentifier });
-
 WebApplication app = builder.Build();

 app.UseHttpLogging();
@@ -49,9 +49,8 @@ var agent = new AzureOpenAIClient(
                AGUIServerSerializerContext.Default.Options)
        ]);

-// WARNING: When adding session persistence (e.g., WithInMemorySessionStore), or running in production,
-// make sure to also register a SessionIsolationKeyProvider to scope sessions by principal in multi-user
-// deployments, e.g.:
+// When running in production, make sure to use an SessionIsolationKeyProvider, e.g. ClaimsIdentity-based
+// if using Claims-based Identity for Authentication/Authorization
 // builder.Services.UseClaimsBasedSessionIsolation(new() { ClaimType = ClaimTypes.NameIdentifier });

 // Register the agent with the host and configure it to use an in-memory session store
@@ -14,7 +14,6 @@

  <ItemGroup>
    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.Hosting.AGUI.AspNetCore\Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.csproj" />
-    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.Hosting.AspNetCore\Microsoft.Agents.AI.Hosting.AspNetCore.csproj" />
    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.AGUI\Microsoft.Agents.AI.AGUI.csproj" />
    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
  </ItemGroup>
@@ -12,11 +12,6 @@ WebApplicationBuilder builder = WebApplication.CreateBuilder(args);
 builder.Services.AddHttpClient().AddLogging();
 builder.Services.AddAGUI();

-// WARNING: When adding session persistence (e.g., WithInMemorySessionStore), or running in production,
-// make sure to also register a SessionIsolationKeyProvider to scope sessions by principal in multi-user
-// deployments, e.g.:
-// builder.Services.UseClaimsBasedSessionIsolation(new() { ClaimType = ClaimTypes.NameIdentifier });
-
 WebApplication app = builder.Build();

 string endpoint = builder.Configuration["AZURE_OPENAI_ENDPOINT"] ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
@@ -1,9 +1,7 @@
 // Copyright (c) Microsoft. All rights reserved.

-using System;
 using System.Diagnostics.CodeAnalysis;
 using Microsoft.Agents.AI;
-using Microsoft.Extensions.Logging;
 using Microsoft.Shared.DiagnosticIds;

 namespace Microsoft.Extensions.AI;
@@ -34,19 +32,11 @@ public static class ChatClientHarnessExtensions
    /// additional context providers, and chat history provider.
    /// When <see langword="null"/>, the agent uses built-in default settings.
    /// </param>
-    /// <param name="loggerFactory">
-    /// Optional logger factory for creating loggers used by the agent and its components.
-    /// </param>
-    /// <param name="services">
-    /// Optional service provider for resolving dependencies required by AI functions and other agent components.
-    /// </param>
    /// <returns>A new <see cref="HarnessAgent"/> instance.</returns>
    public static HarnessAgent AsHarnessAgent(
        this IChatClient chatClient,
        int maxContextWindowTokens,
        int maxOutputTokens,
-        HarnessAgentOptions? options = null,
-        ILoggerFactory? loggerFactory = null,
-        IServiceProvider? services = null) =>
-        new(chatClient, maxContextWindowTokens, maxOutputTokens, options, loggerFactory, services);
+        HarnessAgentOptions? options = null) =>
+        new(chatClient, maxContextWindowTokens, maxOutputTokens, options);
 }
@@ -10,7 +10,6 @@ using Microsoft.Agents.AI.Compaction;
 using Microsoft.Agents.AI.Tools.Shell;
 #endif
 using Microsoft.Extensions.AI;
-using Microsoft.Extensions.Logging;
 using Microsoft.Shared.DiagnosticIds;
 using Microsoft.Shared.Diagnostics;

@@ -106,12 +105,6 @@ public sealed class HarnessAgent : DelegatingAIAgent
    /// additional context providers, and chat history provider.
    /// When <see langword="null"/>, the agent uses built-in default settings.
    /// </param>
-    /// <param name="loggerFactory">
-    /// Optional logger factory for creating loggers used by the agent and its components.
-    /// </param>
-    /// <param name="services">
-    /// Optional service provider for resolving dependencies required by AI functions and other agent components.
-    /// </param>
    /// <exception cref="ArgumentNullException">
    /// <paramref name="chatClient"/> is <see langword="null"/>.
    /// </exception>
@@ -119,20 +112,18 @@ public sealed class HarnessAgent : DelegatingAIAgent
    /// <paramref name="maxContextWindowTokens"/> is not positive, or
    /// <paramref name="maxOutputTokens"/> is negative or greater than or equal to <paramref name="maxContextWindowTokens"/>.
    /// </exception>
-    public HarnessAgent(IChatClient chatClient, int maxContextWindowTokens, int maxOutputTokens, HarnessAgentOptions? options = null, ILoggerFactory? loggerFactory = null, IServiceProvider? services = null)
+    public HarnessAgent(IChatClient chatClient, int maxContextWindowTokens, int maxOutputTokens, HarnessAgentOptions? options = null)
        : base(BuildAgent(
            Throw.IfNull(chatClient),
            maxContextWindowTokens,
            maxOutputTokens,
-            options,
-            loggerFactory,
-            services))
+            options))
    {
    }

-    private static AIAgent BuildAgent(IChatClient chatClient, int maxContextWindowTokens, int maxOutputTokens, HarnessAgentOptions? options, ILoggerFactory? loggerFactory, IServiceProvider? services)
+    private static AIAgent BuildAgent(IChatClient chatClient, int maxContextWindowTokens, int maxOutputTokens, HarnessAgentOptions? options)
    {
-        ChatClientAgent innerAgent = BuildInnerAgent(chatClient, maxContextWindowTokens, maxOutputTokens, options, loggerFactory, services);
+        ChatClientAgent innerAgent = BuildInnerAgent(chatClient, maxContextWindowTokens, maxOutputTokens, options);

        AIAgentBuilder builder = innerAgent.AsBuilder();

@@ -146,10 +137,10 @@ public sealed class HarnessAgent : DelegatingAIAgent
            builder.UseOpenTelemetry(sourceName: options?.OpenTelemetrySourceName);
        }

-        return builder.Build(services);
+        return builder.Build();
    }

-    private static ChatClientAgent BuildInnerAgent(IChatClient chatClient, int maxContextWindowTokens, int maxOutputTokens, HarnessAgentOptions? options, ILoggerFactory? loggerFactory, IServiceProvider? services)
+    private static ChatClientAgent BuildInnerAgent(IChatClient chatClient, int maxContextWindowTokens, int maxOutputTokens, HarnessAgentOptions? options)
    {
        var compactionStrategy = new ContextWindowCompactionStrategy(
            maxContextWindowTokens: maxContextWindowTokens,
@@ -174,13 +165,13 @@ public sealed class HarnessAgent : DelegatingAIAgent

        ChatOptions chatOptions = BuildChatOptions(options, instructions, maxOutputTokens);

-        var compactionProvider = new CompactionProvider(compactionStrategy, loggerFactory: loggerFactory);
+        var compactionProvider = new CompactionProvider(compactionStrategy);

-        IEnumerable<AIContextProvider> contextProviders = BuildContextProviders(options, loggerFactory);
+        IEnumerable<AIContextProvider> contextProviders = BuildContextProviders(options);

        return chatClient
            .AsBuilder()
-            .UseFunctionInvocation(loggerFactory, configure: options?.MaximumIterationsPerRequest is int maxIterations
+            .UseFunctionInvocation(configure: options?.MaximumIterationsPerRequest is int maxIterations
                ? ficc => ficc.MaximumIterationsPerRequest = maxIterations
                : null)
            .UseMessageInjection()
@@ -198,9 +189,7 @@ public sealed class HarnessAgent : DelegatingAIAgent
                RequirePerServiceCallChatHistoryPersistence = true,
                WarnOnChatHistoryProviderConflict = false,
                ThrowOnChatHistoryProviderConflict = false,
-            },
-            loggerFactory,
-            services);
+            });
    }

    private static ChatOptions BuildChatOptions(HarnessAgentOptions? options, string instructions, int maxOutputTokens)
@@ -226,7 +215,7 @@ public sealed class HarnessAgent : DelegatingAIAgent
        return result;
    }

-    private static List<AIContextProvider> BuildContextProviders(HarnessAgentOptions? options, ILoggerFactory? loggerFactory)
+    private static List<AIContextProvider> BuildContextProviders(HarnessAgentOptions? options)
    {
        var providers = new List<AIContextProvider>();

@@ -266,8 +255,8 @@ public sealed class HarnessAgent : DelegatingAIAgent
        if (options?.DisableAgentSkillsProvider is not true)
        {
            AgentSkillsProvider skillsProvider = options?.AgentSkillsSource is AgentSkillsSource source
-                ? new AgentSkillsProvider(source, loggerFactory: loggerFactory)
-                : new AgentSkillsProvider(Directory.GetCurrentDirectory(), loggerFactory: loggerFactory);
+                ? new AgentSkillsProvider(source)
+                : new AgentSkillsProvider(Directory.GetCurrentDirectory());

            providers.Add(skillsProvider);
        }
@@ -103,16 +103,7 @@ public static class AGUIEndpointRouteBuilderExtensions
        ArgumentNullException.ThrowIfNull(aiAgent);

        var agentSessionStore = endpoints.ServiceProvider.GetKeyedService<AgentSessionStore>(aiAgent.Name);
-
-        // Ensure that we have an IsolationKeyScopedAgentSessionStore registered.
-        var isolationKeyProvider = endpoints.ServiceProvider.GetService<SessionIsolationKeyProvider>();
-        if (agentSessionStore?.GetService<IsolationKeyScopedAgentSessionStore>() is null)
-        {
-            agentSessionStore ??= new NoopAgentSessionStore();
-            agentSessionStore = new IsolationKeyScopedAgentSessionStore(agentSessionStore, isolationKeyProvider, new() { Strict = isolationKeyProvider != null });
-        }
-
-        var hostAgent = new AIHostAgent(aiAgent, agentSessionStore);
+        var hostAgent = new AIHostAgent(aiAgent, agentSessionStore ?? new NoopAgentSessionStore());

        return endpoints.MapPost(pattern, async ([FromBody] RunAgentInput? input, HttpContext context, CancellationToken cancellationToken) =>
        {
@@ -27,14 +27,6 @@ internal sealed class InvokeMcpToolExecutor(
    WorkflowFormulaState state) :
    DeclarativeActionExecutor<InvokeMcpTool>(model, state)
 {
-    private const string ApprovalSnapshotStateKey = nameof(_approvalSnapshot);
-
-    /// <summary>
-    /// Snapshot of evaluated parameters at approval-request time.
-    /// Used to prevent TOCTOU attacks where state mutates during the approval window.
-    /// </summary>
-    private ApprovalSnapshot? _approvalSnapshot;
-
    /// <summary>
    /// Step identifiers for the MCP tool invocation workflow.
    /// </summary>
@@ -83,10 +75,6 @@ internal sealed class InvokeMcpToolExecutor(

        if (requireApproval)
        {
-            // Snapshot the evaluated parameters to prevent TOCTOU attacks.
-            // If state mutates during the approval window, the approved values are used on resume.
-            this._approvalSnapshot = new ApprovalSnapshot(serverUrl, serverLabel, toolName, arguments, connectionName);
-
            // Create tool call content for approval request.
            // Transport headers (e.g. Authorization) are intentionally excluded from the
            // approval event: they must not cross into the externally-surfaced approval request.
@@ -149,14 +137,13 @@ internal sealed class InvokeMcpToolExecutor(
            return;
        }

-        // Approved - use the snapshot from approval-request time to prevent TOCTOU attacks.
-        // Headers are re-evaluated (they may contain auth secrets that should not be persisted).
-        string serverUrl = this._approvalSnapshot?.ServerUrl ?? this.GetServerUrl();
-        string? serverLabel = this._approvalSnapshot?.ServerLabel ?? this.GetServerLabel();
-        string toolName = this._approvalSnapshot?.ToolName ?? this.GetToolName();
-        Dictionary<string, object?>? arguments = this._approvalSnapshot?.Arguments ?? this.GetArguments();
+        // Approved - now invoke the tool
+        string serverUrl = this.GetServerUrl();
+        string? serverLabel = this.GetServerLabel();
+        string toolName = this.GetToolName();
+        Dictionary<string, object?>? arguments = this.GetArguments();
        Dictionary<string, string>? headers = this.GetHeaders();
-        string? connectionName = this._approvalSnapshot?.ConnectionName ?? this.GetConnectionName();
+        string? connectionName = this.GetConnectionName();

        McpServerToolResultContent resultContent = await mcpToolHandler.InvokeToolAsync(
            serverUrl,
@@ -175,33 +162,9 @@ internal sealed class InvokeMcpToolExecutor(
    /// </summary>
    public async ValueTask CompleteAsync(IWorkflowContext context, ActionExecutorResult message, CancellationToken cancellationToken)
    {
-        // Clear the approval snapshot after successful completion.
-        this._approvalSnapshot = null;
-        await ClearSnapshotStateAsync(context, cancellationToken).ConfigureAwait(false);
-
        await context.RaiseCompletionEventAsync(this.Model, cancellationToken).ConfigureAwait(false);
    }

-    /// <inheritdoc/>
-    /// <remarks>
-    /// Persists the approval snapshot to workflow state so it survives checkpoint/restore cycles.
-    /// </remarks>
-    protected override async ValueTask OnCheckpointingAsync(IWorkflowContext context, CancellationToken cancellationToken = default)
-    {
-        await context.QueueStateUpdateAsync(ApprovalSnapshotStateKey, this._approvalSnapshot, null, cancellationToken).ConfigureAwait(false);
-        await base.OnCheckpointingAsync(context, cancellationToken).ConfigureAwait(false);
-    }
-
-    /// <inheritdoc/>
-    /// <remarks>
-    /// Restores the approval snapshot from workflow state after a checkpoint restore.
-    /// </remarks>
-    protected override async ValueTask OnCheckpointRestoredAsync(IWorkflowContext context, CancellationToken cancellationToken = default)
-    {
-        await base.OnCheckpointRestoredAsync(context, cancellationToken).ConfigureAwait(false);
-        this._approvalSnapshot = await context.ReadStateAsync<ApprovalSnapshot>(ApprovalSnapshotStateKey, null, cancellationToken).ConfigureAwait(false);
-    }
-
    private async ValueTask ProcessResultAsync(IWorkflowContext context, McpServerToolResultContent resultContent, CancellationToken cancellationToken)
    {
        bool autoSend = this.GetAutoSendValue();
@@ -402,24 +365,4 @@ internal sealed class InvokeMcpToolExecutor(

        return result;
    }
-
-    /// <summary>
-    /// Clears the persisted approval snapshot state after a successful tool invocation.
-    /// </summary>
-    private static async ValueTask ClearSnapshotStateAsync(IWorkflowContext context, CancellationToken cancellationToken)
-    {
-        await context.QueueStateUpdateAsync<ApprovalSnapshot?>(ApprovalSnapshotStateKey, null, null, cancellationToken).ConfigureAwait(false);
-    }
-
-    /// <summary>
-    /// Stores the evaluated parameters at approval-request time so that
-    /// <see cref="CaptureResponseAsync"/> uses the values the user reviewed,
-    /// even if <see cref="WorkflowFormulaState"/> mutates during the approval window.
-    /// </summary>
-    internal sealed record ApprovalSnapshot(
-        string ServerUrl,
-        string? ServerLabel,
-        string ToolName,
-        Dictionary<string, object?>? Arguments,
-        string? ConnectionName);
 }
@@ -49,13 +49,14 @@ public sealed class AgentFileSkill : AgentSkill
    /// <inheritdoc/>
    /// <remarks>
    /// Returns the raw SKILL.md content. When the skill has scripts, a
-    /// <c>&lt;script_schemas&gt;</c> block is appended describing the argument format.
+    /// <c>&lt;scripts&gt;&lt;script name="..."&gt;&lt;parameters_schema&gt;...&lt;/parameters_schema&gt;&lt;/script&gt;&lt;/scripts&gt;</c>
+    /// block is appended with a per-script entry describing the expected argument format.
    /// The result is cached after the first access.
    /// </remarks>
    public override ValueTask<string> GetContentAsync(CancellationToken cancellationToken = default)
    {
        var content = this._content ??= this._scripts is { Count: > 0 }
-            ? this._originalContent + AgentInlineSkillContentBuilder.BuildScriptSchemasBlock(this._scripts)
+            ? this._originalContent + AgentInlineSkillContentBuilder.BuildScriptsBlock(this._scripts)
            : this._originalContent;
        return new(content);
    }
@@ -114,6 +114,7 @@ public abstract class AgentClassSkill<
            this.Frontmatter.Name,
            this.Frontmatter.Description,
            this.Instructions,
+            this.Resources,
            this.Scripts));
    }

@@ -146,17 +147,11 @@ public abstract class AgentClassSkill<
    /// Gets the resources associated with this skill, or <see langword="null"/> if none.
    /// </summary>
    /// <remarks>
-    /// <para>
    /// The default implementation returns resources discovered via reflection by scanning
    /// <typeparamref name="TSelf"/> for members annotated with <see cref="AgentSkillResourceAttribute"/>.
    /// This discovery is compatible with Native AOT because <typeparamref name="TSelf"/> is annotated with
    /// <see cref="DynamicallyAccessedMembersAttribute"/>. The result is cached after the first access.
    /// Override this property in derived classes to provide skill-specific resources.
-    /// </para>
-    /// <para>
-    /// Resources are not automatically included in the skill body.
-    /// To enable discovery, reference resources by name in the skill's instructions or in other resources.
-    /// </para>
    /// </remarks>
    public virtual IReadOnlyList<AgentSkillResource>? Resources => this._resources.Value;

@@ -164,17 +159,11 @@ public abstract class AgentClassSkill<
    /// Gets the scripts associated with this skill, or <see langword="null"/> if none.
    /// </summary>
    /// <remarks>
-    /// <para>
    /// The default implementation returns scripts discovered via reflection by scanning
    /// <typeparamref name="TSelf"/> for methods annotated with <see cref="AgentSkillScriptAttribute"/>.
    /// This discovery is compatible with Native AOT because <typeparamref name="TSelf"/> is annotated with
    /// <see cref="DynamicallyAccessedMembersAttribute"/>. The result is cached after the first access.
    /// Override this property in derived classes to provide skill-specific scripts.
-    /// </para>
-    /// <para>
-    /// Only script parameter schemas are included in the skill body (as a <c>&lt;script_schemas&gt;</c> block).
-    /// To enable discovery, reference scripts by name in the skill's instructions or in a resource.
-    /// </para>
    /// </remarks>
    public virtual IReadOnlyList<AgentSkillScript>? Scripts => this._scripts.Value;

@@ -195,10 +184,6 @@ public abstract class AgentClassSkill<
    /// <summary>
    /// Creates a skill resource backed by a static value.
    /// </summary>
-    /// <remarks>
-    /// Resources are not automatically included in the skill body.
-    /// To enable discovery, reference the resource by name in the skill's instructions or in another resource.
-    /// </remarks>
    /// <param name="name">The resource name.</param>
    /// <param name="value">The static resource value.</param>
    /// <param name="description">An optional description of the resource.</param>
@@ -209,10 +194,6 @@ public abstract class AgentClassSkill<
    /// <summary>
    /// Creates a skill resource backed by a delegate that produces a dynamic value.
    /// </summary>
-    /// <remarks>
-    /// Resources are not automatically included in the skill body.
-    /// To enable discovery, reference the resource by name in the skill's instructions or in another resource.
-    /// </remarks>
    /// <param name="name">The resource name.</param>
    /// <param name="method">A method that produces the resource value when requested.</param>
    /// <param name="description">An optional description of the resource.</param>
@@ -227,10 +208,6 @@ public abstract class AgentClassSkill<
    /// <summary>
    /// Creates a skill script backed by a delegate.
    /// </summary>
-    /// <remarks>
-    /// Only the script's parameter schema is included in the skill body (as a <c>&lt;script_schemas&gt;</c> block).
-    /// To enable discovery, reference the script by name in the skill's instructions or in a resource.
-    /// </remarks>
    /// <param name="name">The script name.</param>
    /// <param name="method">A method to execute when the script is invoked.</param>
    /// <param name="description">An optional description of the script.</param>
@@ -95,7 +95,7 @@ public sealed class AgentInlineSkill : AgentSkill
    /// <inheritdoc/>
    public override ValueTask<string> GetContentAsync(CancellationToken cancellationToken = default)
    {
-        return new(this._cachedContent ??= AgentInlineSkillContentBuilder.Build(this.Frontmatter.Name, this.Frontmatter.Description, this._instructions, this._scripts));
+        return new(this._cachedContent ??= AgentInlineSkillContentBuilder.Build(this.Frontmatter.Name, this.Frontmatter.Description, this._instructions, this._resources, this._scripts));
    }

    /// <inheritdoc/>
@@ -115,10 +115,6 @@ public sealed class AgentInlineSkill : AgentSkill
    /// <summary>
    /// Registers a static resource with this skill.
    /// </summary>
-    /// <remarks>
-    /// Resources are not automatically included in the skill body.
-    /// To enable discovery, reference the resource by name in the skill's instructions or in another resource.
-    /// </remarks>
    /// <param name="name">The resource name.</param>
    /// <param name="value">The static resource value.</param>
    /// <param name="description">An optional description of the resource.</param>
@@ -133,10 +129,6 @@ public sealed class AgentInlineSkill : AgentSkill
    /// Registers a dynamic resource with this skill, backed by a C# delegate.
    /// The delegate's parameters and return type are automatically marshaled via <c>AIFunctionFactory</c>.
    /// </summary>
-    /// <remarks>
-    /// Resources are not automatically included in the skill body.
-    /// To enable discovery, reference the resource by name in the skill's instructions or in another resource.
-    /// </remarks>
    /// <param name="name">The resource name.</param>
    /// <param name="method">A method that produces the resource value when requested.</param>
    /// <param name="description">An optional description of the resource.</param>
@@ -155,10 +147,6 @@ public sealed class AgentInlineSkill : AgentSkill
    /// Registers a script with this skill, backed by a C# delegate.
    /// The delegate's parameters and return type are automatically marshaled via <c>AIFunctionFactory</c>.
    /// </summary>
-    /// <remarks>
-    /// Only the script's parameter schema is included in the skill body (as a <c>&lt;script_schemas&gt;</c> block).
-    /// To enable discovery, reference the script by name in the skill's instructions or in a resource.
-    /// </remarks>
    /// <param name="name">The script name.</param>
    /// <param name="method">A method to execute when the script is invoked.</param>
    /// <param name="description">An optional description of the script.</param>
@@ -12,17 +12,19 @@ namespace Microsoft.Agents.AI;
 internal static class AgentInlineSkillContentBuilder
 {
    /// <summary>
-    /// Builds the complete skill content containing name, description, instructions, and script parameter schemas.
+    /// Builds the complete skill content containing name, description, instructions, resources, and scripts.
    /// </summary>
    /// <param name="name">The skill name.</param>
    /// <param name="description">The skill description.</param>
    /// <param name="instructions">The raw instructions text.</param>
+    /// <param name="resources">Optional resources associated with the skill.</param>
    /// <param name="scripts">Optional scripts associated with the skill.</param>
    /// <returns>An XML-structured content string.</returns>
    public static string Build(
        string name,
        string description,
        string instructions,
+        IReadOnlyList<AgentSkillResource>? resources,
        IReadOnlyList<AgentSkillScript>? scripts)
    {
        _ = Throw.IfNullOrWhitespace(name);
@@ -37,24 +39,41 @@ internal static class AgentInlineSkillContentBuilder
        .Append(EscapeXmlString(instructions))
        .Append("\n</instructions>");

+        if (resources is { Count: > 0 })
+        {
+            sb.Append("\n\n<resources>\n");
+            foreach (var resource in resources)
+            {
+                if (resource.Description is not null)
+                {
+                    sb.Append($"  <resource name=\"{EscapeXmlString(resource.Name)}\" description=\"{EscapeXmlString(resource.Description)}\"/>\n");
+                }
+                else
+                {
+                    sb.Append($"  <resource name=\"{EscapeXmlString(resource.Name)}\"/>\n");
+                }
+            }
+
+            sb.Append("</resources>");
+        }
+
        if (scripts is { Count: > 0 })
        {
            sb.Append('\n');
-            sb.Append(BuildScriptSchemasBlock(scripts));
+            sb.Append(BuildScriptsBlock(scripts));
        }

        return sb.ToString();
    }

    /// <summary>
-    /// Builds a <c>&lt;script_schemas&gt;...&lt;/script_schemas&gt;</c> XML block for the given scripts.
-    /// Each script is emitted as a <c>&lt;schema script="..."&gt;</c> element containing only
-    /// the parameter schema. This block serves as a reference for the model to know how to
-    /// format arguments when calling scripts, not as a discovery mechanism.
+    /// Builds a <c>&lt;scripts&gt;...&lt;/scripts&gt;</c> XML block for the given scripts.
+    /// Each script is emitted as a <c>&lt;script name="..."&gt;</c> element with optional
+    /// <c>description</c> attribute and <c>&lt;parameters_schema&gt;</c> child element.
    /// </summary>
    /// <param name="scripts">The scripts to include in the block.</param>
-    /// <returns>An XML string starting with <c>\n&lt;script_schemas&gt;</c>, or an empty string if the list is empty.</returns>
-    public static string BuildScriptSchemasBlock(IReadOnlyList<AgentSkillScript> scripts)
+    /// <returns>An XML string starting with <c>\n&lt;scripts&gt;</c>, or an empty string if the list is empty.</returns>
+    public static string BuildScriptsBlock(IReadOnlyList<AgentSkillScript> scripts)
    {
        _ = Throw.IfNull(scripts);

@@ -64,23 +83,32 @@ internal static class AgentInlineSkillContentBuilder
        }

        var sb = new StringBuilder();
-        sb.Append("\n<script_schemas>\n");
+        sb.Append("\n<scripts>\n");

        foreach (var script in scripts)
        {
            var parametersSchema = script.ParametersSchema;

-            if (parametersSchema is null)
+            if (script.Description is null && parametersSchema is null)
            {
-                sb.Append($"  <schema script=\"{EscapeXmlString(script.Name)}\"/>\n");
+                sb.Append($"  <script name=\"{EscapeXmlString(script.Name)}\"/>\n");
            }
            else
            {
-                sb.Append($"  <schema script=\"{EscapeXmlString(script.Name)}\">{EscapeXmlString(parametersSchema.Value.GetRawText(), preserveQuotes: true)}</schema>\n");
+                sb.Append(script.Description is not null
+                    ? $"  <script name=\"{EscapeXmlString(script.Name)}\" description=\"{EscapeXmlString(script.Description)}\">\n"
+                    : $"  <script name=\"{EscapeXmlString(script.Name)}\">\n");
+
+                if (parametersSchema is not null)
+                {
+                    sb.Append($"    <parameters_schema>{EscapeXmlString(parametersSchema.Value.GetRawText(), preserveQuotes: true)}</parameters_schema>\n");
+                }
+
+                sb.Append("  </script>\n");
            }
        }

-        sb.Append("</script_schemas>");
+        sb.Append("</scripts>");

        return sb.ToString();
    }
@@ -9,7 +9,6 @@ using System.Threading.Tasks;
 using Microsoft.Agents.AI.Tools.Shell;
 #endif
 using Microsoft.Extensions.AI;
-using Microsoft.Extensions.Logging;
 using Moq;

 namespace Microsoft.Agents.AI.UnitTests;
@@ -1461,131 +1460,4 @@ public class HarnessAgentTests

    #endregion
 #endif
-
-    #region LoggerFactory and ServiceProvider
-
-    /// <summary>
-    /// Verify that the constructor succeeds when loggerFactory is provided.
-    /// </summary>
-    [Fact]
-    public void Constructor_SucceedsWithLoggerFactory()
-    {
-        // Arrange
-        var chatClient = new Mock<IChatClient>().Object;
-        var loggerFactory = new Mock<ILoggerFactory>().Object;
-
-        // Act
-        var agent = new HarnessAgent(chatClient, TestMaxContextWindowTokens, TestMaxOutputTokens, CreateAllDisabledOptions(), loggerFactory);
-
-        // Assert
-        Assert.NotNull(agent);
-    }
-
-    /// <summary>
-    /// Verify that the constructor succeeds when serviceProvider is provided.
-    /// </summary>
-    [Fact]
-    public void Constructor_SucceedsWithServiceProvider()
-    {
-        // Arrange
-        var chatClient = new Mock<IChatClient>().Object;
-        var services = new Mock<IServiceProvider>().Object;
-
-        // Act
-        var agent = new HarnessAgent(chatClient, TestMaxContextWindowTokens, TestMaxOutputTokens, CreateAllDisabledOptions(), services: services);
-
-        // Assert
-        Assert.NotNull(agent);
-    }
-
-    /// <summary>
-    /// Verify that the constructor succeeds when both loggerFactory and serviceProvider are provided.
-    /// </summary>
-    [Fact]
-    public void Constructor_SucceedsWithLoggerFactoryAndServiceProvider()
-    {
-        // Arrange
-        var chatClient = new Mock<IChatClient>().Object;
-        var loggerFactory = new Mock<ILoggerFactory>().Object;
-        var services = new Mock<IServiceProvider>().Object;
-
-        // Act
-        var agent = new HarnessAgent(chatClient, TestMaxContextWindowTokens, TestMaxOutputTokens, CreateAllDisabledOptions(), loggerFactory, services);
-
-        // Assert
-        Assert.NotNull(agent);
-    }
-
-    /// <summary>
-    /// Verify that AsHarnessAgent extension method accepts loggerFactory and serviceProvider.
-    /// </summary>
-    [Fact]
-    public void AsHarnessAgent_SucceedsWithLoggerFactoryAndServiceProvider()
-    {
-        // Arrange
-        var chatClient = new Mock<IChatClient>().Object;
-        var loggerFactory = new Mock<ILoggerFactory>().Object;
-        var services = new Mock<IServiceProvider>().Object;
-
-        // Act
-        var agent = chatClient.AsHarnessAgent(TestMaxContextWindowTokens, TestMaxOutputTokens, CreateAllDisabledOptions(), loggerFactory, services);
-
-        // Assert
-        Assert.NotNull(agent);
-    }
-
-    /// <summary>
-    /// Verify that ILoggerFactory is threaded to downstream components by confirming CreateLogger is called.
-    /// </summary>
-    [Fact]
-    public void Constructor_LoggerFactoryIsUsedByDownstreamComponents()
-    {
-        // Arrange
-        var chatClient = new Mock<IChatClient>().Object;
-        var mockLoggerFactory = new Mock<ILoggerFactory>();
-        mockLoggerFactory
-            .Setup(lf => lf.CreateLogger(It.IsAny<string>()))
-            .Returns(new Mock<ILogger>().Object);
-
-        // Act — use options that leave CompactionProvider and AgentSkillsProvider enabled
-        var options = new HarnessAgentOptions
-        {
-            DisableToolApproval = true,
-            DisableOpenTelemetry = true,
-            DisableFileMemory = true,
-            DisableFileAccess = true,
-            DisableWebSearch = true,
-            DisableTodoProvider = true,
-            DisableAgentModeProvider = true,
-        };
-        var agent = new HarnessAgent(chatClient, TestMaxContextWindowTokens, TestMaxOutputTokens, options, mockLoggerFactory.Object);
-
-        // Assert — CreateLogger should have been called by one or more downstream components
-        Assert.NotNull(agent);
-        mockLoggerFactory.Verify(lf => lf.CreateLogger(It.IsAny<string>()), Times.AtLeastOnce());
-    }
-
-    /// <summary>
-    /// Verify that IServiceProvider is propagated through the agent pipeline by confirming
-    /// it is queried during agent construction.
-    /// </summary>
-    [Fact]
-    public void Constructor_ServiceProviderIsQueriedDuringBuild()
-    {
-        // Arrange
-        var chatClient = new Mock<IChatClient>().Object;
-        var mockServices = new Mock<IServiceProvider>();
-        mockServices
-            .Setup(sp => sp.GetService(It.IsAny<Type>()))
-            .Returns(null!);
-
-        // Act
-        var agent = new HarnessAgent(chatClient, TestMaxContextWindowTokens, TestMaxOutputTokens, CreateAllDisabledOptions(), services: mockServices.Object);
-
-        // Assert — the service provider should have been queried during pipeline construction
-        Assert.NotNull(agent);
-        mockServices.Verify(sp => sp.GetService(It.IsAny<Type>()), Times.AtLeastOnce());
-    }
-
-    #endregion
 }
@@ -51,8 +51,9 @@ public sealed class AgentClassSkillTests
        // Act & Assert — Content is cached
        Assert.Same(await skill.GetContentAsync(), await skill.GetContentAsync());

-        // Act & Assert — Content includes parameter schema from typed script (with preserved quotes)
-        Assert.Contains("\"value\"", await skill.GetContentAsync());
+        // Act & Assert — Content includes parameter schema from typed script
+        Assert.Contains("parameters_schema", await skill.GetContentAsync());
+        Assert.Contains("value", await skill.GetContentAsync());
    }

    [Fact]
@@ -382,9 +383,10 @@ public sealed class AgentClassSkillTests
        // Arrange
        var skill = new AttributedFullSkill();

-        // Act & Assert — Content no longer includes resources in body; scripts are in script_schemas
-        Assert.DoesNotContain("<resources>", await skill.GetContentAsync());
-        Assert.Contains("<script_schemas>", await skill.GetContentAsync());
+        // Act & Assert — Content includes reflected resources and scripts
+        Assert.Contains("<resources>", await skill.GetContentAsync());
+        Assert.Contains("conversion-table", await skill.GetContentAsync());
+        Assert.Contains("<scripts>", await skill.GetContentAsync());
        Assert.Contains("convert", await skill.GetContentAsync());

        // Act & Assert — discovered members are cached
@@ -502,7 +504,7 @@ public sealed class AgentClassSkillTests
    }

    [Fact]
-    public async Task Content_DoesNotRenderResources_InBodyAsync()
+    public async Task Content_IncludesDescription_ForReflectedResourcesAsync()
    {
        // Arrange
        var skill = new AttributedResourcePropertiesSkill();
@@ -510,8 +512,8 @@ public sealed class AgentClassSkillTests
        // Act
        var content = await skill.GetContentAsync();

-        // Assert — resources are no longer rendered in body content
-        Assert.DoesNotContain("<resources>", content);
+        // Assert — descriptions from [Description] attribute appear in synthesized content
+        Assert.Contains("Some important data.", content);
    }

    [Fact]
@@ -122,10 +122,11 @@ public sealed class AgentFileSkillScriptTests

        // Assert — content starts with original and appends per-script entries
        Assert.StartsWith("Original content", content);
-        Assert.Contains("<script_schemas>", content);
-        Assert.Contains("<schema script=\"build\">", content);
-        Assert.Contains("<schema script=\"deploy\">", content);
-        Assert.Contains("</script_schemas>", content);
+        Assert.Contains("<scripts>", content);
+        Assert.Contains("<script name=\"build\">", content);
+        Assert.Contains("<script name=\"deploy\">", content);
+        Assert.Contains("<parameters_schema>", content);
+        Assert.Contains("</scripts>", content);
    }

    [Fact]
@@ -149,7 +149,7 @@ public sealed class AgentInlineSkillTests
    }

    [Fact]
-    public async Task Content_DoesNotIncludeResourcesInBodyAsync()
+    public async Task Content_IncludesResourcesAddedBeforeFirstAccessAsync()
    {
        // Arrange
        var skill = new AgentInlineSkill("my-skill", "A valid skill.", "Instructions.");
@@ -158,12 +158,13 @@ public sealed class AgentInlineSkillTests
        // Act
        var content = await skill.GetContentAsync();

-        // Assert — resources are no longer rendered in the body; they're accessed via GetResourceAsync
-        Assert.DoesNotContain("<resources>", content);
+        // Assert
+        Assert.Contains("<resources>", content);
+        Assert.Contains("config", content);
    }

    [Fact]
-    public async Task Content_DoesNotIncludeDelegateResourcesInBodyAsync()
+    public async Task Content_IncludesDelegateResourcesAddedBeforeFirstAccessAsync()
    {
        // Arrange
        var skill = new AgentInlineSkill("my-skill", "A valid skill.", "Instructions.");
@@ -172,8 +173,9 @@ public sealed class AgentInlineSkillTests
        // Act
        var content = await skill.GetContentAsync();

-        // Assert — resources are no longer rendered in the body
-        Assert.DoesNotContain("<resources>", content);
+        // Assert
+        Assert.Contains("<resources>", content);
+        Assert.Contains("dynamic", content);
    }

    [Fact]
@@ -187,7 +189,7 @@ public sealed class AgentInlineSkillTests
        var content = await skill.GetContentAsync();

        // Assert
-        Assert.Contains("<script_schemas>", content);
+        Assert.Contains("<scripts>", content);
        Assert.Contains("run", content);
    }

@@ -207,7 +209,7 @@ public sealed class AgentInlineSkillTests
    }

    [Fact]
-    public async Task Content_IncludesScriptSchemasAddedBeforeFirstAccessAsync()
+    public async Task Content_IncludesResourcesAndScriptsAddedBeforeFirstAccessAsync()
    {
        // Arrange
        var skill = new AgentInlineSkill("my-skill", "A valid skill.", "Instructions.");
@@ -218,8 +220,9 @@ public sealed class AgentInlineSkillTests
        var content = await skill.GetContentAsync();

        // Assert
-        Assert.DoesNotContain("<resources>", content);
-        Assert.Contains("<script_schemas>", content);
+        Assert.Contains("<resources>", content);
+        Assert.Contains("r1", content);
+        Assert.Contains("<scripts>", content);
        Assert.Contains("s1", content);
    }

@@ -233,9 +236,8 @@ public sealed class AgentInlineSkillTests
        // Act
        var content = await skill.GetContentAsync();

-        // Assert — JSON schema should be present inside <schema> element (no extra wrapper) with preserved quotes
-        Assert.Contains("<schema script=\"search\">", content);
-        Assert.Contains("\"query\"", content);
+        // Assert — JSON schema should be present and XML content chars escaped
+        Assert.Contains("parameters_schema", content);
        Assert.DoesNotContain("<![CDATA[", content);
    }

@@ -427,7 +429,7 @@ public sealed class AgentInlineSkillTests

        // Assert
        Assert.DoesNotContain("<resources>", content);
-        Assert.DoesNotContain("<script_schemas>", content);
+        Assert.DoesNotContain("<scripts>", content);
    }

    [Fact]
@@ -461,7 +463,7 @@ public sealed class AgentInlineSkillTests
    }

    [Fact]
-    public async Task Content_ScriptWithDescription_DoesNotEmitDescriptionAttributeAsync()
+    public async Task Content_ScriptWithDescription_IncludesDescriptionAttributeAsync()
    {
        // Arrange
        var skill = new AgentInlineSkill("my-skill", "A valid skill.", "Instructions.");
@@ -470,10 +472,8 @@ public sealed class AgentInlineSkillTests
        // Act
        var content = await skill.GetContentAsync();

-        // Assert — description is no longer emitted in the script_schemas block;
-        // the block only contains parameter schemas for calling scripts.
-        Assert.Contains("<schema script=\"my-script\"", content);
-        Assert.DoesNotContain("description=\"Runs something.\"", content);
+        // Assert
+        Assert.Contains("description=\"Runs something.\"", content);
    }

    [Fact]
@@ -492,7 +492,7 @@ public sealed class AgentInlineSkillTests
    }

    [Fact]
-    public async Task Content_ResourceWithDescription_NotRenderedInBodyAsync()
+    public async Task Content_ResourceWithDescription_IncludesDescriptionAttributeAsync()
    {
        // Arrange
        var skill = new AgentInlineSkill("my-skill", "A valid skill.", "Instructions.");
@@ -502,10 +502,9 @@ public sealed class AgentInlineSkillTests
        // Act
        var content = await skill.GetContentAsync();

-        // Assert — resources are no longer rendered in the body
-        Assert.DoesNotContain("<resources>", content);
-        Assert.DoesNotContain("with-desc", content);
-        Assert.DoesNotContain("no-desc", content);
+        // Assert
+        Assert.Contains("description=\"A described resource.\"", content);
+        Assert.DoesNotContain("no-desc\" description", content);
    }

    [Fact]
@@ -2,7 +2,6 @@

 using System.Collections.Generic;
 using System.Linq;
-using System.Reflection;
 using System.Threading;
 using System.Threading.Tasks;
 using Microsoft.Agents.AI.Workflows.Declarative.Events;
@@ -12,9 +11,7 @@ using Microsoft.Agents.AI.Workflows.Declarative.ObjectModel;
 using Microsoft.Agents.AI.Workflows.Declarative.PowerFx;
 using Microsoft.Agents.ObjectModel;
 using Microsoft.Extensions.AI;
-using Microsoft.PowerFx.Types;
 using Moq;
-using ApprovalSnapshot = Microsoft.Agents.AI.Workflows.Declarative.ObjectModel.InvokeMcpToolExecutor.ApprovalSnapshot;

 namespace Microsoft.Agents.AI.Workflows.Declarative.UnitTests.ObjectModel;

@@ -845,313 +842,6 @@ public sealed class InvokeMcpToolExecutorTest(ITestOutputHelper output) : Workfl

    #endregion

-    #region Approval Snapshot Security Tests
-
-    /// <summary>
-    /// Verifies that mutating the tool name variable after approval does not change
-    /// which tool is actually invoked. The originally-approved tool name must be used.
-    /// </summary>
-    [Fact]
-    public async Task InvokeMcpToolCaptureResponseUsesApprovedToolNameNotMutatedAsync()
-    {
-        // Arrange
-        const string ApprovedToolName = "safe_readonly_query";
-        const string MutatedToolName = "dangerous_admin_tool";
-
-        this.State.Set("TargetTool", FormulaValue.New(ApprovedToolName));
-        this.State.InitializeSystem();
-        this.State.Bind();
-
-        InvokeMcpTool model = this.CreateModelWithVariableToolName(
-            displayName: nameof(InvokeMcpToolCaptureResponseUsesApprovedToolNameNotMutatedAsync),
-            serverUrl: TestServerUrl,
-            variableName: "TargetTool");
-
-        string? capturedToolName = null;
-        Mock<IMcpToolHandler> mockProvider = new();
-        mockProvider.Setup(provider => provider.InvokeToolAsync(
-                It.IsAny<string>(),
-                It.IsAny<string?>(),
-                It.IsAny<string>(),
-                It.IsAny<IDictionary<string, object?>?>(),
-                It.IsAny<IDictionary<string, string>?>(),
-                It.IsAny<string?>(),
-                It.IsAny<CancellationToken>()))
-            .Callback<string, string?, string, IDictionary<string, object?>?, IDictionary<string, string>?, string?, CancellationToken>(
-                (_, _, toolName, _, _, _, _) => capturedToolName = toolName)
-            .ReturnsAsync(new McpServerToolResultContent("capture-call-id")
-            {
-                Outputs = [new TextContent("result")]
-            });
-        MockAgentProvider mockAgentProvider = new();
-        InvokeMcpToolExecutor action = new(model, mockProvider.Object, mockAgentProvider.Object, this.State);
-
-        // Act - trigger ExecuteAsync to store the approval snapshot
-        Mock<IWorkflowContext> mockContext = CreateMockWorkflowContext();
-        await action.HandleAsync(new ActionExecutorResult(action.Id), mockContext.Object, CancellationToken.None);
-
-        // Simulate parallel branch mutating state during the approval window
-        this.State.Set("TargetTool", FormulaValue.New(MutatedToolName));
-        this.State.Bind();
-
-        // User clicks approve (they saw "safe_readonly_query" in the approval UI)
-        McpServerToolCallContent toolCall = new(action.Id, ApprovedToolName, TestServerUrl);
-        ToolApprovalRequestContent approvalRequest = new(action.Id, toolCall);
-        ToolApprovalResponseContent approvalResponse = approvalRequest.CreateResponse(approved: true);
-        ExternalInputResponse response = new(new ChatMessage(ChatRole.User, [approvalResponse]));
-
-        // Resume after approval
-        await action.CaptureResponseAsync(mockContext.Object, response, CancellationToken.None);
-
-        // Assert - the originally-approved tool name must be used, not the mutated one
-        Assert.NotNull(capturedToolName);
-        Assert.Equal(ApprovedToolName, capturedToolName);
-    }
-
-    /// <summary>
-    /// Verifies that mutating an argument variable after approval does not change
-    /// the arguments actually passed to the MCP tool. The originally-approved arguments must be used.
-    /// </summary>
-    [Fact]
-    public async Task InvokeMcpToolCaptureResponseUsesApprovedArgumentsNotMutatedAsync()
-    {
-        // Arrange
-        const string ApprovedQuery = "SELECT * FROM users LIMIT 10";
-        const string MutatedQuery = "DROP TABLE users CASCADE; --";
-
-        this.State.Set("SqlQuery", FormulaValue.New(ApprovedQuery));
-        this.State.InitializeSystem();
-        this.State.Bind();
-
-        InvokeMcpTool model = this.CreateModelWithVariableArgument(
-            displayName: nameof(InvokeMcpToolCaptureResponseUsesApprovedArgumentsNotMutatedAsync),
-            serverUrl: TestServerUrl,
-            toolName: TestToolName,
-            argumentKey: "query",
-            variableName: "SqlQuery");
-
-        IDictionary<string, object?>? capturedArguments = null;
-        Mock<IMcpToolHandler> mockProvider = new();
-        mockProvider.Setup(provider => provider.InvokeToolAsync(
-                It.IsAny<string>(),
-                It.IsAny<string?>(),
-                It.IsAny<string>(),
-                It.IsAny<IDictionary<string, object?>?>(),
-                It.IsAny<IDictionary<string, string>?>(),
-                It.IsAny<string?>(),
-                It.IsAny<CancellationToken>()))
-            .Callback<string, string?, string, IDictionary<string, object?>?, IDictionary<string, string>?, string?, CancellationToken>(
-                (_, _, _, arguments, _, _, _) => capturedArguments = arguments)
-            .ReturnsAsync(new McpServerToolResultContent("capture-call-id")
-            {
-                Outputs = [new TextContent("result")]
-            });
-        MockAgentProvider mockAgentProvider = new();
-        InvokeMcpToolExecutor action = new(model, mockProvider.Object, mockAgentProvider.Object, this.State);
-
-        // Act - trigger ExecuteAsync to store the approval snapshot
-        Mock<IWorkflowContext> mockContext = CreateMockWorkflowContext();
-        await action.HandleAsync(new ActionExecutorResult(action.Id), mockContext.Object, CancellationToken.None);
-
-        // Simulate parallel branch mutating state during the approval window
-        this.State.Set("SqlQuery", FormulaValue.New(MutatedQuery));
-        this.State.Bind();
-
-        // User clicks approve
-        McpServerToolCallContent toolCall = new(action.Id, TestToolName, TestServerUrl);
-        ToolApprovalRequestContent approvalRequest = new(action.Id, toolCall);
-        ToolApprovalResponseContent approvalResponse = approvalRequest.CreateResponse(approved: true);
-        ExternalInputResponse response = new(new ChatMessage(ChatRole.User, [approvalResponse]));
-
-        // Resume after approval
-        await action.CaptureResponseAsync(mockContext.Object, response, CancellationToken.None);
-
-        // Assert - the originally-approved argument must be used, not the mutated one
-        Assert.NotNull(capturedArguments);
-        Assert.Equal(ApprovedQuery, capturedArguments["query"]?.ToString());
-    }
-
-    /// <summary>
-    /// Verifies that mutating the server URL variable after approval does not redirect
-    /// the MCP tool call to a different server. The originally-approved server URL must be used.
-    /// </summary>
-    [Fact]
-    public async Task InvokeMcpToolCaptureResponseUsesApprovedServerUrlNotMutatedAsync()
-    {
-        // Arrange
-        const string ApprovedServerUrl = "https://internal-mcp.corp";
-        const string MutatedServerUrl = "https://attacker.evil/steal";
-
-        this.State.Set("McpEndpoint", FormulaValue.New(ApprovedServerUrl));
-        this.State.InitializeSystem();
-        this.State.Bind();
-
-        InvokeMcpTool model = this.CreateModelWithVariableServerUrl(
-            displayName: nameof(InvokeMcpToolCaptureResponseUsesApprovedServerUrlNotMutatedAsync),
-            variableName: "McpEndpoint",
-            toolName: TestToolName);
-
-        string? capturedServerUrl = null;
-        Mock<IMcpToolHandler> mockProvider = new();
-        mockProvider.Setup(provider => provider.InvokeToolAsync(
-                It.IsAny<string>(),
-                It.IsAny<string?>(),
-                It.IsAny<string>(),
-                It.IsAny<IDictionary<string, object?>?>(),
-                It.IsAny<IDictionary<string, string>?>(),
-                It.IsAny<string?>(),
-                It.IsAny<CancellationToken>()))
-            .Callback<string, string?, string, IDictionary<string, object?>?, IDictionary<string, string>?, string?, CancellationToken>(
-                (serverUrl, _, _, _, _, _, _) => capturedServerUrl = serverUrl)
-            .ReturnsAsync(new McpServerToolResultContent("capture-call-id")
-            {
-                Outputs = [new TextContent("result")]
-            });
-        MockAgentProvider mockAgentProvider = new();
-        InvokeMcpToolExecutor action = new(model, mockProvider.Object, mockAgentProvider.Object, this.State);
-
-        // Act - trigger ExecuteAsync to store the approval snapshot
-        Mock<IWorkflowContext> mockContext = CreateMockWorkflowContext();
-        await action.HandleAsync(new ActionExecutorResult(action.Id), mockContext.Object, CancellationToken.None);
-
-        // Simulate parallel branch mutating state during the approval window
-        this.State.Set("McpEndpoint", FormulaValue.New(MutatedServerUrl));
-        this.State.Bind();
-
-        // User clicks approve
-        McpServerToolCallContent toolCall = new(action.Id, TestToolName, ApprovedServerUrl);
-        ToolApprovalRequestContent approvalRequest = new(action.Id, toolCall);
-        ToolApprovalResponseContent approvalResponse = approvalRequest.CreateResponse(approved: true);
-        ExternalInputResponse response = new(new ChatMessage(ChatRole.User, [approvalResponse]));
-
-        // Resume after approval
-        await action.CaptureResponseAsync(mockContext.Object, response, CancellationToken.None);
-
-        // Assert - the originally-approved server URL must be used, not the mutated one
-        Assert.NotNull(capturedServerUrl);
-        Assert.Equal(ApprovedServerUrl, capturedServerUrl);
-    }
-
-    /// <summary>
-    /// Verifies that the approval snapshot survives a checkpoint/restore cycle.
-    /// After restore, the originally-approved tool name must still be used even if state was mutated.
-    /// </summary>
-    [Fact]
-    public async Task InvokeMcpToolCaptureResponseUsesSnapshotAfterCheckpointRestoreAsync()
-    {
-        // Arrange
-        const string ApprovedToolName = "safe_readonly_query";
-        const string MutatedToolName = "dangerous_admin_tool";
-
-        this.State.Set("TargetTool", FormulaValue.New(ApprovedToolName));
-        this.State.InitializeSystem();
-        this.State.Bind();
-
-        InvokeMcpTool model = this.CreateModelWithVariableToolName(
-            displayName: nameof(InvokeMcpToolCaptureResponseUsesSnapshotAfterCheckpointRestoreAsync),
-            serverUrl: TestServerUrl,
-            variableName: "TargetTool");
-
-        string? capturedToolName = null;
-        Mock<IMcpToolHandler> mockProvider = new();
-        mockProvider.Setup(provider => provider.InvokeToolAsync(
-                It.IsAny<string>(),
-                It.IsAny<string?>(),
-                It.IsAny<string>(),
-                It.IsAny<IDictionary<string, object?>?>(),
-                It.IsAny<IDictionary<string, string>?>(),
-                It.IsAny<string?>(),
-                It.IsAny<CancellationToken>()))
-            .Callback<string, string?, string, IDictionary<string, object?>?, IDictionary<string, string>?, string?, CancellationToken>(
-                (_, _, toolName, _, _, _, _) => capturedToolName = toolName)
-            .ReturnsAsync(new McpServerToolResultContent("capture-call-id")
-            {
-                Outputs = [new TextContent("result")]
-            });
-        MockAgentProvider mockAgentProvider = new();
-        InvokeMcpToolExecutor action = new(model, mockProvider.Object, mockAgentProvider.Object, this.State);
-
-        // Act - trigger ExecuteAsync to store the approval snapshot
-        Mock<IWorkflowContext> mockContext = CreateMockWorkflowContextWithStateStore();
-        await action.HandleAsync(new ActionExecutorResult(action.Id), mockContext.Object, CancellationToken.None);
-
-        // Simulate checkpoint: persist to state store
-        await InvokeProtectedMethodAsync(action, "OnCheckpointingAsync", mockContext.Object, CancellationToken.None);
-
-        // Simulate restore on a "new" executor instance by clearing the in-memory field via reflection
-        // (In production, a new executor instance would be created with _approvalSnapshot == null)
-        typeof(InvokeMcpToolExecutor)
-            .GetField("_approvalSnapshot", BindingFlags.NonPublic | BindingFlags.Instance)!
-            .SetValue(action, null);
-
-        // Restore from state store
-        await InvokeProtectedMethodAsync(action, "OnCheckpointRestoredAsync", mockContext.Object, CancellationToken.None);
-
-        // Mutate state after restore (simulating parallel branch)
-        this.State.Set("TargetTool", FormulaValue.New(MutatedToolName));
-        this.State.Bind();
-
-        // User clicks approve
-        McpServerToolCallContent toolCall = new(action.Id, ApprovedToolName, TestServerUrl);
-        ToolApprovalRequestContent approvalRequest = new(action.Id, toolCall);
-        ToolApprovalResponseContent approvalResponse = approvalRequest.CreateResponse(approved: true);
-        ExternalInputResponse response = new(new ChatMessage(ChatRole.User, [approvalResponse]));
-
-        // Resume after approval
-        await action.CaptureResponseAsync(mockContext.Object, response, CancellationToken.None);
-
-        // Assert - the originally-approved tool name must be used, not the mutated one
-        Assert.NotNull(capturedToolName);
-        Assert.Equal(ApprovedToolName, capturedToolName);
-    }
-
-    private static Mock<IWorkflowContext> CreateMockWorkflowContext()
-    {
-        Mock<IWorkflowContext> mockContext = new();
-        mockContext.Setup(c => c.AddEventAsync(It.IsAny<WorkflowEvent>(), It.IsAny<CancellationToken>()))
-            .Returns(default(ValueTask));
-        mockContext.Setup(c => c.QueueStateUpdateAsync(It.IsAny<string>(), It.IsAny<object?>(), It.IsAny<string?>(), It.IsAny<CancellationToken>()))
-            .Returns(default(ValueTask));
-        mockContext.Setup(c => c.SendMessageAsync(It.IsAny<object>(), It.IsAny<string?>(), It.IsAny<CancellationToken>()))
-            .Returns(default(ValueTask));
-        return mockContext;
-    }
-
-    /// <summary>
-    /// Creates a mock workflow context that actually stores state values (for checkpoint/restore tests).
-    /// </summary>
-    private static Mock<IWorkflowContext> CreateMockWorkflowContextWithStateStore()
-    {
-        Dictionary<string, object?> stateStore = new();
-        Mock<IWorkflowContext> mockContext = new();
-        mockContext.Setup(c => c.AddEventAsync(It.IsAny<WorkflowEvent>(), It.IsAny<CancellationToken>()))
-            .Returns(default(ValueTask));
-        mockContext.Setup(c => c.QueueStateUpdateAsync(It.IsAny<string>(), It.IsAny<ApprovalSnapshot?>(), It.IsAny<string?>(), It.IsAny<CancellationToken>()))
-            .Callback<string, ApprovalSnapshot?, string?, CancellationToken>((key, value, _, _) => stateStore[key] = value)
-            .Returns(default(ValueTask));
-        mockContext.Setup(c => c.SendMessageAsync(It.IsAny<object>(), It.IsAny<string?>(), It.IsAny<CancellationToken>()))
-            .Returns(default(ValueTask));
-        mockContext.Setup(c => c.ReadStateAsync<ApprovalSnapshot>(It.IsAny<string>(), It.IsAny<string?>(), It.IsAny<CancellationToken>()))
-            .Returns<string, string?, CancellationToken>((key, _, _) =>
-                new ValueTask<ApprovalSnapshot?>(stateStore.TryGetValue(key, out object? val) ? val as ApprovalSnapshot : null));
-        mockContext.Setup(c => c.ReadStateKeysAsync(It.IsAny<string?>(), It.IsAny<CancellationToken>()))
-            .ReturnsAsync(new HashSet<string>());
-        return mockContext;
-    }
-
-    /// <summary>
-    /// Invokes a protected method on an executor via reflection (for testing checkpoint hooks).
-    /// </summary>
-    private static async ValueTask InvokeProtectedMethodAsync(InvokeMcpToolExecutor action, string methodName, IWorkflowContext context, CancellationToken cancellationToken)
-    {
-        MethodInfo method = typeof(InvokeMcpToolExecutor)
-            .GetMethod(methodName, BindingFlags.NonPublic | BindingFlags.Instance)!;
-        ValueTask result = (ValueTask)method.Invoke(action, [context, cancellationToken])!;
-        await result.ConfigureAwait(false);
-    }
-
-    #endregion
-
    #region CompleteAsync Tests

    [Fact]
@@ -1261,50 +951,6 @@ public sealed class InvokeMcpToolExecutorTest(ITestOutputHelper output) : Workfl
        return AssignParent<InvokeMcpTool>(builder);
    }

-    private InvokeMcpTool CreateModelWithVariableToolName(string displayName, string serverUrl, string variableName)
-    {
-        InvokeMcpTool.Builder builder = new()
-        {
-            Id = this.CreateActionId(),
-            DisplayName = this.FormatDisplayName(displayName),
-            ServerUrl = new StringExpression.Builder(StringExpression.Literal(serverUrl)),
-            ToolName = new StringExpression.Builder(
-                StringExpression.Variable(PropertyPath.TopicVariable(variableName))),
-            RequireApproval = new BoolExpression.Builder(BoolExpression.Literal(true)),
-        };
-        return AssignParent<InvokeMcpTool>(builder);
-    }
-
-    private InvokeMcpTool CreateModelWithVariableArgument(
-        string displayName, string serverUrl, string toolName, string argumentKey, string variableName)
-    {
-        InvokeMcpTool.Builder builder = new()
-        {
-            Id = this.CreateActionId(),
-            DisplayName = this.FormatDisplayName(displayName),
-            ServerUrl = new StringExpression.Builder(StringExpression.Literal(serverUrl)),
-            ToolName = new StringExpression.Builder(StringExpression.Literal(toolName)),
-            RequireApproval = new BoolExpression.Builder(BoolExpression.Literal(true)),
-        };
-        builder.Arguments.Add(argumentKey,
-            ValueExpression.Variable(PropertyPath.TopicVariable(variableName)));
-        return AssignParent<InvokeMcpTool>(builder);
-    }
-
-    private InvokeMcpTool CreateModelWithVariableServerUrl(string displayName, string variableName, string toolName)
-    {
-        InvokeMcpTool.Builder builder = new()
-        {
-            Id = this.CreateActionId(),
-            DisplayName = this.FormatDisplayName(displayName),
-            ServerUrl = new StringExpression.Builder(
-                StringExpression.Variable(PropertyPath.TopicVariable(variableName))),
-            ToolName = new StringExpression.Builder(StringExpression.Literal(toolName)),
-            RequireApproval = new BoolExpression.Builder(BoolExpression.Literal(true)),
-        };
-        return AssignParent<InvokeMcpTool>(builder);
-    }
-
    #endregion

    #region Mock MCP Tool Provider
@@ -7,43 +7,6 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0

 ## [Unreleased]

-## [1.8.0] - 2026-06-04
-
-### Added
- **agent-framework-core**: Add MCP-based skills discovery (`McpSkillsSource`) ([#6169](https://github.com/microsoft/agent-framework/pull/6169))
- **agent-framework-core**: Progressive tool exposure via `FunctionInvocationContext` ([#6233](https://github.com/microsoft/agent-framework/pull/6233))
- **agent-framework-core**: Add background agent support to harness agent ([#6155](https://github.com/microsoft/agent-framework/pull/6155))
- **agent-framework-core**: Add `AgentFileStore` and `FileAccessProvider` for file access operations ([#6099](https://github.com/microsoft/agent-framework/pull/6099))
- **agent-framework-core**: Coalesce code interpreter history chunks ([#5801](https://github.com/microsoft/agent-framework/pull/5801))
- **agent-framework-core**: Run sync tools off the event loop ([#5773](https://github.com/microsoft/agent-framework/pull/5773))
- **agent-framework-bedrock**: Implement native structured output support via Converse API ([#6052](https://github.com/microsoft/agent-framework/pull/6052))
- **agent-framework-foundry**: Add Foundry Adaptive Evals integration for rubric-generation ([#6101](https://github.com/microsoft/agent-framework/pull/6101))
- **agent-framework-foundry**: Add `timeout` parameter to `FoundryAgent` to fix `ConnectTimeout` on multi-turn conversations ([#6263](https://github.com/microsoft/agent-framework/pull/6263))
- **agent-framework-mistral**: Add Mistral AI embedding client package ([#5480](https://github.com/microsoft/agent-framework/pull/5480))
- **agent-framework-a2a**: Expose `supported_protocol_bindings` as configurable parameter ([#6098](https://github.com/microsoft/agent-framework/pull/6098))
- **agent-framework-a2a**: Set `message_id` on `AgentResponseUpdate` for message-bearing paths ([#6163](https://github.com/microsoft/agent-framework/pull/6163))
- **agent-framework-foundry-hosting**: Persist hosted MCP call/results as canonical `mcp_call` output ([#6070](https://github.com/microsoft/agent-framework/pull/6070))
-
-### Changed
- **agent-framework-github-copilot**: [BREAKING] Upgrade `github-copilot-sdk` to v1.0.0 (stable) ([#6292](https://github.com/microsoft/agent-framework/pull/6292))
- **agent-framework-core**: [BREAKING — experimental] Refactor Skill API to async resource and script lookup ([#6135](https://github.com/microsoft/agent-framework/pull/6135))
- **agent-framework-github-copilot**: Promote to release candidate (`1.0.0rc1`)
- **agent-framework-declarative**: Promote to release candidate (`1.0.0rc1`) ([#6256](https://github.com/microsoft/agent-framework/pull/6256))
-
-### Fixed
- **agent-framework-core**: Fix compaction message-id collisions and tool-loop summary persistence ([#6299](https://github.com/microsoft/agent-framework/pull/6299))
- **agent-framework-core**: Fix observability unsafe serialization of function-call arguments containing dataclass/framework objects ([#6026](https://github.com/microsoft/agent-framework/pull/6026))
- **agent-framework-core**: Consolidate MCP reliability fixes ([#6145](https://github.com/microsoft/agent-framework/pull/6145))
- **agent-framework-core**: Backfill chat span request model if unknown and response model is available ([#6160](https://github.com/microsoft/agent-framework/pull/6160))
- **agent-framework-anthropic**: Skip orphan anthropic thinking signatures ([#5784](https://github.com/microsoft/agent-framework/pull/5784))
- **agent-framework-foundry**: Fix `FoundryAgent` stripping model from `PromptAgent` requests ([#5526](https://github.com/microsoft/agent-framework/pull/5526))
- **agent-framework-foundry-hosting**: Fix toolbox consent flow in hosted agent ([#6249](https://github.com/microsoft/agent-framework/pull/6249))
- **agent-framework-foundry-hosting**: Drop hosted MCP calls when reasoning is stripped ([#6210](https://github.com/microsoft/agent-framework/pull/6210))
- **agent-framework-openai**: Fix OTLP HTTP base-endpoint losing `/v1/{signal}` auto-append ([#5913](https://github.com/microsoft/agent-framework/pull/5913))
- **agent-framework-openai**: Drop hosted MCP calls when reasoning is stripped ([#6210](https://github.com/microsoft/agent-framework/pull/6210))
- **agent-framework-orchestrations**: Fix spurious Magentic custom manager warning ([#6261](https://github.com/microsoft/agent-framework/pull/6261))
- **agent-framework-azurefunctions**: Fix integration test worker crashes on Py3.13 ([#4260](https://github.com/microsoft/agent-framework/pull/4260))
-
 ## [1.7.0] - 2026-05-28

 ### Added
@@ -1169,8 +1132,7 @@ Release candidate for **agent-framework-core** and **agent-framework-azure-ai**

 For more information, see the [announcement blog post](https://devblogs.microsoft.com/foundry/introducing-microsoft-agent-framework-the-open-source-engine-for-agentic-ai-apps/).

-[Unreleased]: https://github.com/microsoft/agent-framework/compare/python-1.8.0...HEAD
-[1.8.0]: https://github.com/microsoft/agent-framework/compare/python-1.7.0...python-1.8.0
+[Unreleased]: https://github.com/microsoft/agent-framework/compare/python-1.7.0...HEAD
 [1.7.0]: https://github.com/microsoft/agent-framework/compare/python-1.6.0...python-1.7.0
 [1.6.0]: https://github.com/microsoft/agent-framework/compare/python-1.5.0...python-1.6.0
 [1.5.0]: https://github.com/microsoft/agent-framework/compare/python-1.4.0...python-1.5.0
@@ -33,7 +33,7 @@ Status is grouped into these buckets:
 | `agent-framework-foundry` | `python/packages/foundry` | `released` |
 | `agent-framework-foundry-local` | `python/packages/foundry_local` | `beta` |
 | `agent-framework-gemini` | `python/packages/gemini` | `alpha` |
-| `agent-framework-github-copilot` | `python/packages/github_copilot` | `rc` |
+| `agent-framework-github-copilot` | `python/packages/github_copilot` | `beta` |
 | `agent-framework-hyperlight` | `python/packages/hyperlight` | `beta` |
 | `agent-framework-lab` | `python/packages/lab` | `beta` |
 | `agent-framework-mem0` | `python/packages/mem0` | `beta` |
@@ -4,7 +4,7 @@ description = "A2A integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260604"
+version = "1.0.0b260528"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.8.0,<2",
+    "agent-framework-core>=1.7.0,<2",
    "a2a-sdk>=1.0.0,<2",
 ]

@@ -4,7 +4,7 @@ description = "Anthropic integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260604"
+version = "1.0.0b260521"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.8.0,<2",
+    "agent-framework-core>=1.6.0,<2",
    "anthropic>=0.80.0,<0.80.1",
 ]

@@ -4,7 +4,7 @@ description = "Azure Functions integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260604"
+version = "1.0.0b260521"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -22,8 +22,8 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.8.0,<2",
-    "agent-framework-durabletask>=1.0.0b260604,<2",
+    "agent-framework-core>=1.6.0,<2",
+    "agent-framework-durabletask>=1.0.0b260521,<2",
    "azure-functions>=1.24.0,<2",
    "azure-functions-durable>=1.3.1,<2",
 ]
@@ -795,7 +795,10 @@ class BedrockChatClient(
            schema = copy.deepcopy(schema_src)
        else:
            if not isinstance(response_format, type) or not issubclass(response_format, BaseModel):
-                raise TypeError("response_format must be None, a dict JSON schema, or a Pydantic BaseModel subclass.")
+                raise TypeError(
+                    "response_format must be None, a dict JSON schema, "
+                    "or a Pydantic BaseModel subclass."
+                )
            # response_format is a Pydantic model class
            schema = response_format.model_json_schema()
            name = response_format.__name__
@@ -814,7 +817,9 @@ class BedrockChatClient(
        return {
            "textFormat": {
                "type": "json_schema",
-                "structure": {"jsonSchema": json_schema},
+                "structure": {
+                    "jsonSchema": json_schema
+                },
            }
        }

@@ -835,7 +840,9 @@ class BedrockChatClient(
                if node_id in visited:
                    return
                visited.add(node_id)
-                if node.get("type") == "object" or ("properties" in node and "type" not in node):
+                if node.get("type") == "object" or (
+                    "properties" in node and "type" not in node
+                ):
                    existing = node.get("additionalProperties")
                    if existing is None or existing is True:
                        node["additionalProperties"] = False
@@ -4,7 +4,7 @@ description = "Amazon Bedrock integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260604"
+version = "1.0.0b260521"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.8.0,<2",
+    "agent-framework-core>=1.6.0,<2",
    "boto3>=1.35.0,<2.0.0",
    "botocore>=1.35.0,<2.0.0",
 ]
@@ -238,7 +238,6 @@ async def test_chat_response_value_populated_streaming() -> None:

 async def test_unsupported_model_validation_exception() -> None:
    """When a model doesn't support outputConfig, a clear error should be raised."""
-
    class _FailingStubBedrockRuntime:
        def converse(self, **kwargs: Any) -> dict[str, Any]:
            # Simulate botocore ClientError for ValidationException
@@ -56,7 +56,7 @@ agent_framework/
 - **`AgentMiddleware`** - Intercepts agent `run()` calls
 - **`ChatMiddleware`** - Intercepts chat client `get_response()` calls
 - **`FunctionMiddleware`** - Intercepts function/tool invocations
- **`AgentContext`** / **`ChatContext`** / **`FunctionInvocationContext`** - Context objects passed through middleware. A tool can declare a `FunctionInvocationContext` parameter to receive it; `context.tools` is the live, mutable tools list for the run, and `context.add_tools(...)` / `context.remove_tools(...)` enable progressive tool exposure (changes apply on the next function-calling iteration).
+- **`AgentContext`** / **`ChatContext`** / **`FunctionInvocationContext`** - Context objects passed through middleware

 ### Sessions (`_sessions.py`)

@@ -168,9 +168,6 @@ from ._skills import (
    InlineSkillResource,
    InlineSkillScript,
    InMemorySkillsSource,
-    MCPSkill,
-    MCPSkillResource,
-    MCPSkillsSource,
    Skill,
    SkillFrontmatter,
    SkillResource,
@@ -447,9 +444,6 @@ __all__ = [
    "MCPStdioTool",
    "MCPStreamableHTTPTool",
    "MCPWebsocketTool",
-    "MCPSkill",
-    "MCPSkillResource",
-    "MCPSkillsSource",
    "MemoryContextProvider",
    "MemoryFileStore",
    "MemoryIndexEntry",
@@ -380,15 +380,8 @@ class BaseChatClient(SerializationMixin, ABC, Generic[OptionsCoT]):
            return prepared_messages
        from ._compaction import apply_compaction

-        # Compact the caller's list in place when possible. A compaction operation has
-        # two halves: exclusion flags (mutated on shared Message objects) and inserted
-        # summary messages. Operating on the original list keeps both halves on the list
-        # the function-invocation tool loop reuses across iterations; otherwise inserted
-        # summaries would be lost on a throwaway copy while exclusions persisted, silently
-        # dropping older groups (issue #4991).
-        working_messages = messages if isinstance(messages, list) else prepared_messages
        return await apply_compaction(
-            working_messages,
+            prepared_messages,
            strategy=compaction_strategy,
            tokenizer=tokenizer,
        )
@@ -4,7 +4,7 @@ from __future__ import annotations

 import json
 import logging
-from collections.abc import Iterable, Mapping, Sequence
+from collections.abc import Mapping, Sequence
 from typing import (
    TYPE_CHECKING,
    Any,
@@ -92,23 +92,10 @@ def _is_reasoning_only_assistant(message: Message) -> bool:
    return all(content.type == "text_reasoning" for content in message.contents)


-def _ensure_message_ids(
-    messages: list[Message], *, id_offset: int = 0, reserved_ids: Iterable[str] | None = None
-) -> None:
-    existing_ids: set[str] = set(reserved_ids) if reserved_ids is not None else set()
-    existing_ids.update(message.message_id for message in messages if message.message_id)
+def _ensure_message_ids(messages: list[Message]) -> None:
    for index, message in enumerate(messages):
-        if message.message_id:
-            continue
-        candidate = f"msg_{id_offset + index}"
-        if candidate in existing_ids:
-            counter = id_offset + len(messages)
-            candidate = f"msg_{counter}"
-            while candidate in existing_ids:
-                counter += 1
-                candidate = f"msg_{counter}"
-        message.message_id = candidate
-        existing_ids.add(candidate)
+        if not message.message_id:
+            message.message_id = f"msg_{index}"


 def _group_id_for(message: Message, group_index: int) -> str:
@@ -117,27 +104,14 @@ def _group_id_for(message: Message, group_index: int) -> str:
    return f"group_index_{group_index}"


-def group_messages(
-    messages: list[Message], *, id_offset: int = 0, reserved_ids: Iterable[str] | None = None
-) -> list[dict[str, Any]]:
+def group_messages(messages: list[Message]) -> list[dict[str, Any]]:
    """Compute group spans and metadata for annotation.

-    Args:
-        messages: The messages (or a slice of them) to group.
-
-    Keyword Args:
-        id_offset: Absolute starting index used when auto-assigning ``message_id``
-            values, so incremental annotation of a list slice produces ids that
-            stay unique across the full list.
-        reserved_ids: Message ids that already exist outside ``messages`` (for
-            example in a preserved prefix). Auto-assigned ids are guaranteed not
-            to collide with these, preventing duplicate ids across the full list.
-
    Returns:
        Ordered list of lightweight span dicts with keys:
        ``group_id``, ``kind``, ``start_index``, ``end_index``, ``has_reasoning``.
    """
-    _ensure_message_ids(messages, id_offset=id_offset, reserved_ids=reserved_ids)
+    _ensure_message_ids(messages)
    spans: list[dict[str, Any]] = []
    i = 0
    group_index = 0
@@ -465,8 +439,7 @@ def annotate_message_groups(
        if previous_group_index is not None:
            group_index_offset = previous_group_index + 1

-    reserved_ids = {message.message_id for message in messages[:start_index] if message.message_id}
-    spans = group_messages(messages[start_index:], id_offset=start_index, reserved_ids=reserved_ids)
+    spans = group_messages(messages[start_index:])
    for span_index, span in enumerate(spans):
        group_id = str(span["group_id"])
        kind = _coerce_group_kind(span["kind"])
@@ -58,8 +58,6 @@ class ExperimentalFeature(str, Enum):
    FOUNDRY_PREVIEW_TOOLS = "FOUNDRY_PREVIEW_TOOLS"
    FUNCTIONAL_WORKFLOWS = "FUNCTIONAL_WORKFLOWS"
    HARNESS = "HARNESS"
-    MCP_SKILLS = "MCP_SKILLS"
-    PROGRESSIVE_TOOLS = "PROGRESSIVE_TOOLS"
    SKILLS = "SKILLS"
    TO_PROMPT_AGENT = "TO_PROMPT_AGENT"

@@ -349,8 +349,6 @@ class BackgroundAgentsProvider(ContextProvider):
            _save_provider_state(session, provider_state, source_id=source_id)
            return f"Background task {task_id} started on agent '{agent_name}'."

-        background_agents_start_task._invoke_sync_on_event_loop = True  # pyright: ignore[reportPrivateUsage]
-
        @tool(name="background_agents_wait_for_first_completion", approval_mode="never_require")
        async def background_agents_wait_for_first_completion(task_ids: list[int]) -> str:
            """Block until the first of the specified background tasks completes. Returns the completed task's ID."""
@@ -473,8 +471,6 @@ class BackgroundAgentsProvider(ContextProvider):
            _save_provider_state(session, provider_state, source_id=source_id)
            return f"Task {task_id} continued with new input."

-        background_agents_continue_task._invoke_sync_on_event_loop = True  # pyright: ignore[reportPrivateUsage]
-
        @tool(name="background_agents_clear_completed_task", approval_mode="never_require")
        def background_agents_clear_completed_task(task_id: int) -> str:
            """Remove a completed or failed task and release its session to free memory."""
@@ -11,7 +11,6 @@ from enum import Enum
 from typing import TYPE_CHECKING, Any, Generic, Literal, TypeAlias, cast, overload

 from ._clients import SupportsChatGetResponse
-from ._feature_stage import ExperimentalFeature, experimental
 from ._types import (
    AgentResponse,
    AgentResponseUpdate,
@@ -215,12 +214,6 @@ class FunctionInvocationContext:
        result: Function execution result. Can be observed after calling ``call_next()``
                to see the actual execution result or can be set to override the execution result.
        kwargs: Additional runtime keyword arguments forwarded to the function invocation.
-        tools: The live, mutable list of tools available to the model for the current
-                agent run, or ``None`` when the function is invoked outside of a
-                function-calling loop (for example via ``FunctionTool.invoke`` directly).
-                Tools can add or remove tools during execution using :meth:`add_tools`
-                and :meth:`remove_tools` (progressive tool exposure). Mutations take
-                effect on the **next** model iteration, not the in-flight batch.

    Examples:
        .. code-block:: python
@@ -239,18 +232,6 @@ class FunctionInvocationContext:

                    # Continue execution
                    await call_next()
-
-        Progressive tool exposure from inside a tool:
-
-        .. code-block:: python
-
-            from agent_framework import FunctionInvocationContext, tool
-
-
-            @tool(approval_mode="never_require")
-            def load_math_tools(ctx: FunctionInvocationContext) -> str:
-                ctx.add_tools([factorial, fibonacci])
-                return "Math tools are now available."
    """

    def __init__(
@@ -261,7 +242,6 @@ class FunctionInvocationContext:
        metadata: Mapping[str, Any] | None = None,
        result: Any = None,
        kwargs: Mapping[str, Any] | None = None,
-        tools: list[ToolTypes] | None = None,
    ) -> None:
        """Initialize the FunctionInvocationContext.

@@ -272,9 +252,6 @@ class FunctionInvocationContext:
            metadata: Metadata dictionary for sharing data between function middleware.
            result: Function execution result.
            kwargs: Additional runtime keyword arguments forwarded to the function invocation.
-            tools: The live, mutable list of tools for the current agent run. When provided,
-                this is the same list object the model sees on the next iteration, so
-                appending or removing tools changes the model's available tools.
        """
        self.function = function
        self.arguments = arguments
@@ -282,96 +259,6 @@ class FunctionInvocationContext:
        self.metadata: dict[str, Any] = dict(metadata) if metadata is not None else {}
        self.result = result
        self.kwargs: dict[str, Any] = dict(kwargs) if kwargs is not None else {}
-        self.tools = tools
-
-    @experimental(feature_id=ExperimentalFeature.PROGRESSIVE_TOOLS)
-    def add_tools(
-        self,
-        tools: ToolTypes | Callable[..., Any] | Sequence[ToolTypes | Callable[..., Any]],
-    ) -> None:
-        """Add one or more tools to the current agent run (progressive tool exposure).
-
-        Callable inputs are converted to :class:`FunctionTool`, and tool collections are
-        flattened, using the same normalization as the rest of the framework. Added tools
-        become available to the model on the **next** iteration of the function-calling
-        loop; they do not affect tool calls already requested in the in-flight batch.
-
-        Adding a tool whose name already exists is a no-op when it is the same object, and
-        raises ``ValueError`` when it is a different object with a duplicate name.
-
-        Args:
-            tools: A single tool/callable or a sequence of tools/callables to add.
-
-        Raises:
-            RuntimeError: If the context has no live tools list (for example when the
-                function is invoked outside of a function-calling loop).
-            ValueError: If a different tool with a duplicate name is added.
-        """
-        from ._tools import _append_unique_tools, normalize_tools  # type: ignore[reportPrivateUsage]
-
-        if self.tools is None:
-            raise RuntimeError(
-                "Cannot add tools: this FunctionInvocationContext is not bound to a live "
-                "agent run. add_tools is only available for functions invoked within an "
-                "agent's function-calling loop."
-            )
-        # Validate the whole batch against a throwaway copy first, so a duplicate-name
-        # clash partway through the batch raises before the live tool list is mutated
-        # (all-or-nothing semantics).
-        merged = _append_unique_tools(list(self.tools), normalize_tools(tools))
-        self.tools[:] = merged
-
-    @experimental(feature_id=ExperimentalFeature.PROGRESSIVE_TOOLS)
-    def remove_tools(
-        self,
-        tools: ToolTypes | Callable[..., Any] | Sequence[ToolTypes | Callable[..., Any]] | str | Sequence[str],
-    ) -> None:
-        """Remove one or more tools from the current agent run (progressive tool exposure).
-
-        Tools may be specified by name, by tool object, or by the original callable. Names
-        that are not currently present are ignored. Removals take effect on the **next**
-        iteration of the function-calling loop; tool calls already requested in the
-        in-flight batch still execute.
-
-        Args:
-            tools: A tool name, tool/callable, or a sequence of any of these to remove.
-
-        Raises:
-            RuntimeError: If the context has no live tools list (for example when the
-                function is invoked outside of a function-calling loop).
-        """
-        from ._tools import _get_tool_name, normalize_tools  # type: ignore[reportPrivateUsage]
-
-        if self.tools is None:
-            raise RuntimeError(
-                "Cannot remove tools: this FunctionInvocationContext is not bound to a live "
-                "agent run. remove_tools is only available for functions invoked within an "
-                "agent's function-calling loop."
-            )
-
-        names_to_remove: set[str] = set()
-        raw_items: list[Any]
-        if isinstance(tools, str):
-            raw_items = [tools]
-        elif isinstance(tools, Sequence) and not isinstance(tools, (bytes, bytearray)):
-            raw_items = list(cast("Sequence[Any]", tools))
-        else:
-            raw_items = [tools]
-        for item in raw_items:
-            if isinstance(item, str):
-                names_to_remove.add(item)
-                continue
-            for normalized in normalize_tools(item):
-                if name := _get_tool_name(normalized):  # type: ignore[reportPrivateUsage]
-                    names_to_remove.add(name)
-
-        if not names_to_remove:
-            return
-        self.tools[:] = [
-            tool
-            for tool in self.tools
-            if _get_tool_name(tool) not in names_to_remove  # type: ignore[reportPrivateUsage]
-        ]


 class ChatContext:
@@ -44,7 +44,6 @@ Only use skills from trusted sources.
 from __future__ import annotations

 import asyncio
-import base64
 import inspect
 import json
 import logging
@@ -61,10 +60,6 @@ from ._sessions import ContextProvider
 from ._tools import FunctionTool

 if TYPE_CHECKING:
-    from mcp.client.session import ClientSession
-    from mcp.types import ReadResourceResult
-    from pydantic import AnyUrl
-
    from ._agents import SupportsAgentRun
    from ._sessions import AgentSession, SessionContext

@@ -3290,443 +3285,4 @@ class AggregatingSkillsSource(SkillsSource):
        return result


-# region MCP Skills
-
-
-def _mcp_any_url(uri: str) -> AnyUrl:
-    """Convert a string URI to a :class:`pydantic.AnyUrl` for MCP client calls."""
-    from pydantic import AnyUrl as _AnyUrl
-
-    return _AnyUrl(uri)
-
-
-def _is_mcp_resource_not_found(ex: Exception) -> bool:
-    """Return ``True`` when *ex* is an :class:`McpError` indicating a missing resource.
-
-    Two codes are treated as "not found":
-
-    * ``-32002`` — the MCP-spec "Resource not found" code returned by a
-      compliant server when the URI does not exist. Not exported as a
-      constant from ``mcp.types`` but defined by the resources subprotocol.
-    * ``METHOD_NOT_FOUND`` (``-32601``) — the server does not implement
-      ``resources/read`` at all, which for the skills source is functionally
-      equivalent to "no skills available."
-
-    All other codes — ``INVALID_PARAMS``, ``INTERNAL_ERROR``, ``PARSE_ERROR``,
-    ``CONNECTION_CLOSED``, auth rejections, and generic handler errors
-    (code ``0``) — are treated as real failures so that a misconfigured
-    token or crashing server is not silently mistaken for "the server has no
-    skills."
-    """
-    from mcp.shared.exceptions import McpError as _McpError
-
-    if not isinstance(ex, _McpError):
-        return False
-    from mcp.types import METHOD_NOT_FOUND as _METHOD_NOT_FOUND
-
-    return ex.error.code in {-32002, _METHOD_NOT_FOUND}
-
-
-def _mcp_join_text(result: ReadResourceResult) -> str:
-    """Join all :class:`TextResourceContents` items in a result into a single string."""
-    from mcp.types import TextResourceContents as _TextResourceContents
-
-    return "\n".join(c.text for c in result.contents if isinstance(c, _TextResourceContents))
-
-
-class _McpSkillIndexEntry:  # noqa: B903
-    """A single entry in the ``skill://index.json`` discovery document.
-
-    All fields are optional to support lenient deserialization; callers
-    validate required fields before use.
-    """
-
-    def __init__(
-        self,
-        *,
-        name: str | None = None,
-        type: str | None = None,
-        description: str | None = None,
-        url: str | None = None,
-        digest: str | None = None,
-    ) -> None:
-        self.name = name
-        self.type = type
-        self.description = description
-        self.url = url
-        self.digest = digest
-
-
-class _McpSkillIndex:
-    """DTO for the ``skill://index.json`` discovery document.
-
-    Represents the Agent Skills Discovery v0.2.0 schema as bound to MCP
-    by SEP-2640.
-    """
-
-    def __init__(
-        self,
-        *,
-        schema: str | None = None,
-        skills: list[_McpSkillIndexEntry] | None = None,
-    ) -> None:
-        self.schema = schema
-        self.skills: list[_McpSkillIndexEntry] = skills if skills is not None else []
-
-
-def _parse_mcp_skill_index(text: str) -> _McpSkillIndex:
-    """Parse a JSON string into a :class:`_McpSkillIndex`.
-
-    Args:
-        text: Raw JSON text from ``skill://index.json``.
-
-    Returns:
-        A populated :class:`_McpSkillIndex` instance.
-
-    Raises:
-        json.JSONDecodeError: If the text is not valid JSON.
-        ValueError: If the top-level value is not a JSON object.
-    """
-    raw: dict[str, Any] = json.loads(text)
-
-    if not isinstance(raw, dict):
-        raise ValueError("skill://index.json must be a JSON object")
-
-    entries: list[_McpSkillIndexEntry] = []
-
-    raw_skills: list[Any] = raw.get("skills") or []
-
-    for item in raw_skills:
-        if isinstance(item, dict):
-            d = cast(dict[str, Any], item)
-
-            entries.append(
-                _McpSkillIndexEntry(
-                    name=d.get("name"),
-                    type=d.get("type"),
-                    description=d.get("description"),
-                    url=d.get("url"),
-                    digest=d.get("digest"),
-                )
-            )
-
-    return _McpSkillIndex(schema=raw.get("$schema"), skills=entries)
-
-
-@experimental(feature_id=ExperimentalFeature.MCP_SKILLS)
-class MCPSkillResource(SkillResource):
-    """A :class:`SkillResource` backed by content fetched from an MCP server.
-
-    The :class:`~mcp.types.ReadResourceResult` is fetched eagerly by
-    :meth:`MCPSkill.get_resource` at construction time; :meth:`read`
-    extracts text or binary content from the result.
-    """
-
-    def __init__(self, *, name: str, result: ReadResourceResult) -> None:
-        """Initialize an MCPSkillResource.
-
-        Args:
-            name: The resource name (e.g. a relative path or identifier).
-            result: The result returned by the MCP server's ``resources/read`` request.
-        """
-        super().__init__(name=name)
-        self._result = result
-
-    async def read(self, **kwargs: Any) -> Any:
-        """Read the resource content.
-
-        Returns:
-            A ``bytes`` object when the resource contains binary content,
-            a ``str`` when it contains text, or ``None`` when the server
-            returned no content blocks.
-        """
-        from mcp.types import BlobResourceContents, TextResourceContents
-
-        for content in self._result.contents:
-            if isinstance(content, BlobResourceContents):
-                blob = content.blob
-                # Strip data-URI prefix if present (some MCP servers send
-                # full data URIs instead of raw base64).
-                if blob.startswith("data:"):
-                    blob = blob.split(",", 1)[-1]
-                return base64.b64decode(blob)
-
-        text = "\n".join(c.text for c in self._result.contents if isinstance(c, TextResourceContents))
-        return text if text else None
-
-
-@experimental(feature_id=ExperimentalFeature.MCP_SKILLS)
-class MCPSkill(Skill):
-    """A :class:`Skill` discovered from an MCP server exposing the Agent Skills convention.
-
-    The skill is constructed from ``skill://index.json`` discovery metadata;
-    :meth:`get_content` fetches the full ``SKILL.md`` content from the MCP
-    server on demand via ``resources/read``.
-
-    Per SEP-2640, resources referenced inside SKILL.md are fetched on demand
-     via the originating MCP server: :meth:`get_resource` resolves a relative
-    resource name against the skill's root URI, issues a ``resources/read``
-     request, and returns an :class:`MCPSkillResource` with pre-fetched content.
-    """
-
-    _SKILL_MD_SUFFIX: Final[str] = "SKILL.md"
-
-    def __init__(
-        self,
-        frontmatter: SkillFrontmatter,
-        skill_md_uri: str,
-        client: ClientSession,
-    ) -> None:
-        """Initialize an MCPSkill.
-
-        Args:
-            frontmatter: The parsed frontmatter metadata for this skill.
-            skill_md_uri: The full MCP resource URI of the ``SKILL.md`` resource
-                (e.g. ``skill://unit-converter/SKILL.md``). The skill's root URI
-                is derived by stripping the trailing ``SKILL.md`` segment.
-            client: The MCP client session used to fetch resources on demand.
-        """
-        self._frontmatter = frontmatter
-        self._skill_md_uri = skill_md_uri
-        self._skill_root_uri = self._compute_skill_root_uri(skill_md_uri)
-        self._client = client
-        self._content: str | None = None
-
-    @property
-    def frontmatter(self) -> SkillFrontmatter:
-        """The L1 discovery metadata for this skill."""
-        return self._frontmatter
-
-    async def get_content(self) -> str:
-        """Get the full SKILL.md content from the MCP server.
-
-        Fetches the content via ``resources/read`` on the first call and
-        caches the result for subsequent calls.
-
-        Returns:
-            The SKILL.md content string.
-
-        Raises:
-            ValueError: If the MCP server returned no text content for the
-                SKILL.md resource.
-        """
-        if self._content is not None:
-            return self._content
-
-        result = await self._client.read_resource(_mcp_any_url(self._skill_md_uri))
-        text = _mcp_join_text(result)
-        if not text:
-            raise ValueError(
-                f"The MCP server returned no text content for SKILL.md resource '{self._skill_md_uri}'."
-            )
-        self._content = text
-        return text
-
-    async def get_resource(self, name: str) -> SkillResource | None:
-        """Get a sibling resource by name from the MCP server.
-
-        Resolves *name* as a relative path against the skill's root URI,
-        issues a ``resources/read`` request to the MCP server, and returns
-        an :class:`MCPSkillResource` with the pre-fetched content.
-
-        Args:
-            name: The resource name (e.g. ``references/checklist.md``).
-
-        Returns:
-            An :class:`MCPSkillResource`, or ``None`` when the name is empty
-            or the resource does not exist on the server.
-        """
-        if not name or not name.strip():
-            return None
-
-        normalized = self._validate_resource_name(name)
-        if normalized is None:
-            return None
-
-        uri = self._skill_root_uri + normalized
-        try:
-            result = await self._client.read_resource(_mcp_any_url(uri))
-        except Exception as ex:
-            if _is_mcp_resource_not_found(ex):
-                logger.debug("MCP resource '%s' not available: %s", uri, ex)
-                return None
-            raise
-
-        return MCPSkillResource(name=name, result=result)
-
-    @staticmethod
-    def _validate_resource_name(name: str) -> str | None:
-        """Validate a resource name and return the normalized form.
-
-        Defense in depth: refuses names that could escape the skill root
-        (absolute paths, embedded URI schemes, parent-traversal segments).
-        The MCP server is the authority on URI resolution, but rejecting
-        obviously unsafe shapes client-side avoids leaking escape attempts
-        upstream.
-
-        Args:
-            name: The raw resource name to validate.
-
-        Returns:
-            The normalized name with backslashes replaced by forward slashes,
-            or ``None`` if the name is unsafe.
-        """
-        normalized = name.replace("\\", "/")
-        if (
-            normalized.startswith("/")
-            or "://" in normalized
-            or any(seg == ".." for seg in normalized.split("/"))
-        ):
-            logger.debug("Rejecting resource name with unsafe path components: %r", name)
-            return None
-        return normalized
-
-    @staticmethod
-    def _compute_skill_root_uri(skill_md_uri: str) -> str:
-        """Strip the trailing ``SKILL.md`` from the URI to produce the skill root.
-
-        If the URI doesn't end with ``SKILL.md``, ensures it ends with a
-        trailing slash.
-        """
-        if skill_md_uri.endswith(MCPSkill._SKILL_MD_SUFFIX):
-            return skill_md_uri[: -len(MCPSkill._SKILL_MD_SUFFIX)]
-        if skill_md_uri.endswith("/"):
-            return skill_md_uri
-        return skill_md_uri + "/"
-
-
-@experimental(feature_id=ExperimentalFeature.MCP_SKILLS)
-class MCPSkillsSource(SkillsSource):
-    """A :class:`SkillsSource` that discovers Agent Skills served over MCP.
-
-    Discovery follows the SEP-2640 recommended approach: the source reads
-    the well-known ``skill://index.json`` resource and constructs one
-    :class:`MCPSkill` per ``skill-md`` entry directly from the entry's
-    ``name``, ``description``, and ``url`` fields.
-
-    The referenced ``SKILL.md`` resource is **not** read during discovery;
-    the host fetches its body on demand via ``resources/read`` when the
-    skill content is needed.
-
-    Only index entries of type ``skill-md`` are supported; entries of any
-    other type are silently skipped.
-
-    If ``skill://index.json`` is absent, unreadable, empty, or fails to
-    parse, this source returns an empty list.
-
-    Examples:
-        .. code-block:: python
-
-            from mcp.client.session import ClientSession
-
-            source = MCPSkillsSource(client=session)
-            skills = await source.get_skills()
-    """
-
-    _INDEX_URI: Final[str] = "skill://index.json"
-    _SKILL_MD_TYPE: Final[str] = "skill-md"
-
-    def __init__(self, client: ClientSession) -> None:
-        """Initialize an MCPSkillsSource.
-
-        Args:
-            client: An MCP client session connected to a server that
-                exposes Agent Skills resources.
-        """
-        self._client = client
-
-    async def get_skills(self) -> list[Skill]:
-        """Discover and return skills from the MCP server.
-
-        Reads ``skill://index.json``, parses it, and creates an
-        :class:`MCPSkill` for each valid ``skill-md`` entry.
-
-        Returns:
-            A list of discovered :class:`MCPSkill` instances.
-        """
-        index = await self._try_read_index()
-        if index is None:
-            return []
-
-        skills: list[Skill] = []
-        for entry in index.skills:
-            result = self._try_create_skill(entry)
-            if result is not None:
-                skills.append(result)
-                logger.info("Loaded MCP skill: %s", result.frontmatter.name)
-            else:
-                logger.debug(
-                    "Skipping skill index entry '%s'",
-                    entry.name or "(unnamed)",
-                )
-
-        logger.info("Successfully loaded %d skills from MCP server", len(skills))
-        return skills
-
-    async def _try_read_index(self) -> _McpSkillIndex | None:
-        """Attempt to read and parse ``skill://index.json`` from the MCP server.
-
-        Returns:
-            A parsed :class:`_McpSkillIndex`, or ``None`` if the index is
-            absent, empty, or malformed.
-        """
-        try:
-            result = await self._client.read_resource(_mcp_any_url(self._INDEX_URI))
-        except Exception as ex:
-            if _is_mcp_resource_not_found(ex):
-                logger.debug("No skill://index.json resource available on MCP server: %s", ex)
-                return None
-            logger.warning("Failed to read skill://index.json from MCP server.", exc_info=True)
-            raise
-
-        index_text = _mcp_join_text(result)
-        if not index_text:
-            logger.debug("skill://index.json on MCP server returned empty/non-text contents")
-            return None
-
-        try:
-            return _parse_mcp_skill_index(index_text)
-        except (json.JSONDecodeError, ValueError):
-            logger.warning("Failed to parse skill://index.json JSON document.", exc_info=True)
-            return None
-
-    def _try_create_skill(self, entry: _McpSkillIndexEntry) -> MCPSkill | None:
-        """Attempt to create an :class:`MCPSkill` from an index entry.
-
-        Args:
-            entry: A single entry from the skill index.
-
-        Returns:
-            An :class:`MCPSkill` if the entry is valid, or ``None`` if the
-            entry should be skipped.
-        """
-        if entry.type != self._SKILL_MD_TYPE:
-            logger.debug(
-                "Skipping entry '%s': unsupported type '%s'",
-                entry.name or "(unnamed)",
-                entry.type or "(none)",
-            )
-            return None
-
-        if not entry.name or not entry.name.strip():
-            logger.debug("Skipping entry: missing required 'name' field")
-            return None
-
-        if not entry.description or not entry.description.strip():
-            logger.debug("Skipping entry '%s': missing required 'description' field", entry.name)
-            return None
-
-        if not entry.url or not entry.url.strip():
-            logger.debug("Skipping entry '%s': missing required 'url' field", entry.name)
-            return None
-
-        try:
-            fm = SkillFrontmatter(name=entry.name, description=entry.description)
-        except ValueError as ex:
-            logger.debug("Skipping entry '%s': invalid metadata: %s", entry.name, ex)
-            return None
-
-        return MCPSkill(frontmatter=fm, skill_md_uri=entry.url, client=self._client)
-
-
 # endregion
@@ -292,7 +292,6 @@ class FunctionTool(SerializationMixin):
        "_cached_parameters",
        "_input_schema",
        "_schema_supplied",
-        "_invoke_sync_on_event_loop",
    }

    def __init__(
@@ -367,7 +366,6 @@ class FunctionTool(SerializationMixin):
        self.description = description
        self.kind = kind
        self.additional_properties = additional_properties
-        self._invoke_sync_on_event_loop = False
        for key, value in kwargs.items():
            setattr(self, key, value)

@@ -539,16 +537,6 @@ class FunctionTool(SerializationMixin):
            self.invocation_exception_count += 1
            raise

-    async def _invoke_function(self, call_kwargs: Mapping[str, Any]) -> Any:
-        """Run sync tools off the event loop during async invocation."""
-        func = self.func.func if isinstance(self.func, FunctionTool) else self.func
-        if inspect.iscoroutinefunction(func) or getattr(self, "_invoke_sync_on_event_loop", False):
-            res = self.__call__(**call_kwargs)
-            return await res if inspect.isawaitable(res) else res
-
-        res = await asyncio.to_thread(self.__call__, **call_kwargs)
-        return await res if inspect.isawaitable(res) else res
-
    @overload
    async def invoke(
        self,
@@ -691,7 +679,8 @@ class FunctionTool(SerializationMixin):
        if not OBSERVABILITY_SETTINGS.ENABLED:  # type: ignore[name-defined]
            logger.info(f"Function name: {self.name}")
            logger.debug(f"Function arguments: {observable_kwargs}")
-            result = await self._invoke_function(call_kwargs)
+            res = self.__call__(**call_kwargs)
+            result = await res if inspect.isawaitable(res) else res
            if skip_parsing:
                logger.info(f"Function {self.name} succeeded.")
                logger.debug(f"Function result: {type(result).__name__}")
@@ -741,7 +730,8 @@ class FunctionTool(SerializationMixin):
            start_time_stamp = perf_counter()
            end_time_stamp: float | None = None
            try:
-                result = await self._invoke_function(call_kwargs)
+                res = self.__call__(**call_kwargs)
+                result = await res if inspect.isawaitable(res) else res
                end_time_stamp = perf_counter()
            except Exception as exception:
                end_time_stamp = perf_counter()
@@ -1428,7 +1418,6 @@ async def _auto_invoke_function(
    sequence_index: int | None = None,
    request_index: int | None = None,
    middleware_pipeline: FunctionMiddlewarePipeline | None = None,
-    live_tools: list[ToolTypes] | None = None,
 ) -> Content:
    """Invoke a function call requested by the agent, applying middleware that is defined.

@@ -1443,8 +1432,6 @@ async def _auto_invoke_function(
        sequence_index: The index of the function call in the sequence.
        request_index: The index of the request iteration.
        middleware_pipeline: Optional middleware pipeline to apply during execution.
-        live_tools: The live, mutable tools list for the current agent run, exposed on
-            the FunctionInvocationContext so tools can add/remove tools at runtime.

    Returns:
        The function result content.
@@ -1536,7 +1523,6 @@ async def _auto_invoke_function(
                    arguments=args,
                    session=invocation_session,
                    kwargs=runtime_kwargs.copy(),
-                    tools=live_tools,
                )
            function_result = await tool.invoke(
                arguments=args,
@@ -1551,10 +1537,6 @@ async def _auto_invoke_function(
        except UserInputRequiredException:
            raise
        except Exception as exc:
-            logger.warning(
-                f"Function '{tool.name}' raised an exception; returning an error result to the "
-                f"model. Set include_detailed_errors=True for the full detail. Exception: {exc!r}"
-            )
            message = "Error: Function failed."
            if config.get("include_detailed_errors", False):
                message = f"{message} Exception: {exc}"
@@ -1570,7 +1552,6 @@ async def _auto_invoke_function(
        arguments=args,
        session=invocation_session,
        kwargs=runtime_kwargs.copy(),
-        tools=live_tools,
    )

    call_id = function_call_content.call_id
@@ -1627,10 +1608,6 @@ async def _auto_invoke_function(
    except UserInputRequiredException:
        raise
    except Exception as exc:
-        logger.warning(
-            f"Function '{tool.name}' raised an exception; returning an error result to the "
-            f"model. Set include_detailed_errors=True for the full detail. Exception: {exc!r}"
-        )
        message = "Error: Function failed."
        if config.get("include_detailed_errors", False):
            message = f"{message} Exception: {exc}"
@@ -1682,9 +1659,6 @@ async def _try_execute_function_calls(
    from ._types import Content

    tool_map = _get_tool_map(tools)
-    # The live tools list (when tools is the run-local list) is exposed on the
-    # FunctionInvocationContext so tools can add/remove tools during the run.
-    live_tools: list[ToolTypes] | None = cast("list[ToolTypes]", tools) if isinstance(tools, list) else None
    approval_tools = [tool_name for tool_name, tool in tool_map.items() if tool.approval_mode == "always_require"]
    logger.debug(
        "_try_execute_function_calls: tool_map keys=%s, approval_tools=%s",
@@ -1759,7 +1733,6 @@ async def _try_execute_function_calls(
                request_index=attempt_idx,
                middleware_pipeline=middleware_pipeline,
                config=config,
-                live_tools=live_tools,
            )
            return (result, False)
        except MiddlewareTermination as exc:
@@ -2398,13 +2371,6 @@ class FunctionInvocationLayer(Generic[OptionsCoT]):
                function_invocation_kwargs=function_invocation_kwargs,
                client_kwargs=filtered_kwargs,
            )
-        # Establish a single, run-local mutable tools list so that tools can add or remove
-        # tools during the run (progressive tool exposure). A fresh list is created via
-        # normalize_tools so the caller's original tools container is never mutated, while
-        # the same list object is shared with the model (options["tools"]) and the tool map
-        # rebuilt on every loop iteration.
-        if mutable_options.get("tools"):
-            mutable_options["tools"] = normalize_tools(mutable_options["tools"])
        if not stream:

            async def _get_response() -> ChatResponse[Any]:
@@ -2,7 +2,6 @@

 from __future__ import annotations

-import json
 import logging
 import sys
 import uuid
@@ -12,7 +11,6 @@ from datetime import datetime, timezone
 from typing import TYPE_CHECKING, Any, ClassVar, Literal, cast, overload

 from .._agents import BaseAgent
-from .._serialization import make_json_safe
 from .._sessions import (
    AgentSession,
    ContextProvider,
@@ -30,11 +28,12 @@ from .._types import (
    UsageDetails,
    add_usage_details,
 )
-from ..exceptions import AgentInvalidRequestException, AgentInvalidResponseException
+from ..exceptions import AgentException, AgentInvalidRequestException, AgentInvalidResponseException
 from ._checkpoint import CheckpointStorage
 from ._events import (
    AGENT_FORWARDED_EVENT_TYPES,
    WorkflowEvent,
+    WorkflowRunState,
 )
 from ._message_utils import normalize_messages_input
 from ._typing_utils import is_instance_of, is_type_compatible
@@ -59,27 +58,24 @@ class WorkflowAgent(BaseAgent):
    @dataclass
    class RequestInfoFunctionArgs:
        request_id: str
-        data: Any
+        request_event: WorkflowEvent

        def to_dict(self) -> dict[str, Any]:
-            return {"request_id": self.request_id, "data": make_json_safe(self.data)}
-
-        def to_json(self) -> str:
-            return json.dumps(self.to_dict())
+            return {"request_id": self.request_id, "request_event": self.request_event.to_dict()}

        @classmethod
        def from_dict(cls, payload: dict[str, Any]) -> WorkflowAgent.RequestInfoFunctionArgs:
-            return cls(request_id=payload.get("request_id", ""), data=payload.get("data"))
+            if "request_id" not in payload or "request_event" not in payload:
+                raise ValueError(
+                    "Invalid payload for RequestInfoFunctionArgs. 'request_id' and 'request_event' are required."
+                )
+            if not payload["request_id"]:
+                raise ValueError("request_id cannot be empty.")

-        @classmethod
-        def from_json(cls, raw: str) -> WorkflowAgent.RequestInfoFunctionArgs:
-            try:
-                parsed: Any = json.loads(raw)
-            except json.JSONDecodeError as exc:
-                raise ValueError(f"RequestInfoFunctionArgs JSON payload is malformed: {exc}") from exc
-            if not isinstance(parsed, dict):
-                raise ValueError("RequestInfoFunctionArgs JSON payload must decode to a mapping")
-            return cls.from_dict(cast(dict[str, Any], parsed))
+            return cls(
+                request_id=payload.get("request_id", ""),
+                request_event=WorkflowEvent.from_dict(payload.get("request_event", {})),
+            )

    def __init__(
        self,
@@ -129,16 +125,11 @@ class WorkflowAgent(BaseAgent):
            **kwargs,
        )
        self._workflow: Workflow = workflow
-        self._pending_requests: dict[str, WorkflowEvent[Any]] = {}

    @property
    def workflow(self) -> Workflow:
        return self._workflow

-    @property
-    def pending_requests(self) -> dict[str, WorkflowEvent[Any]]:
-        return self._pending_requests
-
    # region Run Methods

    @overload
@@ -182,7 +173,7 @@ class WorkflowAgent(BaseAgent):

        Args:
            messages: The message(s) to send to the workflow. Required for new runs,
-                should be None when resuming from checkpoint.
+                could be None if only restoring the underlying workflow from a checkpoint.

        Keyword Args:
            stream: If True, returns an async iterable of updates. If False (default),
@@ -416,101 +407,79 @@ class WorkflowAgent(BaseAgent):
        Yields:
            WorkflowEvent objects from the workflow execution.
        """
-        # Determine the execution mode based on state.
-        # The streaming flag controls the workflow's internal streaming mode,
-        # which affects executor behavior (e.g. AgentExecutor emits different event
-        # types in streaming vs non-streaming mode).
-        if bool(self.pending_requests):
-            function_responses = self._process_pending_requests(input_messages)
+        # Restore the workflow state if a checkpoint is provided
+        if checkpoint_id is not None:
+            if checkpoint_storage is None:
+                raise AgentInvalidRequestException("checkpoint_storage must be provided when checkpoint_id is provided")
+            logger.debug(f"Restoring workflow from checkpoint {checkpoint_id}")
+            # Restore the workflow from checkpoint
            if streaming:
-                async for event in self.workflow.run(
-                    responses=function_responses,
-                    stream=True,
-                    function_invocation_kwargs=function_invocation_kwargs,
-                    client_kwargs=client_kwargs,
-                ):
-                    yield event
-            else:
-                for event in await self.workflow.run(
-                    responses=function_responses,
-                    function_invocation_kwargs=function_invocation_kwargs,
-                    client_kwargs=client_kwargs,
-                ):
-                    yield event
-
-        elif checkpoint_id is not None:
-            # Restore the prior workflow state from the checkpoint. Shared
-            # state (e.g. accumulated conversation history maintained by the
-            # workflow's executors) survives across turns because Workflow.run
-            # no longer wipes state per call. Callers who want to deliver a
-            # new user message after restore should make a second
-            # `workflow.run(message=...)` call - they are NOT mutually
-            # exclusive on the same instance, but each must be its own call.
-            if streaming:
-                async for event in self.workflow.run(
+                async for _ in self.workflow.run(
                    stream=True,
                    checkpoint_id=checkpoint_id,
                    checkpoint_storage=checkpoint_storage,
+                ):
+                    pass
+            else:
+                _ = await self.workflow.run(
+                    checkpoint_id=checkpoint_id,
+                    checkpoint_storage=checkpoint_storage,
+                )
+            if not input_messages:
+                logger.info("No input messages provided; the workflow has been restored to the checkpoint state.")
+                return
+
+        final_state = self._workflow.status
+        logger.debug(f"Workflow state: {final_state}")
+
+        if final_state == WorkflowRunState.IDLE_WITH_PENDING_REQUESTS:
+            # Extract function responses from input messages, and ensure that
+            # only function responses are present in messages if there is any
+            # pending request.
+            # NOTE: It is possible that some pending requests are not fulfilled,
+            # and we will let the workflow to handle this -- the agent does not
+            # have an opinion on this.
+            function_responses = self._extract_function_responses(input_messages)
+            if streaming:
+                async for event in self.workflow.run(
+                    responses=function_responses,
+                    stream=True,
+                    checkpoint_storage=checkpoint_storage,
                    function_invocation_kwargs=function_invocation_kwargs,
                    client_kwargs=client_kwargs,
                ):
                    yield event
            else:
                for event in await self.workflow.run(
-                    checkpoint_id=checkpoint_id,
+                    responses=function_responses,
+                    checkpoint_storage=checkpoint_storage,
+                    function_invocation_kwargs=function_invocation_kwargs,
+                    client_kwargs=client_kwargs,
+                ):
+                    yield event
+        elif final_state == WorkflowRunState.IDLE:
+            if streaming:
+                async for event in self.workflow.run(
+                    message=input_messages,
+                    stream=True,
+                    checkpoint_storage=checkpoint_storage,
+                    function_invocation_kwargs=function_invocation_kwargs,
+                    client_kwargs=client_kwargs,
+                ):
+                    yield event
+            else:
+                for event in await self.workflow.run(
+                    message=input_messages,
                    checkpoint_storage=checkpoint_storage,
                    function_invocation_kwargs=function_invocation_kwargs,
                    client_kwargs=client_kwargs,
                ):
                    yield event
-
        else:
-            if streaming:
-                async for event in self.workflow.run(
-                    message=input_messages,
-                    stream=True,
-                    checkpoint_storage=checkpoint_storage,
-                    function_invocation_kwargs=function_invocation_kwargs,
-                    client_kwargs=client_kwargs,
-                ):
-                    yield event
-            else:
-                for event in await self.workflow.run(
-                    message=input_messages,
-                    checkpoint_storage=checkpoint_storage,
-                    function_invocation_kwargs=function_invocation_kwargs,
-                    client_kwargs=client_kwargs,
-                ):
-                    yield event
+            raise AgentException(f"The underlying workflow is in an invalid state to restart: {final_state}.")

    # endregion Run Methods

-    def _process_pending_requests(self, input_messages: Sequence[Message]) -> dict[str, Any]:
-        """Process pending requests by extracting function responses and updating state.
-
-        Args:
-            input_messages: Input messages that may contain function responses.
-
-        Returns:
-            A dictionary mapping request IDs to their response data.
-        """
-        logger.info(f"Continuing workflow to address {len(self.pending_requests)} requests")
-
-        # Extract function responses from input messages, and ensure that
-        # only function responses are present in messages if there is any
-        # pending request.
-        function_responses = self._extract_function_responses(input_messages)
-
-        # Pop pending requests if fulfilled.
-        for request_id in list(self.pending_requests.keys()):
-            if request_id in function_responses:
-                self.pending_requests.pop(request_id)
-
-        # NOTE: It is possible that some pending requests are not fulfilled,
-        # and we will let the workflow to handle this -- the agent does not
-        # have an opinion on this.
-        return function_responses
-
    def _convert_workflow_events_to_agent_response(
        self,
        response_id: str,
@@ -528,10 +497,10 @@ class WorkflowAgent(BaseAgent):

        for output_event in output_events:
            if output_event.type == "request_info":
-                function_call, approval_request = self._process_request_info_event(output_event)
+                request_content = self._process_request_info_event(output_event)
                messages.append(
                    Message(
-                        contents=[function_call, approval_request],
+                        contents=[request_content],
                        role="assistant",
                        author_name=output_event.source_executor_id,
                        message_id=str(uuid.uuid4()),
@@ -598,38 +567,6 @@ class WorkflowAgent(BaseAgent):
            raw_representation=raw_representations,
        )

-    def _process_request_info_event(
-        self,
-        event: WorkflowEvent[Any],
-    ) -> tuple[Content, Content]:
-        """Convert a request_info event to FunctionCallContent and FunctionApprovalRequestContent.
-
-        Args:
-            event: A WorkflowEvent with type='request_info'.
-
-        Returns:
-            A tuple of (FunctionCallContent, FunctionApprovalRequestContent).
-        """
-        request_id = event.request_id
-        if not request_id:
-            raise ValueError("request_info event must have a request_id")
-
-        self.pending_requests[request_id] = event
-
-        args = self.RequestInfoFunctionArgs(request_id=request_id, data=event.data).to_dict()
-
-        function_call = Content.from_function_call(
-            call_id=request_id,
-            name=self.REQUEST_INFO_FUNCTION_NAME,
-            arguments=args,
-        )
-        approval_request = Content.from_function_approval_request(
-            id=request_id,
-            function_call=function_call,
-            additional_properties={"request_id": request_id},
-        )
-        return function_call, approval_request
-
    def _convert_workflow_event_to_agent_response_updates(
        self,
        response_id: str,
@@ -731,85 +668,72 @@ class WorkflowAgent(BaseAgent):
            ]

        if event.type == "request_info":
-            # Store the pending request for later correlation
-            request_id = event.request_id
-            if not request_id:
-                raise ValueError("request_info event must have a request_id")
-
-            self.pending_requests[request_id] = event
-
-            args = self.RequestInfoFunctionArgs(request_id=request_id, data=event.data).to_dict()
-
-            function_call = Content.from_function_call(
-                call_id=request_id,
-                name=self.REQUEST_INFO_FUNCTION_NAME,
-                arguments=args,
-            )
-            approval_request = Content.from_function_approval_request(
-                id=request_id,
-                function_call=function_call,
-                additional_properties={"request_id": request_id},
-            )
+            request_content = self._process_request_info_event(event)
            return [
                AgentResponseUpdate(
-                    contents=[function_call, approval_request],
+                    contents=[request_content],
                    role="assistant",
                    author_name=self.name,
                    response_id=response_id,
                    message_id=str(uuid.uuid4()),
                    created_at=datetime.now(tz=timezone.utc).strftime("%Y-%m-%dT%H:%M:%S.%fZ"),
+                    raw_representation=event,
                )
            ]

        # Ignore workflow-internal events
        return []

+    def _process_request_info_event(
+        self,
+        event: WorkflowEvent[Any],
+    ) -> Content:
+        """Convert a request_info event to FunctionApprovalRequestContent.
+
+        Args:
+            event: A WorkflowEvent with type='request_info'.
+
+        Returns:
+            A content object representing the request info. The content can be a `function_approval_request`
+            or a `function_call` depending on the structure of the event data.
+
+        Note:
+            If the event data is already a FunctionApprovalRequestContent, it will be returned as-is.
+        """
+        if isinstance(event.data, Content) and event.data.user_input_request:
+            # Return the event data as-is if it's already a properly formed FunctionApprovalRequestContent
+            return event.data
+
+        request_id = event.request_id
+        args = self.RequestInfoFunctionArgs(request_id=request_id, request_event=event).to_dict()
+
+        return Content.from_function_call(
+            call_id=request_id,
+            name=self.REQUEST_INFO_FUNCTION_NAME,
+            arguments=args,
+        )
+
    def _extract_function_responses(self, input_messages: Sequence[Message]) -> dict[str, Any]:
-        """Extract function responses from input messages."""
+        """Extract function responses from input messages.
+
+        The responses are for pending requests that the workflow is waiting on, and
+        will be passed to the workflow. The pending requests are processed to either
+        `function_approval_request` or `function_call` content by `_process_request_info_event`.
+        """
        function_responses: dict[str, Any] = {}
        for message in input_messages:
            for content in message.contents:
                if content.type == "function_approval_response":
-                    # Parse the function arguments to recover request payload
-                    arguments_payload = content.function_call.arguments  # type: ignore[attr-defined, union-attr]
-                    if isinstance(arguments_payload, str):
-                        try:
-                            parsed_args = self.RequestInfoFunctionArgs.from_json(arguments_payload)
-                        except ValueError as exc:
-                            raise AgentInvalidResponseException(
-                                "FunctionApprovalResponseContent arguments must decode to a mapping."
-                            ) from exc
-                    elif isinstance(arguments_payload, dict):
-                        parsed_args = self.RequestInfoFunctionArgs.from_dict(arguments_payload)
-                    else:
-                        raise AgentInvalidResponseException(
-                            "FunctionApprovalResponseContent arguments must be a mapping or JSON string."
-                        )
-
-                    request_id = parsed_args.request_id or content.id  # type: ignore[attr-defined]
-                    if not content.approved:  # type: ignore[attr-defined]
-                        raise AgentInvalidResponseException(f"Request '{request_id}' was not approved by the caller.")
-
-                    if request_id in self.pending_requests:
-                        function_responses[request_id] = parsed_args.data
-                    elif bool(self.pending_requests):
-                        raise AgentInvalidRequestException(
-                            "Only responses for pending requests are allowed when there are outstanding approvals."
-                        )
+                    request_id: str = content.id  # type: ignore[assignment]
+                    function_responses[request_id] = content
                elif content.type == "function_result":
-                    request_id = content.call_id  # type: ignore[attr-defined]
-                    if request_id in self.pending_requests:
-                        response_data = content.result if hasattr(content, "result") else str(content)  # type: ignore[attr-defined]
-                        function_responses[request_id] = response_data
-                    elif bool(self.pending_requests):
-                        raise AgentInvalidRequestException(
-                            "Only function responses for pending requests are allowed while requests are outstanding."
-                        )
+                    response_data = content.result if hasattr(content, "result") else str(content)  # type: ignore[attr-defined]
+                    function_responses[content.call_id] = response_data  # type: ignore
                else:
-                    if bool(self.pending_requests):
-                        raise AgentInvalidResponseException(
-                            "Unexpected content type while awaiting request info responses."
-                        )
+                    raise AgentInvalidResponseException(
+                        "Unexpected content type while awaiting request info responses."
+                    )
+
        return function_responses

    def _extract_contents(self, data: Any) -> list[Content]:
@@ -429,15 +429,30 @@ class AgentExecutor(Executor):
            function_invocation_kwargs=function_invocation_kwargs,
            client_kwargs=client_kwargs,
        )
-        await ctx.yield_output(response)

        # Handle any user input requests
        if response.user_input_requests:
+            user_input_request_count = len(response.user_input_requests)
+            total_message_content_count = sum(len(msg.contents) for msg in response.messages)
+            if user_input_request_count != total_message_content_count:
+                logger.warning(
+                    "Response %s contains %d user input requests but total message contents are %d. "
+                    "This indicates the response contains both user input requests and message contents. "
+                    "Double check if this is the intended behavior, as non user input request contents in "
+                    "this response will not be emitted.",
+                    response.response_id,
+                    user_input_request_count,
+                    total_message_content_count,
+                )
            for user_input_request in response.user_input_requests:
                self._pending_agent_requests[user_input_request.id] = user_input_request  # type: ignore[index]
-                await ctx.request_info(user_input_request, Content)
+                await ctx.request_info(user_input_request, Content, request_id=user_input_request.id)
            return None

+        # Only yield output if the response is complete and not waiting for user input.
+        # This is to avoid emitting two events of different types ('output' and 'request_info')
+        # that carry the same payload.
+        await ctx.yield_output(response)
        return response

    async def _run_agent_streaming(self, ctx: WorkflowContext[Never, AgentResponseUpdate]) -> AgentResponse | None:
@@ -472,9 +487,25 @@ class AgentExecutor(Executor):
        )
        async for update in stream:
            updates.append(update)
-            await ctx.yield_output(update)
            if update.user_input_requests:
+                user_input_request_count = len(update.user_input_requests)
+                total_message_content_count = len(update.contents)
+                if user_input_request_count != total_message_content_count:
+                    logger.warning(
+                        "Response update %s contains %d user input requests but total message contents are %d. "
+                        "This indicates the response update contains both user input requests and message contents. "
+                        "Double check if this is the intended behavior, as non user input request contents will "
+                        "not be emitted.",
+                        update.response_id,
+                        user_input_request_count,
+                        total_message_content_count,
+                    )
                streamed_user_input_requests.extend(update.user_input_requests)
+            else:
+                # Only yield output events for updates that do not contain user input requests.
+                # This is to avoid emitting two events of different types ('output' and 'request_info')
+                # that carry the same payload.
+                await ctx.yield_output(update)

        # Prefer stream finalization when available so result hooks run
        # (e.g., thread conversation updates). Fall back to reconstructing from updates
@@ -509,7 +540,7 @@ class AgentExecutor(Executor):
        if user_input_requests:
            for user_input_request in user_input_requests:
                self._pending_agent_requests[user_input_request.id] = user_input_request  # type: ignore[index]
-                await ctx.request_info(user_input_request, Content)
+                await ctx.request_info(user_input_request, Content, request_id=user_input_request.id)
            return None

        return response
@@ -360,6 +360,22 @@ class Workflow(DictConvertible):
        # Flag to prevent concurrent workflow executions
        self._is_running = False

+        # Current run-level status of this workflow instance. Updated in lockstep with
+        # the status events emitted from `_run_workflow_with_tracing`. Defaults to IDLE
+        # for a freshly built workflow that has not yet been run.
+        self._status: WorkflowRunState = WorkflowRunState.IDLE
+
+    @property
+    def status(self) -> WorkflowRunState:
+        """Return the current run-level status of this workflow instance.
+
+        Mirrors the most recent status event emitted by the workflow. Safe to read at
+        any time: workflows run on a single asyncio event loop, and the underlying
+        attribute is a single enum reference whose assignment is atomic under the
+        CPython GIL, so no locking is required.
+        """
+        return self._status
+
    def _ensure_not_running(self) -> None:
        """Ensure the workflow is not already running."""
        if self._is_running:
@@ -513,8 +529,9 @@ class Workflow(DictConvertible):
                with _framework_event_origin():
                    started = WorkflowEvent.started()
                yield started  # noqa: RUF070
+                self._status = WorkflowRunState.IN_PROGRESS
                with _framework_event_origin():
-                    in_progress = WorkflowEvent.status(WorkflowRunState.IN_PROGRESS)
+                    in_progress = WorkflowEvent.status(self._status)
                yield in_progress  # noqa: RUF070

                # Per-run reset for fresh-message runs only. We deliberately
@@ -569,17 +586,20 @@ class Workflow(DictConvertible):

                    if event.type == "request_info" and not emitted_in_progress_pending:
                        emitted_in_progress_pending = True
+                        self._status = WorkflowRunState.IN_PROGRESS_PENDING_REQUESTS
                        with _framework_event_origin():
-                            pending_status = WorkflowEvent.status(WorkflowRunState.IN_PROGRESS_PENDING_REQUESTS)
+                            pending_status = WorkflowEvent.status(self._status)
                        yield pending_status  # noqa: RUF070
                # Workflow runs until idle - emit final status based on whether requests are pending
                if saw_request:
+                    self._status = WorkflowRunState.IDLE_WITH_PENDING_REQUESTS
                    with _framework_event_origin():
-                        terminal_status = WorkflowEvent.status(WorkflowRunState.IDLE_WITH_PENDING_REQUESTS)
+                        terminal_status = WorkflowEvent.status(self._status)
                    yield terminal_status
                else:
+                    self._status = WorkflowRunState.IDLE
                    with _framework_event_origin():
-                        terminal_status = WorkflowEvent.status(WorkflowRunState.IDLE)
+                        terminal_status = WorkflowEvent.status(self._status)
                    yield terminal_status

                span.add_event(OtelAttr.WORKFLOW_COMPLETED)
@@ -593,6 +613,7 @@ class Workflow(DictConvertible):
                with _framework_event_origin():
                    failed_event = WorkflowEvent.failed(details)
                yield failed_event  # noqa: RUF070
+                self._status = WorkflowRunState.FAILED
                with _framework_event_origin():
                    failed_status = WorkflowEvent.status(WorkflowRunState.FAILED)
                yield failed_status  # noqa: RUF070
@@ -4,7 +4,7 @@ description = "Microsoft Agent Framework for building AI Agents with Python. Thi
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.8.0"
+version = "1.7.0"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -11,14 +11,10 @@ from agent_framework import (
    GROUP_TOKEN_COUNT_KEY,
    BaseChatClient,
    ChatResponse,
-    ChatResponseUpdate,
-    Content,
    Message,
    SlidingWindowStrategy,
    SupportsChatGetResponse,
-    ToolResultCompactionStrategy,
    TruncationStrategy,
-    tool,
 )


@@ -262,196 +258,6 @@ async def test_base_client_default_tokenizer_without_strategy_annotates_messages
    assert captured_token_counts == [[19, 19]]


-def _tool_call_response(call_id: str, location: str) -> ChatResponse:
-    return ChatResponse(
-        messages=Message(
-            role="assistant",
-            contents=[
-                Content.from_function_call(
-                    call_id=call_id,
-                    name="lookup_weather",
-                    arguments=f'{{"location": "{location}"}}',
-                )
-            ],
-        ),
-        response_id=f"resp_{call_id}",
-    )
-
-
-def _is_tool_result_summary(message: Message) -> bool:
-    text = message.text or ""
-    return message.role == "assistant" and text.startswith("[Tool results:")
-
-
-async def test_function_loop_persists_inserted_summaries_across_iterations(
-    chat_client_base: SupportsChatGetResponse,
-) -> None:
-    # Regression test for #4991: compaction inserts summary messages and excludes the
-    # originals. Across tool-loop iterations the exclusion flags persisted (shared Message
-    # objects) but the inserted summaries were dropped (they only lived on a throwaway copy),
-    # so older tool groups were silently lost with no summary representing them.
-    chat_client_base.function_invocation_configuration["enabled"] = True  # type: ignore[attr-defined]
-    chat_client_base.function_invocation_configuration["max_iterations"] = 3  # type: ignore[attr-defined]
-    chat_client_base.compaction_strategy = ToolResultCompactionStrategy(keep_last_tool_call_groups=1)  # type: ignore[attr-defined]
-
-    @tool(name="lookup_weather", approval_mode="never_require")
-    def lookup_weather(location: str) -> str:
-        return f"Weather in {location}: sunny"
-
-    chat_client_base.run_responses = [  # type: ignore[attr-defined]
-        _tool_call_response("call_1", "London"),
-        _tool_call_response("call_2", "Paris"),
-        _tool_call_response("call_3", "Tokyo"),
-    ]
-
-    captured_inputs: list[list[Message]] = []
-    original = chat_client_base._get_non_streaming_response  # type: ignore[attr-defined]
-
-    async def _capture(
-        *,
-        messages: list[Message],
-        options: dict[str, Any],
-        **kwargs: Any,
-    ) -> ChatResponse:
-        captured_inputs.append(list(messages))
-        return await original(messages=messages, options=options, **kwargs)
-
-    chat_client_base._get_non_streaming_response = _capture  # type: ignore[attr-defined,method-assign]
-
-    await chat_client_base.get_response(
-        [Message(role="user", contents=["What is the weather in London?"])],
-        options={"tools": [lookup_weather]},  # type: ignore[typeddict-unknown-key]
-    )
-
-    # The final model call should represent every compacted tool group with a summary.
-    # Two older tool groups get collapsed (London, Paris) while the last (Tokyo) is kept.
-    final_input = captured_inputs[-1]
-    summaries = [message for message in final_input if _is_tool_result_summary(message)]
-    summary_text = " ".join(message.text or "" for message in summaries)
-
-    assert len(summaries) == 2, [message.text for message in final_input]
-    assert "London" in summary_text
-    assert "Paris" in summary_text
-
-
-def _tool_call_update(call_id: str, location: str) -> list[ChatResponseUpdate]:
-    return [
-        ChatResponseUpdate(
-            contents=[
-                Content.from_function_call(
-                    call_id=call_id,
-                    name="lookup_weather",
-                    arguments=f'{{"location": "{location}"}}',
-                )
-            ],
-            role="assistant",
-            finish_reason="stop",
-            response_id=f"resp_{call_id}",
-        )
-    ]
-
-
-async def test_function_loop_persists_inserted_summaries_across_iterations_streaming(
-    chat_client_base: SupportsChatGetResponse,
-) -> None:
-    # Streaming counterpart of the #4991 regression test: the summary persistence fix in
-    # ``_prepare_messages_for_model_call`` must cover the streaming tool loop too.
-    chat_client_base.function_invocation_configuration["enabled"] = True  # type: ignore[attr-defined]
-    chat_client_base.function_invocation_configuration["max_iterations"] = 3  # type: ignore[attr-defined]
-    chat_client_base.compaction_strategy = ToolResultCompactionStrategy(keep_last_tool_call_groups=1)  # type: ignore[attr-defined]
-
-    @tool(name="lookup_weather", approval_mode="never_require")
-    def lookup_weather(location: str) -> str:
-        return f"Weather in {location}: sunny"
-
-    chat_client_base.streaming_responses = [  # type: ignore[attr-defined]
-        _tool_call_update("call_1", "London"),
-        _tool_call_update("call_2", "Paris"),
-        _tool_call_update("call_3", "Tokyo"),
-    ]
-
-    captured_inputs: list[list[Message]] = []
-    original = chat_client_base._get_streaming_response  # type: ignore[attr-defined]
-
-    def _capture(
-        *,
-        messages: list[Message],
-        options: dict[str, Any],
-        **kwargs: Any,
-    ):
-        captured_inputs.append(list(messages))
-        return original(messages=messages, options=options, **kwargs)
-
-    chat_client_base._get_streaming_response = _capture  # type: ignore[attr-defined,method-assign]
-
-    stream = chat_client_base.get_response(
-        [Message(role="user", contents=["What is the weather in London?"])],
-        stream=True,
-        options={"tools": [lookup_weather]},  # type: ignore[typeddict-unknown-key]
-    )
-    async for _ in stream:
-        pass
-
-    final_input = captured_inputs[-1]
-    summaries = [message for message in final_input if _is_tool_result_summary(message)]
-    summary_text = " ".join(message.text or "" for message in summaries)
-
-    assert len(summaries) == 2, [message.text for message in final_input]
-    assert "London" in summary_text
-    assert "Paris" in summary_text
-
-
-async def test_function_loop_compaction_conversation_id_mode_does_not_resend_history(
-    chat_client_base: SupportsChatGetResponse,
-) -> None:
-    # In conversation-id mode the server owns prior context, so the tool loop clears
-    # ``prepped_messages`` and only sends the latest message. Compaction must not fight that
-    # by re-inserting summaries or re-sending earlier turns.
-    chat_client_base.function_invocation_configuration["enabled"] = True  # type: ignore[attr-defined]
-    chat_client_base.function_invocation_configuration["max_iterations"] = 3  # type: ignore[attr-defined]
-    chat_client_base.compaction_strategy = ToolResultCompactionStrategy(keep_last_tool_call_groups=1)  # type: ignore[attr-defined]
-
-    @tool(name="lookup_weather", approval_mode="never_require")
-    def lookup_weather(location: str) -> str:
-        return f"Weather in {location}: sunny"
-
-    def _conversation_tool_call(call_id: str, location: str) -> ChatResponse:
-        response = _tool_call_response(call_id, location)
-        response.conversation_id = "conv_1"
-        return response
-
-    chat_client_base.run_responses = [  # type: ignore[attr-defined]
-        _conversation_tool_call("call_1", "London"),
-        _conversation_tool_call("call_2", "Paris"),
-        _conversation_tool_call("call_3", "Tokyo"),
-    ]
-
-    captured_inputs: list[list[Message]] = []
-    original = chat_client_base._get_non_streaming_response  # type: ignore[attr-defined]
-
-    async def _capture(
-        *,
-        messages: list[Message],
-        options: dict[str, Any],
-        **kwargs: Any,
-    ) -> ChatResponse:
-        captured_inputs.append(list(messages))
-        return await original(messages=messages, options=options, **kwargs)
-
-    chat_client_base._get_non_streaming_response = _capture  # type: ignore[attr-defined,method-assign]
-
-    await chat_client_base.get_response(
-        [Message(role="user", contents=["What is the weather in London?"])],
-        options={"tools": [lookup_weather]},  # type: ignore[typeddict-unknown-key]
-    )
-
-    # After the conversation id is established the loop only forwards the latest message,
-    # so subsequent model calls never receive the full history or summary messages.
-    for sent in captured_inputs[1:]:
-        assert len(sent) <= 1, [message.text for message in sent]
-        assert not any(_is_tool_result_summary(message) for message in sent)
-
-
 def test_base_client_as_agent_does_not_copy_client_compaction_defaults(
    chat_client_base: SupportsChatGetResponse,
 ) -> None:
@@ -196,64 +196,6 @@ def test_append_compaction_message_annotates_new_message() -> None:
    assert isinstance(_group_id(messages[1]), str)


-def test_incremental_annotation_assigns_unique_message_ids() -> None:
-    # Regression test for #5237: ``_ensure_message_ids`` assigned ``msg_{index}``
-    # using the position within the slice handed to ``group_messages``. Successive
-    # incremental annotations restart the index at 0, so distinct messages collided
-    # on the same ``message_id``.
-    messages: list[Message] = []
-    for turn in range(4):
-        messages.append(Message(role="user", contents=[f"user {turn}"]))
-        annotate_message_groups(messages)
-        messages.append(Message(role="assistant", contents=[f"assistant {turn}"]))
-        annotate_message_groups(messages)
-
-    message_ids = [message.message_id for message in messages]
-    assert all(message_ids), "every message should receive an id"
-    assert len(set(message_ids)) == len(message_ids), f"duplicate message ids: {message_ids}"
-
-
-def test_ensure_message_ids_avoids_existing_id_collisions() -> None:
-    # An auto-generated ``msg_{index}`` must not collide with an id already present
-    # on another message (user-supplied or assigned by an earlier annotation pass).
-    messages = [
-        Message(role="user", contents=["zero"]),
-        Message(role="assistant", contents=["one"], message_id="msg_2"),
-        Message(role="user", contents=["two"]),
-    ]
-    annotate_message_groups(messages)
-
-    message_ids = [message.message_id for message in messages]
-    assert message_ids[1] == "msg_2"
-    assert len(set(message_ids)) == len(message_ids), f"duplicate message ids: {message_ids}"
-
-
-def test_incremental_annotation_avoids_prefix_id_collision() -> None:
-    # Regression for the PR review on #5237: when only a suffix is re-annotated,
-    # an auto-assigned ``msg_{index}`` in the suffix must not collide with a
-    # preexisting id carried by a message in the *preserved prefix* (a group
-    # before the one re-annotation pulls back to). Otherwise ``_group_id_for``
-    # derives the same group id and merges groups across the boundary.
-    messages = [
-        # Out-of-position, user-supplied id that matches the ``msg_{index}`` the
-        # suffix pass would assign to the appended message below. This message is
-        # two groups back, so it stays outside the re-annotated slice.
-        Message(role="user", contents=["zero"], message_id="msg_2"),
-        Message(role="user", contents=["one"]),
-    ]
-    annotate_message_groups(messages)
-    assert messages[0].message_id == "msg_2"
-    assert messages[1].message_id == "msg_1"
-
-    messages.append(Message(role="user", contents=["two"]))
-    annotate_message_groups(messages, from_index=2)
-
-    message_ids = [message.message_id for message in messages]
-    assert all(message_ids), "every message should receive an id"
-    assert len(set(message_ids)) == len(message_ids), f"duplicate message ids: {message_ids}"
-    assert messages[0].message_id == "msg_2"
-
-
 async def test_truncation_strategy_keeps_system_anchor() -> None:
    messages = [
        Message(role="system", contents=["you are helpful"]),
@@ -542,44 +484,6 @@ async def test_tool_result_compaction_collapses_old_groups_into_summary() -> Non
    assert any(m.role == "tool" for m in projected)


-async def test_tool_result_compaction_is_idempotent_after_summary_insertion() -> None:
-    """Re-running compaction after a mid-list summary insertion must not duplicate it.
-
-    Mirrors a subsequent tool-loop iteration (issue #4991): the inserted summary and the
-    excluded originals now persist on the same list, so a second annotate + compaction pass
-    over the same groups should be a no-op rather than collapsing the group again.
-    """
-    messages = [
-        Message(role="user", contents=["u"]),
-        _assistant_function_call("call-1"),
-        _tool_result("call-1", "r1"),
-        _assistant_function_call("call-2"),
-        _tool_result("call-2", "r2"),
-        Message(role="assistant", contents=["done"]),
-    ]
-    strategy = ToolResultCompactionStrategy(keep_last_tool_call_groups=1)
-    annotate_message_groups(messages)
-    assert await strategy(messages) is True
-
-    summaries_after_first = [m for m in messages if (m.text or "").startswith("[Tool results:")]
-    assert len(summaries_after_first) == 1
-    summary = summaries_after_first[0]
-    summary_group_ids = _group_unknown_value(summary, SUMMARY_OF_GROUP_IDS_KEY)
-
-    # Second pass over the same (now partially compacted) list.
-    annotate_message_groups(messages)
-    changed = await strategy(messages)
-
-    assert changed is False
-    summaries_after_second = [m for m in messages if (m.text or "").startswith("[Tool results:")]
-    assert len(summaries_after_second) == 1
-    assert _group_unknown_value(summaries_after_second[0], SUMMARY_OF_GROUP_IDS_KEY) == summary_group_ids
-
-    # The kept tool-call group stays atomic and included.
-    projected = included_messages(messages)
-    assert any(m.role == "tool" for m in projected)
-
-
 async def test_tool_result_compaction_zero_collapses_all() -> None:
    """With keep=0, all tool-call groups are collapsed into summaries."""
    messages = [
@@ -3975,425 +3975,3 @@ async def test_user_input_request_empty_contents_returns_fallback(chat_client_ba
    ]
    assert len(function_results) >= 1
    assert any("user input" in (fr.result or "").lower() for fr in function_results)
-
-
-# region Progressive tool exposure (FunctionInvocationContext.add_tools / remove_tools)
-
-
-def _pte_function_call_response(call_id: str, name: str, arguments: str = "{}") -> ChatResponse:
-    return ChatResponse(
-        messages=Message(
-            role="assistant",
-            contents=[Content.from_function_call(call_id=call_id, name=name, arguments=arguments)],
-        )
-    )
-
-
-def _pte_text_response(text: str = "done") -> ChatResponse:
-    return ChatResponse(messages=Message(role="assistant", contents=[text]))
-
-
-@tool(name="factorial", approval_mode="never_require")
-def _pte_factorial(n: int) -> int:
-    """Compute the factorial of n."""
-    result = 1
-    for value in range(2, n + 1):
-        result *= value
-    return result
-
-
-async def test_context_exposes_live_tools(chat_client_base: SupportsChatGetResponse):
-    from agent_framework import FunctionTool
-
-    seen_names: list[str] = []
-
-    @tool(name="inspect_tools", approval_mode="never_require")
-    def inspect_tools(ctx: FunctionInvocationContext) -> str:
-        assert ctx.tools is not None
-        seen_names.extend(t.name for t in ctx.tools if isinstance(t, FunctionTool))
-        return "inspected"
-
-    chat_client_base.run_responses = [
-        _pte_function_call_response("1", "inspect_tools"),
-        _pte_text_response(),
-    ]
-    await chat_client_base.get_response(
-        [Message(role="user", contents=["hi"])],
-        options={"tool_choice": "auto", "tools": [inspect_tools]},
-    )
-    assert "inspect_tools" in seen_names
-
-
-async def test_add_tools_available_next_iteration(chat_client_base: SupportsChatGetResponse):
-    exec_counter = 0
-
-    @tool(name="factorial", approval_mode="never_require")
-    def factorial(n: int) -> int:
-        nonlocal exec_counter
-        exec_counter += 1
-        return 120
-
-    @tool(name="load_math", approval_mode="never_require")
-    def load_math(ctx: FunctionInvocationContext) -> str:
-        ctx.add_tools(factorial)
-        return "math tools loaded"
-
-    chat_client_base.function_invocation_configuration["max_iterations"] = 3  # type: ignore[attr-defined]
-    chat_client_base.run_responses = [
-        _pte_function_call_response("1", "load_math"),
-        _pte_function_call_response("2", "factorial", '{"n": 5}'),
-        _pte_text_response(),
-    ]
-    response = await chat_client_base.get_response(
-        [Message(role="user", contents=["compute 5!"])],
-        options={"tool_choice": "auto", "tools": [load_math]},
-    )
-    assert exec_counter == 1
-    assert response.messages[-1].text == "done"
-
-
-async def test_add_tools_model_sees_added_tools_in_options(chat_client_base: SupportsChatGetResponse):
-    from agent_framework import FunctionTool
-
-    recorded: list[list[str]] = []
-    client_cls = type(chat_client_base)
-    original = client_cls._get_non_streaming_response
-
-    async def recording(self: Any, *, messages: Any, options: dict[str, Any], **kwargs: Any) -> ChatResponse:
-        tools = options.get("tools") or []
-        recorded.append([t.name for t in tools if isinstance(t, FunctionTool)])
-        return await original(self, messages=messages, options=options, **kwargs)
-
-    @tool(name="load_math", approval_mode="never_require")
-    def load_math(ctx: FunctionInvocationContext) -> str:
-        ctx.add_tools(_pte_factorial)
-        return "loaded"
-
-    chat_client_base.function_invocation_configuration["max_iterations"] = 3  # type: ignore[attr-defined]
-    chat_client_base.run_responses = [
-        _pte_function_call_response("1", "load_math"),
-        _pte_function_call_response("2", "factorial", '{"n": 5}'),
-        _pte_text_response(),
-    ]
-    monkey = pytest.MonkeyPatch()
-    monkey.setattr(client_cls, "_get_non_streaming_response", recording)
-    try:
-        await chat_client_base.get_response(
-            [Message(role="user", contents=["compute 5!"])],
-            options={"tool_choice": "auto", "tools": [load_math]},
-        )
-    finally:
-        monkey.undo()
-
-    assert recorded[0] == ["load_math"]
-    assert "factorial" in recorded[1]
-
-
-async def test_remove_tools_next_iteration(chat_client_base: SupportsChatGetResponse):
-    from agent_framework import FunctionTool
-
-    recorded: list[list[str]] = []
-    client_cls = type(chat_client_base)
-    original = client_cls._get_non_streaming_response
-
-    async def recording(self: Any, *, messages: Any, options: dict[str, Any], **kwargs: Any) -> ChatResponse:
-        tools = options.get("tools") or []
-        recorded.append([t.name for t in tools if isinstance(t, FunctionTool)])
-        return await original(self, messages=messages, options=options, **kwargs)
-
-    @tool(name="get_weather", approval_mode="never_require")
-    def get_weather(location: str) -> str:
-        return "sunny"
-
-    @tool(name="drop_weather", approval_mode="never_require")
-    def drop_weather(ctx: FunctionInvocationContext) -> str:
-        ctx.remove_tools("get_weather")
-        return "removed"
-
-    chat_client_base.function_invocation_configuration["max_iterations"] = 3  # type: ignore[attr-defined]
-    chat_client_base.run_responses = [
-        _pte_function_call_response("1", "drop_weather"),
-        _pte_text_response(),
-    ]
-    monkey = pytest.MonkeyPatch()
-    monkey.setattr(client_cls, "_get_non_streaming_response", recording)
-    try:
-        await chat_client_base.get_response(
-            [Message(role="user", contents=["hi"])],
-            options={"tool_choice": "auto", "tools": [get_weather, drop_weather]},
-        )
-    finally:
-        monkey.undo()
-
-    assert set(recorded[0]) == {"get_weather", "drop_weather"}
-    assert "get_weather" not in recorded[1]
-
-
-async def test_add_tools_does_not_mutate_caller_tools_list(chat_client_base: SupportsChatGetResponse):
-    @tool(name="load_math", approval_mode="never_require")
-    def load_math(ctx: FunctionInvocationContext) -> str:
-        ctx.add_tools(_pte_factorial)
-        return "loaded"
-
-    original_tools: list[Any] = [load_math]
-    chat_client_base.function_invocation_configuration["max_iterations"] = 3  # type: ignore[attr-defined]
-    chat_client_base.run_responses = [
-        _pte_function_call_response("1", "load_math"),
-        _pte_text_response(),
-    ]
-    await chat_client_base.get_response(
-        [Message(role="user", contents=["hi"])],
-        options={"tool_choice": "auto", "tools": original_tools},
-    )
-    assert original_tools == [load_math]
-
-
-async def test_add_tools_persists_across_iterations(chat_client_base: SupportsChatGetResponse):
-    from agent_framework import FunctionTool
-
-    recorded: list[list[str]] = []
-    client_cls = type(chat_client_base)
-    original = client_cls._get_non_streaming_response
-
-    async def recording(self: Any, *, messages: Any, options: dict[str, Any], **kwargs: Any) -> ChatResponse:
-        tools = options.get("tools") or []
-        recorded.append([t.name for t in tools if isinstance(t, FunctionTool)])
-        return await original(self, messages=messages, options=options, **kwargs)
-
-    @tool(name="load_math", approval_mode="never_require")
-    def load_math(ctx: FunctionInvocationContext) -> str:
-        ctx.add_tools(_pte_factorial)
-        return "loaded"
-
-    chat_client_base.function_invocation_configuration["max_iterations"] = 4  # type: ignore[attr-defined]
-    chat_client_base.run_responses = [
-        _pte_function_call_response("1", "load_math"),
-        _pte_function_call_response("2", "factorial", '{"n": 5}'),
-        _pte_function_call_response("3", "factorial", '{"n": 3}'),
-        _pte_text_response(),
-    ]
-    monkey = pytest.MonkeyPatch()
-    monkey.setattr(client_cls, "_get_non_streaming_response", recording)
-    try:
-        await chat_client_base.get_response(
-            [Message(role="user", contents=["hi"])],
-            options={"tool_choice": "auto", "tools": [load_math]},
-        )
-    finally:
-        monkey.undo()
-
-    assert "factorial" in recorded[1]
-    assert "factorial" in recorded[2]
-
-
-async def test_add_tools_through_function_middleware(chat_client_base: SupportsChatGetResponse):
-    exec_counter = 0
-
-    class PassthroughMiddleware(FunctionMiddleware):
-        async def process(self, context: FunctionInvocationContext, call_next: Any) -> None:
-            await call_next()
-
-    @tool(name="factorial", approval_mode="never_require")
-    def factorial(n: int) -> int:
-        nonlocal exec_counter
-        exec_counter += 1
-        return 120
-
-    @tool(name="load_math", approval_mode="never_require")
-    def load_math(ctx: FunctionInvocationContext) -> str:
-        ctx.add_tools(factorial)
-        return "loaded"
-
-    chat_client_base.function_invocation_configuration["max_iterations"] = 3  # type: ignore[attr-defined]
-    chat_client_base.run_responses = [
-        _pte_function_call_response("1", "load_math"),
-        _pte_function_call_response("2", "factorial", '{"n": 5}'),
-        _pte_text_response(),
-    ]
-    await chat_client_base.get_response(
-        [Message(role="user", contents=["hi"])],
-        options={"tool_choice": "auto", "tools": [load_math]},
-        middleware=[PassthroughMiddleware()],
-    )
-    assert exec_counter == 1
-
-
-async def test_add_tools_with_approval_required_tool(chat_client_base: SupportsChatGetResponse):
-    @tool(name="secure_tool", approval_mode="always_require")
-    def secure_tool(value: str) -> str:
-        return f"secure: {value}"
-
-    @tool(name="load_secure", approval_mode="never_require")
-    def load_secure(ctx: FunctionInvocationContext) -> str:
-        ctx.add_tools(secure_tool)
-        return "loaded"
-
-    chat_client_base.function_invocation_configuration["max_iterations"] = 3  # type: ignore[attr-defined]
-    chat_client_base.run_responses = [
-        _pte_function_call_response("1", "load_secure"),
-        _pte_function_call_response("2", "secure_tool", '{"value": "x"}'),
-        _pte_text_response(),
-    ]
-    response = await chat_client_base.get_response(
-        [Message(role="user", contents=["hi"])],
-        options={"tool_choice": "auto", "tools": [load_secure]},
-    )
-    assert any(item.type == "function_approval_request" for msg in response.messages for item in msg.contents)
-
-
-async def test_add_tools_accepts_plain_callable(chat_client_base: SupportsChatGetResponse):
-    exec_counter = 0
-
-    def plain_factorial(n: int) -> int:
-        """Compute factorial."""
-        nonlocal exec_counter
-        exec_counter += 1
-        return 120
-
-    @tool(name="load_math", approval_mode="never_require")
-    def load_math(ctx: FunctionInvocationContext) -> str:
-        ctx.add_tools(plain_factorial)
-        return "loaded"
-
-    chat_client_base.function_invocation_configuration["max_iterations"] = 3  # type: ignore[attr-defined]
-    chat_client_base.run_responses = [
-        _pte_function_call_response("1", "load_math"),
-        _pte_function_call_response("2", "plain_factorial", '{"n": 5}'),
-        _pte_text_response(),
-    ]
-    await chat_client_base.get_response(
-        [Message(role="user", contents=["hi"])],
-        options={"tool_choice": "auto", "tools": [load_math]},
-    )
-    assert exec_counter == 1
-
-
-async def test_add_tools_streaming(chat_client_base: SupportsChatGetResponse):
-    exec_counter = 0
-
-    @tool(name="factorial", approval_mode="never_require")
-    def factorial(n: int) -> int:
-        nonlocal exec_counter
-        exec_counter += 1
-        return 120
-
-    @tool(name="load_math", approval_mode="never_require")
-    def load_math(ctx: FunctionInvocationContext) -> str:
-        ctx.add_tools(factorial)
-        return "loaded"
-
-    chat_client_base.function_invocation_configuration["max_iterations"] = 3  # type: ignore[attr-defined]
-    chat_client_base.streaming_responses = [
-        [
-            ChatResponseUpdate(
-                contents=[Content.from_function_call(call_id="1", name="load_math", arguments="{}")],
-                role="assistant",
-            )
-        ],
-        [
-            ChatResponseUpdate(
-                contents=[Content.from_function_call(call_id="2", name="factorial", arguments='{"n": 5}')],
-                role="assistant",
-            )
-        ],
-        [ChatResponseUpdate(contents=[Content.from_text("done")], role="assistant", finish_reason="stop")],
-    ]
-    async for _ in chat_client_base.get_response(
-        [Message(role="user", contents=["hi"])],
-        stream=True,
-        options={"tool_choice": "auto", "tools": [load_math]},
-    ):
-        pass
-    assert exec_counter == 1
-
-
-def test_add_tools_duplicate_same_object_is_noop():
-    @tool(name="dup", approval_mode="never_require")
-    def dup(x: int) -> int:
-        return x
-
-    ctx = FunctionInvocationContext(function=dup, arguments={}, tools=[dup])
-    ctx.add_tools(dup)
-    assert ctx.tools is not None
-    assert len(ctx.tools) == 1
-
-
-def test_add_tools_duplicate_name_different_object_raises():
-    @tool(name="dup", approval_mode="never_require")
-    def dup_a(x: int) -> int:
-        return x
-
-    @tool(name="dup", approval_mode="never_require")
-    def dup_b(x: int) -> int:
-        return x
-
-    ctx = FunctionInvocationContext(function=dup_a, arguments={}, tools=[dup_a])
-    with pytest.raises(ValueError):
-        ctx.add_tools(dup_b)
-
-
-def test_add_tools_batch_with_duplicate_is_atomic():
-    """A duplicate-name clash partway through a batch must leave the live list unchanged."""
-
-    @tool(name="existing", approval_mode="never_require")
-    def existing(x: int) -> int:
-        return x
-
-    @tool(name="fresh", approval_mode="never_require")
-    def fresh(x: int) -> int:
-        return x
-
-    @tool(name="existing", approval_mode="never_require")
-    def clashing(x: int) -> int:
-        return x
-
-    ctx = FunctionInvocationContext(function=existing, arguments={}, tools=[existing])
-    with pytest.raises(ValueError):
-        ctx.add_tools([fresh, clashing])
-    assert ctx.tools is not None
-    # The valid "fresh" tool must not have been committed before the clash raised.
-    assert ctx.tools == [existing]
-
-
-def test_remove_tools_by_name_and_object():
-    @tool(name="a", approval_mode="never_require")
-    def a(x: int) -> int:
-        return x
-
-    @tool(name="b", approval_mode="never_require")
-    def b(x: int) -> int:
-        return x
-
-    ctx = FunctionInvocationContext(function=a, arguments={}, tools=[a, b])
-    ctx.remove_tools("a")
-    assert ctx.tools is not None
-    assert [t.name for t in ctx.tools] == ["b"]
-    ctx.remove_tools(b)
-    assert ctx.tools == []
-
-
-def test_remove_tools_unknown_name_is_noop():
-    @tool(name="a", approval_mode="never_require")
-    def a(x: int) -> int:
-        return x
-
-    ctx = FunctionInvocationContext(function=a, arguments={}, tools=[a])
-    ctx.remove_tools("nonexistent")
-    assert ctx.tools is not None
-    assert [t.name for t in ctx.tools] == ["a"]
-
-
-def test_progressive_tools_helpers_raise_without_live_tools():
-    @tool(name="a", approval_mode="never_require")
-    def a(x: int) -> int:
-        return x
-
-    ctx = FunctionInvocationContext(function=a, arguments={})
-    assert ctx.tools is None
-    with pytest.raises(RuntimeError):
-        ctx.add_tools(a)
-    with pytest.raises(RuntimeError):
-        ctx.remove_tools("a")
-
-
-# endregion
@@ -1,667 +0,0 @@
-# Copyright (c) Microsoft. All rights reserved.
-
-"""Tests for MCP-based skills (MCPSkillsSource, MCPSkill, MCPSkillResource)."""
-
-from __future__ import annotations
-
-import base64
-import json
-from unittest.mock import AsyncMock
-
-import pytest
-from mcp.shared.exceptions import McpError
-from mcp.types import (
-    BlobResourceContents,
-    ErrorData,
-    ReadResourceResult,
-    TextResourceContents,
-)
-from pydantic import AnyUrl
-
-from agent_framework import MCPSkill, MCPSkillResource, MCPSkillsSource
-from agent_framework._skills import _parse_mcp_skill_index
-
-# ---------------------------------------------------------------------------
-# Fixtures & helpers
-# ---------------------------------------------------------------------------
-
-SAMPLE_SKILL_MD = """\
---
-name: unit-converter
-description: Convert between common units.
---
-# Unit Converter
-
-Body content here.
-"""
-
-SAMPLE_SKILL_INDEX = json.dumps(
-    {
-        "$schema": "https://schemas.agentskills.io/discovery/0.2.0/schema.json",
-        "skills": [
-            {
-                "name": "unit-converter",
-                "type": "skill-md",
-                "description": "Convert between common units.",
-                "url": "skill://unit-converter/SKILL.md",
-            }
-        ],
-    }
-)
-
-
-def _make_text_result(text: str, uri: str = "skill://test") -> ReadResourceResult:
-    """Create a ReadResourceResult with a single TextResourceContents."""
-    return ReadResourceResult(
-        contents=[TextResourceContents(uri=AnyUrl(uri), text=text, mimeType="text/markdown")]
-    )
-
-
-def _make_blob_result(
-    data: bytes,
-    uri: str = "skill://test",
-    mime_type: str = "application/octet-stream",
-) -> ReadResourceResult:
-    """Create a ReadResourceResult with a single BlobResourceContents."""
-    return ReadResourceResult(
-        contents=[BlobResourceContents(uri=AnyUrl(uri), blob=base64.b64encode(data).decode(), mimeType=mime_type)]
-    )
-
-
-def _make_empty_result() -> ReadResourceResult:
-    """Create a ReadResourceResult with no contents."""
-    return ReadResourceResult(contents=[])
-
-
-def _make_client(**read_resource_responses: ReadResourceResult) -> AsyncMock:
-    """Create a mock ClientSession whose read_resource returns different results per URI.
-
-    Args:
-        **read_resource_responses: Mapping of URI string to ReadResourceResult.
-            Any URI not in this mapping raises McpError with the MCP-spec
-            "Resource not found" code (-32002).
-    """
-    client = AsyncMock()
-
-    async def _read_resource(uri: AnyUrl) -> ReadResourceResult:
-        uri_str = str(uri)
-        if uri_str in read_resource_responses:
-            return read_resource_responses[uri_str]
-        raise McpError(error=ErrorData(code=-32002, message=f"Resource not found: {uri_str}"))
-
-    client.read_resource = AsyncMock(side_effect=_read_resource)
-    return client
-
-
-# ---------------------------------------------------------------------------
-# _parse_mcp_skill_index tests
-# ---------------------------------------------------------------------------
-
-
-class TestParseMCPSkillIndex:
-    """Tests for the _parse_mcp_skill_index helper."""
-
-    def test_parses_valid_index(self) -> None:
-        index = _parse_mcp_skill_index(SAMPLE_SKILL_INDEX)
-        assert index.schema == "https://schemas.agentskills.io/discovery/0.2.0/schema.json"
-        assert len(index.skills) == 1
-        assert index.skills[0].name == "unit-converter"
-        assert index.skills[0].type == "skill-md"
-        assert index.skills[0].url == "skill://unit-converter/SKILL.md"
-
-    def test_parses_empty_skills_array(self) -> None:
-        index = _parse_mcp_skill_index('{"$schema": "test", "skills": []}')
-        assert index.skills == []
-
-    def test_parses_missing_skills_key(self) -> None:
-        index = _parse_mcp_skill_index('{"$schema": "test"}')
-        assert index.skills == []
-
-    def test_raises_on_non_object(self) -> None:
-        with pytest.raises(ValueError, match="must be a JSON object"):
-            _parse_mcp_skill_index("[]")
-
-    def test_raises_on_invalid_json(self) -> None:
-        with pytest.raises(json.JSONDecodeError):
-            _parse_mcp_skill_index("not json")
-
-    def test_skips_non_dict_entries(self) -> None:
-        index = _parse_mcp_skill_index('{"skills": ["not-a-dict", {"name": "ok", "type": "skill-md"}]}')
-        assert len(index.skills) == 1
-        assert index.skills[0].name == "ok"
-
-
-# ---------------------------------------------------------------------------
-# MCPSkillResource tests
-# ---------------------------------------------------------------------------
-
-
-class TestMCPSkillResource:
-    """Tests for MCPSkillResource."""
-
-    @pytest.mark.asyncio
-    async def test_read_text_content(self) -> None:
-        result = _make_text_result("hello world")
-        resource = MCPSkillResource(name="test.md", result=result)
-        content = await resource.read()
-        assert content == "hello world"
-
-    @pytest.mark.asyncio
-    async def test_read_binary_content(self) -> None:
-        data = bytes([0x01, 0x02, 0x03, 0x04])
-        result = _make_blob_result(data)
-        resource = MCPSkillResource(name="icon.bin", result=result)
-        content = await resource.read()
-        assert content == data
-
-    @pytest.mark.asyncio
-    async def test_read_empty_returns_none(self) -> None:
-        result = _make_empty_result()
-        resource = MCPSkillResource(name="empty", result=result)
-        content = await resource.read()
-        assert content is None
-
-    @pytest.mark.asyncio
-    async def test_read_multiple_text_contents_joined(self) -> None:
-        result = ReadResourceResult(
-            contents=[
-                TextResourceContents(uri=AnyUrl("skill://a"), text="line1", mimeType="text/plain"),
-                TextResourceContents(uri=AnyUrl("skill://b"), text="line2", mimeType="text/plain"),
-            ]
-        )
-        resource = MCPSkillResource(name="multi", result=result)
-        content = await resource.read()
-        assert content == "line1\nline2"
-
-    @pytest.mark.asyncio
-    async def test_binary_takes_precedence_over_text(self) -> None:
-        data = b"\xff\xfe"
-        result = ReadResourceResult(
-            contents=[
-                TextResourceContents(uri=AnyUrl("skill://a"), text="text", mimeType="text/plain"),
-                BlobResourceContents(
-                    uri=AnyUrl("skill://b"),
-                    blob=base64.b64encode(data).decode(),
-                    mimeType="application/octet-stream",
-                ),
-            ]
-        )
-        resource = MCPSkillResource(name="mixed", result=result)
-        content = await resource.read()
-        # The implementation iterates all contents checking for BlobResourceContents
-        # first, so when both text and binary are present, binary is returned.
-        assert content == data
-
-
-# ---------------------------------------------------------------------------
-# MCPSkill tests
-# ---------------------------------------------------------------------------
-
-
-class TestMCPSkill:
-    """Tests for MCPSkill."""
-
-    @pytest.mark.asyncio
-    async def test_get_content_fetches_and_caches(self) -> None:
-        client = _make_client(**{"skill://unit-converter/SKILL.md": _make_text_result(SAMPLE_SKILL_MD)})
-        from agent_framework import SkillFrontmatter
-
-        fm = SkillFrontmatter(name="unit-converter", description="Convert between common units.")
-        skill = MCPSkill(frontmatter=fm, skill_md_uri="skill://unit-converter/SKILL.md", client=client)
-
-        content1 = await skill.get_content()
-        content2 = await skill.get_content()
-
-        assert "Body content here." in content1
-        assert content1 == content2
-        # Only one MCP call should be made (cached)
-        assert client.read_resource.call_count == 1
-
-    @pytest.mark.asyncio
-    async def test_get_content_raises_on_empty(self) -> None:
-        client = _make_client(**{"skill://empty/SKILL.md": _make_empty_result()})
-        from agent_framework import SkillFrontmatter
-
-        fm = SkillFrontmatter(name="empty-skill", description="Empty skill.")
-        skill = MCPSkill(frontmatter=fm, skill_md_uri="skill://empty/SKILL.md", client=client)
-
-        with pytest.raises(ValueError, match="no text content"):
-            await skill.get_content()
-
-    @pytest.mark.asyncio
-    async def test_get_resource_text(self) -> None:
-        client = _make_client(
-            **{
-                "skill://unit-converter/SKILL.md": _make_text_result(SAMPLE_SKILL_MD),
-                "skill://unit-converter/references/checklist.md": _make_text_result("- check thing 1\n- check thing 2"),
-            }
-        )
-        from agent_framework import SkillFrontmatter
-
-        fm = SkillFrontmatter(name="unit-converter", description="Convert between common units.")
-        skill = MCPSkill(frontmatter=fm, skill_md_uri="skill://unit-converter/SKILL.md", client=client)
-
-        resource = await skill.get_resource("references/checklist.md")
-        assert resource is not None
-        content = await resource.read()
-        assert content == "- check thing 1\n- check thing 2"
-
-    @pytest.mark.asyncio
-    async def test_get_resource_binary(self) -> None:
-        data = bytes([0x01, 0x02, 0x03, 0x04])
-        client = _make_client(
-            **{
-                "skill://unit-converter/SKILL.md": _make_text_result(SAMPLE_SKILL_MD),
-                "skill://unit-converter/assets/icon.bin": _make_blob_result(data),
-            }
-        )
-        from agent_framework import SkillFrontmatter
-
-        fm = SkillFrontmatter(name="unit-converter", description="Convert between common units.")
-        skill = MCPSkill(frontmatter=fm, skill_md_uri="skill://unit-converter/SKILL.md", client=client)
-
-        resource = await skill.get_resource("assets/icon.bin")
-        assert resource is not None
-        content = await resource.read()
-        assert content == data
-
-    @pytest.mark.asyncio
-    async def test_get_resource_unknown_returns_none(self) -> None:
-        client = _make_client(**{"skill://unit-converter/SKILL.md": _make_text_result(SAMPLE_SKILL_MD)})
-        from agent_framework import SkillFrontmatter
-
-        fm = SkillFrontmatter(name="unit-converter", description="Convert between common units.")
-        skill = MCPSkill(frontmatter=fm, skill_md_uri="skill://unit-converter/SKILL.md", client=client)
-
-        resource = await skill.get_resource("references/does-not-exist.md")
-        assert resource is None
-
-    @pytest.mark.asyncio
-    @pytest.mark.parametrize(
-        "name",
-        [
-            "../escape.md",
-            "references/../../escape.md",
-            "..",
-            "..\\escape.md",
-            "/etc/passwd",
-            "http://attacker.example.com/payload",
-        ],
-    )
-    async def test_get_resource_path_traversal_returns_none(self, name: str) -> None:
-        # Register a permissive mock that would happily return content for any URI,
-        # so the test fails unless the client-side validation rejects the name
-        # before issuing the read.
-        client = AsyncMock()
-        client.read_resource = AsyncMock(return_value=_make_text_result("should never be returned"))
-
-        from agent_framework import SkillFrontmatter
-
-        fm = SkillFrontmatter(name="unit-converter", description="Convert between common units.")
-        skill = MCPSkill(frontmatter=fm, skill_md_uri="skill://unit-converter/SKILL.md", client=client)
-
-        resource = await skill.get_resource(name)
-        assert resource is None
-        client.read_resource.assert_not_called()
-
-    @pytest.mark.asyncio
-    async def test_get_resource_empty_name_returns_none(self) -> None:
-        client = _make_client()
-        from agent_framework import SkillFrontmatter
-
-        fm = SkillFrontmatter(name="test-skill", description="Test.")
-        skill = MCPSkill(frontmatter=fm, skill_md_uri="skill://test/SKILL.md", client=client)
-
-        assert await skill.get_resource("") is None
-        assert await skill.get_resource("   ") is None
-
-    @pytest.mark.asyncio
-    async def test_get_script_returns_none(self) -> None:
-        client = _make_client()
-        from agent_framework import SkillFrontmatter
-
-        fm = SkillFrontmatter(name="test-skill", description="Test.")
-        skill = MCPSkill(frontmatter=fm, skill_md_uri="skill://test/SKILL.md", client=client)
-
-        assert await skill.get_script("anything") is None
-
-    def test_compute_skill_root_uri_strips_suffix(self) -> None:
-        assert MCPSkill._compute_skill_root_uri("skill://unit-converter/SKILL.md") == "skill://unit-converter/"
-
-    def test_compute_skill_root_uri_trailing_slash(self) -> None:
-        assert MCPSkill._compute_skill_root_uri("skill://unit-converter/") == "skill://unit-converter/"
-
-    def test_compute_skill_root_uri_no_suffix_adds_slash(self) -> None:
-        assert MCPSkill._compute_skill_root_uri("skill://unit-converter") == "skill://unit-converter/"
-
-
-# ---------------------------------------------------------------------------
-# MCPSkillsSource tests
-# ---------------------------------------------------------------------------
-
-
-class TestMCPSkillsSource:
-    """Tests for MCPSkillsSource."""
-
-    @pytest.mark.asyncio
-    async def test_index_based_discovery_returns_skill(self) -> None:
-        client = _make_client(
-            **{
-                "skill://index.json": _make_text_result(SAMPLE_SKILL_INDEX, uri="skill://index.json"),
-                "skill://unit-converter/SKILL.md": _make_text_result(SAMPLE_SKILL_MD),
-            }
-        )
-        source = MCPSkillsSource(client=client)
-        skills = await source.get_skills()
-
-        assert len(skills) == 1
-        assert skills[0].frontmatter.name == "unit-converter"
-        assert skills[0].frontmatter.description == "Convert between common units."
-
-        # Content is fetched on demand, not during discovery
-        content = await skills[0].get_content()
-        assert "Body content here." in content
-
-    @pytest.mark.asyncio
-    async def test_no_index_returns_empty(self) -> None:
-        client = _make_client()  # No resources at all
-        source = MCPSkillsSource(client=client)
-        skills = await source.get_skills()
-        assert skills == []
-
-    @pytest.mark.asyncio
-    async def test_does_not_read_skill_md_during_discovery(self) -> None:
-        # Index points to a skill, but SKILL.md is not registered on the server.
-        # Discovery should succeed because it only reads the index.
-        client = _make_client(
-            **{"skill://index.json": _make_text_result(SAMPLE_SKILL_INDEX, uri="skill://index.json")}
-        )
-        source = MCPSkillsSource(client=client)
-        skills = await source.get_skills()
-
-        assert len(skills) == 1
-        assert skills[0].frontmatter.name == "unit-converter"
-
-    @pytest.mark.asyncio
-    async def test_invalid_name_is_skipped(self) -> None:
-        index_json = json.dumps(
-            {
-                "$schema": "https://schemas.agentskills.io/discovery/0.2.0/schema.json",
-                "skills": [
-                    {
-                        "name": "UnitConverter",  # Invalid: uppercase
-                        "type": "skill-md",
-                        "description": "Convert between common units.",
-                        "url": "skill://UnitConverter/SKILL.md",
-                    }
-                ],
-            }
-        )
-        client = _make_client(**{"skill://index.json": _make_text_result(index_json, uri="skill://index.json")})
-        source = MCPSkillsSource(client=client)
-        skills = await source.get_skills()
-        assert skills == []
-
-    @pytest.mark.asyncio
-    async def test_missing_required_fields_is_skipped(self) -> None:
-        index_json = json.dumps(
-            {
-                "$schema": "https://schemas.agentskills.io/discovery/0.2.0/schema.json",
-                "skills": [
-                    {
-                        "name": "unit-converter",
-                        "type": "skill-md",
-                        # Missing description and url
-                    }
-                ],
-            }
-        )
-        client = _make_client(**{"skill://index.json": _make_text_result(index_json, uri="skill://index.json")})
-        source = MCPSkillsSource(client=client)
-        skills = await source.get_skills()
-        assert skills == []
-
-    @pytest.mark.asyncio
-    async def test_unsupported_type_is_skipped(self) -> None:
-        index_json = json.dumps(
-            {
-                "$schema": "https://schemas.agentskills.io/discovery/0.2.0/schema.json",
-                "skills": [
-                    {
-                        "name": "some-skill",
-                        "type": "archive",
-                        "description": "Packaged skill.",
-                        "url": "skill://some-skill.tar.gz",
-                    }
-                ],
-            }
-        )
-        client = _make_client(**{"skill://index.json": _make_text_result(index_json, uri="skill://index.json")})
-        source = MCPSkillsSource(client=client)
-        skills = await source.get_skills()
-        assert skills == []
-
-    @pytest.mark.asyncio
-    async def test_template_type_is_skipped(self) -> None:
-        index_json = json.dumps(
-            {
-                "$schema": "https://schemas.agentskills.io/discovery/0.2.0/schema.json",
-                "skills": [
-                    {
-                        "type": "mcp-resource-template",
-                        "description": "Per-product documentation skill",
-                        "url": "skill://docs/{product}/SKILL.md",
-                    }
-                ],
-            }
-        )
-        client = _make_client(**{"skill://index.json": _make_text_result(index_json, uri="skill://index.json")})
-        source = MCPSkillsSource(client=client)
-        skills = await source.get_skills()
-        assert skills == []
-
-    @pytest.mark.asyncio
-    async def test_empty_index_returns_empty(self) -> None:
-        client = _make_client(
-            **{"skill://index.json": _make_text_result('{"skills": []}', uri="skill://index.json")}
-        )
-        source = MCPSkillsSource(client=client)
-        skills = await source.get_skills()
-        assert skills == []
-
-    @pytest.mark.asyncio
-    async def test_malformed_index_json_returns_empty(self) -> None:
-        client = _make_client(
-            **{"skill://index.json": _make_text_result("not valid json", uri="skill://index.json")}
-        )
-        source = MCPSkillsSource(client=client)
-        skills = await source.get_skills()
-        assert skills == []
-
-    @pytest.mark.asyncio
-    async def test_sibling_text_resource(self) -> None:
-        client = _make_client(
-            **{
-                "skill://index.json": _make_text_result(SAMPLE_SKILL_INDEX, uri="skill://index.json"),
-                "skill://unit-converter/SKILL.md": _make_text_result(SAMPLE_SKILL_MD),
-                "skill://unit-converter/references/checklist.md": _make_text_result("- check thing 1\n- check thing 2"),
-            }
-        )
-        source = MCPSkillsSource(client=client)
-        skill = (await source.get_skills())[0]
-        resource = await skill.get_resource("references/checklist.md")
-        assert resource is not None
-        content = await resource.read()
-        assert content == "- check thing 1\n- check thing 2"
-
-    @pytest.mark.asyncio
-    async def test_sibling_binary_resource(self) -> None:
-        data = bytes([0x01, 0x02, 0x03, 0x04])
-        client = _make_client(
-            **{
-                "skill://index.json": _make_text_result(SAMPLE_SKILL_INDEX, uri="skill://index.json"),
-                "skill://unit-converter/SKILL.md": _make_text_result(SAMPLE_SKILL_MD),
-                "skill://unit-converter/assets/icon.bin": _make_blob_result(data),
-            }
-        )
-        source = MCPSkillsSource(client=client)
-        skill = (await source.get_skills())[0]
-        resource = await skill.get_resource("assets/icon.bin")
-        assert resource is not None
-        content = await resource.read()
-        assert content == data
-
-
-# ---------------------------------------------------------------------------
-# McpError code branching tests
-# ---------------------------------------------------------------------------
-
-
-class TestMCPSkillsSourceErrorCodeBranching:
-    """Tests that MCPSkillsSource and MCPSkill branch on McpError.error.code.
-
-    Only "not found" codes (RESOURCE_NOT_FOUND -32002, METHOD_NOT_FOUND -32601)
-    should be silently swallowed as "no skills available." Other McpError codes
-    and non-McpError exceptions must propagate so that auth failures, server
-    crashes, and connection drops are visible.
-    """
-
-    @pytest.mark.asyncio
-    async def test_index_method_not_found_returns_empty(self) -> None:
-        """METHOD_NOT_FOUND (-32601) -> server doesn't support resources/read."""
-        client = AsyncMock()
-        client.read_resource = AsyncMock(side_effect=McpError(error=ErrorData(code=-32601, message="Method not found")))
-        source = MCPSkillsSource(client=client)
-        skills = await source.get_skills()
-        assert skills == []
-
-    @pytest.mark.asyncio
-    async def test_index_resource_not_found_returns_empty(self) -> None:
-        """MCP-spec "Resource not found" (-32002) -> server has no index."""
-        client = AsyncMock()
-        client.read_resource = AsyncMock(
-            side_effect=McpError(error=ErrorData(code=-32002, message="Resource not found"))
-        )
-        source = MCPSkillsSource(client=client)
-        skills = await source.get_skills()
-        assert skills == []
-
-    @pytest.mark.asyncio
-    async def test_index_invalid_params_propagates(self) -> None:
-        """INVALID_PARAMS (-32602) is a real bug, must propagate (not "not found")."""
-        client = AsyncMock()
-        client.read_resource = AsyncMock(side_effect=McpError(error=ErrorData(code=-32602, message="Invalid params")))
-        source = MCPSkillsSource(client=client)
-        with pytest.raises(McpError):
-            await source.get_skills()
-
-    @pytest.mark.asyncio
-    async def test_index_internal_error_propagates(self) -> None:
-        """INTERNAL_ERROR (-32603) must propagate, not silently return empty."""
-        client = AsyncMock()
-        client.read_resource = AsyncMock(side_effect=McpError(error=ErrorData(code=-32603, message="Internal error")))
-        source = MCPSkillsSource(client=client)
-        with pytest.raises(McpError):
-            await source.get_skills()
-
-    @pytest.mark.asyncio
-    async def test_index_connection_closed_propagates(self) -> None:
-        """CONNECTION_CLOSED (-32000) must propagate."""
-        client = AsyncMock()
-        client.read_resource = AsyncMock(
-            side_effect=McpError(error=ErrorData(code=-32000, message="Connection closed"))
-        )
-        source = MCPSkillsSource(client=client)
-        with pytest.raises(McpError):
-            await source.get_skills()
-
-    @pytest.mark.asyncio
-    async def test_index_generic_error_code_propagates(self) -> None:
-        """Generic handler error (code 0) must propagate."""
-        client = AsyncMock()
-        client.read_resource = AsyncMock(side_effect=McpError(error=ErrorData(code=0, message="Some handler error")))
-        source = MCPSkillsSource(client=client)
-        with pytest.raises(McpError):
-            await source.get_skills()
-
-    @pytest.mark.asyncio
-    async def test_index_non_mcp_error_propagates(self) -> None:
-        """Non-McpError exceptions (connection drop, timeout) must propagate."""
-        client = AsyncMock()
-        client.read_resource = AsyncMock(side_effect=ConnectionError("connection lost"))
-        source = MCPSkillsSource(client=client)
-        with pytest.raises(ConnectionError):
-            await source.get_skills()
-
-    @pytest.mark.asyncio
-    async def test_get_resource_internal_error_propagates(self) -> None:
-        """McpError with INTERNAL_ERROR on get_resource must propagate."""
-        from agent_framework import SkillFrontmatter
-
-        client = AsyncMock()
-        client.read_resource = AsyncMock(side_effect=McpError(error=ErrorData(code=-32603, message="Server crashed")))
-        fm = SkillFrontmatter(name="test-skill", description="Test.")
-        skill = MCPSkill(frontmatter=fm, skill_md_uri="skill://test/SKILL.md", client=client)
-        with pytest.raises(McpError):
-            await skill.get_resource("references/file.md")
-
-    @pytest.mark.asyncio
-    async def test_get_resource_not_found_returns_none(self) -> None:
-        """McpError with RESOURCE_NOT_FOUND (-32002) on get_resource returns None."""
-        from agent_framework import SkillFrontmatter
-
-        client = AsyncMock()
-        client.read_resource = AsyncMock(
-            side_effect=McpError(error=ErrorData(code=-32002, message="Resource not found"))
-        )
-        fm = SkillFrontmatter(name="test-skill", description="Test.")
-        skill = MCPSkill(frontmatter=fm, skill_md_uri="skill://test/SKILL.md", client=client)
-        result = await skill.get_resource("references/file.md")
-        assert result is None
-
-    @pytest.mark.asyncio
-    async def test_get_resource_connection_error_propagates(self) -> None:
-        """A plain ConnectionError on get_resource must propagate, not return None."""
-        from agent_framework import SkillFrontmatter
-
-        client = AsyncMock()
-        client.read_resource = AsyncMock(side_effect=ConnectionError("connection lost"))
-        fm = SkillFrontmatter(name="test-skill", description="Test.")
-        skill = MCPSkill(frontmatter=fm, skill_md_uri="skill://test/SKILL.md", client=client)
-        with pytest.raises(ConnectionError):
-            await skill.get_resource("references/file.md")
-
-    @pytest.mark.asyncio
-    async def test_get_resource_timeout_error_propagates(self) -> None:
-        """A TimeoutError on get_resource must propagate, not return None."""
-        from agent_framework import SkillFrontmatter
-
-        client = AsyncMock()
-        client.read_resource = AsyncMock(side_effect=TimeoutError("read timed out"))
-        fm = SkillFrontmatter(name="test-skill", description="Test.")
-        skill = MCPSkill(frontmatter=fm, skill_md_uri="skill://test/SKILL.md", client=client)
-        with pytest.raises(TimeoutError):
-            await skill.get_resource("references/file.md")
-
-    @pytest.mark.asyncio
-    async def test_get_resource_generic_mcp_error_propagates(self) -> None:
-        """McpError with a generic code (0) on get_resource must propagate."""
-        from agent_framework import SkillFrontmatter
-
-        client = AsyncMock()
-        client.read_resource = AsyncMock(
-            side_effect=McpError(error=ErrorData(code=0, message="Handler error"))
-        )
-        fm = SkillFrontmatter(name="test-skill", description="Test.")
-        skill = MCPSkill(frontmatter=fm, skill_md_uri="skill://test/SKILL.md", client=client)
-        with pytest.raises(McpError):
-            await skill.get_resource("references/file.md")
-
-    @pytest.mark.asyncio
-    async def test_index_timeout_error_propagates(self) -> None:
-        """A TimeoutError reading skill://index.json must propagate."""
-        client = AsyncMock()
-        client.read_resource = AsyncMock(side_effect=TimeoutError("read timed out"))
-        source = MCPSkillsSource(client=client)
-        with pytest.raises(TimeoutError):
-            await source.get_skills()
@@ -25,6 +25,7 @@ from agent_framework import (
    prepend_agent_framework_to_user_agent,
    tool,
 )
+from agent_framework._serialization import make_json_safe
 from agent_framework.observability import (
    ROLE_EVENT_MAP,
    AgentTelemetryLayer,
@@ -3195,17 +3196,15 @@ def test_capture_messages_with_prepared_request_info_function_call_arguments(spa

    from opentelemetry import trace

-    from agent_framework import WorkflowAgent
-
    @dataclasses.dataclass
    class HandoffRequest:
        target_agent: str
        reason: str

-    arguments = WorkflowAgent.RequestInfoFunctionArgs(
-        request_id="call_dc",
-        data=HandoffRequest(target_agent="helper", reason="overflow"),
-    ).to_dict()
+    arguments = {
+        "request_id": "call_dc",
+        "data": make_json_safe(HandoffRequest(target_agent="helper", reason="overflow")),
+    }
    msg = Message(
        role="assistant",
        contents=[
@@ -1,6 +1,4 @@
 # Copyright (c) Microsoft. All rights reserved.
-import asyncio
-import threading
 from typing import Annotated, Any, Literal, get_args, get_origin
 from unittest.mock import Mock

@@ -1348,45 +1346,6 @@ async def test_invoke_skip_parsing_awaits_async_functions() -> None:
    assert raw == 42


-async def test_invoke_sync_tool_does_not_block_event_loop() -> None:
-    release_tool = threading.Event()
-    tool_thread_ids: list[int] = []
-    event_loop_thread_id = threading.get_ident()
-
-    @tool
-    def wait_for_release() -> str:
-        tool_thread_ids.append(threading.get_ident())
-        return "released" if release_tool.wait(timeout=0.2) else "timed out"
-
-    async def release_soon() -> None:
-        await asyncio.sleep(0.01)
-        release_tool.set()
-
-    tool_task = asyncio.create_task(wait_for_release.invoke(skip_parsing=True))
-    release_task = asyncio.create_task(release_soon())
-
-    assert await asyncio.wait_for(tool_task, timeout=1) == "released"
-    await release_task
-    assert tool_thread_ids
-    assert tool_thread_ids[0] != event_loop_thread_id
-
-
-async def test_invoke_sync_tool_can_stay_on_event_loop() -> None:
-    event_loop_thread_id = threading.get_ident()
-    tool_thread_ids: list[int] = []
-
-    @tool
-    def needs_event_loop() -> str:
-        tool_thread_ids.append(threading.get_ident())
-        asyncio.get_running_loop()
-        return "ok"
-
-    needs_event_loop._invoke_sync_on_event_loop = True
-
-    assert await needs_event_loop.invoke(skip_parsing=True) == "ok"
-    assert tool_thread_ids == [event_loop_thread_id]
-
-
 async def test_invoke_skip_parsing_bypasses_configured_result_parser() -> None:
    """The tool's own result_parser is bypassed when skip_parsing=True is requested."""
    parser_calls: list[Any] = []
@@ -699,3 +699,171 @@ async def test_resolve_executor_kwargs_empty_per_executor_does_not_fallback_to_g
    resolved = {"exec_a": {}, GLOBAL_KWARGS_KEY: {"global_key": "global_val"}}
    result = executor._resolve_executor_kwargs(resolved)  # pyright: ignore[reportPrivateUsage]
    assert result == {}
+
+
+# region Tool approval emission
+
+
+class _ApprovalEmittingAgent(BaseAgent):
+    """Agent that returns a single ``function_approval_request`` Content.
+
+    Used to verify that ``AgentExecutor`` does *not* surface the approval
+    payload via both an ``output`` event and a ``request_info`` event in the
+    same superstep — only the ``request_info`` event must carry it.
+    """
+
+    def __init__(
+        self,
+        *,
+        approval_request_id: str = "apr_1",
+        tool_name: str = "delete_file",
+        tool_arguments: dict[str, Any] | None = None,
+        **kwargs: Any,
+    ):
+        super().__init__(**kwargs)
+        self._approval_request_id = approval_request_id
+        self._tool_name = tool_name
+        self._tool_arguments: dict[str, Any] = tool_arguments or {"path": "/tmp/secret.txt"}
+        self.run_count = 0
+
+    def _build_approval_content(self) -> Content:
+        function_call = Content.from_function_call(
+            call_id=self._approval_request_id,
+            name=self._tool_name,
+            arguments=self._tool_arguments,
+        )
+        return Content.from_function_approval_request(id=self._approval_request_id, function_call=function_call)
+
+    @overload
+    def run(
+        self,
+        messages: AgentRunInputs | None = ...,
+        *,
+        stream: Literal[False] = ...,
+        session: AgentSession | None = ...,
+        **kwargs: Any,
+    ) -> Awaitable[AgentResponse[Any]]: ...
+
+    @overload
+    def run(
+        self,
+        messages: AgentRunInputs | None = ...,
+        *,
+        stream: Literal[True],
+        session: AgentSession | None = ...,
+        **kwargs: Any,
+    ) -> ResponseStream[AgentResponseUpdate, AgentResponse[Any]]: ...
+
+    def run(
+        self,
+        messages: AgentRunInputs | None = None,
+        *,
+        stream: bool = False,
+        session: AgentSession | None = None,
+        **kwargs: Any,
+    ) -> Awaitable[AgentResponse[Any]] | ResponseStream[AgentResponseUpdate, AgentResponse[Any]]:
+        self.run_count += 1
+        approval = self._build_approval_content()
+
+        if stream:
+
+            async def _stream() -> AsyncIterable[AgentResponseUpdate]:
+                yield AgentResponseUpdate(contents=[approval], role="assistant")
+
+            return ResponseStream(_stream(), finalizer=AgentResponse.from_updates)
+
+        async def _run() -> AgentResponse:
+            return AgentResponse(messages=[Message("assistant", [approval])])
+
+        return _run()
+
+
+def _has_approval_payload(event: WorkflowEvent[Any]) -> bool:
+    """Return True if the event's data carries a ``function_approval_request`` content."""
+    data: Any = event.data
+
+    def _contents_of(value: Any) -> list[Content]:
+        if isinstance(value, AgentResponseUpdate):
+            return list(value.contents)
+        if isinstance(value, AgentResponse):
+            return [c for m in value.messages for c in m.contents]
+        if isinstance(value, AgentExecutorResponse):
+            return [c for m in value.agent_response.messages for c in m.contents]
+        if isinstance(value, Message):
+            return list(value.contents)
+        if isinstance(value, Content):
+            return [value]
+        return []
+
+    return any(c.type == "function_approval_request" for c in _contents_of(data))
+
+
+async def test_agent_executor_does_not_double_emit_approval_non_streaming() -> None:
+    """Non-streaming: approval payload must only appear in the ``request_info`` event.
+
+    Regression test for the bug where ``AgentExecutor._run_agent`` first
+    ``yield_output``-ed the response (carrying the approval Content) and then
+    additionally emitted a ``request_info`` event for the same payload.
+    """
+    agent = _ApprovalEmittingAgent(id="approve_agent", name="ApproveAgent", approval_request_id="apr_ns_1")
+    executor = AgentExecutor(agent, id="approve_exec")
+    workflow = WorkflowBuilder(start_executor=executor).build()
+
+    request_info_events: list[WorkflowEvent[Any]] = []
+    output_events: list[WorkflowEvent[Any]] = []
+
+    for event in await workflow.run("please delete it"):
+        if event.type == "request_info":
+            request_info_events.append(event)
+        elif event.type == "output":
+            output_events.append(event)
+
+    assert len(request_info_events) == 1
+    assert _has_approval_payload(request_info_events[0])
+    # The approval payload must not also be surfaced as a workflow output.
+    assert not any(_has_approval_payload(e) for e in output_events)
+    assert agent.run_count == 1
+
+
+async def test_agent_executor_does_not_double_emit_approval_streaming() -> None:
+    """Streaming: per-update approval payload must not be ``yield_output``-ed."""
+    agent = _ApprovalEmittingAgent(id="approve_agent_s", name="ApproveAgentS", approval_request_id="apr_st_1")
+    executor = AgentExecutor(agent, id="approve_exec_s")
+    workflow = WorkflowBuilder(start_executor=executor).build()
+
+    request_info_events: list[WorkflowEvent[Any]] = []
+    output_events: list[WorkflowEvent[Any]] = []
+
+    async for event in workflow.run("please delete it", stream=True):
+        if event.type == "request_info":
+            request_info_events.append(event)
+        elif event.type == "output":
+            output_events.append(event)
+
+    assert len(request_info_events) == 1
+    assert _has_approval_payload(request_info_events[0])
+    assert not any(_has_approval_payload(e) for e in output_events)
+    assert agent.run_count == 1
+
+
+async def test_agent_executor_request_info_uses_user_input_request_id() -> None:
+    """``ctx.request_info`` must register the request under the agent's approval id.
+
+    This makes the workflow's pending-request id round-trip with the
+    ``function_approval_response.id`` the caller echoes back, so
+    ``Workflow._send_responses_internal`` can look it up directly.
+    """
+    agent = _ApprovalEmittingAgent(id="approve_agent_id", name="ApproveAgentId", approval_request_id="apr_match")
+    executor = AgentExecutor(agent, id="approve_exec_id")
+    workflow = WorkflowBuilder(start_executor=executor).build()
+
+    request_info_events: list[WorkflowEvent[Any]] = []
+    async for event in workflow.run("please delete it", stream=True):
+        if event.type == "request_info":
+            request_info_events.append(event)
+
+    assert len(request_info_events) == 1
+    assert request_info_events[0].request_id == "apr_match"
+
+
+# endregion Tool approval emission
@@ -1,6 +1,5 @@
 # Copyright (c) Microsoft. All rights reserved.

-import json
 import uuid
 from collections.abc import Awaitable, Sequence
 from dataclasses import dataclass
@@ -30,6 +29,20 @@ from agent_framework import (
    handler,
    response_handler,
 )
+from agent_framework._workflows._typing_utils import deserialize_type
+
+
+@dataclass
+class HandoffRequest:
+    """Module-level dataclass used by request_info tests.
+
+    Defined at module scope (not nested inside a test method) so
+    ``serialize_type``/``deserialize_type`` can round-trip the request_type via
+    the importable qualified name ``tests.workflow.test_workflow_agent.HandoffRequest``.
+    """
+
+    target_agent: str
+    reason: str


 class SimpleExecutor(Executor):
@@ -240,52 +253,45 @@ class TestWorkflowAgent:
        # Should have received an approval request for the request info
        assert len(updates) > 0

-        approval_update: AgentResponseUpdate | None = None
+        request_update: AgentResponseUpdate | None = None
        for update in updates:
-            if any(content.type == "function_approval_request" for content in update.contents):
-                approval_update = update
+            if any(content.type == "function_call" for content in update.contents):
+                request_update = update
                break

-        assert approval_update is not None, "Should have received a request_info approval request"
+        assert request_update is not None, "Should have received a request_info wrapped in a function_call content"

-        function_call = next(content for content in approval_update.contents if content.type == "function_call")
-        approval_request = next(
-            content for content in approval_update.contents if content.type == "function_approval_request"
-        )
+        request_function_call = next(content for content in request_update.contents if content.type == "function_call")
+        assert request_function_call.call_id is not None

        # Verify the function call has expected structure
-        assert function_call.call_id is not None
-        assert function_call.name == "request_info"
-        assert isinstance(function_call.arguments, dict)
-        assert function_call.arguments.get("request_id") == approval_request.id
+        assert request_function_call.name == WorkflowAgent.REQUEST_INFO_FUNCTION_NAME
+        assert isinstance(request_function_call.arguments, dict)
+        assert request_function_call.arguments.get("request_id") is not None
+        assert request_function_call.arguments.get("request_event") is not None
+        request_event = request_function_call.arguments["request_event"]
+        assert request_event.get("type") == "request_info"
+        assert deserialize_type(request_event.get("response_type")) is str

-        # Approval request should reference the same function call
-        assert approval_request.id is not None
-        assert approval_request.function_call is not None
-        assert approval_request.function_call.call_id == function_call.call_id
-        assert approval_request.function_call.name == function_call.name
+        deserialized_args = WorkflowAgent.RequestInfoFunctionArgs.from_dict(request_function_call.arguments)
+        assert deserialized_args.request_id == request_function_call.call_id
+        assert isinstance(deserialized_args.request_event, WorkflowEvent)
+        assert deserialized_args.request_event.type == "request_info"
+        assert deserialized_args.request_event.data == "Mock request data"
+        assert deserialized_args.request_event.response_type is str

        # Verify the request is tracked in pending_requests
-        assert len(agent.pending_requests) == 1
-        assert function_call.call_id in agent.pending_requests
+        pending_requests = await workflow._runner_context.get_pending_request_info_events()
+        assert len(pending_requests) == 1
+        assert request_function_call.call_id in pending_requests

-        # Now provide an approval response with updated arguments to test continuation
-        response_args = WorkflowAgent.RequestInfoFunctionArgs(
-            request_id=approval_request.id,
-            data="User provided answer",
-        ).to_dict()
-
-        approval_response = Content.from_function_approval_response(
-            approved=True,
-            id=approval_request.id,
-            function_call=Content.from_function_call(
-                call_id=function_call.call_id,
-                name=function_call.name,
-                arguments=response_args,
-            ),
+        # Now provide a function result response with updated arguments to test continuation
+        function_result = Content.from_function_result(
+            call_id=request_function_call.call_id,
+            result="Mock response to request info",
        )

-        response_message = Message(role="user", contents=[approval_response])
+        response_message = Message(role="user", contents=[function_result])

        # Continue the workflow with the response
        continuation_result = await agent.run(response_message)
@@ -294,16 +300,11 @@ class TestWorkflowAgent:
        assert isinstance(continuation_result, AgentResponse)

        # Verify cleanup - pending requests should be cleared after function response handling
-        assert len(agent.pending_requests) == 0
+        pending_requests = await workflow._runner_context.get_pending_request_info_events()
+        assert len(pending_requests) == 0

    def test_request_info_dataclass_arguments_are_serialized_when_content_is_created(self) -> None:
        """Test WorkflowAgent prepares request_info arguments before observability captures messages."""
-
-        @dataclass
-        class HandoffRequest:
-            target_agent: str
-            reason: str
-
        executor = SimpleExecutor(id="executor1", response_text="Response")
        workflow = WorkflowBuilder(start_executor=executor).build()
        agent = WorkflowAgent(workflow=workflow, name="Request Test Agent")
@@ -314,14 +315,367 @@ class TestWorkflowAgent:
            response_type=str,
        )

-        function_call, approval_request = agent._process_request_info_event(event)  # pyright: ignore[reportPrivateUsage]
+        request_function_call = agent._process_request_info_event(event)  # pyright: ignore[reportPrivateUsage]

-        assert function_call.arguments == {
-            "request_id": "request_123",
-            "data": {"target_agent": "helper", "reason": "overflow"},
-        }
-        assert approval_request.function_call is function_call
-        assert json.loads(json.dumps(function_call.arguments)) == function_call.arguments
+        assert request_function_call.call_id == "request_123"
+        assert isinstance(request_function_call.arguments, dict)
+        assert request_function_call.arguments.get("request_event") is not None
+        request_event = request_function_call.arguments["request_event"]
+        assert request_event.get("type") == "request_info"
+        assert request_event.get("request_id") == "request_123"
+        assert request_event.get("source_executor_id") == "executor1"
+        assert deserialize_type(request_event.get("response_type")) is str
+        assert request_event.get("data") == HandoffRequest(target_agent="helper", reason="overflow")
+
+        deserialized_args = WorkflowAgent.RequestInfoFunctionArgs.from_dict(request_function_call.arguments)
+        assert deserialized_args.request_id == "request_123"
+        assert isinstance(deserialized_args.request_event, WorkflowEvent)
+        assert deserialized_args.request_event.type == "request_info"
+        assert deserialized_args.request_event.data == HandoffRequest(target_agent="helper", reason="overflow")
+        assert deserialized_args.request_event.response_type is str
+
+    def test_process_request_info_event_passes_through_function_approval_request(self) -> None:
+        """If the event data is already a function approval request, it is forwarded unchanged.
+
+        Tool-approval requests emitted by an inner agent surface as ``Content``
+        objects with ``user_input_request=True``. ``WorkflowAgent`` must not
+        re-wrap these inside a synthesized ``request_info`` function call;
+        instead it should return the original content as-is so callers can
+        respond with a matching ``function_approval_response``.
+        """
+        executor = SimpleExecutor(id="executor1", response_text="Response")
+        workflow = WorkflowBuilder(start_executor=executor).build()
+        agent = WorkflowAgent(workflow=workflow, name="Approval Passthrough Agent")
+
+        approval_id = "approval-passthrough-1"
+        inner_function_call = Content.from_function_call(
+            call_id="tool-call-1",
+            name="delete_file",
+            arguments={"path": "/tmp/x"},
+        )
+        approval_request = Content.from_function_approval_request(
+            id=approval_id,
+            function_call=inner_function_call,
+        )
+        event = WorkflowEvent.request_info(
+            request_id=approval_id,
+            source_executor_id="executor1",
+            request_data=approval_request,
+            response_type=Content,
+        )
+
+        result = agent._process_request_info_event(event)  # pyright: ignore[reportPrivateUsage]
+
+        # The original FunctionApprovalRequestContent is returned as-is — same
+        # instance, with the original tool name preserved (NOT replaced by the
+        # synthesized REQUEST_INFO_FUNCTION_NAME).
+        assert result is approval_request
+        assert result.type == "function_approval_request"
+        assert result.id == approval_id
+        assert result.user_input_request is True
+        assert result.function_call is inner_function_call  # type: ignore[attr-defined]
+        assert result.function_call.name == "delete_file"  # type: ignore[attr-defined]
+        assert result.function_call.name != WorkflowAgent.REQUEST_INFO_FUNCTION_NAME  # type: ignore[attr-defined]
+
+    def test_extract_function_responses_passes_through_approval_response_approved(self) -> None:
+        """A function_approval_response with approved=True is keyed by content.id and forwarded as-is.
+
+        After the refactor, ``WorkflowAgent`` no longer unwraps a synthesized
+        ``request_info`` function call from approval responses — the response
+        content is routed straight back to the workflow under its own ``id``,
+        which matches the pending request id surfaced by
+        ``_process_request_info_event``.
+        """
+        executor = SimpleExecutor(id="executor1", response_text="Response")
+        workflow = WorkflowBuilder(start_executor=executor).build()
+        agent = WorkflowAgent(workflow=workflow, name="Approval Response Agent")
+
+        approval_id = "approval-response-approved-1"
+        inner_function_call = Content.from_function_call(
+            call_id="tool-call-1",
+            name="delete_file",
+            arguments={"path": "/tmp/x"},
+        )
+        approval_request = Content.from_function_approval_request(
+            id=approval_id,
+            function_call=inner_function_call,
+        )
+        approval_response = approval_request.to_function_approval_response(approved=True)  # type: ignore[attr-defined]
+        message = Message(role="user", contents=[approval_response])
+
+        responses = agent._extract_function_responses([message])  # pyright: ignore[reportPrivateUsage]
+
+        assert set(responses.keys()) == {approval_id}
+        assert responses[approval_id] is approval_response
+        assert responses[approval_id].approved is True  # type: ignore[attr-defined]
+
+    def test_extract_function_responses_passes_through_approval_response_denied(self) -> None:
+        """A function_approval_response with approved=False is forwarded the same way as an approval.
+
+        Only the ``approved`` flag changes — routing back to the workflow is
+        identical for accept and reject paths.
+        """
+        executor = SimpleExecutor(id="executor1", response_text="Response")
+        workflow = WorkflowBuilder(start_executor=executor).build()
+        agent = WorkflowAgent(workflow=workflow, name="Approval Response Agent")
+
+        approval_id = "approval-response-denied-1"
+        inner_function_call = Content.from_function_call(
+            call_id="tool-call-2",
+            name="send_email",
+            arguments={"to": "alice@example.com"},
+        )
+        approval_request = Content.from_function_approval_request(
+            id=approval_id,
+            function_call=inner_function_call,
+        )
+        approval_response = approval_request.to_function_approval_response(approved=False)  # type: ignore[attr-defined]
+        message = Message(role="user", contents=[approval_response])
+
+        responses = agent._extract_function_responses([message])  # pyright: ignore[reportPrivateUsage]
+
+        assert set(responses.keys()) == {approval_id}
+        assert responses[approval_id] is approval_response
+        assert responses[approval_id].approved is False  # type: ignore[attr-defined]
+
+    async def test_function_approval_request_flows_end_to_end_approved(self) -> None:
+        """End-to-end: an executor emits a function_approval_request, the agent
+        forwards it unchanged, and an ``approved=True`` response resumes the workflow.
+
+        This exercises the full pass-through path:
+        ``ctx.request_info(approval_content, ...)`` -> ``WorkflowAgent`` surfaces
+        the original ``FunctionApprovalRequestContent`` -> caller responds with a
+        ``FunctionApprovalResponseContent`` -> ``WorkflowAgent`` routes it back
+        to the workflow which delivers it to the executor's ``@response_handler``.
+        """
+        approval_id = "e2e-approval-1"
+        inner_function_call = Content.from_function_call(
+            call_id="tool-call-e2e-1",
+            name="delete_file",
+            arguments={"path": "/tmp/x"},
+        )
+        approval_request = Content.from_function_approval_request(
+            id=approval_id,
+            function_call=inner_function_call,
+        )
+
+        class ApprovalRequestingExecutor(Executor):
+            @handler
+            async def handle_message(self, _: list[Message], ctx: WorkflowContext) -> None:
+                await ctx.request_info(approval_request, Content, request_id=approval_id)
+
+            @response_handler
+            async def handle_response(
+                self,
+                original_request: Content,
+                response: Content,
+                ctx: WorkflowContext[Never, AgentResponse],
+            ) -> None:
+                assert response.type == "function_approval_response"
+                assert response.id == approval_id  # type: ignore[attr-defined]
+                approved = bool(response.approved)  # type: ignore[attr-defined]
+                tool_name = original_request.function_call.name  # type: ignore[attr-defined]
+                await ctx.yield_output(
+                    AgentResponse(
+                        messages=[
+                            Message(
+                                role="assistant",
+                                contents=[Content.from_text(text=f"{tool_name} approved={approved}")],
+                            )
+                        ]
+                    )
+                )
+
+        executor = ApprovalRequestingExecutor(id="approval_requester")
+        workflow = WorkflowBuilder(start_executor=executor).build()
+        agent = WorkflowAgent(workflow=workflow, name="E2E Approval Agent")
+
+        # First run: workflow pauses with the approval request.
+        first = await agent.run("please delete it")
+        assert isinstance(first, AgentResponse)
+
+        forwarded = next(
+            (
+                c
+                for m in first.messages
+                for c in m.contents
+                if c.type == "function_approval_request" and c.id == approval_id
+            ),
+            None,
+        )
+        assert forwarded is approval_request, "Approval request must surface unchanged"
+
+        pending = await workflow._runner_context.get_pending_request_info_events()
+        assert approval_id in pending
+
+        # Respond with approved=True.
+        approval_response = approval_request.to_function_approval_response(approved=True)  # type: ignore[attr-defined]
+        final = await agent.run(Message(role="user", contents=[approval_response]))
+
+        assert isinstance(final, AgentResponse)
+        final_text = " ".join(m.text or "" for m in final.messages)
+        assert "delete_file approved=True" in final_text
+
+        pending = await workflow._runner_context.get_pending_request_info_events()
+        assert approval_id not in pending
+
+    async def test_function_approval_request_flows_end_to_end_denied(self) -> None:
+        """End-to-end denied path: ``approved=False`` is delivered to the executor's
+        response handler so the workflow can branch on the rejection."""
+        approval_id = "e2e-approval-deny-1"
+        inner_function_call = Content.from_function_call(
+            call_id="tool-call-e2e-deny-1",
+            name="send_email",
+            arguments={"to": "alice@example.com"},
+        )
+        approval_request = Content.from_function_approval_request(
+            id=approval_id,
+            function_call=inner_function_call,
+        )
+
+        class ApprovalRequestingExecutor(Executor):
+            @handler
+            async def handle_message(self, _: list[Message], ctx: WorkflowContext) -> None:
+                await ctx.request_info(approval_request, Content, request_id=approval_id)
+
+            @response_handler
+            async def handle_response(
+                self,
+                original_request: Content,
+                response: Content,
+                ctx: WorkflowContext[Never, AgentResponse],
+            ) -> None:
+                assert response.type == "function_approval_response"
+                assert response.id == approval_id  # type: ignore[attr-defined]
+                approved = bool(response.approved)  # type: ignore[attr-defined]
+                tool_name = original_request.function_call.name  # type: ignore[attr-defined]
+                await ctx.yield_output(
+                    AgentResponse(
+                        messages=[
+                            Message(
+                                role="assistant",
+                                contents=[Content.from_text(text=f"{tool_name} approved={approved}")],
+                            )
+                        ]
+                    )
+                )
+
+        executor = ApprovalRequestingExecutor(id="approval_requester_deny")
+        workflow = WorkflowBuilder(start_executor=executor).build()
+        agent = WorkflowAgent(workflow=workflow, name="E2E Approval Deny Agent")
+
+        first = await agent.run("please send")
+        assert isinstance(first, AgentResponse)
+        forwarded = next(
+            (
+                c
+                for m in first.messages
+                for c in m.contents
+                if c.type == "function_approval_request" and c.id == approval_id
+            ),
+            None,
+        )
+        assert forwarded is approval_request
+
+        # Respond with approved=False.
+        approval_response = approval_request.to_function_approval_response(approved=False)  # type: ignore[attr-defined]
+        final = await agent.run(Message(role="user", contents=[approval_response]))
+
+        assert isinstance(final, AgentResponse)
+        final_text = " ".join(m.text or "" for m in final.messages)
+        assert "send_email approved=False" in final_text
+
+        pending = await workflow._runner_context.get_pending_request_info_events()
+        assert approval_id not in pending
+
+    async def test_request_info_non_approval_flows_end_to_end(self) -> None:
+        """End-to-end: when request data is not a function approval content, the
+        agent surfaces a synthesized ``function_call`` (name=REQUEST_INFO_FUNCTION_NAME)
+        and routes a matching ``function_result`` back to the executor.
+        """
+        captured: dict[str, Any] = {}
+
+        class HandoffRequestingExecutor(Executor):
+            @handler
+            async def handle_message(self, _: list[Message], ctx: WorkflowContext) -> None:
+                await ctx.request_info(
+                    HandoffRequest(target_agent="helper", reason="overflow"),
+                    str,
+                )
+
+            @response_handler
+            async def handle_response(
+                self,
+                original_request: HandoffRequest,
+                response: str,
+                ctx: WorkflowContext[Never, AgentResponse],
+            ) -> None:
+                captured["original"] = original_request
+                captured["response"] = response
+                await ctx.yield_output(
+                    AgentResponse(
+                        messages=[
+                            Message(
+                                role="assistant",
+                                contents=[
+                                    Content.from_text(text=f"handoff to {original_request.target_agent}: {response}")
+                                ],
+                            )
+                        ]
+                    )
+                )
+
+        executor = HandoffRequestingExecutor(id="handoff_requester")
+        workflow = WorkflowBuilder(start_executor=executor).build()
+        agent = WorkflowAgent(workflow=workflow, name="E2E Handoff Agent")
+
+        # First run: workflow pauses with a synthesized request_info function_call.
+        first = await agent.run("start handoff")
+        assert isinstance(first, AgentResponse)
+
+        function_call = next(
+            (
+                c
+                for m in first.messages
+                for c in m.contents
+                if c.type == "function_call" and c.name == WorkflowAgent.REQUEST_INFO_FUNCTION_NAME
+            ),
+            None,
+        )
+        assert function_call is not None, "Expected a synthesized request_info function_call"
+        assert function_call.call_id is not None
+        assert isinstance(function_call.arguments, dict)
+        request_id = function_call.arguments["request_id"]
+        assert function_call.call_id == request_id
+        request_payload = function_call.arguments["request_event"]
+        assert request_payload.get("type") == "request_info"
+        assert request_payload.get("data") == HandoffRequest(target_agent="helper", reason="overflow")
+
+        deserialized_args = WorkflowAgent.RequestInfoFunctionArgs.from_dict(function_call.arguments)
+        assert deserialized_args.request_id == request_id
+        assert isinstance(deserialized_args.request_event, WorkflowEvent)
+        assert deserialized_args.request_event.type == "request_info"
+        assert deserialized_args.request_event.data == HandoffRequest(target_agent="helper", reason="overflow")
+        assert deserialized_args.request_event.response_type is str
+
+        pending = await workflow._runner_context.get_pending_request_info_events()
+        assert request_id in pending
+
+        # Respond with a function_result keyed by the call_id.
+        function_result = Content.from_function_result(call_id=request_id, result="ok-do-it")
+        final = await agent.run(Message(role="user", contents=[function_result]))
+
+        assert isinstance(final, AgentResponse)
+        final_text = " ".join(m.text or "" for m in final.messages)
+        assert "handoff to helper: ok-do-it" in final_text
+
+        # The executor's response handler received the original request and the response.
+        assert isinstance(captured.get("original"), HandoffRequest)
+        assert captured["original"].target_agent == "helper"
+        assert captured["response"] == "ok-do-it"
+
+        pending = await workflow._runner_context.get_pending_request_info_events()
+        assert request_id not in pending

    def test_workflow_as_agent_method(self) -> None:
        """Test that Workflow.as_agent() creates a properly configured WorkflowAgent."""
@@ -1592,3 +1946,406 @@ class TestWorkflowAgentMergeUpdates:

        # Order: text (user), text (assistant), function_result (orphan at end)
        assert content_types == ["text", "text", "function_result"]
+
+
+class _ToolApprovalMockAgent(SupportsAgentRun):
+    """Mock agent whose first run returns a FunctionApprovalRequestContent.
+
+    Subsequent runs (after receiving an approval response in the input messages)
+    return a final assistant text response that echoes the approved arguments.
+
+    This mirrors a real agent whose tool invocation requires user approval.
+    """
+
+    def __init__(
+        self,
+        name: str,
+        *,
+        tool_name: str = "delete_file",
+        tool_arguments: dict[str, Any] | None = None,
+        approval_request_ids: Sequence[str] | None = None,
+    ) -> None:
+        self.id = str(uuid.uuid4())
+        self.name = name
+        self.description: str | None = None
+        self._tool_name = tool_name
+        self._tool_arguments = tool_arguments or {"path": "/tmp/example"}
+        # Pre-allocated request ids so the test can verify what the WorkflowAgent forwards.
+        self._approval_request_ids: list[str] = list(approval_request_ids) if approval_request_ids else []
+        self.run_count = 0
+        # Inputs received on the most recent (continuation) run, for assertions.
+        self.last_run_messages: list[Message] = []
+
+    def create_session(self, **kwargs: Any) -> AgentSession:
+        return AgentSession()
+
+    def get_session(self, *, service_session_id: str, **kwargs: Any) -> AgentSession:
+        return AgentSession()
+
+    def _next_request_id(self) -> str:
+        if self._approval_request_ids:
+            return self._approval_request_ids.pop(0)
+        return str(uuid.uuid4())
+
+    def _build_approval_request(self) -> Content:
+        request_id = self._next_request_id()
+        function_call = Content.from_function_call(
+            call_id=request_id,
+            name=self._tool_name,
+            arguments=self._tool_arguments,
+        )
+        return Content.from_function_approval_request(id=request_id, function_call=function_call)
+
+    @overload
+    def run(
+        self,
+        messages: str | Content | Message | Sequence[str | Content | Message] | None = ...,
+        *,
+        stream: Literal[False] = ...,
+        session: AgentSession | None = ...,
+        **kwargs: Any,
+    ) -> Awaitable[AgentResponse[Any]]: ...
+
+    @overload
+    def run(
+        self,
+        messages: str | Content | Message | Sequence[str | Content | Message] | None = ...,
+        *,
+        stream: Literal[True],
+        session: AgentSession | None = ...,
+        **kwargs: Any,
+    ) -> ResponseStream[AgentResponseUpdate, AgentResponse[Any]]: ...
+
+    def run(
+        self,
+        messages: str | Content | Message | Sequence[str | Content | Message] | None = None,
+        *,
+        stream: bool = False,
+        session: AgentSession | None = None,
+        **kwargs: Any,
+    ) -> Awaitable[AgentResponse] | ResponseStream[AgentResponseUpdate, AgentResponse]:
+        if stream:
+            return self._run_stream(messages=messages, session=session, **kwargs)
+        return self._run(messages=messages, session=session, **kwargs)
+
+    def _normalize(
+        self,
+        messages: str | Content | Message | Sequence[str | Content | Message] | None,
+    ) -> list[Message]:
+        if messages is None:
+            return []
+        if isinstance(messages, str):
+            return [Message(role="user", contents=[Content.from_text(text=messages)])]
+        if isinstance(messages, Message):
+            return [messages]
+        if isinstance(messages, Content):
+            return [Message(role="user", contents=[messages])]
+        result: list[Message] = []
+        for item in messages:
+            if isinstance(item, Message):
+                result.append(item)
+            elif isinstance(item, Content):
+                result.append(Message(role="user", contents=[item]))
+            else:
+                result.append(Message(role="user", contents=[Content.from_text(text=item)]))
+        return result
+
+    def _approval_responses_in(self, messages: list[Message]) -> list[Content]:
+        approvals: list[Content] = []
+        for msg in messages:
+            for content in msg.contents:
+                if content.type == "function_approval_response":
+                    approvals.append(content)
+        return approvals
+
+    async def _run(
+        self,
+        messages: str | Content | Message | Sequence[str | Content | Message] | None = None,
+        *,
+        session: AgentSession | None = None,
+        **kwargs: Any,
+    ) -> AgentResponse:
+        normalized = self._normalize(messages)
+        self.last_run_messages = normalized
+        self.run_count += 1
+
+        approvals = self._approval_responses_in(normalized)
+        if approvals:
+            # Continuation: reflect approved arguments in the final response text.
+            approved_text = "; ".join(
+                f"approved={a.approved} id={a.id}"  # type: ignore[attr-defined]
+                for a in approvals
+            )
+            return AgentResponse(messages=[Message("assistant", [Content.from_text(text=f"done ({approved_text})")])])
+
+        # First run: ask for tool approval.
+        approval = self._build_approval_request()
+        return AgentResponse(messages=[Message("assistant", [approval])])
+
+    def _run_stream(
+        self,
+        messages: str | Content | Message | Sequence[str | Content | Message] | None = None,
+        *,
+        session: AgentSession | None = None,
+        **kwargs: Any,
+    ) -> ResponseStream[AgentResponseUpdate, AgentResponse]:
+        normalized = self._normalize(messages)
+        self.last_run_messages = normalized
+        self.run_count += 1
+        approvals = self._approval_responses_in(normalized)
+
+        async def _iter():
+            if approvals:
+                approved_text = "; ".join(
+                    f"approved={a.approved} id={a.id}"  # type: ignore[attr-defined]
+                    for a in approvals
+                )
+                yield AgentResponseUpdate(
+                    contents=[Content.from_text(text=f"done ({approved_text})")],
+                    role="assistant",
+                    author_name=self.name,
+                )
+                return
+            approval = self._build_approval_request()
+            yield AgentResponseUpdate(
+                contents=[approval],
+                role="assistant",
+                author_name=self.name,
+            )
+
+        return ResponseStream(_iter(), finalizer=AgentResponse.from_updates)
+
+
+class TestWorkflowAgentToolApproval:
+    """Tests for tool-approval requests bubbling through WorkflowAgent.
+
+    Covers the case where a workflow contains an AgentExecutor whose underlying
+    agent emits a FunctionApprovalRequestContent (tool needing user approval).
+    The WorkflowAgent must:
+      * forward the original FunctionApprovalRequestContent unchanged (no
+        wrapping inside a synthesized 'request_info' function call), and
+      * route a subsequent FunctionApprovalResponseContent back to the
+        AgentExecutor so the agent can resume.
+    """
+
+    def _find_approval_request(
+        self,
+        contents: Sequence[Content],
+        tool_name: str,
+    ) -> Content | None:
+        for content in contents:
+            if (
+                content.type == "function_approval_request"
+                and getattr(content.function_call, "name", None) == tool_name  # type: ignore[attr-defined]
+            ):
+                return content
+        return None
+
+    async def test_tool_approval_request_forwarded_unchanged(self) -> None:
+        """The agent's FunctionApprovalRequestContent surfaces verbatim (not re-wrapped)."""
+        approval_id = "approval-abc-123"
+        mock_agent = _ToolApprovalMockAgent(
+            name="approval-agent",
+            tool_name="delete_file",
+            tool_arguments={"path": "/tmp/secret.txt"},
+            approval_request_ids=[approval_id],
+        )
+
+        @executor
+        async def start(messages: list[Message], ctx: WorkflowContext[AgentExecutorRequest]) -> None:
+            await ctx.send_message(AgentExecutorRequest(messages=messages, should_respond=True))
+
+        workflow = WorkflowBuilder(start_executor=start).add_edge(start, mock_agent).build()
+        agent = WorkflowAgent(workflow=workflow, name="Approval Test Agent")
+
+        result = await agent.run("please delete the file")
+
+        assert isinstance(result, AgentResponse)
+
+        # Locate the approval request emitted by the WorkflowAgent.
+        all_contents: list[Content] = [c for m in result.messages for c in m.contents]
+        approval = self._find_approval_request(all_contents, tool_name="delete_file")
+        assert approval is not None, "WorkflowAgent did not forward the tool approval request"
+
+        # The id and inner function_call must match what the underlying agent produced
+        # — i.e. the WorkflowAgent must NOT have re-wrapped it inside a synthesized
+        # 'request_info' approval request.
+        assert approval.id == approval_id
+        function_call = approval.function_call  # type: ignore[attr-defined]
+        assert function_call is not None
+        assert function_call.name == "delete_file"
+        assert function_call.name != WorkflowAgent.REQUEST_INFO_FUNCTION_NAME
+        assert function_call.arguments == {"path": "/tmp/secret.txt"}
+
+        # The agent must be paused awaiting the approval response.
+        pending = await workflow._runner_context.get_pending_request_info_events()
+        assert approval_id in pending
+
+    async def test_tool_approval_request_forwarded_unchanged_streaming(self) -> None:
+        """Streaming variant: the approval request is forwarded as-is in updates."""
+        approval_id = "approval-stream-1"
+        mock_agent = _ToolApprovalMockAgent(
+            name="approval-agent-stream",
+            tool_name="send_email",
+            tool_arguments={"to": "alice@example.com"},
+            approval_request_ids=[approval_id],
+        )
+
+        @executor
+        async def start(messages: list[Message], ctx: WorkflowContext[AgentExecutorRequest]) -> None:
+            await ctx.send_message(AgentExecutorRequest(messages=messages, should_respond=True))
+
+        workflow = WorkflowBuilder(start_executor=start).add_edge(start, mock_agent).build()
+        agent = WorkflowAgent(workflow=workflow, name="Approval Stream Agent")
+
+        updates: list[AgentResponseUpdate] = []
+        async for update in agent.run("hi", stream=True):
+            updates.append(update)
+
+        approval_updates = [u for u in updates if any(c.type == "function_approval_request" for c in u.contents)]
+        assert approval_updates, "Streaming did not surface a tool approval request"
+
+        approval = self._find_approval_request(approval_updates[-1].contents, tool_name="send_email")
+        assert approval is not None
+        assert approval.id == approval_id
+        function_call = approval.function_call  # type: ignore[attr-defined]
+        assert function_call is not None
+        assert function_call.name == "send_email"
+        assert function_call.name != WorkflowAgent.REQUEST_INFO_FUNCTION_NAME
+        assert function_call.arguments == {"to": "alice@example.com"}
+
+    async def test_tool_approval_response_resumes_agent(self) -> None:
+        """Sending the approval response back resumes the agent and clears pending requests."""
+        approval_id = "approval-resume-1"
+        mock_agent = _ToolApprovalMockAgent(
+            name="approval-resume-agent",
+            tool_name="delete_file",
+            tool_arguments={"path": "/tmp/x"},
+            approval_request_ids=[approval_id],
+        )
+
+        @executor
+        async def start(messages: list[Message], ctx: WorkflowContext[AgentExecutorRequest]) -> None:
+            await ctx.send_message(AgentExecutorRequest(messages=messages, should_respond=True))
+
+        workflow = WorkflowBuilder(start_executor=start).add_edge(start, mock_agent).build()
+        agent = WorkflowAgent(workflow=workflow, name="Approval Resume Agent")
+
+        first_result = await agent.run("delete it")
+        approval = self._find_approval_request(
+            [c for m in first_result.messages for c in m.contents],
+            tool_name="delete_file",
+        )
+        assert approval is not None
+        assert mock_agent.run_count == 1
+
+        # Build the approval response. NOTE: the inner function_call's name is the
+        # original tool name ('delete_file'), NOT 'request_info'. This exercises the
+        # branch in WorkflowAgent._extract_function_responses that routes raw
+        # tool-approval responses straight through using content.id.
+        approval_response = approval.to_function_approval_response(approved=True)  # type: ignore[attr-defined]
+        response_message = Message(role="user", contents=[approval_response])
+
+        final_result = await agent.run(response_message)
+        assert isinstance(final_result, AgentResponse)
+
+        # The mock agent should have been invoked a second time and seen the
+        # approval response in its inputs.
+        assert mock_agent.run_count == 2
+        approvals_seen = [
+            c for m in mock_agent.last_run_messages for c in m.contents if c.type == "function_approval_response"
+        ]
+        assert len(approvals_seen) == 1
+        assert approvals_seen[0].id == approval_id  # type: ignore[attr-defined]
+        assert approvals_seen[0].approved is True  # type: ignore[attr-defined]
+
+        # The pending approval should now be cleared.
+        pending = await workflow._runner_context.get_pending_request_info_events()
+        assert approval_id not in pending
+
+        # The final assistant message reflects the resumption.
+        final_text = " ".join(m.text or "" for m in final_result.messages)
+        assert "done" in final_text
+        assert approval_id in final_text
+
+    async def test_tool_approval_response_rejected_resumes_agent(self) -> None:
+        """Rejection path: ``approved=False`` is forwarded to the inner agent and clears the pending request.
+
+        The WorkflowAgent must route a rejection response back to the paused
+        ``AgentExecutor`` exactly the same way as an approval — only the
+        ``approved`` flag differs. The inner agent decides what to do with it.
+        """
+        approval_id = "approval-reject-1"
+        mock_agent = _ToolApprovalMockAgent(
+            name="approval-reject-agent",
+            tool_name="delete_file",
+            tool_arguments={"path": "/tmp/x"},
+            approval_request_ids=[approval_id],
+        )
+
+        @executor
+        async def start(messages: list[Message], ctx: WorkflowContext[AgentExecutorRequest]) -> None:
+            await ctx.send_message(AgentExecutorRequest(messages=messages, should_respond=True))
+
+        workflow = WorkflowBuilder(start_executor=start).add_edge(start, mock_agent).build()
+        agent = WorkflowAgent(workflow=workflow, name="Approval Reject Agent")
+
+        first_result = await agent.run("delete it")
+        approval = self._find_approval_request(
+            [c for m in first_result.messages for c in m.contents],
+            tool_name="delete_file",
+        )
+        assert approval is not None
+        assert mock_agent.run_count == 1
+
+        # Reject the tool invocation.
+        approval_response = approval.to_function_approval_response(approved=False)  # type: ignore[attr-defined]
+        response_message = Message(role="user", contents=[approval_response])
+
+        final_result = await agent.run(response_message)
+        assert isinstance(final_result, AgentResponse)
+
+        # The inner agent must have been resumed and seen ``approved=False``.
+        assert mock_agent.run_count == 2
+        approvals_seen = [
+            c for m in mock_agent.last_run_messages for c in m.contents if c.type == "function_approval_response"
+        ]
+        assert len(approvals_seen) == 1
+        assert approvals_seen[0].id == approval_id  # type: ignore[attr-defined]
+        assert approvals_seen[0].approved is False  # type: ignore[attr-defined]
+
+        # Pending approval cleared regardless of approve/reject.
+        pending = await workflow._runner_context.get_pending_request_info_events()
+        assert approval_id not in pending
+
+        # The final assistant message reflects the rejection.
+        final_text = " ".join(m.text or "" for m in final_result.messages)
+        assert "approved=False" in final_text
+        assert approval_id in final_text
+
+    async def test_tool_approval_request_id_matches_pending_request(self) -> None:
+        """The approval request id surfaced by WorkflowAgent matches the workflow's pending request id.
+
+        This guards the AgentExecutor change that forwards
+        request_id=user_input_request.id to ctx.request_info(...), which is what
+        allows the response routed back via WorkflowAgent to resolve the pending
+        request without an id-mismatch error.
+        """
+        approval_id = "approval-id-match-1"
+        mock_agent = _ToolApprovalMockAgent(
+            name="approval-id-match-agent",
+            approval_request_ids=[approval_id],
+        )
+
+        @executor
+        async def start(messages: list[Message], ctx: WorkflowContext[AgentExecutorRequest]) -> None:
+            await ctx.send_message(AgentExecutorRequest(messages=messages, should_respond=True))
+
+        workflow = WorkflowBuilder(start_executor=start).add_edge(start, mock_agent).build()
+        agent = WorkflowAgent(workflow=workflow, name="Approval Id Agent")
+
+        await agent.run("go")
+
+        pending = await workflow._runner_context.get_pending_request_info_events()
+        # The agent's approval id is used as the workflow's pending request id.
+        assert list(pending.keys()) == [approval_id]
@@ -0,0 +1,149 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""Tests for the ``Workflow.status`` property."""
+
+from dataclasses import dataclass
+
+import pytest
+
+from agent_framework import (
+    Executor,
+    Workflow,
+    WorkflowBuilder,
+    WorkflowContext,
+    WorkflowEvent,
+    WorkflowRunState,
+    handler,
+    response_handler,
+)
+from agent_framework._workflows._executor import Executor as _Executor
+from agent_framework._workflows._request_info_mixin import RequestInfoMixin
+
+
+class PassThroughExecutor(Executor):
+    """Executor that yields its input as a workflow output and stops."""
+
+    @handler
+    async def passthrough(self, msg: str, ctx: WorkflowContext[str, str]) -> None:
+        await ctx.yield_output(msg)
+
+
+class FailingExecutor(Executor):
+    """Executor that raises at runtime to drive the FAILED status."""
+
+    @handler
+    async def fail(self, msg: int, ctx: WorkflowContext) -> None:  # pragma: no cover - invoked via workflow
+        raise RuntimeError("boom")
+
+
+@dataclass
+class _ApprovalRequest:
+    prompt: str
+    request_id: str = ""
+
+    def __post_init__(self) -> None:
+        if not self.request_id:
+            import uuid
+
+            self.request_id = str(uuid.uuid4())
+
+
+class ApprovalExecutor(_Executor, RequestInfoMixin):
+    """Executor that issues a single request_info call and finalizes on response."""
+
+    def __init__(self, id: str = "approval"):
+        super().__init__(id=id)
+
+    @handler
+    async def start(self, message: str, ctx: WorkflowContext[str, str]) -> None:
+        await ctx.request_info(_ApprovalRequest(prompt=message), bool)
+
+    @response_handler
+    async def on_response(
+        self, original_request: _ApprovalRequest, approved: bool, ctx: WorkflowContext[str, str]
+    ) -> None:
+        await ctx.yield_output(f"approved={approved}")
+
+
+def _build_passthrough_workflow() -> Workflow:
+    executor = PassThroughExecutor(id="p")
+    return WorkflowBuilder(start_executor=executor, output_from=[executor]).build()
+
+
+def _build_failing_workflow() -> Workflow:
+    # FailingExecutor has no workflow_output_types, so we leave designation
+    # implicit; the deprecation warning is filtered at call sites that need it.
+    return WorkflowBuilder(start_executor=FailingExecutor(id="f")).build()
+
+
+def _build_approval_workflow() -> Workflow:
+    executor = ApprovalExecutor(id="approval")
+    return WorkflowBuilder(start_executor=executor, output_from=[executor]).build()
+
+
+async def test_status_default_is_idle_before_first_run():
+    wf = _build_passthrough_workflow()
+    assert wf.status is WorkflowRunState.IDLE
+
+
+async def test_status_is_idle_after_successful_run():
+    wf = _build_passthrough_workflow()
+    await wf.run("hello")
+    assert wf.status is WorkflowRunState.IDLE
+
+
+async def test_status_is_failed_after_failure():
+    wf = _build_failing_workflow()
+    with pytest.raises(RuntimeError, match="boom"):
+        await wf.run(0)
+    assert wf.status is WorkflowRunState.FAILED
+
+
+async def test_status_transitions_during_streaming_run():
+    """Workflow.status mirrors the most recent emitted status event."""
+    wf = _build_passthrough_workflow()
+    observed: list[WorkflowRunState] = []
+
+    async for event in wf.run("hi", stream=True):
+        if isinstance(event, WorkflowEvent) and event.type == "status":
+            # By the time a status event surfaces to the consumer, the property
+            # must already reflect that state (updated in lockstep with emission).
+            assert wf.status == event.state
+            observed.append(event.state)  # type: ignore
+
+    # IN_PROGRESS must precede IDLE; both must appear.
+    assert WorkflowRunState.IN_PROGRESS in observed
+    assert observed[-1] is WorkflowRunState.IDLE
+    assert wf.status is WorkflowRunState.IDLE
+
+
+async def test_status_idle_with_pending_requests_then_resolves_to_idle():
+    wf = _build_approval_workflow()
+
+    request_event: WorkflowEvent | None = None
+    async for event in wf.run("please approve", stream=True):
+        if isinstance(event, WorkflowEvent) and event.type == "request_info":
+            request_event = event
+
+    assert request_event is not None
+    assert wf.status is WorkflowRunState.IDLE_WITH_PENDING_REQUESTS
+
+    async for _ in wf.run(stream=True, responses={request_event.request_id: True}):
+        pass
+
+    assert wf.status is WorkflowRunState.IDLE
+
+
+async def test_status_in_progress_pending_requests_observed_mid_run():
+    """While streaming, status reaches IN_PROGRESS_PENDING_REQUESTS after a request_info event."""
+    wf = _build_approval_workflow()
+    seen_states: list[WorkflowRunState] = []
+
+    async for event in wf.run("please approve", stream=True):
+        if isinstance(event, WorkflowEvent) and event.type == "status":
+            seen_states.append(event.state)  # type: ignore
+
+    assert WorkflowRunState.IN_PROGRESS in seen_states
+    assert WorkflowRunState.IN_PROGRESS_PENDING_REQUESTS in seen_states
+    assert seen_states[-1] is WorkflowRunState.IDLE_WITH_PENDING_REQUESTS
+    assert wf.status is WorkflowRunState.IDLE_WITH_PENDING_REQUESTS
@@ -191,7 +191,6 @@ class RawFoundryAgentChatClient(  # type: ignore[misc]
        compaction_strategy: CompactionStrategy | None = None,
        tokenizer: TokenizerProtocol | None = None,
        additional_properties: dict[str, Any] | None = None,
-        timeout: float | None = None,
    ) -> None:
        """Initialize a raw Foundry Agent client.

@@ -212,8 +211,6 @@ class RawFoundryAgentChatClient(  # type: ignore[misc]
            compaction_strategy: Optional per-client compaction override.
            tokenizer: Optional tokenizer for compaction strategies.
            additional_properties: Additional properties stored on the client instance.
-            timeout: HTTP timeout in seconds for requests. When not provided, the
-                OpenAI SDK default is used (connect: 5s, total: 600s).
        """
        settings = load_settings(
            FoundryAgentSettings,
@@ -263,11 +260,8 @@ class RawFoundryAgentChatClient(  # type: ignore[misc]
            openai_client_kwargs["default_headers"] = dict(default_headers)
        if allow_preview:
            openai_client_kwargs["agent_name"] = self.agent_name
-        openai_client = self.project_client.get_openai_client(**openai_client_kwargs)
-        if timeout is not None:
-            openai_client = openai_client.with_options(timeout=timeout)
        super().__init__(
-            async_client=openai_client,
+            async_client=self.project_client.get_openai_client(**openai_client_kwargs),
            default_headers=default_headers,
            instruction_role=instruction_role,
            compaction_strategy=compaction_strategy,
@@ -543,7 +537,6 @@ class _FoundryAgentChatClient(  # type: ignore[misc]
        additional_properties: dict[str, Any] | None = None,
        middleware: (Sequence[ChatAndFunctionMiddlewareTypes] | None) = None,
        function_invocation_configuration: FunctionInvocationConfiguration | None = None,
-        timeout: float | None = None,
    ) -> None:
        """Initialize a Foundry Agent client with full middleware support.

@@ -563,8 +556,6 @@ class _FoundryAgentChatClient(  # type: ignore[misc]
            additional_properties: Additional properties stored on the client instance.
            middleware: Optional sequence of middleware.
            function_invocation_configuration: Optional function invocation configuration.
-            timeout: HTTP timeout in seconds for requests. When not provided, the
-                OpenAI SDK default is used (connect: 5s, total: 600s).
        """
        super().__init__(
            project_endpoint=project_endpoint,
@@ -582,7 +573,6 @@ class _FoundryAgentChatClient(  # type: ignore[misc]
            additional_properties=additional_properties,
            middleware=middleware,
            function_invocation_configuration=function_invocation_configuration,
-            timeout=timeout,
        )


@@ -635,7 +625,6 @@ class RawFoundryAgent(  # type: ignore[misc]
        compaction_strategy: CompactionStrategy | None = None,
        tokenizer: TokenizerProtocol | None = None,
        additional_properties: Mapping[str, Any] | None = None,
-        timeout: float | None = None,
    ) -> None:
        """Initialize a Foundry Agent.

@@ -668,8 +657,6 @@ class RawFoundryAgent(  # type: ignore[misc]
            compaction_strategy: Optional agent-level in-run compaction override.
            tokenizer: Optional agent-level tokenizer override.
            additional_properties: Additional properties stored on the local agent wrapper.
-            timeout: HTTP timeout in seconds for requests. When not provided, the
-                OpenAI SDK default is used (connect: 5s, total: 600s).
        """
        # Create the client
        actual_client_type = client_type or _FoundryAgentChatClient
@@ -688,7 +675,6 @@ class RawFoundryAgent(  # type: ignore[misc]
            "default_headers": default_headers,
            "env_file_path": env_file_path,
            "env_file_encoding": env_file_encoding,
-            "timeout": timeout,
        }
        if function_invocation_configuration is not None:
            if not issubclass(actual_client_type, FunctionInvocationLayer):
@@ -926,7 +912,6 @@ class FoundryAgent(  # type: ignore[misc]
        compaction_strategy: CompactionStrategy | None = None,
        tokenizer: TokenizerProtocol | None = None,
        additional_properties: Mapping[str, Any] | None = None,
-        timeout: float | None = None,
    ) -> None:
        """Initialize a Foundry Agent with full middleware and telemetry.

@@ -973,8 +958,6 @@ class FoundryAgent(  # type: ignore[misc]
            compaction_strategy: Optional agent-level in-run compaction override.
            tokenizer: Optional agent-level tokenizer override.
            additional_properties: Additional properties stored on the local agent wrapper.
-            timeout: HTTP timeout in seconds for requests. When not provided, the
-                OpenAI SDK default is used (connect: 5s, total: 600s).
        """
        super().__init__(
            project_endpoint=project_endpoint,
@@ -1000,5 +983,4 @@ class FoundryAgent(  # type: ignore[misc]
            compaction_strategy=compaction_strategy,
            tokenizer=tokenizer,
            additional_properties=additional_properties,
-            timeout=timeout,
        )
@@ -4,7 +4,7 @@ description = "Microsoft Foundry integrations for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.8.0"
+version = "1.7.0"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,10 +23,10 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.8.0,<2",
-    "agent-framework-openai>=1.8.0,<2",
+    "agent-framework-core>=1.7.0,<2",
+    "agent-framework-openai>=1.7.0,<2",
    "azure-ai-inference>=1.0.0b9,<1.0.0b10",
-    "azure-ai-projects>=2.1.0,<3.0",
+    "azure-ai-projects>=2.2.0,<3.0",
 ]

 [tool.uv]
@@ -109,67 +109,9 @@ def test_raw_foundry_agent_chat_client_init_uses_explicit_parameters() -> None:
    assert "compaction_strategy" in signature.parameters
    assert "tokenizer" in signature.parameters
    assert "additional_properties" in signature.parameters
-    assert "timeout" in signature.parameters
    assert all(parameter.kind != inspect.Parameter.VAR_KEYWORD for parameter in signature.parameters.values())


-def test_raw_foundry_agent_chat_client_init_applies_timeout_to_openai_client() -> None:
-    """Test that timeout is applied via with_options without mutating the shared OpenAI client."""
-
-    mock_project = MagicMock()
-    openai_client_mock = MagicMock()
-    openai_client_mock.timeout = 5.0
-    mock_project.get_openai_client.return_value = openai_client_mock
-
-    client = RawFoundryAgentChatClient(
-        project_client=mock_project,
-        agent_name="test-agent",
-        timeout=60.0,
-    )
-
-    openai_client_mock.with_options.assert_called_once_with(timeout=60.0)
-    assert openai_client_mock.timeout == 5.0, "Original shared client must not be mutated"
-    assert client.client is openai_client_mock.with_options.return_value
-
-
-def test_raw_foundry_agent_chat_client_init_timeout_none_leaves_client_unchanged() -> None:
-    """Test that timeout=None does not call with_options and leaves the shared client intact."""
-
-    mock_project = MagicMock()
-    openai_client_mock = MagicMock()
-    openai_client_mock.timeout = 5.0
-    mock_project.get_openai_client.return_value = openai_client_mock
-
-    RawFoundryAgentChatClient(
-        project_client=mock_project,
-        agent_name="test-agent",
-        timeout=None,
-    )
-
-    openai_client_mock.with_options.assert_not_called()
-    assert openai_client_mock.timeout == 5.0
-
-
-def test_raw_foundry_agent_chat_client_init_applies_timeout_with_preview_enabled() -> None:
-    """Test that timeout uses with_options even when allow_preview=True (hosted agent path)."""
-
-    mock_project = MagicMock()
-    openai_client_mock = MagicMock()
-    openai_client_mock.timeout = 5.0
-    mock_project.get_openai_client.return_value = openai_client_mock
-
-    client = RawFoundryAgentChatClient(
-        project_client=mock_project,
-        agent_name="hosted-agent",
-        allow_preview=True,
-        timeout=120.0,
-    )
-
-    openai_client_mock.with_options.assert_called_once_with(timeout=120.0)
-    assert openai_client_mock.timeout == 5.0, "Original shared client must not be mutated"
-    assert client.client is openai_client_mock.with_options.return_value
-
-
 def test_raw_foundry_agent_chat_client_as_agent_preserves_client_type() -> None:
    """Test that as_agent() wraps the client in FoundryAgent using the same client class."""

@@ -610,29 +552,9 @@ def test_foundry_agent_chat_client_init_uses_explicit_parameters() -> None:
    assert "compaction_strategy" in signature.parameters
    assert "tokenizer" in signature.parameters
    assert "additional_properties" in signature.parameters
-    assert "timeout" in signature.parameters
    assert all(parameter.kind != inspect.Parameter.VAR_KEYWORD for parameter in signature.parameters.values())


-def test_foundry_agent_chat_client_init_propagates_timeout() -> None:
-    """Test that _FoundryAgentChatClient calls with_options instead of mutating the shared client."""
-
-    mock_project = MagicMock()
-    openai_client_mock = MagicMock()
-    openai_client_mock.timeout = 5.0
-    mock_project.get_openai_client.return_value = openai_client_mock
-
-    client = _FoundryAgentChatClient(
-        project_client=mock_project,
-        agent_name="test-agent",
-        timeout=45.0,
-    )
-
-    openai_client_mock.with_options.assert_called_once_with(timeout=45.0)
-    assert openai_client_mock.timeout == 5.0, "Original shared client must not be mutated"
-    assert client.client is openai_client_mock.with_options.return_value
-
-
 def test_raw_foundry_agent_init_creates_client() -> None:
    """Test that RawFoundryAgent creates a client internally."""

@@ -707,7 +629,6 @@ def test_raw_foundry_agent_init_uses_explicit_parameters() -> None:
    assert "compaction_strategy" in signature.parameters
    assert "tokenizer" in signature.parameters
    assert "additional_properties" in signature.parameters
-    assert "timeout" in signature.parameters
    assert all(parameter.kind != inspect.Parameter.VAR_KEYWORD for parameter in signature.parameters.values())


@@ -720,47 +641,9 @@ def test_foundry_agent_init_uses_explicit_parameters() -> None:
    assert "compaction_strategy" in signature.parameters
    assert "tokenizer" in signature.parameters
    assert "additional_properties" in signature.parameters
-    assert "timeout" in signature.parameters
    assert all(parameter.kind != inspect.Parameter.VAR_KEYWORD for parameter in signature.parameters.values())


-def test_foundry_agent_init_propagates_timeout_to_openai_client() -> None:
-    """Test that FoundryAgent uses with_options instead of mutating the shared OpenAI client."""
-
-    mock_project = MagicMock()
-    openai_client_mock = MagicMock()
-    openai_client_mock.timeout = 5.0
-    mock_project.get_openai_client.return_value = openai_client_mock
-
-    agent = FoundryAgent(
-        project_client=mock_project,
-        agent_name="test-agent",
-        timeout=90.0,
-    )
-
-    openai_client_mock.with_options.assert_called_once_with(timeout=90.0)
-    assert openai_client_mock.timeout == 5.0, "Original shared client must not be mutated"
-    assert agent.client.client is openai_client_mock.with_options.return_value
-
-
-def test_foundry_agent_init_timeout_none_leaves_client_default() -> None:
-    """Test that FoundryAgent with timeout=None does not call with_options or mutate the client."""
-
-    mock_project = MagicMock()
-    openai_client_mock = MagicMock()
-    openai_client_mock.timeout = 5.0
-    mock_project.get_openai_client.return_value = openai_client_mock
-
-    FoundryAgent(
-        project_client=mock_project,
-        agent_name="test-agent",
-        timeout=None,
-    )
-
-    openai_client_mock.with_options.assert_not_called()
-    assert openai_client_mock.timeout == 5.0
-
-
 def test_raw_foundry_agent_init_rejects_invalid_client_type() -> None:
    """Test that invalid client_type raises TypeError."""

@@ -11,7 +11,7 @@ import tempfile
 import threading
 from collections.abc import AsyncIterable, AsyncIterator, Generator, Mapping, Sequence
 from contextlib import AbstractAsyncContextManager, AsyncExitStack, suppress
-from dataclasses import asdict, dataclass, is_dataclass
+from dataclasses import asdict, is_dataclass
 from pathlib import Path
 from typing import Protocol, cast

@@ -264,73 +264,28 @@ def _checkpoint_storage_for_context(root: str, context_id: str) -> FileCheckpoin

 # Foundry Toolbox Auth integration
 # Consent-URL error code returned by the Foundry MCP gateway when calling `/list`
-CONSENT_ERROR_CODE = -32006
+CONSENT_ERROR_CODE = -32007


-@dataclass
-class ConsentError:
-    name: str
-    consent_url: str
+def consent_url_from_error(exc: BaseException) -> str | None:
+    """Return the consent URL when ``exc`` wraps a Foundry MCP gateway consent error.

-
-def consent_url_from_error(exc: BaseException) -> list[ConsentError] | None:
-    """Return the consent URLs when ``exc`` wraps Foundry MCP gateway consent errors.
+    The Agent Framework MCP layer surfaces gateway consent failures by wrapping the underlying
+    ``McpError`` inside an :class:`AgentFrameworkException` (typically a ``ToolExecutionException``
+    raised from ``MCPStreamableHTTPTool.__aenter__``). This helper inspects ``exc.args`` for a
+    wrapped ``McpError`` whose ``error.code`` is :data:`CONSENT_ERROR_CODE`; when found, the
+    consent link the gateway returned in ``error.message`` is returned. Returns ``None`` for
+    anything else, so callers can do ``if (url := consent_url_from_error(ex)) is None: raise``.

    Args:
        exc: The exception to inspect.

    Returns:
-        The consent URL(s) extracted from the error, or ``None`` if no consent error was found.
+        The consent URL if ``exc`` wraps a consent ``McpError``, otherwise ``None``.
    """
    inner_exception = next((arg for arg in exc.args if isinstance(arg, McpError)), None)
    if inner_exception is not None and inner_exception.error.code == CONSENT_ERROR_CODE:
-        # Parse the error message
-        # The error message is structured with the following format:
-        # "tools/list failed for 1 tool source(s), succeeded for 0 tool source(s) {"errors":[{"name": ..."
-        # where the second part is a JSON string that can be deserialized into an object with the following shape:
-        # ruff: disable[ERA001]
-        # {
-        #   "errors" : [
-        #       {
-        #           "name": "Name of the MCP tool that requires consent",
-        #           "type" : "mcp",
-        #           "error": {
-        #               "code": "CONSENT_REQUIRED",
-        #               "message": consent_url,
-        #           }
-        #       }
-        #   ]
-        # }
-        # ruff: enable[ERA001]
-        try:
-            consent_errors: list[ConsentError] = []
-            error_message_start = inner_exception.error.message.find("{")
-            if error_message_start == -1:
-                logger.warning("Consent error message does not contain JSON: %s", inner_exception.error.message)
-                return None
-            consent_details_json = inner_exception.error.message[error_message_start:]
-            consent_details = json.loads(consent_details_json)
-            if "errors" not in consent_details or not isinstance(consent_details["errors"], list):
-                logger.warning("Consent error message JSON does not contain 'errors' list: %s", consent_details_json)
-                return None
-            for error in consent_details["errors"]:
-                if (
-                    isinstance(error, dict)
-                    and error.get("type") == "mcp"  # type: ignore
-                    and "error" in error
-                    and isinstance(error["error"], dict)
-                    and error["error"].get("code") == "CONSENT_REQUIRED"  # type: ignore
-                    and "message" in error["error"]
-                ):
-                    consent_url = error["error"]["message"]  # type: ignore
-                    if isinstance(consent_url, str):
-                        consent_errors.append(ConsentError(name=error.get("name", "Unknown"), consent_url=consent_url))  # type: ignore
-                    else:
-                        logger.warning("Consent URL in error message is not a valid URL: %s", consent_url)  # type: ignore
-            if consent_errors:
-                return consent_errors
-        except json.JSONDecodeError:
-            logger.warning("Failed to parse consent details JSON: %s", inner_exception.error.message)
+        return inner_exception.error.message
    return None


@@ -493,19 +448,18 @@ class ResponsesHostServer(ResponsesAgentServerHost):
        try:
            await self._ensure_agent_ready()
        except AgentFrameworkException as ex:
-            consent_errors = consent_url_from_error(ex)
-            if consent_errors is None:
+            consent_url = consent_url_from_error(ex)
+            if consent_url is None:
                raise
-            for consent_error in consent_errors:
-                logger.warning("Consent URL for tool '%s': %s", consent_error.name, consent_error.consent_url)
-                oauth_item = OAuthConsentRequestOutputItem(
-                    id=IdGenerator.new_id("oacr"),
-                    consent_link=consent_error.consent_url,
-                    server_label=consent_error.name,
-                )
-                builder = response_event_stream.add_output_item(oauth_item.id)
-                yield builder.emit_added(oauth_item)
-                yield builder.emit_done(oauth_item)
+            logger.warning("OAuth consent required for Foundry MCP gateway.")
+            oauth_item = OAuthConsentRequestOutputItem(
+                id=IdGenerator.new_id("oacr"),
+                consent_link=consent_url,
+                server_label="Foundry Toolbox",
+            )
+            builder = response_event_stream.add_output_item(oauth_item.id)
+            yield builder.emit_added(oauth_item)
+            yield builder.emit_done(oauth_item)
            yield response_event_stream.emit_completed()
            return

@@ -567,7 +521,7 @@ class ResponsesHostServer(ResponsesAgentServerHost):
        by the hosting infrastructure or files will be preserved upon deactivation.
        """
        input_items = await context.get_input_items()
-        input_messages = await _items_to_messages(input_items)
+        input_messages = await _items_to_messages(input_items, approval_storage=self._approval_storage)
        is_streaming_request = request.stream is not None and request.stream is True

        _, are_options_set = _to_chat_options(request)
@@ -664,7 +618,11 @@ class ResponsesHostServer(ResponsesAgentServerHost):
                checkpoint_storage=write_storage,
            )

-            async for item in _to_outputs_for_messages(response_event_stream, response.messages):
+            async for item in _to_outputs_for_messages(
+                response_event_stream,
+                response.messages,
+                approval_storage=self._approval_storage,
+            ):
                yield item

            await self._delete_not_latest_checkpoints(write_storage, self._agent.workflow.name)
@@ -685,7 +643,9 @@ class ResponsesHostServer(ResponsesAgentServerHost):
                for event in tracker.handle(content):
                    yield event
                if tracker.needs_async:
-                    async for item in _to_outputs(response_event_stream, content):
+                    async for item in _to_outputs(
+                        response_event_stream, content, approval_storage=self._approval_storage
+                    ):
                        yield item
                    tracker.needs_async = False

@@ -4,7 +4,7 @@ description = "Foundry Hosting integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0a260604"
+version = "1.0.0a260528"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.8.0,<2",
+    "agent-framework-core>=1.7.0,<2",
    "azure-ai-agentserver-core>=2.0.0b3,<3",
    "azure-ai-agentserver-responses>=1.0.0b7,<2",
    "azure-ai-agentserver-invocations>=1.0.0b3,<2",
@@ -11,24 +11,33 @@ the registered _handle_create handler.
 from __future__ import annotations

 import json
-from collections.abc import AsyncIterator, Callable
+import uuid
+from collections.abc import AsyncIterator, Awaitable, Callable, Sequence
 from dataclasses import dataclass
+from typing import Literal, overload
 from unittest.mock import AsyncMock, MagicMock, patch

 import httpx
 import pytest
 from agent_framework import (
+    AgentExecutorRequest,
    AgentResponse,
    AgentResponseUpdate,
+    AgentSession,
    Content,
    FileCheckpointStorage,
    HistoryProvider,
    Message,
    RawAgent,
    ResponseStream,
+    SupportsAgentRun,
+    WorkflowAgent,
+    WorkflowBuilder,
    WorkflowCheckpoint,
    WorkflowCheckpointException,
+    WorkflowContext,
    WorkflowMessage,
+    executor,
 )
 from azure.ai.agentserver.responses import InMemoryResponseProvider
 from mcp import McpError
@@ -39,7 +48,6 @@ from agent_framework_foundry_hosting import ResponsesHostServer
 from agent_framework_foundry_hosting._responses import (
    _AZURE_RESPONSES_MESSAGE_ROLE_TYPE,  # pyright: ignore[reportPrivateUsage]
    CONSENT_ERROR_CODE,
-    ConsentError,
    FileBasedFunctionApprovalStorage,  # pyright: ignore[reportPrivateUsage]
    InMemoryFunctionApprovalStorage,  # pyright: ignore[reportPrivateUsage]
    _item_to_message,  # pyright: ignore[reportPrivateUsage]
@@ -102,7 +110,7 @@ def _make_agent(
    return agent


-def _make_server(agent: MagicMock, **kwargs: Any) -> ResponsesHostServer:
+def _make_server(agent: Any, **kwargs: Any) -> ResponsesHostServer:
    """Create a ResponsesHostServer with an in-memory store."""
    return ResponsesHostServer(agent, store=InMemoryResponseProvider(), **kwargs)

@@ -3261,10 +3269,7 @@ class TestCheckpointContextPathValidation:
 # region Agent lifecycle (lazy entry & OAuth consent surfacing)


-def _make_consent_error(
-    url: str = "https://consent.example.com/auth",
-    name: str = "Foundry Toolbox",
-) -> Exception:
+def _make_consent_error(url: str = "https://consent.example.com/auth") -> Exception:
    """Build an exception wrapping a Foundry MCP gateway consent error.

    Mirrors the real-world wrapping produced by ``MCPStreamableHTTPTool.__aenter__``,
@@ -3272,34 +3277,17 @@ def _make_consent_error(
    ``ToolExecutionException`` (an ``AgentFrameworkException`` subclass) with the
    original error attached via ``inner_exception``. ``consent_url_from_error``
    then finds the wrapped ``McpError`` in ``exc.args``.
-
-    The McpError message uses the structured Foundry MCP gateway format:
-    a human-readable prefix followed by a JSON document describing each
-    failed tool source and its consent URL.
    """
    from agent_framework.exceptions import ToolExecutionException

-    payload = json.dumps({
-        "errors": [
-            {
-                "name": name,
-                "type": "mcp",
-                "error": {
-                    "code": "CONSENT_REQUIRED",
-                    "message": url,
-                },
-            }
-        ]
-    })
-    message = f"tools/list failed for 1 tool source(s), succeeded for 0 tool source(s) {payload}"
-    inner = McpError(ErrorData(code=CONSENT_ERROR_CODE, message=message))
+    inner = McpError(ErrorData(code=CONSENT_ERROR_CODE, message=url))
    return ToolExecutionException("MCP consent required", inner_exception=inner)


 class TestConsentUrlFromError:
    def test_returns_consent_url_when_inner_arg_is_consent_mcp_error(self) -> None:
-        exc = _make_consent_error("https://example.com/consent", name="my-tool")
-        assert consent_url_from_error(exc) == [ConsentError(name="my-tool", consent_url="https://example.com/consent")]
+        exc = _make_consent_error("https://example.com/consent")
+        assert consent_url_from_error(exc) == "https://example.com/consent"

    def test_returns_none_when_no_mcp_error_in_args(self) -> None:
        assert consent_url_from_error(Exception("boom")) is None
@@ -3316,13 +3304,6 @@ class TestConsentUrlFromError:
        bare = McpError(ErrorData(code=CONSENT_ERROR_CODE, message="https://x"))
        assert consent_url_from_error(bare) is None

-    def test_returns_none_when_message_has_no_json(self) -> None:
-        from agent_framework.exceptions import ToolExecutionException
-
-        inner = McpError(ErrorData(code=CONSENT_ERROR_CODE, message="no json here"))
-        exc = ToolExecutionException("MCP consent required", inner_exception=inner)
-        assert consent_url_from_error(exc) is None
-

 class TestAgentLifecycle:
    async def test_agent_entered_lazily_on_first_request(self) -> None:
@@ -3469,3 +3450,498 @@ class TestOAuthConsentSurfacing:


 # endregion
+
+# region Workflow agent hosting (end-to-end)
+
+
+class _ToolApprovalWorkflowAgentMock(SupportsAgentRun):
+    """Inner agent for a hosted ``WorkflowAgent`` whose first run emits a
+    ``FunctionApprovalRequestContent`` and whose follow-up run (after
+    receiving a ``FunctionApprovalResponseContent`` in its inputs) returns a
+    final assistant text response.
+
+    Mirrors a real agent whose tool invocation requires user approval. Used
+    here to exercise the full HTTP pipeline through ``ResponsesHostServer``
+    when the hosted agent is a ``WorkflowAgent`` containing a tool-approval
+    flow.
+    """
+
+    def __init__(
+        self,
+        name: str,
+        *,
+        tool_name: str = "delete_file",
+        tool_arguments: dict[str, Any] | None = None,
+        approval_request_ids: Sequence[str] | None = None,
+        final_text: str = "done",
+    ) -> None:
+        self.id = str(uuid.uuid4())
+        self.name = name
+        self.description: str | None = None
+        self._tool_name = tool_name
+        self._tool_arguments = tool_arguments or {"path": "/tmp/example"}
+        self._approval_request_ids: list[str] = list(approval_request_ids) if approval_request_ids else []
+        self._final_text = final_text
+        self.run_count = 0
+        self.last_run_messages: list[Message] = []
+
+    def create_session(self, **kwargs: Any) -> AgentSession:
+        return AgentSession()
+
+    def get_session(self, *, service_session_id: str, **kwargs: Any) -> AgentSession:
+        return AgentSession()
+
+    def _next_request_id(self) -> str:
+        # Stable across calls: when the workflow checkpoint round-trips through
+        # restore, ``AgentExecutor`` re-invokes the inner agent during replay.
+        # We must surface the *same* approval request id on each invocation so
+        # the workflow's pending-request id matches the id the test echoes
+        # back as ``mcp_approval_response``.
+        if self._approval_request_ids:
+            return self._approval_request_ids[0]
+        return str(uuid.uuid4())
+
+    def _build_approval_request(self) -> Content:
+        request_id = self._next_request_id()
+        function_call = Content.from_function_call(
+            call_id=request_id,
+            name=self._tool_name,
+            arguments=self._tool_arguments,
+            additional_properties={"server_label": "test_server"},
+        )
+        return Content.from_function_approval_request(id=request_id, function_call=function_call)
+
+    @overload
+    def run(
+        self,
+        messages: str | Content | Message | Sequence[str | Content | Message] | None = ...,
+        *,
+        stream: Literal[False] = ...,
+        session: AgentSession | None = ...,
+        **kwargs: Any,
+    ) -> Awaitable[AgentResponse[Any]]: ...
+
+    @overload
+    def run(
+        self,
+        messages: str | Content | Message | Sequence[str | Content | Message] | None = ...,
+        *,
+        stream: Literal[True],
+        session: AgentSession | None = ...,
+        **kwargs: Any,
+    ) -> ResponseStream[AgentResponseUpdate, AgentResponse[Any]]: ...
+
+    def run(
+        self,
+        messages: str | Content | Message | Sequence[str | Content | Message] | None = None,
+        *,
+        stream: bool = False,
+        session: AgentSession | None = None,
+        **kwargs: Any,
+    ) -> Awaitable[AgentResponse] | ResponseStream[AgentResponseUpdate, AgentResponse]:
+        if stream:
+            return self._run_stream(messages=messages, **kwargs)
+        return self._run(messages=messages, **kwargs)
+
+    @staticmethod
+    def _normalize(
+        messages: str | Content | Message | Sequence[str | Content | Message] | None,
+    ) -> list[Message]:
+        if messages is None:
+            return []
+        if isinstance(messages, str):
+            return [Message(role="user", contents=[Content.from_text(text=messages)])]
+        if isinstance(messages, Message):
+            return [messages]
+        if isinstance(messages, Content):
+            return [Message(role="user", contents=[messages])]
+        result: list[Message] = []
+        for item in messages:
+            if isinstance(item, Message):
+                result.append(item)
+            elif isinstance(item, Content):
+                result.append(Message(role="user", contents=[item]))
+            else:
+                result.append(Message(role="user", contents=[Content.from_text(text=item)]))
+        return result
+
+    @staticmethod
+    def _approval_responses_in(messages: list[Message]) -> list[Content]:
+        return [c for m in messages for c in m.contents if c.type == "function_approval_response"]
+
+    async def _run(
+        self,
+        messages: str | Content | Message | Sequence[str | Content | Message] | None = None,
+        **kwargs: Any,
+    ) -> AgentResponse:
+        normalized = self._normalize(messages)
+        self.last_run_messages = normalized
+        self.run_count += 1
+        if self._approval_responses_in(normalized):
+            return AgentResponse(messages=[Message("assistant", [Content.from_text(text=self._final_text)])])
+        approval = self._build_approval_request()
+        return AgentResponse(messages=[Message("assistant", [approval])])
+
+    def _run_stream(
+        self,
+        messages: str | Content | Message | Sequence[str | Content | Message] | None = None,
+        **kwargs: Any,
+    ) -> ResponseStream[AgentResponseUpdate, AgentResponse]:
+        normalized = self._normalize(messages)
+        self.last_run_messages = normalized
+        self.run_count += 1
+        approvals = self._approval_responses_in(normalized)
+
+        async def _iter() -> AsyncIterator[AgentResponseUpdate]:
+            if approvals:
+                yield AgentResponseUpdate(
+                    contents=[Content.from_text(text=self._final_text)],
+                    role="assistant",
+                    author_name=self.name,
+                )
+                return
+            yield AgentResponseUpdate(
+                contents=[self._build_approval_request()],
+                role="assistant",
+                author_name=self.name,
+            )
+
+        return ResponseStream(_iter(), finalizer=AgentResponse.from_updates)
+
+
+def _build_text_workflow_agent(text: str) -> WorkflowAgent:
+    """Build a minimal ``WorkflowAgent`` whose inner agent emits a fixed text."""
+
+    class _TextAgent(SupportsAgentRun):
+        def __init__(self, name: str, text: str) -> None:
+            self.id = str(uuid.uuid4())
+            self.name = name
+            self.description: str | None = None
+            self._text = text
+
+        def create_session(self, **kwargs: Any) -> AgentSession:
+            return AgentSession()
+
+        def get_session(self, *, service_session_id: str, **kwargs: Any) -> AgentSession:
+            return AgentSession()
+
+        @overload
+        def run(
+            self,
+            messages: Any = ...,
+            *,
+            stream: Literal[False] = ...,
+            session: AgentSession | None = ...,
+            **kwargs: Any,
+        ) -> Awaitable[AgentResponse[Any]]: ...
+
+        @overload
+        def run(
+            self,
+            messages: Any = ...,
+            *,
+            stream: Literal[True],
+            session: AgentSession | None = ...,
+            **kwargs: Any,
+        ) -> ResponseStream[AgentResponseUpdate, AgentResponse[Any]]: ...
+
+        def run(
+            self,
+            messages: Any = None,
+            *,
+            stream: bool = False,
+            session: AgentSession | None = None,
+            **kwargs: Any,
+        ) -> Awaitable[AgentResponse] | ResponseStream[AgentResponseUpdate, AgentResponse]:
+            text = self._text
+            name = self.name
+
+            async def _aresult() -> AgentResponse:
+                return AgentResponse(messages=[Message("assistant", [Content.from_text(text=text)])])
+
+            async def _aiter() -> AsyncIterator[AgentResponseUpdate]:
+                yield AgentResponseUpdate(
+                    contents=[Content.from_text(text=text)],
+                    role="assistant",
+                    author_name=name,
+                )
+
+            if stream:
+                return ResponseStream(_aiter(), finalizer=AgentResponse.from_updates)
+            return _aresult()
+
+    inner = _TextAgent("text-agent", text)
+
+    @executor
+    async def start(messages: list[Message], ctx: WorkflowContext[AgentExecutorRequest]) -> None:
+        await ctx.send_message(AgentExecutorRequest(messages=messages, should_respond=True))
+
+    workflow = WorkflowBuilder(start_executor=start).add_edge(start, inner).build()
+    return WorkflowAgent(workflow=workflow, name="Text Workflow Agent")
+
+
+def _build_approval_workflow_agent(
+    *,
+    approval_request_id: str,
+    tool_name: str = "delete_file",
+    tool_arguments: dict[str, Any] | None = None,
+    final_text: str = "done",
+) -> tuple[WorkflowAgent, _ToolApprovalWorkflowAgentMock]:
+    """Build a ``WorkflowAgent`` whose inner agent emits a tool approval request."""
+    mock_agent = _ToolApprovalWorkflowAgentMock(
+        name="approval-agent",
+        tool_name=tool_name,
+        tool_arguments=tool_arguments or {"path": "/tmp/secret.txt"},
+        approval_request_ids=[approval_request_id],
+        final_text=final_text,
+    )
+
+    @executor
+    async def start(messages: list[Message], ctx: WorkflowContext[AgentExecutorRequest]) -> None:
+        await ctx.send_message(AgentExecutorRequest(messages=messages, should_respond=True))
+
+    workflow = WorkflowBuilder(start_executor=start).add_edge(start, mock_agent).build()
+    workflow_agent = WorkflowAgent(workflow=workflow, name="Approval Workflow Agent")
+    return workflow_agent, mock_agent
+
+
+class TestWorkflowAgentHosting:
+    """End-to-end HTTP tests for ``ResponsesHostServer`` hosting a ``WorkflowAgent``.
+
+    These tests drive ``_handle_inner_workflow`` through the ASGI stack:
+    they exercise checkpoint write/restore (multi-turn) and the
+    tool-approval round-trip path, which is the primary differentiator
+    relative to the regular agent path.
+    """
+
+    async def test_basic_text_response(self) -> None:
+        workflow_agent = _build_text_workflow_agent("hello from workflow")
+        server = _make_server(workflow_agent)
+
+        resp = await _post(server, input_text="hi", stream=False)
+        assert resp.status_code == 200
+        body = resp.json()
+        assert body["status"] == "completed"
+
+        text_found = any(
+            part.get("type") == "output_text" and part.get("text") == "hello from workflow"
+            for item in body["output"]
+            if item["type"] == "message"
+            for part in item.get("content", [])
+        )
+        assert text_found, f"Expected workflow output text in {body['output']}"
+
+    async def test_basic_text_response_streaming(self) -> None:
+        workflow_agent = _build_text_workflow_agent("hello stream")
+        server = _make_server(workflow_agent)
+
+        resp = await _post(server, input_text="hi", stream=True)
+        assert resp.status_code == 200
+        events = _parse_sse_events(resp.text)
+        types = _sse_event_types(events)
+        assert types[0] == "response.created"
+        assert types[-1] == "response.completed"
+        assert "response.output_text.delta" in types
+        text_done = [e for e in events if e["event"] == "response.output_text.done"]
+        assert any(e["data"]["text"] == "hello stream" for e in text_done)
+
+    async def test_non_streaming_emits_mcp_approval_request_and_persists_to_storage(self) -> None:
+        workflow_agent, mock_agent = _build_approval_workflow_agent(approval_request_id="apr_wf_ns")
+        server = _make_server(workflow_agent)
+
+        resp = await _post(server, stream=False)
+        assert resp.status_code == 200
+        body = resp.json()
+        assert body["status"] == "completed"
+
+        approval_items = [it for it in body["output"] if it["type"] == "mcp_approval_request"]
+        assert len(approval_items) == 1
+        assert approval_items[0]["name"] == "delete_file"
+        assert approval_items[0]["server_label"] == "test_server"
+        approval_request_id = approval_items[0]["id"]
+
+        # The id surfaced over the wire is generated by the response stream
+        # builder; the original approval ``Content`` (carrying the inner
+        # ``function_call``) must be persisted under that id so the next
+        # turn can reconstruct it.
+        loaded = await server._approval_storage.load_approval_request(  # pyright: ignore[reportPrivateUsage]
+            approval_request_id
+        )
+        assert loaded.type == "function_approval_request"
+        assert loaded.function_call.name == "delete_file"  # type: ignore[attr-defined]
+        assert mock_agent.run_count == 1
+
+    async def test_streaming_emits_mcp_approval_request_and_persists_to_storage(self) -> None:
+        workflow_agent, mock_agent = _build_approval_workflow_agent(approval_request_id="apr_wf_st")
+        server = _make_server(workflow_agent)
+
+        resp = await _post(server, stream=True)
+        assert resp.status_code == 200
+
+        events = _parse_sse_events(resp.text)
+        types = _sse_event_types(events)
+        assert types[0] == "response.created"
+        assert types[-1] == "response.completed"
+
+        approval_request_id: str | None = None
+        for e in events:
+            if e["event"] != "response.output_item.added":
+                continue
+            item = e["data"].get("item") or {}
+            if item.get("type") == "mcp_approval_request":
+                approval_request_id = item.get("id")
+                break
+        assert approval_request_id is not None
+
+        loaded = await server._approval_storage.load_approval_request(  # pyright: ignore[reportPrivateUsage]
+            approval_request_id
+        )
+        assert loaded.type == "function_approval_request"
+        assert mock_agent.run_count == 1
+
+    async def test_round_trip_approval_response_resumes_workflow_agent(self) -> None:
+        """Two-turn HTTP round-trip:
+
+        Turn 1 emits ``mcp_approval_request`` and writes a workflow
+        checkpoint under the response id. Turn 2 sends the
+        ``mcp_approval_response`` with ``previous_response_id`` set, so the
+        host restores the checkpoint, the WorkflowAgent routes the
+        approval response back to the paused inner agent, and the inner
+        agent emits the final assistant text.
+        """
+        workflow_agent, mock_agent = _build_approval_workflow_agent(
+            approval_request_id="apr_wf_rt",
+            final_text="done with approval",
+        )
+        server = _make_server(workflow_agent)
+
+        first = await _post(server, stream=False)
+        assert first.status_code == 200
+        first_body = first.json()
+        first_response_id = first_body["id"]
+        approval_items = [it for it in first_body["output"] if it["type"] == "mcp_approval_request"]
+        assert len(approval_items) == 1
+        approval_request_id = approval_items[0]["id"]
+        assert mock_agent.run_count == 1
+
+        second_payload: dict[str, Any] = {
+            "model": "test-model",
+            "input": [
+                {
+                    "type": "mcp_approval_response",
+                    "approval_request_id": approval_request_id,
+                    "approve": True,
+                }
+            ],
+            "stream": False,
+            "previous_response_id": first_response_id,
+        }
+        second = await _post_json(server, second_payload)
+        assert second.status_code == 200
+        second_body = second.json()
+        assert second_body["status"] == "completed"
+
+        # The inner agent must have been resumed (restore replay + new turn).
+        # Restore call is a no-op for the mock (no input); the new-turn call
+        # delivers the approval response, so run_count grows by at least 1.
+        assert mock_agent.run_count >= 2
+
+        # The final assistant text from the resumed inner agent surfaces in
+        # the HTTP output.
+        text_pieces = [
+            part.get("text", "")
+            for item in second_body["output"]
+            if item["type"] == "message"
+            for part in item.get("content", [])
+            if part.get("type") == "output_text"
+        ]
+        assert any("done with approval" in t for t in text_pieces), (
+            f"expected resumed workflow output, got {second_body['output']}"
+        )
+
+        # The new-turn invocation of the inner agent must have received the
+        # approval response routed back through WorkflowAgent.
+        approval_responses = [
+            c for m in mock_agent.last_run_messages for c in m.contents if c.type == "function_approval_response"
+        ]
+        assert len(approval_responses) == 1
+        assert approval_responses[0].approved is True  # type: ignore[attr-defined]
+
+    async def test_round_trip_approval_response_streaming(self) -> None:
+        """Streaming variant of the round-trip: turn 2 is requested with
+        ``stream=true`` and surfaces the resumed text as SSE events."""
+        workflow_agent, mock_agent = _build_approval_workflow_agent(
+            approval_request_id="apr_wf_rt_st",
+            final_text="streamed-done",
+        )
+        server = _make_server(workflow_agent)
+
+        first = await _post(server, stream=False)
+        first_body = first.json()
+        first_response_id = first_body["id"]
+        approval_request_id = next(it["id"] for it in first_body["output"] if it["type"] == "mcp_approval_request")
+
+        second = await _post_json(
+            server,
+            {
+                "model": "test-model",
+                "input": [
+                    {
+                        "type": "mcp_approval_response",
+                        "approval_request_id": approval_request_id,
+                        "approve": True,
+                    }
+                ],
+                "stream": True,
+                "previous_response_id": first_response_id,
+            },
+        )
+        assert second.status_code == 200
+        events = _parse_sse_events(second.text)
+        types = _sse_event_types(events)
+        assert types[0] == "response.created"
+        assert types[-1] == "response.completed"
+
+        text_done = [e for e in events if e["event"] == "response.output_text.done"]
+        assert any("streamed-done" in e["data"]["text"] for e in text_done)
+        assert mock_agent.run_count >= 2
+
+    async def test_round_trip_approval_response_rejected(self) -> None:
+        """Sending ``approve=False`` must surface as ``approved=False`` to the
+        inner agent on resume."""
+        workflow_agent, mock_agent = _build_approval_workflow_agent(
+            approval_request_id="apr_wf_reject",
+            final_text="acknowledged",
+        )
+        server = _make_server(workflow_agent)
+
+        first = await _post(server, stream=False)
+        first_body = first.json()
+        first_response_id = first_body["id"]
+        approval_request_id = next(it["id"] for it in first_body["output"] if it["type"] == "mcp_approval_request")
+
+        second = await _post_json(
+            server,
+            {
+                "model": "test-model",
+                "input": [
+                    {
+                        "type": "mcp_approval_response",
+                        "approval_request_id": approval_request_id,
+                        "approve": False,
+                    }
+                ],
+                "stream": False,
+                "previous_response_id": first_response_id,
+            },
+        )
+        assert second.status_code == 200
+
+        approval_responses = [
+            c for m in mock_agent.last_run_messages for c in m.contents if c.type == "function_approval_response"
+        ]
+        assert len(approval_responses) == 1
+        assert approval_responses[0].approved is False  # type: ignore[attr-defined]
+
+
+# endregion
@@ -37,10 +37,9 @@ from agent_framework.exceptions import AgentException
 from agent_framework.observability import AgentTelemetryLayer

 try:
-    from copilot import CopilotClient, CopilotSession, RuntimeConnection
-    from copilot.generated.rpc import PermissionDecisionUserNotAvailable
+    from copilot import CopilotClient, CopilotSession, SubprocessConfig
+    from copilot.generated.session_events import PermissionRequest, SessionEvent, SessionEventType
    from copilot.session import MCPServerConfig, PermissionRequestResult, ProviderConfig, SystemMessageConfig
-    from copilot.session_events import PermissionRequest, SessionEvent, SessionEventType
    from copilot.tools import Tool as CopilotTool
    from copilot.tools import ToolInvocation, ToolResult
 except ImportError as _copilot_import_error:
@@ -58,10 +57,8 @@ else:
 DEFAULT_TIMEOUT_SECONDS: float = 60.0
 """Default timeout in seconds for Copilot requests."""

-PermissionHandlerType = Callable[
-    [PermissionRequest, dict[str, str]], "PermissionRequestResult | Awaitable[PermissionRequestResult]"
-]
-"""Type for permission request handlers. Supports both sync and async callbacks."""
+PermissionHandlerType = Callable[[PermissionRequest, dict[str, str]], PermissionRequestResult]
+"""Type for permission request handlers."""


 FunctionApprovalCallback = Callable[[Content], "bool | Awaitable[bool]"]
@@ -124,7 +121,7 @@ def _deny_all_permissions(
    _invocation: dict[str, str],
 ) -> PermissionRequestResult:
    """Default permission handler that denies all requests."""
-    return PermissionDecisionUserNotAvailable()
+    return PermissionRequestResult()


 class GitHubCopilotSettings(TypedDict, total=False):
@@ -143,9 +140,9 @@ class GitHubCopilotSettings(TypedDict, total=False):
            Can be set via environment variable GITHUB_COPILOT_TIMEOUT.
        log_level: CLI log level.
            Can be set via environment variable GITHUB_COPILOT_LOG_LEVEL.
-        base_directory: Directory where the CLI stores session state, configuration,
+        copilot_home: Directory where the CLI stores session state, configuration,
            and other persistent data. Can be set via environment variable
-            GITHUB_COPILOT_BASE_DIRECTORY. Defaults to ~/.copilot when not set.
+            GITHUB_COPILOT_COPILOT_HOME. Defaults to ~/.copilot when not set.
            Only applicable when the SDK spawns the CLI process (ignored when
            connecting to an external server via a pre-configured client).
    """
@@ -154,7 +151,7 @@ class GitHubCopilotSettings(TypedDict, total=False):
    model: str | None
    timeout: float | None
    log_level: str | None
-    base_directory: str | None
+    copilot_home: str | None


 class GitHubCopilotOptions(TypedDict, total=False):
@@ -317,7 +314,7 @@ class RawGitHubCopilotAgent(BaseAgent, Generic[OptionsT]):
        provider: ProviderConfig | None = opts.pop("provider", None)
        instruction_directories: list[str] | None = opts.pop("instruction_directories", None)
        on_function_approval: FunctionApprovalCallback | None = opts.pop("on_function_approval", None)
-        base_directory = opts.pop("base_directory", None)
+        copilot_home = opts.pop("copilot_home", None)

        self._settings = load_settings(
            GitHubCopilotSettings,
@@ -326,7 +323,7 @@ class RawGitHubCopilotAgent(BaseAgent, Generic[OptionsT]):
            model=model,
            timeout=timeout,
            log_level=log_level,
-            base_directory=base_directory,
+            copilot_home=copilot_home,
            env_file_path=env_file_path,
            env_file_encoding=env_file_encoding,
        )
@@ -365,16 +362,14 @@ class RawGitHubCopilotAgent(BaseAgent, Generic[OptionsT]):
        if self._client is None:
            cli_path = self._settings.get("cli_path") or None
            log_level = self._settings.get("log_level") or None
-            base_directory = self._settings.get("base_directory") or None
+            copilot_home = self._settings.get("copilot_home") or None

-            client_kwargs: dict[str, Any] = {}
-            if cli_path:
-                client_kwargs["connection"] = RuntimeConnection.for_stdio(path=cli_path)
+            subprocess_kwargs: dict[str, Any] = {"cli_path": cli_path}
            if log_level:
-                client_kwargs["log_level"] = log_level
-            if base_directory:
-                client_kwargs["base_directory"] = base_directory
-            self._client = CopilotClient(**client_kwargs)
+                subprocess_kwargs["log_level"] = log_level
+            if copilot_home:
+                subprocess_kwargs["copilot_home"] = copilot_home
+            self._client = CopilotClient(SubprocessConfig(**subprocess_kwargs))

        try:
            await self._client.start()
@@ -4,7 +4,7 @@ description = "GitHub Copilot integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0rc1"
+version = "1.0.0b260521"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,8 +23,8 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.8.0,<2",
-    "github-copilot-sdk>=1.0.0,<2; python_version >= '3.11'",
+    "agent-framework-core>=1.6.0,<2",
+    "github-copilot-sdk>=1.0.0b2,<=1.0.0b2; python_version >= '3.11'",
 ]

 [tool.uv]
@@ -2,7 +2,6 @@

 # ruff: noqa: E402

-import os
 import unittest.mock
 from datetime import datetime, timezone
 from typing import Any
@@ -21,11 +20,9 @@ from agent_framework import (
    ContextProvider,
    HistoryProvider,
    Message,
-    tool,
 )
 from agent_framework.exceptions import AgentException
-from copilot.session import PermissionHandler
-from copilot.session_events import (
+from copilot.generated.session_events import (
    Data,
    SessionEvent,
    SessionEventType,
@@ -311,27 +308,27 @@ class TestGitHubCopilotAgentLifecycle:
            )
            await agent.start()

-            kwargs = MockClient.call_args.kwargs
-            assert kwargs["connection"].path == "/custom/path"
-            assert kwargs["log_level"] == "debug"
+            call_args = MockClient.call_args[0][0]
+            assert call_args.cli_path == "/custom/path"
+            assert call_args.log_level == "debug"

-    async def test_start_passes_base_directory_to_client(self) -> None:
-        """Test that base_directory is passed through to CopilotClient."""
+    async def test_start_passes_copilot_home_to_subprocess_config(self) -> None:
+        """Test that copilot_home is passed through to SubprocessConfig."""
        with patch("agent_framework_github_copilot._agent.CopilotClient") as MockClient:
            mock_client = MagicMock()
            mock_client.start = AsyncMock()
            MockClient.return_value = mock_client

            agent: GitHubCopilotAgent[GitHubCopilotOptions] = GitHubCopilotAgent(
-                default_options={"base_directory": "/custom/copilot/home"}
+                default_options={"copilot_home": "/custom/copilot/home"}
            )
            await agent.start()

-            kwargs = MockClient.call_args.kwargs
-            assert kwargs["base_directory"] == "/custom/copilot/home"
+            call_args = MockClient.call_args[0][0]
+            assert call_args.copilot_home == "/custom/copilot/home"

-    async def test_start_base_directory_not_set_when_unspecified(self) -> None:
-        """Test that base_directory is not included in client kwargs when not specified."""
+    async def test_start_copilot_home_not_set_when_unspecified(self) -> None:
+        """Test that copilot_home is not included in SubprocessConfig when not specified."""
        with patch("agent_framework_github_copilot._agent.CopilotClient") as MockClient:
            mock_client = MagicMock()
            mock_client.start = AsyncMock()
@@ -340,14 +337,14 @@ class TestGitHubCopilotAgentLifecycle:
            agent = GitHubCopilotAgent()
            await agent.start()

-            kwargs = MockClient.call_args.kwargs
-            assert "base_directory" not in kwargs
+            call_args = MockClient.call_args[0][0]
+            assert call_args.copilot_home is None

-    async def test_start_base_directory_from_env_variable(self) -> None:
-        """Test that base_directory can be set via GITHUB_COPILOT_BASE_DIRECTORY env variable."""
+    async def test_start_copilot_home_from_env_variable(self) -> None:
+        """Test that copilot_home can be set via GITHUB_COPILOT_COPILOT_HOME env variable."""
        with (
            patch("agent_framework_github_copilot._agent.CopilotClient") as MockClient,
-            patch.dict("os.environ", {"GITHUB_COPILOT_BASE_DIRECTORY": "/env/copilot/home"}),
+            patch.dict("os.environ", {"GITHUB_COPILOT_COPILOT_HOME": "/env/copilot/home"}),
        ):
            mock_client = MagicMock()
            mock_client.start = AsyncMock()
@@ -356,8 +353,8 @@ class TestGitHubCopilotAgentLifecycle:
            agent = GitHubCopilotAgent()
            await agent.start()

-            kwargs = MockClient.call_args.kwargs
-            assert kwargs["base_directory"] == "/env/copilot/home"
+            call_args = MockClient.call_args[0][0]
+            assert call_args.copilot_home == "/env/copilot/home"


 class TestGitHubCopilotAgentRun:
@@ -1056,11 +1053,11 @@ class TestGitHubCopilotAgentSessionManagement:
        mock_session: MagicMock,
    ) -> None:
        """Test that resumed session config includes tools and permission handler."""
-        from copilot.session import PermissionDecisionApproveOnce, PermissionRequestResult
-        from copilot.session_events import PermissionRequest
+        from copilot.generated.session_events import PermissionRequest
+        from copilot.session import PermissionRequestResult

        def my_handler(request: PermissionRequest, context: dict[str, str]) -> PermissionRequestResult:
-            return PermissionDecisionApproveOnce()
+            return PermissionRequestResult(kind="approved")

        def my_tool(arg: str) -> str:
            """A test tool."""
@@ -1872,15 +1869,6 @@ class TestGitHubCopilotAgentErrorHandling:
 class TestGitHubCopilotAgentPermissions:
    """Test cases for permission handling."""

-    def test_deny_all_permissions_returns_user_not_available(self) -> None:
-        """Test that the default deny handler returns PermissionDecisionUserNotAvailable."""
-        from copilot.generated.rpc import PermissionDecisionUserNotAvailable
-
-        from agent_framework_github_copilot._agent import _deny_all_permissions
-
-        result = _deny_all_permissions(MagicMock(), {})
-        assert isinstance(result, PermissionDecisionUserNotAvailable)
-
    def test_no_permission_handler_when_not_provided(self) -> None:
        """Test that no handler is set when on_permission_request is not provided."""
        agent = GitHubCopilotAgent()
@@ -1888,14 +1876,13 @@ class TestGitHubCopilotAgentPermissions:

    def test_permission_handler_set_when_provided(self) -> None:
        """Test that a handler is set when on_permission_request is provided."""
-        from copilot.generated.rpc import PermissionDecisionDeniedInteractivelyByUser
-        from copilot.session import PermissionDecisionApproveOnce, PermissionRequestResult
-        from copilot.session_events import PermissionRequest
+        from copilot.generated.session_events import PermissionRequest
+        from copilot.session import PermissionRequestResult

        def approve_shell(request: PermissionRequest, context: dict[str, str]) -> PermissionRequestResult:
            if request.kind == "shell":
-                return PermissionDecisionApproveOnce()
-            return PermissionDecisionDeniedInteractivelyByUser()
+                return PermissionRequestResult(kind="approved")
+            return PermissionRequestResult(kind="denied-interactively-by-user")

        agent: GitHubCopilotAgent[GitHubCopilotOptions] = GitHubCopilotAgent(
            default_options={"on_permission_request": approve_shell}
@@ -1908,14 +1895,13 @@ class TestGitHubCopilotAgentPermissions:
        mock_session: MagicMock,
    ) -> None:
        """Test that session config includes permission handler when provided."""
-        from copilot.generated.rpc import PermissionDecisionDeniedInteractivelyByUser
-        from copilot.session import PermissionDecisionApproveOnce, PermissionRequestResult
-        from copilot.session_events import PermissionRequest
+        from copilot.generated.session_events import PermissionRequest
+        from copilot.session import PermissionRequestResult

        def approve_shell_read(request: PermissionRequest, context: dict[str, str]) -> PermissionRequestResult:
            if request.kind in ("shell", "read"):
-                return PermissionDecisionApproveOnce()
-            return PermissionDecisionDeniedInteractivelyByUser()
+                return PermissionRequestResult(kind="approved")
+            return PermissionRequestResult(kind="denied-interactively-by-user")

        agent: GitHubCopilotAgent[GitHubCopilotOptions] = GitHubCopilotAgent(
            client=mock_client,
@@ -2719,163 +2705,3 @@ class TestGitHubCopilotAgentContextProviders:
        assert call_kwargs.get("tools") is not None
        tool_names = [t.name for t in call_kwargs["tools"]]
        assert "load_skill" in tool_names
-
-
-# ---------------------------------------------------------------------------
-# Integration tests — require COPILOT_GITHUB_TOKEN env var
-# ---------------------------------------------------------------------------
-
-skip_if_copilot_integration_tests_disabled = pytest.mark.skipif(
-    os.getenv("COPILOT_GITHUB_TOKEN", "") == "",
-    reason="No COPILOT_GITHUB_TOKEN provided; skipping integration tests.",
-)
-
-
-@tool(approval_mode="never_require")
-def get_weather(location: str) -> str:
-    """Get the weather for a given location."""
-    return f"The weather in {location} is sunny with a high of 25C."
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_copilot_integration_tests_disabled
-async def test_integration_run_with_simple_prompt_returns_response() -> None:
-    """Integration test: basic non-streaming response."""
-    agent = GitHubCopilotAgent(
-        instructions="You are a helpful assistant. Keep your answers short.",
-        default_options={"on_permission_request": PermissionHandler.approve_all},
-    )
-
-    async with agent:
-        session = agent.create_session()
-        response = await agent.run("What is 2 + 2? Answer with just the number.", session=session)
-
-        assert response is not None
-        assert len(response.messages) > 0
-        assert "4" in response.text
-
-        if session.service_session_id and agent._client:
-            await agent._client.delete_session(session.service_session_id)
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_copilot_integration_tests_disabled
-async def test_integration_run_streaming_returns_updates() -> None:
-    """Integration test: streaming response yields updates."""
-    agent = GitHubCopilotAgent(
-        instructions="You are a helpful assistant. Keep your answers short.",
-        default_options={"on_permission_request": PermissionHandler.approve_all},
-    )
-
-    async with agent:
-        session = agent.create_session()
-        updates = []
-        async for chunk in agent.run("Count from 1 to 5.", stream=True, session=session):
-            updates.append(chunk)
-
-        assert len(updates) > 0
-        full_text = "".join(u.text for u in updates if u.text)
-        assert len(full_text) > 0
-
-        if session.service_session_id and agent._client:
-            await agent._client.delete_session(session.service_session_id)
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_copilot_integration_tests_disabled
-async def test_integration_run_with_function_tool_invokes_tool() -> None:
-    """Integration test: function tool is invoked by the agent."""
-    agent = GitHubCopilotAgent(
-        instructions="You are a helpful weather agent. Use the get_weather tool to answer weather questions.",
-        tools=[get_weather],
-        default_options={"on_permission_request": PermissionHandler.approve_all},
-    )
-
-    async with agent:
-        session = agent.create_session()
-        response = await agent.run("What's the weather like in Seattle?", session=session)
-
-        assert response is not None
-        assert len(response.messages) > 0
-        assert any(word in response.text.lower() for word in ["sunny", "25", "weather", "seattle"])
-
-        if session.service_session_id and agent._client:
-            await agent._client.delete_session(session.service_session_id)
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_copilot_integration_tests_disabled
-async def test_integration_run_with_session_maintains_context() -> None:
-    """Integration test: session maintains conversation context across turns."""
-    agent = GitHubCopilotAgent(
-        instructions="You are a helpful assistant. Keep your answers short.",
-        default_options={"on_permission_request": PermissionHandler.approve_all},
-    )
-
-    async with agent:
-        session = agent.create_session()
-
-        response1 = await agent.run("My name is Alice.", session=session)
-        assert response1 is not None
-
-        response2 = await agent.run("What is my name?", session=session)
-
-        assert response2 is not None
-        assert "alice" in response2.text.lower()
-
-        if session.service_session_id and agent._client:
-            await agent._client.delete_session(session.service_session_id)
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_copilot_integration_tests_disabled
-async def test_integration_run_with_session_resume_continues_conversation() -> None:
-    """Integration test: session can be resumed by ID."""
-    agent = GitHubCopilotAgent(
-        instructions="You are a helpful assistant. Keep your answers short.",
-        default_options={"on_permission_request": PermissionHandler.approve_all},
-    )
-
-    async with agent:
-        session1 = agent.create_session()
-        await agent.run("Remember this number: 42.", session=session1)
-
-        session_id = session1.service_session_id
-        assert session_id is not None
-
-        session2 = AgentSession()
-        session2.service_session_id = session_id
-
-        response = await agent.run("What number did I ask you to remember?", session=session2)
-
-        assert response is not None
-        assert "42" in response.text
-
-        if agent._client:
-            await agent._client.delete_session(session_id)
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_copilot_integration_tests_disabled
-async def test_integration_run_with_shell_permissions_executes_command() -> None:
-    """Integration test: shell commands can be executed with permission handler."""
-    agent = GitHubCopilotAgent(
-        instructions="You are a helpful assistant that can execute shell commands.",
-        default_options={"on_permission_request": PermissionHandler.approve_all},
-    )
-
-    async with agent:
-        session = agent.create_session()
-        response = await agent.run("Run a shell command to print 'hello world'", session=session)
-
-        assert response is not None
-        assert "hello" in response.text.lower()
-
-        if session.service_session_id and agent._client:
-            await agent._client.delete_session(session.service_session_id)
@@ -4,7 +4,7 @@ description = "Mistral AI integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0a260604"
+version = "1.0.0a260505"
 license-files = ["LICENSE"]
 urls.homepage = "https://learn.microsoft.com/en-us/agent-framework/"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.8.0,<2",
+    "agent-framework-core>=1.1.0,<2",
    "mistralai>=2.0.0,<3",
 ]

@@ -385,7 +385,6 @@ class RawOpenAIChatClient(  # type: ignore[misc]
        additional_properties: dict[str, Any] | None = None,
        env_file_path: str | None = None,
        env_file_encoding: str | None = None,
-        timeout: float | None = None,
    ) -> None:
        """Initialize a raw OpenAI Chat client.

@@ -407,7 +406,6 @@ class RawOpenAIChatClient(  # type: ignore[misc]
            env_file_path: Optional ``.env`` file that is checked before the process environment
                for ``OPENAI_*`` values.
            env_file_encoding: Encoding for the ``.env`` file.
-            timeout: Optional timeout in seconds for requests.
        """
        ...

@@ -429,7 +427,6 @@ class RawOpenAIChatClient(  # type: ignore[misc]
        additional_properties: dict[str, Any] | None = None,
        env_file_path: str | None = None,
        env_file_encoding: str | None = None,
-        timeout: float | None = None,
    ) -> None:
        """Initialize a raw OpenAI Chat client.

@@ -458,7 +455,6 @@ class RawOpenAIChatClient(  # type: ignore[misc]
            env_file_path: Optional ``.env`` file that is checked before process environment
                variables for ``AZURE_OPENAI_*`` values.
            env_file_encoding: Encoding for the ``.env`` file.
-            timeout: Optional timeout in seconds for requests.
        """
        ...

@@ -480,7 +476,6 @@ class RawOpenAIChatClient(  # type: ignore[misc]
        additional_properties: dict[str, Any] | None = None,
        env_file_path: str | None = None,
        env_file_encoding: str | None = None,
-        timeout: float | None = None,
    ) -> None:
        """Initialize a raw OpenAI Chat client.

@@ -516,8 +511,6 @@ class RawOpenAIChatClient(  # type: ignore[misc]
                variables. The same file is used for both ``OPENAI_*`` and ``AZURE_OPENAI_*``
                lookups.
            env_file_encoding: Encoding for the ``.env`` file.
-            timeout: HTTP timeout in seconds for requests. When not provided, the
-                OpenAI SDK default is used (connect: 5s, total: 600s).

        Notes:
            Environment resolution and routing precedence are:
@@ -548,7 +541,6 @@ class RawOpenAIChatClient(  # type: ignore[misc]
            openai_model_fields=("chat_model", "model"),
            azure_model_fields=("chat_model", "model"),
            responses_mode=True,
-            timeout=timeout,
        )

        self.client = client
@@ -1462,21 +1454,10 @@ class RawOpenAIChatClient(  # type: ignore[misc]
        Returns:
            The prepared chat messages for a request.
        """
-        drops_reasoning_without_storage = not request_uses_service_side_storage and any(
-            content.type == "text_reasoning" for message in chat_messages for content in message.contents
-        )
-        drop_mcp_call_ids: set[str] = set()
-        if drops_reasoning_without_storage:
-            for message in chat_messages:
-                for content in message.contents:
-                    if content.type == "mcp_server_tool_call" and content.call_id:
-                        drop_mcp_call_ids.add(content.call_id)
-
        list_of_list = [
            self._prepare_message_for_openai(
                message,
                request_uses_service_side_storage=request_uses_service_side_storage,
-                drop_mcp_call_ids=drop_mcp_call_ids,
            )
            for message in chat_messages
        ]
@@ -1491,7 +1472,6 @@ class RawOpenAIChatClient(  # type: ignore[misc]
        message: Message,
        *,
        request_uses_service_side_storage: bool = True,
-        drop_mcp_call_ids: set[str] | None = None,
    ) -> list[dict[str, Any]]:
        """Prepare a chat message for the OpenAI Responses API format."""
        all_messages: list[dict[str, Any]] = []
@@ -1511,10 +1491,7 @@ class RawOpenAIChatClient(  # type: ignore[misc]
        # (replays_local_storage) still need stripping when the request also carries a continuation
        # marker, since the server-stored items would otherwise duplicate the inline ones. Without
        # storage, standalone reasoning items are invalid per the API ("reasoning was provided
-        # without its required following item"), so the reasoning branch always drops. When that
-        # happens, `_prepare_messages_for_openai` also drops the paired hosted-MCP IDs across
-        # message boundaries rather than replaying bare MCP items.
-        drop_mcp_call_ids = drop_mcp_call_ids or set()
+        # without its required following item"), so the reasoning branch always drops.
        for content in message.contents:
            match content.type:
                case "text_reasoning":
@@ -1569,10 +1546,7 @@ class RawOpenAIChatClient(  # type: ignore[misc]
                    # server-side `id`, so under continuation it would duplicate
                    # the prior response's items (#3295). Drop the call here; the
                    # orphan result is dropped by the coalesce step that follows.
-                    #
-                    # Without storage, a reasoning + hosted-MCP pair cannot be replayed
-                    # partially: reasoning is stripped above, and a bare mcp_call is rejected.
-                    if request_uses_service_side_storage or content.call_id in drop_mcp_call_ids:
+                    if request_uses_service_side_storage:
                        continue
                    prepared_mcp = self._prepare_content_for_openai(
                        message.role,
@@ -162,7 +162,6 @@ def load_openai_service_settings(
    openai_model_fields: Sequence[OpenAIModelSettingName] = ("model",),
    azure_model_fields: Sequence[OpenAIModelSettingName] = ("model",),
    responses_mode: bool = False,
-    timeout: float | None = None,
 ) -> tuple[dict[str, Any], AsyncOpenAI, bool]:
    """Load OpenAI settings, including Azure OpenAI model aliases.

@@ -219,8 +218,6 @@ def load_openai_service_settings(
            }
            if base_url := openai_settings.get("base_url"):
                client_args["base_url"] = base_url
-            if timeout is not None:
-                client_args["timeout"] = timeout
            return openai_settings, AsyncOpenAI(**client_args), False  # type: ignore[return-value]
        checked_openai = True
    azure_settings = load_settings(
@@ -302,12 +299,8 @@ def load_openai_service_settings(
            openai_args["api_key"] = _ensure_async_token_provider(client_args["azure_ad_token_provider"])
        elif "api_key" in client_args:
            openai_args["api_key"] = client_args["api_key"]
-        if timeout is not None:
-            openai_args["timeout"] = timeout
        return azure_settings, AsyncOpenAI(**openai_args), True  # type: ignore[return-value]

-    if timeout is not None:
-        client_args["timeout"] = timeout
    return azure_settings, AsyncAzureOpenAI(**client_args), True  # type: ignore[return-value]


@@ -4,7 +4,7 @@ description = "OpenAI integrations for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.8.0"
+version = "1.7.0"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.8.0,<2",
+    "agent-framework-core>=1.7.0,<2",
    "openai>=1.99.0,<3",
 ]

@@ -36,7 +36,7 @@ from agent_framework.exceptions import (
    ChatClientInvalidRequestException,
    SettingNotFoundError,
 )
-from openai import AsyncOpenAI, BadRequestError
+from openai import BadRequestError
 from openai.types.responses.response_reasoning_item import Summary
 from openai.types.responses.response_reasoning_summary_text_delta_event import (
    ResponseReasoningSummaryTextDeltaEvent,
@@ -55,7 +55,7 @@ from pydantic import BaseModel
 from pytest import param

 from agent_framework_openai import OpenAIChatClient
-from agent_framework_openai._chat_client import OPENAI_LOCAL_SHELL_CALL_ITEM_ID_KEY, RawOpenAIChatClient
+from agent_framework_openai._chat_client import OPENAI_LOCAL_SHELL_CALL_ITEM_ID_KEY
 from agent_framework_openai._exceptions import OpenAIContentFilterException

 skip_if_openai_integration_tests_disabled = pytest.mark.skipif(
@@ -194,26 +194,6 @@ def test_init_uses_explicit_parameters() -> None:
    assert all(parameter.kind != inspect.Parameter.VAR_KEYWORD for parameter in signature.parameters.values())


-def test_raw_openai_chat_client_init_uses_explicit_parameters() -> None:
-    signature = inspect.signature(RawOpenAIChatClient.__init__)
-
-    assert "additional_properties" in signature.parameters
-    assert "compaction_strategy" in signature.parameters
-    assert "tokenizer" in signature.parameters
-    assert "timeout" in signature.parameters
-    assert all(parameter.kind != inspect.Parameter.VAR_KEYWORD for parameter in signature.parameters.values())
-
-
-def test_raw_openai_chat_client_accepts_preconfigured_client_with_timeout() -> None:
-    """Test that timeout is accepted without error when async_client is pre-provided."""
-
-    mock_client = MagicMock(spec=AsyncOpenAI)
-    mock_client.timeout = 5.0
-
-    client = RawOpenAIChatClient(async_client=mock_client, timeout=30.0)
-    assert client is not None
-
-
 def test_openai_chat_client_supports_all_tool_protocols() -> None:
    assert isinstance(OpenAIChatClient, SupportsCodeInterpreterTool)
    assert isinstance(OpenAIChatClient, SupportsWebSearchTool)
@@ -5668,79 +5648,6 @@ def test_prepare_messages_for_openai_coalesces_mcp_call_and_result_into_single_i
    assert fco_items == [], f"unexpected orphan function_call_output items: {fco_items}"


-def test_prepare_messages_for_openai_drops_mcp_call_when_paired_reasoning_is_stripped() -> None:
-    client = OpenAIChatClient(model="test-model", api_key="test-key")
-
-    messages = [
-        Message(
-            role="assistant",
-            contents=[
-                Content.from_text_reasoning(id="rs_abc123", text="Need the MCP server."),
-                Content.from_mcp_server_tool_call(
-                    call_id="mcp_abc123",
-                    tool_name="search",
-                    server_name="api_specs",
-                    arguments='{"q": "cats"}',
-                ),
-            ],
-        ),
-        Message(
-            role="tool",
-            contents=[
-                Content.from_mcp_server_tool_result(
-                    call_id="mcp_abc123",
-                    output=[Content.from_text(text="found 10 cats")],
-                )
-            ],
-        ),
-    ]
-
-    result = client._prepare_messages_for_openai(messages, request_uses_service_side_storage=False)
-
-    types = [item.get("type") for item in result if isinstance(item, dict)]
-    assert "reasoning" not in types
-    assert "mcp_call" not in types
-    assert "function_call_output" not in types
-
-
-def test_prepare_messages_for_openai_drops_mcp_call_across_reasoning_messages() -> None:
-    client = OpenAIChatClient(model="test-model", api_key="test-key")
-
-    messages = [
-        Message(
-            role="assistant",
-            contents=[Content.from_text_reasoning(id="rs_abc123", text="Need a tool call.")],
-        ),
-        Message(
-            role="assistant",
-            contents=[
-                Content.from_mcp_server_tool_call(
-                    call_id="mcp_abc123",
-                    tool_name="search",
-                    server_name="api_specs",
-                    arguments='{"q": "cats"}',
-                )
-            ],
-        ),
-        Message(
-            role="tool",
-            contents=[
-                Content.from_mcp_server_tool_result(
-                    call_id="mcp_abc123",
-                    output=[Content.from_text(text="found 10 cats")],
-                )
-            ],
-        ),
-    ]
-
-    result = client._prepare_messages_for_openai(messages, request_uses_service_side_storage=False)
-
-    types = [item.get("type") for item in result if isinstance(item, dict)]
-    assert "reasoning" not in types
-    assert "mcp_call" not in types
-    assert "function_call_output" not in types
-
-
 def test_prepare_messages_for_openai_drops_orphan_mcp_server_tool_result() -> None:
    """When an mcp_server_tool_result has no matching mcp_server_tool_call in
    the message list, it must be dropped, NOT serialized as a
@@ -19,7 +19,7 @@ from typing_extensions import Never

 from ._orchestration_request_info import AgentApprovalExecutor
 from ._participant_output_config import (
-    UNSET,
+    _MISSING,  # pyright: ignore[reportPrivateUsage]
    _coalesce_output_from,  # pyright: ignore[reportPrivateUsage]
    _coerce_intermediate_output_from,  # pyright: ignore[reportPrivateUsage]
    _ParticipantIntermediateOutputSelection,  # pyright: ignore[reportPrivateUsage]
@@ -213,7 +213,7 @@ class ConcurrentBuilder:
        *,
        participants: Sequence[SupportsAgentRun | Executor],
        checkpoint_storage: CheckpointStorage | None = None,
-        output_from: Sequence[_ParticipantOutputSpecifier] | Literal["all"] | None = cast(Any, UNSET),
+        output_from: Sequence[_ParticipantOutputSpecifier] | Literal["all"] | None = cast(Any, _MISSING),
        intermediate_output_from: _ParticipantIntermediateOutputSelection = None,
    ) -> None:
        """Initialize the ConcurrentBuilder.
@@ -52,7 +52,7 @@ from ._base_group_chat_orchestrator import (
 from ._orchestration_request_info import AgentApprovalExecutor
 from ._orchestrator_helpers import clean_conversation_for_handoff
 from ._participant_output_config import (
-    UNSET,
+    _MISSING,  # pyright: ignore[reportPrivateUsage]
    _coalesce_output_from,  # pyright: ignore[reportPrivateUsage]
    _coerce_intermediate_output_from,  # pyright: ignore[reportPrivateUsage]
    _ParticipantIntermediateOutputSelection,  # pyright: ignore[reportPrivateUsage]
@@ -626,7 +626,7 @@ class GroupChatBuilder:
        termination_condition: TerminationCondition | None = None,
        max_rounds: int | None = None,
        checkpoint_storage: CheckpointStorage | None = None,
-        output_from: Sequence[_ParticipantOutputSpecifier] | Literal["all"] | None = cast(Any, UNSET),
+        output_from: Sequence[_ParticipantOutputSpecifier] | Literal["all"] | None = cast(Any, _MISSING),
        intermediate_output_from: _ParticipantIntermediateOutputSelection = None,
    ) -> None:
        """Initialize the GroupChatBuilder.
@@ -54,7 +54,7 @@ from agent_framework._workflows._workflow_context import WorkflowContext
 from ._base_group_chat_orchestrator import TerminationCondition
 from ._orchestrator_helpers import clean_conversation_for_handoff
 from ._participant_output_config import (
-    UNSET,
+    _MISSING,  # pyright: ignore[reportPrivateUsage]
    _coalesce_output_from,  # pyright: ignore[reportPrivateUsage]
    _coerce_intermediate_output_from,  # pyright: ignore[reportPrivateUsage]
    _ParticipantIntermediateOutputSelection,  # pyright: ignore[reportPrivateUsage]
@@ -597,7 +597,7 @@ class HandoffBuilder:
        description: str | None = None,
        checkpoint_storage: CheckpointStorage | None = None,
        termination_condition: TerminationCondition | None = None,
-        output_from: Sequence[_ParticipantOutputSpecifier] | Literal["all"] | None = cast(Any, UNSET),
+        output_from: Sequence[_ParticipantOutputSpecifier] | Literal["all"] | None = cast(Any, _MISSING),
        intermediate_output_from: _ParticipantIntermediateOutputSelection = None,
    ) -> None:
        r"""Initialize a HandoffBuilder for creating conversational handoff workflows.
@@ -28,7 +28,7 @@ from agent_framework._workflows._request_info_mixin import response_handler
 from agent_framework._workflows._workflow import Workflow
 from agent_framework._workflows._workflow_builder import WorkflowBuilder
 from agent_framework._workflows._workflow_context import WorkflowContext
-from typing_extensions import Never, Sentinel
+from typing_extensions import Never

 from ._base_group_chat_orchestrator import (
    BaseGroupChatOrchestrator,
@@ -39,7 +39,7 @@ from ._base_group_chat_orchestrator import (
    ParticipantRegistry,
 )
 from ._participant_output_config import (
-    UNSET,
+    _MISSING,  # pyright: ignore[reportPrivateUsage]
    _coalesce_output_from,  # pyright: ignore[reportPrivateUsage]
    _coerce_intermediate_output_from,  # pyright: ignore[reportPrivateUsage]
    _ParticipantIntermediateOutputSelection,  # pyright: ignore[reportPrivateUsage]
@@ -1411,13 +1411,13 @@ class MagenticBuilder:
        task_ledger_plan_update_prompt: str | None = None,
        progress_ledger_prompt: str | None = None,
        final_answer_prompt: str | None = None,
-        max_stall_count: int | Sentinel = UNSET,
+        max_stall_count: int = 3,
        max_reset_count: int | None = None,
        max_round_count: int | None = None,
        # Existing params
        enable_plan_review: bool = False,
        checkpoint_storage: CheckpointStorage | None = None,
-        output_from: Sequence[_ParticipantOutputSpecifier] | Literal["all"] | None = cast(Any, UNSET),
+        output_from: Sequence[_ParticipantOutputSpecifier] | Literal["all"] | None = cast(Any, _MISSING),
        intermediate_output_from: _ParticipantIntermediateOutputSelection = None,
    ) -> None:
        """Initialize the Magentic workflow builder.
@@ -1621,7 +1621,7 @@ class MagenticBuilder:
        progress_ledger_prompt: str | None = None,
        final_answer_prompt: str | None = None,
        # Limits
-        max_stall_count: int | Sentinel = UNSET,
+        max_stall_count: int = 3,
        max_reset_count: int | None = None,
        max_round_count: int | None = None,
    ) -> None:
@@ -1656,10 +1656,8 @@ class MagenticBuilder:
                "Exactly one of manager, manager_agent, manager_factory, or manager_agent_factory must be provided."
            )

-        resolved_max_stall_count: int = 3 if max_stall_count is UNSET else cast(int, max_stall_count)
-
        def _log_warning_if_constructor_args_provided() -> None:
-            if max_stall_count is not UNSET or any(
+            if any(
                arg is not None
                for arg in [
                    task_ledger,
@@ -1670,6 +1668,7 @@ class MagenticBuilder:
                    task_ledger_plan_update_prompt,
                    progress_ledger_prompt,
                    final_answer_prompt,
+                    max_stall_count,
                    max_reset_count,
                    max_round_count,
                ]
@@ -1690,7 +1689,7 @@ class MagenticBuilder:
                task_ledger_plan_update_prompt=task_ledger_plan_update_prompt,
                progress_ledger_prompt=progress_ledger_prompt,
                final_answer_prompt=final_answer_prompt,
-                max_stall_count=resolved_max_stall_count,
+                max_stall_count=max_stall_count,
                max_reset_count=max_reset_count,
                max_round_count=max_round_count,
            )
@@ -1708,7 +1707,7 @@ class MagenticBuilder:
                "task_ledger_plan_update_prompt": task_ledger_plan_update_prompt,
                "progress_ledger_prompt": progress_ledger_prompt,
                "final_answer_prompt": final_answer_prompt,
-                "max_stall_count": resolved_max_stall_count,
+                "max_stall_count": max_stall_count,
                "max_reset_count": max_reset_count,
                "max_round_count": max_round_count,
            }
@@ -8,9 +8,8 @@ from typing import Any, Literal
 from agent_framework import SupportsAgentRun
 from agent_framework._workflows._agent_utils import resolve_agent_id
 from agent_framework._workflows._executor import Executor
-from typing_extensions import Sentinel

-UNSET = Sentinel("UNSET")
+_MISSING = object()
 _ALL_OUTPUTS: Literal["all"] = "all"
 _ALL_OTHER_OUTPUTS: Literal["all_other"] = "all_other"
 _ParticipantOutputSpecifier = str | SupportsAgentRun | Executor
@@ -21,10 +20,10 @@ _WorkflowExecutorSpecifier = Executor | SupportsAgentRun

 def _coalesce_output_from(  # pyright: ignore[reportUnusedFunction]
    *,
-    output_from: Any = UNSET,
+    output_from: Any = _MISSING,
 ) -> _ParticipantOutputSelection:
    """Resolve orchestration output selection to ``output_from``."""
-    if output_from is not UNSET:
+    if output_from is not _MISSING:
        return _coerce_output_from(output_from)
    return None

@@ -33,7 +33,7 @@ from agent_framework._workflows._workflow_context import WorkflowContext

 from ._orchestration_request_info import AgentApprovalExecutor
 from ._participant_output_config import (
-    UNSET,
+    _MISSING,  # pyright: ignore[reportPrivateUsage]
    _coalesce_output_from,  # pyright: ignore[reportPrivateUsage]
    _coerce_intermediate_output_from,  # pyright: ignore[reportPrivateUsage]
    _ParticipantIntermediateOutputSelection,  # pyright: ignore[reportPrivateUsage]
@@ -99,7 +99,7 @@ class SequentialBuilder:
        participants: Sequence[SupportsAgentRun | Executor],
        checkpoint_storage: CheckpointStorage | None = None,
        chain_only_agent_responses: bool = False,
-        output_from: Sequence[_ParticipantOutputSpecifier] | Literal["all"] | None = cast(Any, UNSET),
+        output_from: Sequence[_ParticipantOutputSpecifier] | Literal["all"] | None = cast(Any, _MISSING),
        intermediate_output_from: _ParticipantIntermediateOutputSelection = None,
    ) -> None:
        """Initialize the SequentialBuilder.
@@ -4,7 +4,7 @@ description = "Orchestration patterns for Microsoft Agent Framework. Includes Se
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0rc3"
+version = "1.0.0rc2"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.8.0,<2",
+    "agent-framework-core>=1.6.0,<2",
 ]

 [tool.uv]
@@ -1,6 +1,5 @@
 # Copyright (c) Microsoft. All rights reserved.

-import logging
 import sys
 from collections.abc import AsyncIterable, Awaitable, Sequence
 from dataclasses import dataclass
@@ -988,33 +987,6 @@ def test_magentic_builder_requires_exactly_one_manager_option():
        MagenticBuilder(participants=[agent], manager=manager, manager_factory=manager_factory)


-def test_magentic_with_custom_manager_does_not_warn_without_standard_manager_options(caplog: Any) -> None:
-    caplog.set_level(logging.WARNING, logger="agent_framework_orchestrations._magentic")
-
-    MagenticBuilder(participants=[StubAgent("agentA", "reply")], manager=FakeManager())
-
-    assert "Custom manager provided; all other manager arguments will be ignored." not in caplog.text
-
-
-def test_magentic_with_custom_manager_factory_does_not_warn_without_standard_manager_options(caplog: Any) -> None:
-    caplog.set_level(logging.WARNING, logger="agent_framework_orchestrations._magentic")
-
-    def manager_factory() -> MagenticManagerBase:
-        return FakeManager()
-
-    MagenticBuilder(participants=[StubAgent("agentA", "reply")], manager_factory=manager_factory)
-
-    assert "Custom manager provided; all other manager arguments will be ignored." not in caplog.text
-
-
-def test_magentic_with_custom_manager_warns_when_standard_manager_option_is_provided(caplog: Any) -> None:
-    caplog.set_level(logging.WARNING, logger="agent_framework_orchestrations._magentic")
-
-    MagenticBuilder(participants=[StubAgent("agentA", "reply")], manager=FakeManager(), max_stall_count=3)
-
-    assert "Custom manager provided; all other manager arguments will be ignored." in caplog.text
-
-
 async def test_magentic_with_manager_factory():
    """Test workflow creation using manager_factory."""
    factory_call_count = 0
@@ -1065,20 +1037,6 @@ async def test_magentic_with_agent_factory():
    assert event_count > 0


-def test_magentic_agent_factory_uses_default_max_stall_count() -> None:
-    def agent_factory() -> SupportsAgentRun:
-        return cast(SupportsAgentRun, StubManagerAgent())
-
-    participant = StubAgent("agentA", "reply from agentA")
-    workflow = MagenticBuilder(participants=[participant], manager_agent_factory=agent_factory).build()
-
-    orchestrator = next(e for e in workflow.executors.values() if isinstance(e, MagenticOrchestrator))
-    manager = orchestrator._manager  # type: ignore[reportPrivateUsage]
-
-    assert isinstance(manager, StandardMagenticManager)
-    assert manager.max_stall_count == 3
-
-
 async def test_magentic_manager_factory_reusable_builder():
    """Test that the builder can be reused to build multiple workflows with manager factory."""
    factory_call_count = 0
@@ -4,7 +4,7 @@ description = "Microsoft Agent Framework for building AI Agents with Python. Thi
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.8.0"
+version = "1.7.0"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core[all]==1.8.0",
+    "agent-framework-core[all]==1.7.0",
 ]

 [dependency-groups]
@@ -5,8 +5,7 @@ This folder demonstrates context compaction patterns introduced by ADR-0019.
 ## Files

 - `basics.py` — builds a local message list and applies each built-in strategy one at a time.
- `summarization.py` — runs `SummarizationStrategy` directly with a real summarizing chat client.
- `advanced.py` — composes multiple strategies with `TokenBudgetComposedStrategy`, including a real summarizer and tool-call groups.
+- `advanced.py` — composes multiple strategies with `TokenBudgetComposedStrategy`.
 - `agent_client_overrides.py` — shows client defaults, agent-level overrides, and per-run compaction overrides.
 - `custom.py` — defines a custom strategy implementing the `CompactionStrategy` protocol.
 - `tiktoken_tokenizer.py` — shows a `TokenizerProtocol` implementation backed by `tiktoken`.
@@ -16,8 +15,7 @@ Run samples with:

 ```bash
 uv run samples/02-agents/compaction/basics.py
-uv run samples/02-agents/compaction/summarization.py  # requires OPENAI_API_KEY
-uv run samples/02-agents/compaction/advanced.py  # requires OPENAI_API_KEY
+uv run samples/02-agents/compaction/advanced.py
 uv run samples/02-agents/compaction/agent_client_overrides.py
 uv run samples/02-agents/compaction/custom.py
 uv run samples/02-agents/compaction/tiktoken_tokenizer.py
@@ -1,14 +1,11 @@
 # Copyright (c) Microsoft. All rights reserved.

 import asyncio
-from typing import Any, cast
+from typing import Any

 from agent_framework import (
-    GROUP_ANNOTATION_KEY,
-    GROUP_TOKEN_COUNT_KEY,
-    SUMMARY_OF_MESSAGE_IDS_KEY,
    CharacterEstimatorTokenizer,
-    Content,
+    ChatResponse,
    Message,
    SelectiveToolCallCompactionStrategy,
    SlidingWindowStrategy,
@@ -18,48 +15,36 @@ from agent_framework import (
    apply_compaction,
    included_token_count,
 )
-from agent_framework.openai import OpenAIChatClient
-from dotenv import load_dotenv

-load_dotenv()
-
-"""This sample demonstrates composed in-run compaction under a token budget.
-
-A long, tool-using conversation is compacted with a single
-``TokenBudgetComposedStrategy`` that runs three strategies in order until the
-included-token count fits the budget:
-
-1. ``SelectiveToolCallCompactionStrategy`` — drop older tool-call groups
-   (assistant ``function_call`` + ``tool`` result messages) that are expensive
-   and rarely needed verbatim once acted upon.
-2. ``SummarizationStrategy`` — use a *real* chat client to summarize the oldest
-   remaining turns into a single linked summary message.
-3. ``SlidingWindowStrategy`` — as a final guard, keep only the most recent
-   groups if the budget is still exceeded.
+"""This sample demonstrates composed in-run compaction with a token budget.

 Key components:
- TokenBudgetComposedStrategy with ordered, escalating strategies
- A real OpenAIChatClient used as the summarizer (not a stub)
- Tool-call groups in the history so tool-call compaction is meaningful
- Token accounting before/after via a TokenizerProtocol
-
-Run with:
-    uv run samples/02-agents/compaction/advanced.py  # requires OPENAI_API_KEY
+- TokenBudgetComposedStrategy
+- Sequential strategy composition
+- Summarization with a SupportsChatGetResponse-compatible summarizer client
 """


-def _build_long_history() -> list[Message]:
-    """Build a long, tool-using migration conversation to create token pressure."""
-    history: list[Message] = [
-        Message(role="system", contents=["You are a migration copilot that plans and executes database migrations."]),
-    ]
+class BudgetSummaryClient:
+    async def get_response(
+        self,
+        messages: list[Message],
+        *,
+        stream: bool = False,
+        options: dict[str, Any] | None = None,
+        **kwargs: Any,
+    ) -> ChatResponse:
+        summary_text = f"Budget summary generated from {len(messages)} prompt messages."
+        return ChatResponse(messages=[Message(role="assistant", contents=[summary_text])])

-    # A few verbose planning turns to build up token pressure.
-    for i in range(1, 5):
+
+def _build_long_history() -> list[Message]:
+    history = [Message(role="system", contents=["You are a migration copilot."])]
+    for i in range(1, 8):
        history.append(
            Message(
                role="user",
-                contents=[f"Iteration {i}: capture migration requirements, constraints, and edge cases in detail."],
+                contents=[f"Iteration {i}: capture migration requirements and edge cases."],
            )
        )
        history.append(
@@ -67,62 +52,17 @@ def _build_long_history() -> list[Message]:
                role="assistant",
                contents=[
                    (
-                        f"Iteration {i}: produced a detailed plan covering dependencies, rollback guidance, data "
-                        "backfill, and a full testing matrix. This response is intentionally verbose to add pressure."
+                        f"Iteration {i}: detailed plan with dependencies, rollback guidance, and testing details. "
+                        "This sentence is intentionally long to create token pressure."
                    )
                ],
            )
        )
-
-    # A tool-call group: the assistant inspects the schema via a tool.
-    history.append(
-        Message(
-            role="assistant",
-            contents=[Content.from_function_call(call_id="call_1", name="inspect_schema", arguments='{"db":"legacy"}')],
-        )
-    )
-    history.append(
-        Message(
-            role="tool",
-            contents=[Content.from_function_result(call_id="call_1", result="tables: users, orders, invoices, events")],
-        )
-    )
-    history.append(Message(role="assistant", contents=["Schema inspection found four core tables to migrate."]))
-
-    # The most recent turn — this should survive compaction verbatim.
-    history.append(Message(role="user", contents=["What is the safest order to migrate these tables?"]))
-    history.append(
-        Message(
-            role="assistant",
-            contents=["Migrate reference tables (users) first, then orders, then invoices, and events last."],
-        )
-    )
    return history


-def _annotation(message: Message) -> dict[str, Any] | None:
-    annotation = message.additional_properties.get(GROUP_ANNOTATION_KEY)
-    return cast("dict[str, Any]", annotation) if isinstance(annotation, dict) else None
-
-
-def _token_count(message: Message) -> int | None:
-    annotation = _annotation(message)
-    return annotation.get(GROUP_TOKEN_COUNT_KEY) if annotation else None
-
-
-def _relation(message: Message) -> str:
-    """Describe how a projected message relates to the original messages."""
-    annotation = _annotation(message)
-    if annotation is None:
-        return ""
-    summarizes = annotation.get(SUMMARY_OF_MESSAGE_IDS_KEY)
-    if summarizes:
-        return f" <- summary of {summarizes}"
-    return ""
-
-
 async def main() -> None:
-    # 1. Build synthetic history representing long-running, tool-using growth.
+    # 1. Build synthetic history representing long-running in-run growth.
    messages = _build_long_history()

    # 2. Configure tokenizer and measure token count before compaction.
@@ -130,35 +70,22 @@ async def main() -> None:
    annotate_message_groups(messages, tokenizer=tokenizer)
    budget_before = included_token_count(messages)

-    print("Before compaction message set:")
-    for msg in messages:
-        text_preview = msg.text[:80] if msg.text else "<non-text>"
-        print(f"- [{msg.role}] {text_preview} ({msg.message_id}, {_token_count(msg)} tokens)")
-    print()
-
-    # 3. Create a real summarizer client. SummarizationStrategy only requires a
-    #    SupportsChatGetResponse-compatible client.
-    summarizer = OpenAIChatClient(model="gpt-4o-mini")
-
-    # 4. Configure the composed strategy stack. Strategies run in order and the
-    #    composed strategy stops as soon as the included-token budget is met.
-    #    The budget is set high enough that the generated summary fits within it:
-    #    a tighter budget would trip the composed fallback, which excludes the
-    #    oldest group first (the summary) once the included set exceeds the
-    #    budget. SlidingWindowStrategy remains as a recency safety net for longer
-    #    histories; for this sample summarization alone reaches budget, so the
-    #    window does not need to fire.
+    # 3. Configure composed strategy stack.
    composed = TokenBudgetComposedStrategy(
-        token_budget=400,
+        token_budget=200,
        tokenizer=tokenizer,
        strategies=[
            SelectiveToolCallCompactionStrategy(keep_last_tool_call_groups=0),
-            SummarizationStrategy(client=summarizer, target_count=3, threshold=2),
+            SummarizationStrategy(
+                client=BudgetSummaryClient(),
+                target_count=3,
+                threshold=3,
+            ),
            SlidingWindowStrategy(keep_last_groups=4),
        ],
    )

-    # 5. Apply compaction and inspect the budget result.
+    # 4. Apply compaction and inspect the budget result.
    projected = await apply_compaction(messages, strategy=composed, tokenizer=tokenizer)
    budget_after = included_token_count(messages)

@@ -168,44 +95,23 @@ async def main() -> None:
    print("Projected roles:", [m.role for m in projected])
    print("Projected messages with token counts:")
    for msg in projected:
+        group = msg.additional_properties.get("_group")
+        token_count = group.get("token_count") if isinstance(group, dict) else None
        text_preview = msg.text[:80] if msg.text else "<non-text>"
-        print(f"- [{msg.role}] {text_preview} ({msg.message_id}, {_token_count(msg)} tokens){_relation(msg)}")
-
-    # 6. Surface the model-generated summary, if summarization fired.
-    for msg in messages:
-        annotation = _annotation(msg)
-        if annotation and annotation.get(SUMMARY_OF_MESSAGE_IDS_KEY):
-            print("\nGenerated summary:")
-            print(f"  {msg.text}")
-            print(f"  summarizes: {annotation.get(SUMMARY_OF_MESSAGE_IDS_KEY)}")
+        print(f"- [{msg.role}] {text_preview} ({token_count} tokens)")


 if __name__ == "__main__":
    asyncio.run(main())

 """
-Sample output (summary text and token counts vary because the summary is generated by the model):
-
-Before compaction message set:
- [system] You are a migration copilot that plans and executes database migrations. (msg_0, 46 tokens)
- [user] Iteration 1: capture migration requirements, constraints, and edge cases in deta (msg_1, 48 tokens)
- [assistant] Iteration 1: produced a detailed plan covering dependencies, rollback guidance,  (msg_2, 73 tokens)
-...
- [user] What is the safest order to migrate these tables? (msg_12, 40 tokens)
- [assistant] Migrate reference tables (users) first, then orders, then invoices, and events l (msg_13, 50 tokens)
-
-Projected messages after compaction: 5
-Included token count before compaction: 757
-Included token count after compaction: 274
-Projected roles: ['system', 'assistant', 'assistant', 'user', 'assistant']
+Sample output:
+Projected messages after compaction: 3
+Included token count before compaction: 793
+Included token count after compaction: 144
+Projected roles: ['system', 'user', 'assistant']
 Projected messages with token counts:
- [system] You are a migration copilot that plans and executes database migrations. (msg_0, 46 tokens)
- [assistant] Across four planning turns the user and assistant... (summary_14, 96 tokens) <- summary of [msg_1..8]
- [assistant] Schema inspection found four core tables to migrate. (msg_11, 42 tokens)
- [user] What is the safest order to migrate these tables? (msg_12, 40 tokens)
- [assistant] Migrate reference tables (users) first, then orders, then invoices, and events l (msg_13, 50 tokens)
-
-Generated summary:
-  Across four planning turns the user and assistant defined the migration requirements...
-  summarizes: ['msg_1', 'msg_2', 'msg_3', 'msg_4', 'msg_5', 'msg_6', 'msg_7', 'msg_8']
+- [system] You are a migration copilot. (35 tokens)
+- [user] Iteration 7: capture migration requirements and edge cases. (43 tokens)
+- [assistant] Iteration 7: detailed plan with dependencies, rollback guidance, and testing det (66 tokens)
 """
@@ -1,159 +0,0 @@
-# Copyright (c) Microsoft. All rights reserved.
-
-import asyncio
-from typing import Any, cast
-
-from agent_framework import (
-    GROUP_ANNOTATION_KEY,
-    SUMMARIZED_BY_SUMMARY_ID_KEY,
-    SUMMARY_OF_MESSAGE_IDS_KEY,
-    Message,
-    SummarizationStrategy,
-    apply_compaction,
-)
-from agent_framework.openai import OpenAIChatClient
-from dotenv import load_dotenv
-
-load_dotenv()
-
-"""This sample demonstrates the SummarizationStrategy directly.
-
-Unlike SlidingWindow/Truncation strategies that simply drop older groups,
-``SummarizationStrategy`` calls a real chat client to *summarize* the oldest
-message groups, replaces them with a single linked summary message, and keeps
-the most recent turns verbatim. This preserves long-range context (decisions,
-goals, unresolved items) while bounding the prompt size.
-
-Key components:
- SummarizationStrategy with a real OpenAIChatClient summarizer
- ``apply_compaction`` to run the strategy over a message list
- Bidirectional summary trace metadata (summary -> originals, original -> summary)
-
-Run with:
-    uv run samples/02-agents/compaction/summarization.py  # requires OPENAI_API_KEY
-"""
-
-
-def _annotation(message: Message) -> dict[str, Any] | None:
-    annotation = message.additional_properties.get(GROUP_ANNOTATION_KEY)
-    return cast("dict[str, Any]", annotation) if isinstance(annotation, dict) else None
-
-
-def _build_history() -> list[Message]:
-    """Build a multi-turn conversation long enough to trigger summarization."""
-    return [
-        Message(role="system", contents=["You are a project planning assistant."]),
-        Message(role="user", contents=["We are migrating a monolith to microservices. Where do we start?"]),
-        Message(
-            role="assistant",
-            contents=["Start by mapping bounded contexts and identifying the highest-churn modules to extract first."],
-        ),
-        Message(role="user", contents=["The billing module changes most often. What are the risks of extracting it?"]),
-        Message(
-            role="assistant",
-            contents=["Main risks: distributed transactions, invoices-table ownership, and latency on hot paths."],
-        ),
-        Message(role="user", contents=["How should we handle the shared invoices table?"]),
-        Message(
-            role="assistant",
-            contents=["Use the strangler-fig pattern: dual-write during transition, then make billing the owner."],
-        ),
-        Message(role="user", contents=["What is the most recent decision we made?"]),
-        Message(role="assistant", contents=["We decided to extract billing first using the strangler-fig pattern."]),
-    ]
-
-
-def _print_messages(label: str, messages: list[Message]) -> None:
-    print(f"\n--- {label} ---")
-    print(f"Message count: {len(messages)}")
-    for index, message in enumerate(messages, start=1):
-        text = message.text or ", ".join(content.type for content in message.contents)
-        print(f"{index:02d}. [{message.role}] {text[:90]}")
-
-
-async def main() -> None:
-    # 1. Create a real summarizing client. SummarizationStrategy only requires a
-    #    SupportsChatGetResponse-compatible client, so any chat client works.
-    summarizer = OpenAIChatClient(model="gpt-4o-mini")
-
-    # 2. Build a conversation and show it before compaction.
-    messages = _build_history()
-    _print_messages("Before compaction", messages)
-
-    # 3. Configure the strategy. It triggers once the included non-system message
-    #    count exceeds ``target_count + threshold`` (here 4 + 2 = 6), summarizing
-    #    the oldest groups down toward ``target_count`` while keeping recent turns.
-    strategy = SummarizationStrategy(
-        client=summarizer,
-        target_count=4,
-        threshold=2,
-    )
-
-    # 4. Apply the strategy. The oldest groups are summarized into a single
-    #    assistant message; the projected list is what the model would receive.
-    projected = await apply_compaction(messages, strategy=strategy)
-    _print_messages("After compaction (SummarizationStrategy)", projected)
-
-    # 5. Inspect the generated summary and its bidirectional trace metadata.
-    print("\n--- Summary trace ---")
-    for message in messages:
-        annotation = _annotation(message)
-        if annotation is None:
-            continue
-        summarizes = annotation.get(SUMMARY_OF_MESSAGE_IDS_KEY)
-        if summarizes:
-            print(f"Generated summary ({message.message_id}):")
-            print(f"  {message.text}")
-            print(f"  summarizes original ids: {summarizes}")
-    summarized_by: dict[str | None, Any] = {}
-    for message in messages:
-        annotation = _annotation(message)
-        if annotation is None:
-            continue
-        summary_id = annotation.get(SUMMARIZED_BY_SUMMARY_ID_KEY)
-        if summary_id:
-            summarized_by[message.message_id] = summary_id
-    if summarized_by:
-        print("Originals replaced by the summary:")
-        for original_id, summary_id in summarized_by.items():
-            print(f"  {original_id} -> {summary_id}")
-
-
-if __name__ == "__main__":
-    asyncio.run(main())
-
-"""
-Sample output (summary text varies because it is generated by the model):
-
--- Before compaction ---
-Message count: 9
-01. [system] You are a project planning assistant.
-02. [user] We are migrating a monolith to microservices. Where do we start?
-03. [assistant] Start by mapping bounded contexts and identifying the highest-churn modules to ex
-04. [user] The billing module changes most often. What are the risks of extracting it?
-05. [assistant] Main risks: distributed transactions, data ownership of the invoices table, and lat
-06. [user] How should we handle the shared invoices table?
-07. [assistant] Use the strangler-fig pattern: dual-write during transition, then make billing the
-08. [user] What is the most recent decision we made?
-09. [assistant] We decided to extract billing first using the strangler-fig pattern.
-
--- After compaction (SummarizationStrategy) ---
-Message count: 6
-01. [system] You are a project planning assistant.
-02. [assistant] The user is migrating a monolith to microservices and decided to extract the billin
-03. [user] How should we handle the shared invoices table?
-04. [assistant] Use the strangler-fig pattern: dual-write during transition, then make billing the
-05. [user] What is the most recent decision we made?
-06. [assistant] We decided to extract billing first using the strangler-fig pattern.
-
--- Summary trace ---
-Generated summary (summary_9):
-  The user is migrating a monolith to microservices and decided to extract the billing module first...
-  summarizes original ids: ['msg_1', 'msg_2', 'msg_3', 'msg_4', 'msg_5']
-Originals replaced by the summary:
-  msg_1 -> summary_9
-  msg_2 -> summary_9
-  msg_3 -> summary_9
-  msg_4 -> summary_9
-  msg_5 -> summary_9
-"""
@@ -27,7 +27,6 @@ This folder contains Azure AI Foundry and Foundry Local samples for Agent Framew
 | [`foundry_chat_client_with_local_mcp.py`](foundry_chat_client_with_local_mcp.py) | Foundry Chat Client with local MCP |
 | [`foundry_chat_client_with_session.py`](foundry_chat_client_with_session.py) | Foundry Chat Client with session management |
 | [`foundry_chat_client_with_toolbox.py`](foundry_chat_client_with_toolbox.py) | Foundry Chat Client connected to a toolbox via its MCP endpoint using `MCPStreamableHTTPTool` |
-| [`foundry_chat_client_with_toolbox_skills.py`](foundry_chat_client_with_toolbox_skills.py) | Foundry Chat Client that discovers MCP-based skills from a Foundry Toolbox endpoint via `MCPSkillsSource` (uses an Azure AD bearer token and the toolbox preview header) |

 ## FoundryLocalClient Samples

@@ -1,87 +0,0 @@
-# Copyright (c) Microsoft. All rights reserved.
-
-import asyncio
-import os
-from collections.abc import Generator
-
-import httpx
-from agent_framework import Agent, MCPSkillsSource, SkillsProvider
-from agent_framework.foundry import FoundryChatClient
-from azure.core.credentials import TokenCredential
-from azure.identity import AzureCliCredential, get_bearer_token_provider
-from dotenv import load_dotenv
-from mcp.client.session import ClientSession
-from mcp.client.streamable_http import streamable_http_client
-
-# Load environment variables from .env file
-load_dotenv()
-
-"""
-Foundry Chat Client with Toolbox-Hosted Skills
-
-Discover Agent Skills served by a Microsoft Foundry Toolbox MCP endpoint
-and inject them into a ``FoundryChatClient`` agent via ``MCPSkillsSource``.
-The toolbox's discovery document (``skill://index.json``) is read once at
-startup; SKILL.md bodies are fetched on demand as the agent uses them.
-
-Prerequisites:
- A Microsoft Foundry project with a toolbox that exposes
-  ``skill://index.json`` with ``skill-md`` entries
- FOUNDRY_PROJECT_ENDPOINT and FOUNDRY_MODEL environment variables set
- FOUNDRY_TOOLBOX_MCP_SERVER_URL: the toolbox's MCP endpoint URL, e.g.
-  ``https://<account>.services.ai.azure.com/api/projects/<project>/toolboxes/<name>/mcp?api-version=v1``
- Azure CLI authentication (``az login``)
-"""
-
-
-class _BearerAuth(httpx.Auth):
-    """Attach a fresh Foundry bearer token to every request."""
-
-    def __init__(self, credential: TokenCredential) -> None:
-        self._get_token = get_bearer_token_provider(credential, "https://ai.azure.com/.default")
-
-    def auth_flow(self, request: httpx.Request) -> Generator[httpx.Request, httpx.Response, None]:
-        request.headers["Authorization"] = f"Bearer {self._get_token()}"
-        yield request
-
-
-async def main() -> None:
-    """Example showing toolbox-hosted MCP skills for a Foundry Chat Client agent."""
-    credential = AzureCliCredential()
-
-    # HTTP client that signs every request with a fresh Foundry bearer token
-    # and advertises the toolbox preview feature flag, plus the MCP streamable
-    # HTTP transport that uses it.
-    async with (
-        httpx.AsyncClient(
-            auth=_BearerAuth(credential),
-            headers={"Foundry-Features": "Toolboxes=V1Preview"},
-            timeout=httpx.Timeout(30.0, read=300.0),
-            follow_redirects=True,
-        ) as http_client,
-        streamable_http_client(
-            url=os.environ["FOUNDRY_TOOLBOX_MCP_SERVER_URL"],
-            http_client=http_client,
-        ) as (read, write, _),
-        ClientSession(read, write) as session,
-    ):
-        await session.initialize()
-
-        # Discover skills served by the toolbox and inject them as a context provider.
-        skills_provider = SkillsProvider(MCPSkillsSource(client=session))
-
-        async with Agent(
-            client=FoundryChatClient(credential=credential),
-            name="ToolboxMCPSkillsAgent",
-            instructions="You are a helpful assistant. Use available skills to answer the user.",
-            context_providers=[skills_provider],
-        ) as agent:
-            query = input("User: ").strip()  # noqa: ASYNC250
-            if not query:
-                return
-            response = await agent.run(query)
-            print(f"Assistant: {response.text}")
-
-
-if __name__ == "__main__":
-    asyncio.run(main())
@@ -23,7 +23,7 @@ The following environment variables can be configured:
 | `GITHUB_COPILOT_MODEL` | Model to use (e.g., "gpt-5", "claude-sonnet-4") | Server default |
 | `GITHUB_COPILOT_TIMEOUT` | Request timeout in seconds | `60` |
 | `GITHUB_COPILOT_LOG_LEVEL` | CLI log level | `info` |
-| `GITHUB_COPILOT_BASE_DIRECTORY` | Directory for CLI session state and config | `~/.copilot` |
+| `GITHUB_COPILOT_COPILOT_HOME` | Directory for CLI session state and config | `~/.copilot` |

 ## Observability

@@ -19,7 +19,8 @@ from typing import Annotated

 from agent_framework import tool
 from agent_framework.github import GitHubCopilotAgent
-from copilot.session import PermissionHandler
+from copilot.generated.session_events import PermissionRequest
+from copilot.session import PermissionRequestResult
 from dotenv import load_dotenv
 from pydantic import Field

@@ -27,6 +28,19 @@ from pydantic import Field
 load_dotenv()


+def prompt_permission(request: PermissionRequest, context: dict[str, str]) -> PermissionRequestResult:
+    """Permission handler that prompts the user for approval."""
+    print(f"\n[Permission Request: {request.kind}]")
+
+    if request.full_command_text is not None:
+        print(f"  Command: {request.full_command_text}")
+
+    response = input("Approve? (y/n): ").strip().lower()
+    if response in ("y", "yes"):
+        return PermissionRequestResult(kind="approved")
+    return PermissionRequestResult(kind="denied-interactively-by-user")
+
+
 # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production;
 # see samples/02-agents/tools/function_tool_with_approval.py
 # and samples/02-agents/tools/function_tool_with_approval_and_sessions.py.
@@ -46,7 +60,7 @@ async def non_streaming_example() -> None:
    agent = GitHubCopilotAgent(
        instructions="You are a helpful weather agent.",
        tools=[get_weather],
-        default_options={"on_permission_request": PermissionHandler.approve_all},
+        default_options={"on_permission_request": prompt_permission},
    )

    async with agent:
@@ -63,7 +77,7 @@ async def streaming_example() -> None:
    agent = GitHubCopilotAgent(
        instructions="You are a helpful weather agent.",
        tools=[get_weather],
-        default_options={"on_permission_request": PermissionHandler.approve_all},
+        default_options={"on_permission_request": prompt_permission},
    )

    async with agent:
@@ -83,7 +97,7 @@ async def runtime_options_example() -> None:
    agent = GitHubCopilotAgent(
        instructions="Always respond in exactly 3 words.",
        tools=[get_weather],
-        default_options={"on_permission_request": PermissionHandler.approve_all},
+        default_options={"on_permission_request": prompt_permission},
    )

    async with agent:
@@ -4,7 +4,8 @@
 GitHub Copilot Agent with File Operation Permissions

 This sample demonstrates how to enable file read and write operations with GitHubCopilotAgent.
-By providing a permission handler, the agent can read from and write to files on the filesystem.
+By providing a permission handler that approves "read" and/or "write" requests, the agent can
+read from and write to files on the filesystem.

 SECURITY NOTE: Only enable file permissions when you trust the agent's actions.
 - "read" allows the agent to read any accessible file
@@ -14,18 +15,21 @@ SECURITY NOTE: Only enable file permissions when you trust the agent's actions.
 import asyncio

 from agent_framework.github import GitHubCopilotAgent
-from copilot.generated.rpc import PermissionDecisionDeniedInteractivelyByUser
-from copilot.session import PermissionHandler, PermissionRequestResult
-from copilot.session_events import PermissionRequest
+from copilot.generated.session_events import PermissionRequest
+from copilot.session import PermissionRequestResult


-async def prompt_permission(request: PermissionRequest, context: dict[str, str]) -> PermissionRequestResult:
+def prompt_permission(request: PermissionRequest, context: dict[str, str]) -> PermissionRequestResult:
    """Permission handler that prompts the user for approval."""
    print(f"\n[Permission Request: {request.kind}]")
-    response = (await asyncio.to_thread(input, "Approve? (y/n): ")).strip().lower()
+
+    if request.path is not None:
+        print(f"  Path: {request.path}")
+
+    response = input("Approve? (y/n): ").strip().lower()
    if response in ("y", "yes"):
-        return PermissionHandler.approve_all(request, context)
-    return PermissionDecisionDeniedInteractivelyByUser()
+        return PermissionRequestResult(kind="approved")
+    return PermissionRequestResult(kind="denied-interactively-by-user")


 async def main() -> None:
@@ -32,7 +32,6 @@ from typing import Annotated

 from agent_framework import Content, tool
 from agent_framework.github import GitHubCopilotAgent
-from copilot.session import PermissionHandler
 from dotenv import load_dotenv

 load_dotenv()
@@ -49,42 +48,37 @@ def get_weather_detail(location: Annotated[str, "The city and state, e.g. San Fr
    )


-async def prompt_for_approval(call: Content) -> bool:
-    """Async approval callback that prompts the user interactively.
+def prompt_for_approval(call: Content) -> bool:
+    """Synchronous approval prompt.

    The callback receives a ``FunctionCallContent`` so the operator can review
    the tool name and arguments before deciding. Returning ``True`` allows the
    call; returning ``False`` denies it and a tool-error is returned to the
    model.
-
-    Uses ``asyncio.to_thread`` so the event loop is not blocked by ``input()``.
    """
-    print(f"\n  [Function Approval Request]\n  Tool: {call.name}\n  Arguments: {call.arguments}")
-    response = (await asyncio.to_thread(input, "  Approve this tool call? (y/n): ")).strip().lower()
+    print(f"\n[Function Approval Request]\n  Tool: {call.name}\n  Arguments: {call.arguments}")
+    response = input("Approve this tool call? (y/n): ").strip().lower()
    return response in ("y", "yes")


-def auto_approve(call: Content) -> bool:
-    """Synchronous approval callback that always approves.
+async def prompt_for_approval_async(call: Content) -> bool:
+    """Async approval prompt.

-    Use a sync callback for simple, non-blocking decisions that don't require
-    I/O (e.g. checking an allow-list of tool names).
+    Use an async callback when approval requires I/O (e.g. an HTTP call to a
+    review service or queueing the request to a UI). ``input()`` is wrapped
+    with ``asyncio.to_thread`` so the event loop is not blocked.
    """
-    print(f"\n  [Function Approval Request]\n  Tool: {call.name}\n  Arguments: {call.arguments}")
-    print("  -> Auto-approved")
-    return True
+    print(f"\n[Function Approval Request - async]\n  Tool: {call.name}\n  Arguments: {call.arguments}")
+    response = await asyncio.to_thread(input, "Approve this tool call? (y/n): ")
+    return response.strip().lower() in ("y", "yes")


-async def run_with_interactive_callback() -> None:
-    """Demonstrates an interactive approval prompt before tool execution."""
-    print("\n=== GitHub Copilot Agent: interactive approval callback ===")
+async def run_with_sync_callback() -> None:
+    print("\n=== GitHub Copilot Agent: synchronous approval callback ===")
    agent = GitHubCopilotAgent(
        instructions="You are a helpful weather assistant.",
        tools=[get_weather_detail],
-        default_options={
-            "on_function_approval": prompt_for_approval,
-            "on_permission_request": PermissionHandler.approve_all,
-        },
+        default_options={"on_function_approval": prompt_for_approval},
    )
    async with agent:
        query = "Give me the detailed weather for Seattle."
@@ -93,16 +87,12 @@ async def run_with_interactive_callback() -> None:
        print(f"Agent: {result}")


-async def run_with_auto_approve_callback() -> None:
-    """Demonstrates a synchronous callback that always approves."""
-    print("\n=== GitHub Copilot Agent: synchronous auto-approve callback ===")
+async def run_with_async_callback() -> None:
+    print("\n=== GitHub Copilot Agent: asynchronous approval callback ===")
    agent = GitHubCopilotAgent(
        instructions="You are a helpful weather assistant.",
        tools=[get_weather_detail],
-        default_options={
-            "on_function_approval": auto_approve,
-            "on_permission_request": PermissionHandler.approve_all,
-        },
+        default_options={"on_function_approval": prompt_for_approval_async},
    )
    async with agent:
        query = "Give me the detailed weather for Tokyo."
@@ -122,7 +112,6 @@ async def run_without_callback() -> None:
    agent = GitHubCopilotAgent(
        instructions="You are a helpful weather assistant.",
        tools=[get_weather_detail],
-        default_options={"on_permission_request": PermissionHandler.approve_all},
    )
    async with agent:
        query = "Give me the detailed weather for Paris."
@@ -133,8 +122,8 @@ async def run_without_callback() -> None:

 async def main() -> None:
    print("=== GitHub Copilot Agent: Function approval enforcement ===")
-    await run_with_interactive_callback()
-    await run_with_auto_approve_callback()
+    await run_with_sync_callback()
+    await run_with_async_callback()
    await run_without_callback()


@@ -22,13 +22,24 @@ import asyncio
 from pathlib import Path

 from agent_framework.github import GitHubCopilotAgent
-from copilot.session import PermissionHandler
+from copilot.generated.session_events import PermissionRequest
+from copilot.session import PermissionRequestResult
 from dotenv import load_dotenv

 # Load environment variables from .env file
 load_dotenv()


+def prompt_permission(request: PermissionRequest, context: dict[str, str]) -> PermissionRequestResult:
+    """Permission handler that prompts the user for approval."""
+    print(f"\n[Permission Request: {request.kind}]")
+
+    response = input("Approve? (y/n): ").strip().lower()
+    if response in ("y", "yes"):
+        return PermissionRequestResult(kind="approved")
+    return PermissionRequestResult(kind="denied-interactively-by-user")
+
+
 async def default_instructions_example() -> None:
    """Example of pointing the agent at project-specific instruction directories."""
    print("=== Instruction Directories (Default) ===\n")
@@ -47,7 +58,7 @@ async def default_instructions_example() -> None:
    agent = GitHubCopilotAgent(
        instructions="You are a helpful coding assistant.",
        default_options={
-            "on_permission_request": PermissionHandler.approve_all,
+            "on_permission_request": prompt_permission,
            "instruction_directories": instruction_dirs,
        },
    )
@@ -68,7 +79,7 @@ async def runtime_override_example() -> None:
    agent = GitHubCopilotAgent(
        instructions="You are a helpful assistant.",
        default_options={
-            "on_permission_request": PermissionHandler.approve_all,
+            "on_permission_request": prompt_permission,
            "instruction_directories": ["/team/shared/instructions"],
        },
    )
@@ -15,13 +15,24 @@ of MCP-related actions.
 import asyncio

 from agent_framework.github import GitHubCopilotAgent
-from copilot.session import MCPServerConfig, PermissionHandler
+from copilot.generated.session_events import PermissionRequest
+from copilot.session import MCPServerConfig, PermissionRequestResult
 from dotenv import load_dotenv

 # Load environment variables from .env file
 load_dotenv()


+def prompt_permission(request: PermissionRequest, context: dict[str, str]) -> PermissionRequestResult:
+    """Permission handler that prompts the user for approval."""
+    print(f"\n[Permission Request: {request.kind}]")
+
+    response = input("Approve? (y/n): ").strip().lower()
+    if response in ("y", "yes"):
+        return PermissionRequestResult(kind="approved")
+    return PermissionRequestResult(kind="denied-interactively-by-user")
+
+
 async def main() -> None:
    print("=== GitHub Copilot Agent with MCP Servers ===\n")

@@ -45,7 +56,7 @@ async def main() -> None:
    agent = GitHubCopilotAgent(
        instructions="You are a helpful assistant with access to the local filesystem and Microsoft Learn.",
        default_options={
-            "on_permission_request": PermissionHandler.approve_all,
+            "on_permission_request": prompt_permission,
            "mcp_servers": mcp_servers,
        },
    )
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
Tao Chen	3a520a1cc2	Fix sample	2026-06-05 09:24:17 -07:00
Tao Chen	2f385003fc	Fix failing tests	2026-06-04 11:26:53 -07:00
Tao Chen	c229a873d4	fix tests	2026-06-03 17:18:23 -07:00
Tao Chen	88528f3dd2	Remove RequestInfoFunctionArgs	2026-06-03 17:09:11 -07:00
Tao Chen	76ec3efaed	Bump min version of azure-ai-project	2026-06-03 15:22:42 -07:00
Tao Chen	e4dcbe555a	Fix mypy	2026-06-03 14:43:48 -07:00
Tao Chen	a9863c038d	Revert uv.lock	2026-06-03 14:09:48 -07:00
Tao Chen	4018d1c46d	Request info non function approval now becomes function call	2026-06-03 13:15:06 -07:00
Tao Chen	f33e5d507a	Merge branch 'main' into local-branch-fix-workflow-as-agent-pending-request-handling	2026-06-02 15:09:28 -07:00
Tao Chen	072c5ad39d	Address comments and fix pipeline	2026-06-02 15:02:24 -07:00
Tao Chen	4f942a3b3f	Fix mypy	2026-06-01 23:01:55 -07:00
Tao Chen	0cea147074	Address Copilot comments	2026-06-01 22:45:00 -07:00
Tao Chen	ed2dd1ff41	Merge branch 'main' into local-branch-fix-workflow-as-agent-pending-request-handling	2026-06-01 22:15:14 -07:00
Tao Chen	5fade9e2a8	Working: Workflow as agent with function approval	2026-06-01 22:10:28 -07:00
Tao Chen	9c0623ca5f	WIP: debugging empty message bug	2026-06-01 09:39:52 -07:00
Tao Chen	4428d53a1e	WIP: Refactor Workflow as agent pending request handling	2026-05-28 17:20:52 -07:00