Python: Bump agent-framework-devui to 1.0.0b260414 for release (#5259 )

Update devui version and changelog for the streaming memory fix release. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Python: Fix reasoning replay when store=False (#5250 )
2026-06-16 21:04:09 +08:00 · 2026-04-15 18:22:15 +00:00 · 2026-04-15 17:30:12 +00:00 · 2026-04-14 10:18:26 +00:00 · 2026-04-14 09:30:31 +00:00 · 2026-04-14 09:27:52 +00:00
1002 changed files with 33939 additions and 15524 deletions
@@ -47,7 +47,7 @@ body:
    attributes:
      label: Package Versions
      description: List the agent-framework-* packages and versions you are using
-      placeholder: "e.g., agent-framework-core: 1.0.0, agent-framework-azure-ai: 1.0.0"
+      placeholder: "e.g., agent-framework-core: 1.0.0, agent-framework-foundry: 1.0.0"
    validations:
      required: true

@@ -82,7 +82,7 @@ jobs:
              .github
              dotnet
              python
-              workflow-samples
+              declarative-agents

      - name: Setup dotnet
        uses: actions/setup-dotnet@v5.2.0
@@ -152,7 +152,7 @@ jobs:
              .github
              dotnet
              python
-              workflow-samples
+              declarative-agents

      # Start Cosmos DB Emulator for all integration tests and only for unit tests when CosmosDB changes happened)
      - name: Start Azure Cosmos DB Emulator
@@ -38,7 +38,7 @@ jobs:
            .github
            dotnet
            python
-            workflow-samples
+            declarative-agents

      - name: Start Azure Cosmos DB Emulator
        if: runner.os == 'Windows'
@@ -0,0 +1,137 @@
+#
+# Runs the .NET sample verification tool, which builds and executes sample projects
+# and verifies their output using deterministic checks and AI-powered verification.
+#
+# Results are displayed as a GitHub Job Summary and the CSV report is uploaded as an artifact.
+#
+
+name: dotnet-verify-samples
+
+on:
+  workflow_dispatch:
+    inputs:
+      category:
+        description: "Sample category to run (blank for all)"
+        required: false
+        type: choice
+        options:
+          - ""
+          - "01-get-started"
+          - "02-agents"
+          - "03-workflows"
+      parallelism:
+        description: "Max parallel sample runs"
+        required: false
+        default: "8"
+        type: string
+  schedule:
+    - cron: "0 6 * * 1-5" # Weekdays at 6:00 UTC
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: true
+
+permissions:
+  contents: read
+  id-token: write
+
+jobs:
+  verify-samples:
+    runs-on: ubuntu-latest
+    environment: 'integration'
+    timeout-minutes: 90
+    steps:
+      - uses: actions/checkout@v6
+        with:
+          persist-credentials: false
+          sparse-checkout: |
+            .
+            .github
+            dotnet
+            python
+            declarative-agents
+
+      - name: Setup dotnet
+        uses: actions/setup-dotnet@v5.2.0
+        with:
+          global-json-file: ${{ github.workspace }}/dotnet/global.json
+
+      - name: Azure CLI Login
+        if: github.event_name != 'pull_request'
+        uses: azure/login@v2
+        with:
+          client-id: ${{ secrets.AZURE_CLIENT_ID }}
+          tenant-id: ${{ secrets.AZURE_TENANT_ID }}
+          subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
+
+      - name: Generate filtered solution
+        shell: pwsh
+        run: |
+          ./dotnet/eng/scripts/New-FilteredSolution.ps1 `
+            -Solution dotnet/agent-framework-dotnet.slnx `
+            -TargetFramework net10.0 `
+            -Configuration Debug `
+            -OutputPath dotnet/filtered.slnx `
+            -Verbose
+
+      - name: Build solution
+        shell: bash
+        run: dotnet build dotnet/filtered.slnx -f net10.0 --warnaserror
+
+      - name: Run verify-samples
+        id: verify
+        working-directory: dotnet
+        shell: bash
+        run: |
+          CATEGORY_ARG=""
+          if [ -n "$CATEGORY_INPUT" ]; then
+            CATEGORY_ARG="--category $CATEGORY_INPUT"
+          fi
+
+          dotnet run --project eng/verify-samples -- \
+            $CATEGORY_ARG \
+            --parallel "$PARALLELISM" \
+            --md results.md \
+            --csv results.csv \
+            --log results.log
+        env:
+          CATEGORY_INPUT: ${{ github.event.inputs.category || '' }}
+          PARALLELISM: ${{ github.event.inputs.parallelism || '8' }}
+          # OpenAI Models
+          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+          OPENAI_CHAT_MODEL_NAME: ${{ vars.OPENAI_CHAT_MODEL_NAME }}
+          OPENAI_REASONING_MODEL_NAME: ${{ vars.OPENAI_REASONING_MODEL_NAME }}
+          # Azure OpenAI Models
+          AZURE_OPENAI_DEPLOYMENT_NAME: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME }}
+          AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME }}
+          AZURE_OPENAI_ENDPOINT: ${{ vars.AZURE_OPENAI_ENDPOINT }}
+          # Azure AI Foundry
+          AZURE_AI_PROJECT_ENDPOINT: ${{ vars.AZURE_AI_PROJECT_ENDPOINT }}
+          AZURE_AI_MODEL_DEPLOYMENT_NAME: ${{ vars.AZURE_AI_MODEL_DEPLOYMENT_NAME }}
+          AZURE_AI_BING_CONNECTION_ID: ${{ vars.AZURE_AI_BING_CONNECTION_ID }}
+
+      - name: Write Job Summary
+        if: always()
+        working-directory: dotnet
+        shell: bash
+        run: |
+          if [ -f results.md ]; then
+            cat results.md >> "$GITHUB_STEP_SUMMARY"
+          else
+            echo "⚠️ No results.md generated — verify-samples may have failed to start." >> "$GITHUB_STEP_SUMMARY"
+          fi
+
+      - name: Upload results
+        if: always()
+        uses: actions/upload-artifact@v7
+        with:
+          name: verify-samples-results
+          path: |
+            dotnet/results.csv
+            dotnet/results.log
+          if-no-files-found: warn
+
+      - name: Fail if samples failed
+        if: always() && steps.verify.outcome == 'failure'
+        shell: bash
+        run: exit 1
@@ -34,14 +34,14 @@ from dataclasses import dataclass
 #   (e.g., "packages/core/agent_framework/observability.py")
 # =============================================================================
 ENFORCED_TARGETS: set[str] = {
-    # Packages
-    "packages.azure-ai.agent_framework_azure_ai",
-    "packages.core.agent_framework",
-    "packages.core.agent_framework._workflows",
-    "packages.purview.agent_framework_purview",
+    # Packages (sorted alphabetically)
    "packages.anthropic.agent_framework_anthropic",
    "packages.azure-ai-search.agent_framework_azure_ai_search",
+    "packages.core.agent_framework",
+    "packages.core.agent_framework._workflows",
+    "packages.foundry.agent_framework_foundry",
    "packages.openai.agent_framework_openai",
+    "packages.purview.agent_framework_purview",
    # Individual files (if you want to enforce specific files instead of whole packages)
    "packages/core/agent_framework/observability.py",
    # Add more targets here as coverage improves
@@ -60,8 +60,8 @@ jobs:
    environment: integration
    timeout-minutes: 60
    env:
-      OPENAI_CHAT_MODEL: ${{ vars.OPENAI__CHATMODELID }}
-      OPENAI_RESPONSES_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
+      OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.OPENAI__CHATMODELID }}
+      OPENAI_CHAT_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
      OPENAI_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
      OPENAI_EMBEDDING_MODEL: ${{ vars.OPENAI_EMBEDDING_MODEL_ID }}
      OPENAI_API_KEY: ${{ secrets.OPENAI__APIKEY }}
@@ -95,10 +95,10 @@ jobs:
    environment: integration
    timeout-minutes: 60
    env:
-      AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__CHATDEPLOYMENTNAME }}
-      AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
-      AZURE_OPENAI_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
-      AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME: ${{ vars.AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME }}
+      AZURE_OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.AZUREOPENAI__CHATDEPLOYMENTNAME }}
+      AZURE_OPENAI_CHAT_MODEL: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
+      AZURE_OPENAI_MODEL: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
+      AZURE_OPENAI_EMBEDDING_MODEL: ${{ vars.AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME }}
      AZURE_OPENAI_ENDPOINT: ${{ vars.AZUREOPENAI__ENDPOINT }}
    defaults:
      run:
@@ -139,7 +139,7 @@ jobs:
    timeout-minutes: 60
    env:
      ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
-      ANTHROPIC_CHAT_MODEL_ID: ${{ vars.ANTHROPIC_CHAT_MODEL_ID }}
+      ANTHROPIC_CHAT_MODEL: ${{ vars.ANTHROPIC_CHAT_MODEL_ID }}
      LOCAL_MCP_URL: ${{ vars.LOCAL_MCP__URL }}
    defaults:
      run:
@@ -201,14 +201,15 @@ jobs:
    timeout-minutes: 60
    env:
      UV_PYTHON: "3.11"
-      OPENAI_CHAT_MODEL: ${{ vars.OPENAI__CHATMODELID }}
-      OPENAI_RESPONSES_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
+      OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.OPENAI__CHATMODELID }}
+      OPENAI_CHAT_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
      OPENAI_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
      OPENAI_EMBEDDING_MODEL: ${{ vars.OPENAI_EMBEDDING_MODEL_ID }}
      OPENAI_API_KEY: ${{ secrets.OPENAI__APIKEY }}
      AZURE_OPENAI_ENDPOINT: ${{ vars.AZUREOPENAI__ENDPOINT }}
-      AZURE_OPENAI_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
-      AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__CHATDEPLOYMENTNAME }}
+      AZURE_OPENAI_MODEL: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
+      AZURE_OPENAI_CHAT_MODEL: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
+      AZURE_OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.AZUREOPENAI__CHATDEPLOYMENTNAME }}
      FOUNDRY_PROJECT_ENDPOINT: ${{ vars.FOUNDRY_PROJECT_ENDPOINT }}
      FOUNDRY_MODEL: ${{ vars.FOUNDRY_MODEL }}
      FUNCTIONS_WORKER_RUNTIME: "python"
@@ -255,12 +256,14 @@ jobs:
    environment: integration
    timeout-minutes: 60
    env:
-      AZURE_AI_PROJECT_ENDPOINT: ${{ secrets.AZUREAI__ENDPOINT }}
-      AZURE_AI_MODEL_DEPLOYMENT_NAME: ${{ vars.AZUREAI__DEPLOYMENTNAME }}
      FOUNDRY_PROJECT_ENDPOINT: ${{ vars.FOUNDRY_PROJECT_ENDPOINT }}
      FOUNDRY_MODEL: ${{ vars.FOUNDRY_MODEL }}
      FOUNDRY_AGENT_NAME: ${{ vars.FOUNDRY_AGENT_NAME }}
      FOUNDRY_AGENT_VERSION: ${{ vars.FOUNDRY_AGENT_VERSION }}
+      FOUNDRY_MODELS_ENDPOINT: ${{ vars.FOUNDRY_MODELS_ENDPOINT || '' }}
+      FOUNDRY_MODELS_API_KEY: ${{ secrets.FOUNDRY_MODELS_API_KEY || '' }}
+      FOUNDRY_EMBEDDING_MODEL: ${{ vars.FOUNDRY_EMBEDDING_MODEL || '' }}
+      FOUNDRY_IMAGE_EMBEDDING_MODEL: ${{ vars.FOUNDRY_IMAGE_EMBEDDING_MODEL || '' }}
      LOCAL_MCP_URL: ${{ vars.LOCAL_MCP__URL }}
    defaults:
      run:
@@ -37,7 +37,7 @@ jobs:
      azureChanged: ${{ steps.filter.outputs.azure }}
      miscChanged: ${{ steps.filter.outputs.misc }}
      functionsChanged: ${{ steps.filter.outputs.functions }}
-      azureAiChanged: ${{ steps.filter.outputs.azure-ai }}
+      foundryChanged: ${{ steps.filter.outputs.foundry }}
      cosmosChanged: ${{ steps.filter.outputs.cosmos }}
    steps:
      - uses: actions/checkout@v6
@@ -75,10 +75,10 @@ jobs:
            functions:
              - 'python/packages/azurefunctions/**'
              - 'python/packages/durabletask/**'
-            azure-ai:
-              - 'python/packages/azure-ai/**'
+            foundry:
              - 'python/packages/foundry/**'
              - 'python/samples/**/providers/foundry/**'
+              - 'python/samples/02-agents/embeddings/foundry_embeddings.py'
            cosmos:
              - 'python/packages/azure-cosmos/**'
      # run only if 'python' files were changed
@@ -115,12 +115,13 @@ jobs:
          -m "not integration"
          --timeout=120 --session-timeout=900 --timeout_method thread
          --retries 2 --retry-delay 5
+          --junitxml=pytest.xml
        working-directory: ./python
      - name: Surface failing tests
        if: always()
        uses: pmeier/pytest-results-action@v0.7.2
        with:
-          path: ./python/**.xml
+          path: ./python/pytest.xml
          summary: true
          display-options: fEX
          fail-on-empty: false
@@ -139,8 +140,8 @@ jobs:
    runs-on: ubuntu-latest
    environment: integration
    env:
-      OPENAI_CHAT_MODEL: ${{ vars.OPENAI__CHATMODELID }}
-      OPENAI_RESPONSES_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
+      OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.OPENAI__CHATMODELID }}
+      OPENAI_CHAT_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
      OPENAI_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
      OPENAI_EMBEDDING_MODEL: ${{ vars.OPENAI_EMBEDDING_MODEL_ID }}
      OPENAI_API_KEY: ${{ secrets.OPENAI__APIKEY }}
@@ -163,6 +164,7 @@ jobs:
          -n logical --dist worksteal
          --timeout=120 --session-timeout=900 --timeout_method thread
          --retries 2 --retry-delay 5
+          --junitxml=pytest.xml
        working-directory: ./python
      - name: Test OpenAI samples
        timeout-minutes: 10
@@ -173,7 +175,7 @@ jobs:
        if: always()
        uses: pmeier/pytest-results-action@v0.7.2
        with:
-          path: ./python/**.xml
+          path: ./python/pytest.xml
          summary: true
          display-options: fEX
          fail-on-empty: false
@@ -192,10 +194,10 @@ jobs:
    runs-on: ubuntu-latest
    environment: integration
    env:
-      AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__CHATDEPLOYMENTNAME }}
-      AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
-      AZURE_OPENAI_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
-      AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME: ${{ vars.AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME }}
+      AZURE_OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.AZUREOPENAI__CHATDEPLOYMENTNAME }}
+      AZURE_OPENAI_CHAT_MODEL: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
+      AZURE_OPENAI_MODEL: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
+      AZURE_OPENAI_EMBEDDING_MODEL: ${{ vars.AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME }}
      AZURE_OPENAI_ENDPOINT: ${{ vars.AZUREOPENAI__ENDPOINT }}
    defaults:
      run:
@@ -225,6 +227,7 @@ jobs:
          -n logical --dist worksteal
          --timeout=120 --session-timeout=900 --timeout_method thread
          --retries 2 --retry-delay 5
+          --junitxml=pytest.xml
        working-directory: ./python
      - name: Test Azure samples
        timeout-minutes: 10
@@ -235,7 +238,7 @@ jobs:
        if: always()
        uses: pmeier/pytest-results-action@v0.7.2
        with:
-          path: ./python/**.xml
+          path: ./python/pytest.xml
          summary: true
          display-options: fEX
          fail-on-empty: false
@@ -255,7 +258,7 @@ jobs:
    environment: integration
    env:
      ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
-      ANTHROPIC_CHAT_MODEL_ID: ${{ vars.ANTHROPIC_CHAT_MODEL_ID }}
+      ANTHROPIC_CHAT_MODEL: ${{ vars.ANTHROPIC_CHAT_MODEL_ID }}
      LOCAL_MCP_URL: ${{ vars.LOCAL_MCP__URL }}
    defaults:
      run:
@@ -285,6 +288,7 @@ jobs:
          -n logical --dist worksteal
          --timeout=120 --session-timeout=900 --timeout_method thread
          --retries 2 --retry-delay 5
+          --junitxml=pytest.xml
        working-directory: ./python
      - name: Stop local MCP server
        if: always()
@@ -310,7 +314,7 @@ jobs:
        if: always()
        uses: pmeier/pytest-results-action@v0.7.2
        with:
-          path: ./python/**.xml
+          path: ./python/pytest.xml
          summary: true
          display-options: fEX
          fail-on-empty: false
@@ -330,14 +334,15 @@ jobs:
    environment: integration
    env:
      UV_PYTHON: "3.11"
-      OPENAI_CHAT_MODEL: ${{ vars.OPENAI__CHATMODELID }}
-      OPENAI_RESPONSES_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
+      OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.OPENAI__CHATMODELID }}
+      OPENAI_CHAT_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
      OPENAI_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
      OPENAI_EMBEDDING_MODEL: ${{ vars.OPENAI_EMBEDDING_MODEL_ID }}
      OPENAI_API_KEY: ${{ secrets.OPENAI__APIKEY }}
      AZURE_OPENAI_ENDPOINT: ${{ vars.AZUREOPENAI__ENDPOINT }}
-      AZURE_OPENAI_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
-      AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__CHATDEPLOYMENTNAME }}
+      AZURE_OPENAI_MODEL: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
+      AZURE_OPENAI_CHAT_MODEL: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
+      AZURE_OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.AZUREOPENAI__CHATDEPLOYMENTNAME }}
      FOUNDRY_PROJECT_ENDPOINT: ${{ vars.FOUNDRY_PROJECT_ENDPOINT }}
      FOUNDRY_MODEL: ${{ vars.FOUNDRY_MODEL }}
      FUNCTIONS_WORKER_RUNTIME: "python"
@@ -374,12 +379,13 @@ jobs:
          -x
          --timeout=360 --session-timeout=900 --timeout_method thread
          --retries 2 --retry-delay 5
+          --junitxml=pytest.xml
        working-directory: ./python
      - name: Surface failing tests
        if: always()
        uses: pmeier/pytest-results-action@v0.7.2
        with:
-          path: ./python/**.xml
+          path: ./python/pytest.xml
          summary: true
          display-options: fEX
          fail-on-empty: false
@@ -392,13 +398,11 @@ jobs:
      github.event_name != 'pull_request' &&
      needs.paths-filter.outputs.pythonChanges == 'true' &&
      (github.event_name != 'merge_group' ||
-       needs.paths-filter.outputs.azureAiChanged == 'true' ||
+       needs.paths-filter.outputs.foundryChanged == 'true' ||
       needs.paths-filter.outputs.coreChanged == 'true')
    runs-on: ubuntu-latest
    environment: integration
    env:
-      AZURE_AI_PROJECT_ENDPOINT: ${{ secrets.AZUREAI__ENDPOINT }}
-      AZURE_AI_MODEL_DEPLOYMENT_NAME: ${{ vars.AZUREAI__DEPLOYMENTNAME }}
      FOUNDRY_PROJECT_ENDPOINT: ${{ vars.FOUNDRY_PROJECT_ENDPOINT }}
      FOUNDRY_MODEL: ${{ vars.FOUNDRY_MODEL }}
      FOUNDRY_AGENT_NAME: ${{ vars.FOUNDRY_AGENT_NAME }}
@@ -431,17 +435,13 @@ jobs:
          -n logical --dist worksteal
          --timeout=120 --session-timeout=900 --timeout_method thread
          --retries 2 --retry-delay 5
-        working-directory: ./python
-      - name: Test Azure AI samples
-        timeout-minutes: 10
-        if: env.RUN_SAMPLES_TESTS == 'true'
-        run: uv run pytest tests/samples/ -m "azure-ai"
+          --junitxml=pytest.xml
        working-directory: ./python
      - name: Surface failing tests
        if: always()
        uses: pmeier/pytest-results-action@v0.7.2
        with:
-          path: ./python/**.xml
+          path: ./python/pytest.xml
          summary: true
          display-options: fEX
          fail-on-empty: false
@@ -495,13 +495,13 @@ jobs:
          echo "Cosmos DB emulator did not become ready in time." >&2
          exit 1
      - name: Test with pytest (Cosmos integration)
-        run: uv run --directory packages/azure-cosmos poe integration-tests -n logical --dist worksteal --timeout=120 --session-timeout=900 --timeout_method thread --retries 2 --retry-delay 5
+        run: uv run --directory packages/azure-cosmos poe integration-tests -n logical --dist worksteal --timeout=120 --session-timeout=900 --timeout_method thread --retries 2 --retry-delay 5 --junitxml=pytest.xml
        working-directory: ./python
      - name: Surface failing tests
        if: always()
        uses: pmeier/pytest-results-action@v0.7.2
        with:
-          path: ./python/**.xml
+          path: ./python/pytest.xml
          summary: true
          display-options: fEX
          fail-on-empty: false
@@ -65,12 +65,14 @@ jobs:
      FOUNDRY_MODEL: ${{ vars.FOUNDRY_MODEL || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
      # Azure OpenAI configuration
      AZURE_OPENAI_ENDPOINT: ${{ vars.AZUREOPENAI__ENDPOINT }}
-      AZURE_OPENAI_DEPLOYMENT_NAME: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
-      AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME: ${{ vars.AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME || vars.AZUREOPENAI__EMBEDDINGDEPLOYMENTNAME }}
+      AZURE_OPENAI_MODEL: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
+      AZURE_OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.AZUREOPENAI__CHATDEPLOYMENTNAME }}
+      AZURE_OPENAI_CHAT_MODEL: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
+      AZURE_OPENAI_EMBEDDING_MODEL: ${{ vars.AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME || vars.AZUREOPENAI__EMBEDDINGDEPLOYMENTNAME }}
      # OpenAI configuration
      OPENAI_API_KEY: ${{ secrets.OPENAI__APIKEY }}
-      OPENAI_CHAT_MODEL_ID: ${{ vars.OPENAI__CHATMODELID }}
-      OPENAI_RESPONSES_MODEL_ID: ${{ vars.OPENAI__RESPONSESMODELID }}
+      OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.OPENAI__CHATMODELID }}
+      OPENAI_CHAT_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
      # GitHub MCP
      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
      OPENAI_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
@@ -95,11 +97,13 @@ jobs:
          echo "FOUNDRY_PROJECT_ENDPOINT=$FOUNDRY_PROJECT_ENDPOINT" >> .env
          echo "FOUNDRY_MODEL=$FOUNDRY_MODEL" >> .env
          echo "AZURE_OPENAI_ENDPOINT=$AZURE_OPENAI_ENDPOINT" >> .env
-          echo "AZURE_OPENAI_DEPLOYMENT_NAME=$AZURE_OPENAI_DEPLOYMENT_NAME" >> .env
-          echo "AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME=$AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME" >> .env
+          echo "AZURE_OPENAI_MODEL=$AZURE_OPENAI_MODEL" >> .env
+          echo "AZURE_OPENAI_CHAT_COMPLETION_MODEL=$AZURE_OPENAI_CHAT_COMPLETION_MODEL" >> .env
+          echo "AZURE_OPENAI_CHAT_MODEL=$AZURE_OPENAI_CHAT_MODEL" >> .env
+          echo "AZURE_OPENAI_EMBEDDING_MODEL=$AZURE_OPENAI_EMBEDDING_MODEL" >> .env
          echo "OPENAI_API_KEY=$OPENAI_API_KEY" >> .env
-          echo "OPENAI_CHAT_MODEL_ID=$OPENAI_CHAT_MODEL_ID" >> .env
-          echo "OPENAI_RESPONSES_MODEL_ID=$OPENAI_RESPONSES_MODEL_ID" >> .env
+          echo "OPENAI_CHAT_COMPLETION_MODEL=$OPENAI_CHAT_COMPLETION_MODEL" >> .env
+          echo "OPENAI_CHAT_MODEL=$OPENAI_CHAT_MODEL" >> .env
          echo "GITHUB_PAT=$GITHUB_PAT" >> .env

      - name: Run sample validation
@@ -120,8 +124,8 @@ jobs:
    env:
      OPENAI_API_KEY: ${{ secrets.OPENAI__APIKEY }}
      OPENAI_MODEL: ${{ vars.OPENAI__CHATMODELID }}
-      OPENAI_CHAT_MODEL_ID: ${{ vars.OPENAI__CHATMODELID }}
-      OPENAI_RESPONSES_MODEL_ID: ${{ vars.OPENAI__RESPONSESMODELID }}
+      OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.OPENAI__CHATMODELID }}
+      OPENAI_CHAT_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
    defaults:
      run:
        working-directory: python
@@ -140,8 +144,8 @@ jobs:
        run: |
          echo "OPENAI_API_KEY=$OPENAI_API_KEY" >> .env
          echo "OPENAI_MODEL=$OPENAI_MODEL" >> .env
-          echo "OPENAI_CHAT_MODEL_ID=$OPENAI_CHAT_MODEL_ID" >> .env
-          echo "OPENAI_RESPONSES_MODEL_ID=$OPENAI_RESPONSES_MODEL_ID" >> .env
+          echo "OPENAI_CHAT_COMPLETION_MODEL=$OPENAI_CHAT_COMPLETION_MODEL" >> .env
+          echo "OPENAI_CHAT_MODEL=$OPENAI_CHAT_MODEL" >> .env

      - name: Run sample validation
        run: |
@@ -160,7 +164,7 @@ jobs:
    environment: integration
    env:
      AZURE_OPENAI_ENDPOINT: ${{ vars.AZUREOPENAI__ENDPOINT }}
-      AZURE_OPENAI_DEPLOYMENT_NAME: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
+      AZURE_OPENAI_MODEL: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
      AZURE_OPENAI_API_VERSION: ${{ vars.AZURE_OPENAI_API_VERSION || '' }}
    defaults:
      run:
@@ -179,7 +183,7 @@ jobs:
      - name: Create .env for samples
        run: |
          echo "AZURE_OPENAI_ENDPOINT=$AZURE_OPENAI_ENDPOINT" >> .env
-          echo "AZURE_OPENAI_DEPLOYMENT_NAME=$AZURE_OPENAI_DEPLOYMENT_NAME" >> .env
+          echo "AZURE_OPENAI_MODEL=$AZURE_OPENAI_MODEL" >> .env
          echo "AZURE_OPENAI_API_VERSION=$AZURE_OPENAI_API_VERSION" >> .env

      - name: Run sample validation
@@ -199,7 +203,7 @@ jobs:
    environment: integration
    env:
      ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
-      ANTHROPIC_CHAT_MODEL_ID: ${{ vars.ANTHROPIC_CHAT_MODEL_ID }}
+      ANTHROPIC_CHAT_MODEL: ${{ vars.ANTHROPIC_CHAT_MODEL_ID }}
    defaults:
      run:
        working-directory: python
@@ -217,7 +221,7 @@ jobs:
      - name: Create .env for samples
        run: |
          echo "ANTHROPIC_API_KEY=$ANTHROPIC_API_KEY" >> .env
-          echo "ANTHROPIC_CHAT_MODEL_ID=$ANTHROPIC_CHAT_MODEL_ID" >> .env
+          echo "ANTHROPIC_CHAT_MODEL=$ANTHROPIC_CHAT_MODEL" >> .env

      - name: Run sample validation
        run: |
@@ -265,7 +269,7 @@ jobs:
    runs-on: ubuntu-latest
    environment: integration
    env:
-      BEDROCK_CHAT_MODEL_ID: ${{ vars.BEDROCK__CHATMODELID }}
+      BEDROCK_CHAT_MODEL: ${{ vars.BEDROCK__CHATMODELID }}
    defaults:
      run:
        working-directory: python
@@ -518,7 +522,7 @@ jobs:
      FOUNDRY_MODEL: ${{ vars.FOUNDRY_MODEL || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
      # Azure OpenAI configuration
      AZURE_OPENAI_ENDPOINT: ${{ vars.AZUREOPENAI__ENDPOINT }}
-      AZURE_OPENAI_DEPLOYMENT_NAME: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
+      AZURE_OPENAI_MODEL: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
      # Azure AI Search (for evaluation samples)
      AZURE_SEARCH_ENDPOINT: ${{ secrets.AZURE_SEARCH_ENDPOINT }}
      AZURE_SEARCH_API_KEY: ${{ secrets.AZURE_SEARCH_API_KEY }}
@@ -560,11 +564,11 @@ jobs:
      FOUNDRY_MODEL: ${{ vars.FOUNDRY_MODEL || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
      # Azure OpenAI configuration
      AZURE_OPENAI_ENDPOINT: ${{ vars.AZUREOPENAI__ENDPOINT }}
-      AZURE_OPENAI_DEPLOYMENT_NAME: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
+      AZURE_OPENAI_MODEL: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
      # OpenAI configuration
      OPENAI_API_KEY: ${{ secrets.OPENAI__APIKEY }}
-      OPENAI_CHAT_MODEL_ID: ${{ vars.OPENAI__CHATMODELID }}
-      OPENAI_RESPONSES_MODEL_ID: ${{ vars.OPENAI__RESPONSESMODELID }}
+      OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.OPENAI__CHATMODELID }}
+      OPENAI_CHAT_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
      OPENAI_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
    defaults:
      run:
@@ -585,10 +589,10 @@ jobs:
          echo "FOUNDRY_PROJECT_ENDPOINT=$FOUNDRY_PROJECT_ENDPOINT" >> .env
          echo "FOUNDRY_MODEL=$FOUNDRY_MODEL" >> .env
          echo "AZURE_OPENAI_ENDPOINT=$AZURE_OPENAI_ENDPOINT" >> .env
-          echo "AZURE_OPENAI_DEPLOYMENT_NAME=$AZURE_OPENAI_DEPLOYMENT_NAME" >> .env
+          echo "AZURE_OPENAI_MODEL=$AZURE_OPENAI_MODEL" >> .env
          echo "OPENAI_API_KEY=$OPENAI_API_KEY" >> .env
-          echo "OPENAI_CHAT_MODEL_ID=$OPENAI_CHAT_MODEL_ID" >> .env
-          echo "OPENAI_RESPONSES_MODEL_ID=$OPENAI_RESPONSES_MODEL_ID" >> .env
+          echo "OPENAI_CHAT_COMPLETION_MODEL=$OPENAI_CHAT_COMPLETION_MODEL" >> .env
+          echo "OPENAI_CHAT_MODEL=$OPENAI_CHAT_MODEL" >> .env

      - name: Run sample validation
        run: |
@@ -608,14 +612,18 @@ jobs:
    env:
      FOUNDRY_PROJECT_ENDPOINT: ${{ vars.FOUNDRY_PROJECT_ENDPOINT || vars.AZURE_AI_PROJECT_ENDPOINT }}
      FOUNDRY_MODEL: ${{ vars.FOUNDRY_MODEL || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
-      # Azure OpenAI configuration
+      # Azure OpenAI configuration for AF
      AZURE_OPENAI_ENDPOINT: ${{ vars.AZUREOPENAI__ENDPOINT }}
-      AZURE_OPENAI_DEPLOYMENT_NAME: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
-      # OpenAI configuration
+      AZURE_OPENAI_MODEL: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
+      # Azure OpenAI configuration for SK
+      AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME }}
+      # OpenAI key
      OPENAI_API_KEY: ${{ secrets.OPENAI__APIKEY }}
-      OPENAI_CHAT_MODEL_ID: ${{ vars.OPENAI__CHATMODELID }}
-      OPENAI_RESPONSES_MODEL_ID: ${{ vars.OPENAI__RESPONSESMODELID }}
+      OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.OPENAI__CHATMODELID }}
+      OPENAI_CHAT_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
      OPENAI_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
+      # OpenAI configuration for SK
+      OPENAI_CHAT_MODEL_ID: ${{ vars.OPENAI__CHATMODELID }}
      # Copilot Studio
      COPILOTSTUDIOAGENT__ENVIRONMENTID: ${{ secrets.COPILOTSTUDIOAGENT__ENVIRONMENTID }}
      COPILOTSTUDIOAGENT__SCHEMANAME: ${{ secrets.COPILOTSTUDIOAGENT__SCHEMANAME }}
@@ -640,10 +648,10 @@ jobs:
          echo "FOUNDRY_PROJECT_ENDPOINT=$FOUNDRY_PROJECT_ENDPOINT" >> .env
          echo "FOUNDRY_MODEL=$FOUNDRY_MODEL" >> .env
          echo "AZURE_OPENAI_ENDPOINT=$AZURE_OPENAI_ENDPOINT" >> .env
-          echo "AZURE_OPENAI_DEPLOYMENT_NAME=$AZURE_OPENAI_DEPLOYMENT_NAME" >> .env
+          echo "AZURE_OPENAI_MODEL=$AZURE_OPENAI_MODEL" >> .env
          echo "OPENAI_API_KEY=$OPENAI_API_KEY" >> .env
-          echo "OPENAI_CHAT_MODEL_ID=$OPENAI_CHAT_MODEL_ID" >> .env
-          echo "OPENAI_RESPONSES_MODEL_ID=$OPENAI_RESPONSES_MODEL_ID" >> .env
+          echo "OPENAI_CHAT_COMPLETION_MODEL=$OPENAI_CHAT_COMPLETION_MODEL" >> .env
+          echo "OPENAI_CHAT_MODEL=$OPENAI_CHAT_MODEL" >> .env
          echo "COPILOTSTUDIOAGENT__ENVIRONMENTID=$COPILOTSTUDIOAGENT__ENVIRONMENTID" >> .env
          echo "COPILOTSTUDIOAGENT__SCHEMANAME=$COPILOTSTUDIOAGENT__SCHEMANAME" >> .env
          echo "COPILOTSTUDIOAGENT__TENANTID=$COPILOTSTUDIOAGENT__TENANTID" >> .env
@@ -40,7 +40,7 @@ jobs:
          UV_CACHE_DIR: /tmp/.uv-cache
      # Unit tests
      - name: Run all tests
-        run: uv run poe test -A
+        run: uv run poe test -A --junitxml=pytest.xml
        working-directory: ./python

      # Surface failing tests
@@ -48,7 +48,7 @@ jobs:
        if: always()
        uses: pmeier/pytest-results-action@v0.7.2
        with:
-          path: ./python/**.xml
+          path: ./python/pytest.xml
          summary: true
          display-options: fEX
          fail-on-empty: false
@@ -47,6 +47,8 @@ htmlcov/
 .cache
 nosetests.xml
 coverage.xml
+pytest.xml
+python-coverage.xml
 *.cover
 *.py,cover
 .hypothesis/
@@ -230,3 +232,6 @@ local.settings.json
 # Database files
 *.db
 python/dotnet-ref
+
+# Generated filtered solution files (created by eng/scripts/New-FilteredSolution.ps1)
+dotnet/filtered-*.slnx
@@ -28,7 +28,7 @@ Welcome to Microsoft's comprehensive multi-language framework for building, orch
 Python

 ```bash
-pip install agent-framework --pre
+pip install agent-framework
 # This will install all sub-packages, see `python/packages` for individual packages.
 # It may take a minute on first install on Windows.
 ```
@@ -90,27 +90,27 @@ Still have questions? Join our [weekly office hours](./COMMUNITY.md#public-commu
 Create a simple Azure Responses Agent that writes a haiku about the Microsoft Agent Framework

 ```python
-# pip install agent-framework --pre
+# pip install agent-framework
 # Use `az login` to authenticate with Azure CLI
 import os
 import asyncio
-from agent_framework.azure import AzureOpenAIResponsesClient
+from agent_framework import Agent
+from agent_framework.foundry import FoundryChatClient
 from azure.identity import AzureCliCredential


 async def main():
-    # Initialize a chat agent with Azure OpenAI Responses
+    # Initialize a chat agent with Microsoft Foundry
    # the endpoint, deployment name, and api version can be set via environment variables
-    # or they can be passed in directly to the AzureOpenAIResponsesClient constructor
-    agent = AzureOpenAIResponsesClient(
-        # endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],
-        # deployment_name=os.environ["AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME"],
-        # api_version=os.environ["AZURE_OPENAI_API_VERSION"],
-        # api_key=os.environ["AZURE_OPENAI_API_KEY"],  # Optional if using AzureCliCredential
-        credential=AzureCliCredential(), # Optional, if using api_key
-    ).as_agent(
-        name="HaikuBot",
-        instructions="You are an upbeat assistant that writes beautifully.",
+    # or they can be passed in directly to the FoundryChatClient constructor
+    agent = Agent(
+      client=FoundryChatClient(
+          credential=AzureCliCredential(),
+          # project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
+          # model=os.environ["FOUNDRY_MODEL_DEPLOYMENT_NAME"],
+      ),
+      name="HaikuBot",
+      instructions="You are an upbeat assistant that writes beautifully.",
    )

    print(await agent.run("Write a haiku about Microsoft Agent Framework."))
@@ -120,38 +120,38 @@ if __name__ == "__main__":
 ```

 ### Basic Agent - .NET
+Create a simple Agent, using Microsoft Foundry with token-based auth, that writes a haiku about the Microsoft Agent Framework
+
+```c#
+// dotnet add package Microsoft.Agents.AI.Foundry
+// Use `az login` to authenticate with Azure CLI
+using Azure.AI.Projects;
+using Azure.Identity;
+using System;
+using Azure.AI.Projects;
+using Azure.Identity;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+
+var agent = new AIProjectClient(new Uri(endpoint), new DefaultAzureCredential())
+    .AsAIAgent(model: deploymentName, name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");
+
+Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Framework."));
+```

 Create a simple Agent, using OpenAI Responses, that writes a haiku about the Microsoft Agent Framework

 ```c#
-// dotnet add package Microsoft.Agents.AI.OpenAI --prerelease
-using Microsoft.Agents.AI;
+// dotnet add package Microsoft.Agents.AI.OpenAI
+using System;
 using OpenAI;
 using OpenAI.Responses;

 // Replace the <apikey> with your OpenAI API key.
 var agent = new OpenAIClient("<apikey>")
-    .GetResponsesClient("gpt-4o-mini")
-    .AsAIAgent(name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");
-
-Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Framework."));
-```
-
-Create a simple Agent, using Microsoft Foundry with token-based auth, that writes a haiku about the Microsoft Agent Framework
-
-```c#
-// dotnet add package Microsoft.Agents.AI.AzureAI --prerelease
-// dotnet add package Azure.Identity
-// Use `az login` to authenticate with Azure CLI
-using Azure.AI.Projects;
-using Azure.Identity;
-using Microsoft.Agents.AI;
-
-var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
-
-var agent = new AIProjectClient(new Uri(endpoint), new DefaultAzureCredential())
-    .AsAIAgent(model: deploymentName, name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");
+    .GetResponsesClient()
+    .AsAIAgent(model: "gpt-5.4-mini", name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");

 Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Framework."));
 ```
@@ -207,4 +207,9 @@ The samples typically read configuration from environment variables. Common requ

 ## Important Notes

-If you use the Microsoft Agent Framework to build applications that operate with third-party servers or agents, you do so at your own risk. We recommend reviewing all data being shared with third-party servers or agents and being cognizant of third-party practices for retention and location of data. It is your responsibility to manage whether your data will flow outside of your organization's Azure compliance and geographic boundaries and any related implications.
+> [!IMPORTANT]
+> If you use Microsoft Agent Framework to build applications that operate with any third-party servers, agents, code, or non-Azure Direct models (“Third-Party Systems”), you do so at your own risk. Third-Party Systems are Non-Microsoft Products under the Microsoft Product Terms and are governed by their own third-party license terms. You are responsible for any usage and associated costs.
+>
+>We recommend reviewing all data being shared with and received from Third-Party Systems and being cognizant of third-party practices for handling, sharing, retention and location of data. It is your responsibility to manage whether your data will flow outside of your organization’s Azure compliance and geographic boundaries and any related implications, and that appropriate permissions, boundaries and approvals are provisioned.
+> 
+>You are responsible for carefully reviewing and testing applications you build using Microsoft Agent Framework in the context of your specific use cases, and making all appropriate decisions and customizations. This includes implementing your own responsible AI mitigations such as metaprompt, content filters, or other safety systems, and ensuring your applications meet appropriate quality, reliability, security, and trustworthiness standards. See also: [Transparency FAQ](./TRANSPARENCY_FAQ.md)
@@ -1,3 +1,3 @@
 # Declarative Agents

-This folder contains sample agent definitions that can be run using the declarative agent support, for python see the [declarative agent python sample folder](../python/samples/02-agents/declarative/).
+This folder contains sample agent definitions that can be run using the declarative agent support, for python see the [declarative agent python sample folder](../../python/samples/02-agents/declarative/).
@@ -3,13 +3,13 @@ name: MicrosoftLearnAgent
 description: Microsoft Learn Agent
 instructions: You answer questions by searching the Microsoft Learn content only.
 model:
-    id: =Env.AZURE_FOUNDRY_PROJECT_MODEL_ID
+    id: =Env.FOUNDRY_MODEL
    options:
        temperature: 0.9
        topP: 0.95
    connection:
        kind: remote
-        endpoint: =Env.AZURE_FOUNDRY_PROJECT_ENDPOINT
+        endpoint: =Env.FOUNDRY_PROJECT_ENDPOINT
 tools:
  - kind: mcp
    name: microsoft_learn
@@ -10,8 +10,8 @@ Workflow workflow = DeclarativeWorkflowBuilder.Build("Marketing.yaml", options);
 ```

 These example workflows may be executed by the workflow
-[Samples](../dotnet/samples/03-workflows/Declarative)
+[Samples](../../dotnet/samples/03-workflows/Declarative)
 that are present in this repository.

-> See the [README.md](../dotnet/samples/03-workflows/Declarative/README.md) 
+> See the [README.md](../../dotnet/samples/03-workflows/Declarative/README.md) 
 associated with the samples for configuration details.
@@ -37,7 +37,7 @@ Key changes:
 4. **New `FoundryChatClient`** in azure-ai for Azure AI Foundry Responses API access, built on `RawFoundryChatClient(RawOpenAIChatClient)`.
 5. **All deprecated `AzureOpenAI*` classes** consolidated into a single file (`_deprecated_azure_openai.py`) in the azure-ai package for clean future deletion.
 6. **Core's `agent_framework.openai` and `agent_framework.azure` namespaces** become lazy-loading gateways, preserving backward-compatible import paths while removing hard dependencies.
-7. **Unified `model` parameter** replaces `model_id` (OpenAI), `deployment_name` (Azure OpenAI), and `model_deployment_name` (Azure AI) across all client constructors. The term `model` is intentionally generic: it naturally maps to an OpenAI model name *and* to an Azure OpenAI deployment name, making it straightforward to use `OpenAIChatClient` with either OpenAI or Azure OpenAI backends (via `AsyncAzureOpenAI`). Environment variables are similarly unified (e.g., `OPENAI_MODEL` instead of separate `OPENAI_RESPONSES_MODEL_ID` / `OPENAI_CHAT_MODEL_ID`).
+7. **Unified `model` parameter** replaces `model_id` (OpenAI), `deployment_name` (Azure OpenAI), and `model_deployment_name` (Azure AI) across all client constructors. The term `model` is intentionally generic: it naturally maps to an OpenAI model name *and* to an Azure OpenAI deployment name, making it straightforward to use `OpenAIChatClient` with either OpenAI or Azure OpenAI backends (via `AsyncAzureOpenAI`). Environment variables are similarly unified (e.g., `OPENAI_MODEL` instead of separate `OPENAI_CHAT_MODEL_ID` / `OPENAI_CHAT_COMPLETION_MODEL_ID`).
 8. **`FoundryAgent`** replaces the pattern of `Agent(client=AzureAIClient(...))` for connecting to pre-configured agents in Azure AI Foundry (PromptAgents and HostedAgents). The underlying `RawFoundryAgentChatClient` is an implementation detail — most users interact only with `FoundryAgent`. `AzureAIAgentClient` is separately deprecated as it refers to the V1 Agents Service API. See below for design rationale.

 ### Foundry Agent Design: `FoundryAgentClient` vs `FoundryAgent`
@@ -177,7 +177,7 @@ This feature ports the vector store abstractions, embedding generator abstractio
 **Goal:** Add embedding generators to all existing AF provider packages that have chat clients.
 **Mergeable:** Yes — each is independent, added to existing provider packages.

-#### 2.1 — Azure AI Inference embedding (in `packages/azure-ai/`)
+#### 2.1 — Foundry inference embedding (in `packages/foundry/`)
 #### 2.2 — Ollama embedding (in `packages/ollama/`)
 #### 2.3 — Anthropic embedding (in `packages/anthropic/`)
 #### 2.4 — Bedrock embedding (in `packages/bedrock/`)
@@ -12,8 +12,8 @@ dotnet/
 │   ├── Microsoft.Agents.AI.Abstractions/         # Core AI agent abstractions
 │   ├── Microsoft.Agents.AI.A2A/                  # Agent-to-Agent (A2A) provider
 │   ├── Microsoft.Agents.AI.OpenAI/               # OpenAI provider
-│   ├── Microsoft.Agents.AI.AzureAI/              # Azure AI Foundry Agents (v2) provider
-│   ├── Microsoft.Agents.AI.AzureAI.Persistent/   # Legacy Azure AI Foundry Agents (v1) provider
+│   ├── Microsoft.Agents.AI.Foundry/               # Microsoft Foundry Agents (v2) provider
+│   ├── Microsoft.Agents.AI.AzureAI.Persistent/   # Legacy Microsoft Foundry Agents (v1) provider
 │   ├── Microsoft.Agents.AI.Anthropic/            # Anthropic provider
 │   ├── Microsoft.Agents.AI.Workflows/            # Workflow orchestration
 │   └── ...                                       # Other packages
@@ -0,0 +1,225 @@
+---
+name: verify-samples-tool
+description: How to use the verify-samples tool to run, verify, and manage sample definitions in the Agent Framework repository. Use this when adding, updating, or running sample verification.
+---
+
+# verify-samples Tool
+
+The `verify-samples` project (`dotnet/eng/verify-samples/`) is an automated tool that runs sample projects and verifies their output using deterministic checks and AI-powered verification.
+
+## Running verify-samples
+
+**Important:** By default, samples must be pre-built before running verify-samples. Build the solution first, or pass `--build` to build samples during the run:
+
+```bash
+cd dotnet
+dotnet build agent-framework-dotnet.slnx -f net10.0
+```
+
+Then run verify-samples:
+
+```bash
+# Run all samples across all categories
+dotnet run --project eng/verify-samples -- --log results.log --csv results.csv
+
+# Run a specific category
+dotnet run --project eng/verify-samples -- --category 02-agents --log results.log
+
+# Run specific samples by name
+dotnet run --project eng/verify-samples -- Agent_Step02_StructuredOutput Agent_Step09_AsFunctionTool
+
+# Control parallelism (default 8)
+dotnet run --project eng/verify-samples -- --parallel 8 --log results.log
+
+# Build samples during run (skips the need for a prior build step)
+# This may cause build conflicts as multiple samples are built in parallel, so use with caution
+dotnet run --project eng/verify-samples -- --build --log results.log
+
+# Combine options
+dotnet run --project eng/verify-samples -- --category 03-workflows --parallel 4 --log results.log --csv results.csv --md results.md
+```
+
+### Required Environment Variables
+
+The tool itself needs:
+- `AZURE_OPENAI_ENDPOINT` — for the AI verification agent
+- `AZURE_OPENAI_DEPLOYMENT_NAME` (optional, defaults to `gpt-5-mini`)
+
+Individual samples require their own env vars (e.g., `AZURE_AI_PROJECT_ENDPOINT`). The tool automatically checks and skips samples with missing env vars.
+
+### Output Files
+
+- `--log results.log` — detailed per-sample log with stdout/stderr, AI reasoning, and a summary
+- `--csv results.csv` — tabular summary with Sample, ProjectPath, Status, FailedChecks, and Failures columns
+- `--md results.md` — Markdown summary with results table and collapsible failure details (suitable for GitHub PR comments)
+
+## Sample Categories
+
+Definitions are in the `dotnet/eng/verify-samples/` directory:
+
+| Category | Config File | Registered Key |
+|----------|-------------|----------------|
+| 01-get-started | `GetStartedSamples.cs` | `01-get-started` |
+| 02-agents | `AgentsSamples.cs` | `02-agents` |
+| 03-workflows | `WorkflowSamples.cs` | `03-workflows` |
+
+Categories are registered in `VerifyOptions.cs` in the `s_sampleSets` dictionary.
+
+## SampleDefinition Properties
+
+Each sample is defined as a `SampleDefinition` in the appropriate config file. Key properties:
+
+```csharp
+new SampleDefinition
+{
+    // Required: Display name for the sample
+    Name = "Agent_Step02_StructuredOutput",
+
+    // Required: Relative path from dotnet/ to the sample project directory
+    ProjectPath = "samples/02-agents/Agents/Agent_Step02_StructuredOutput",
+
+    // Environment variables the sample requires (throws if missing)
+    RequiredEnvironmentVariables = ["AZURE_OPENAI_ENDPOINT"],
+
+    // Environment variables with defaults that would prompt on console if unset
+    OptionalEnvironmentVariables = ["AZURE_OPENAI_DEPLOYMENT_NAME"],
+
+    // Skip this sample with a reason (for structural issues only)
+    SkipReason = null, // or "Requires external service X."
+
+    // Deterministic checks: substrings that must appear in stdout
+    MustContain = ["=== Section Header ==="],
+
+    // Substrings that must NOT appear in stdout
+    MustNotContain = [],
+
+    // If true, only MustContain checks are used (no AI verification)
+    IsDeterministic = false,
+
+    // AI verification: natural-language descriptions of expected output
+    // Each entry describes one aspect to verify independently
+    ExpectedOutputDescription =
+    [
+        "The output should show structured person information with Name, Age, and Occupation fields.",
+        "The output should not contain error messages or stack traces.",
+    ],
+
+    // Stdin inputs to feed to the sample (for interactive samples)
+    Inputs = ["Y", "Y", "Y"],
+
+    // Delay between stdin inputs in ms (default 2000, increase for LLM calls between inputs)
+    InputDelayMs = 3000,
+}
+```
+
+## How to Add a New Sample Definition
+
+1. **Check the sample's Program.cs** to understand:
+   - What environment variables it reads (look for `GetEnvironmentVariable`)
+   - Whether it needs stdin input (look for `Console.ReadLine`, `Application.GetInput`)
+   - Whether it has an external loop (look for `EXIT` patterns in YAML workflows)
+   - What output it produces (section headers, markers, expected behavior)
+   - Whether it exits on its own or runs as a server
+
+2. **Choose the right verification strategy:**
+   - **Deterministic** (`IsDeterministic = true`): Use `MustContain` for samples with fixed output strings. No AI verification.
+   - **AI-verified** (default): Use `ExpectedOutputDescription` with semantic descriptions. Write expectations that are flexible enough for non-deterministic LLM output.
+   - **Both**: Use `MustContain` for fixed markers AND `ExpectedOutputDescription` for LLM-generated content.
+
+3. **Set `SkipReason` only for structural issues:**
+   - Web servers that don't exit
+   - Multi-process client/server architectures
+   - Samples requiring external infrastructure (MCP servers you can't reach, Docker, etc.)
+   - Do NOT skip for missing env vars — the tool checks those dynamically.
+
+4. **For interactive samples, provide `Inputs`:**
+   - Samples using `Application.GetInput(args)` need one initial input
+   - Samples with `Console.ReadLine()` approval loops need `"Y"` inputs
+   - YAML workflows with `externalLoop` need `"EXIT"` as the last input
+   - Set `InputDelayMs` to 3000-8000ms for samples with LLM calls between inputs
+
+5. **Add the definition** to the appropriate config file (e.g., `AgentsSamples.cs`) in the `All` list.
+
+6. **Register new categories** (if needed) in `VerifyOptions.cs` `s_sampleSets` dictionary.
+
+### Writing Good ExpectedOutputDescription
+
+- Write descriptions that are **semantically flexible** — LLM output varies between runs
+- Each array entry should describe **one independent aspect** to verify
+- Always include `"The output should not contain error messages or stack traces."` as the last entry
+- Avoid exact wording expectations — use "should mention", "should contain information about", "should show"
+- Bad: `"The output should say 'The weather in Amsterdam is cloudy with a high of 15°C'"`
+- Good: `"The output should contain weather information about Amsterdam mentioning cloudy weather with a high of 15°C."`
+
+### Example: Simple LLM Sample
+
+```csharp
+new SampleDefinition
+{
+    Name = "Agent_With_AzureOpenAIChatCompletion",
+    ProjectPath = "samples/02-agents/AgentProviders/Agent_With_AzureOpenAIChatCompletion",
+    RequiredEnvironmentVariables = ["AZURE_OPENAI_ENDPOINT"],
+    OptionalEnvironmentVariables = ["AZURE_OPENAI_DEPLOYMENT_NAME"],
+    ExpectedOutputDescription =
+    [
+        "The output should contain a joke about a pirate.",
+        "The output should not contain error messages or stack traces.",
+    ],
+},
+```
+
+### Example: Deterministic Sample
+
+```csharp
+new SampleDefinition
+{
+    Name = "Workflow_Declarative_GenerateCode",
+    ProjectPath = "samples/03-workflows/Declarative/GenerateCode",
+    IsDeterministic = true,
+    MustContain = ["WORKFLOW: Parsing", "WORKFLOW: Defined"],
+    ExpectedOutputDescription = ["The output should show a YAML workflow being parsed and C# code being generated from it."],
+},
+```
+
+### Example: Interactive Sample with Approval Loop
+
+```csharp
+new SampleDefinition
+{
+    Name = "FoundryAgent_Hosted_MCP",
+    ProjectPath = "samples/02-agents/ModelContextProtocol/FoundryAgent_Hosted_MCP",
+    RequiredEnvironmentVariables = ["AZURE_AI_PROJECT_ENDPOINT"],
+    OptionalEnvironmentVariables = ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+    Inputs = ["Y", "Y", "Y", "Y", "Y"],
+    InputDelayMs = 5000,
+    ExpectedOutputDescription = ["The output should show an agent using the Microsoft Learn MCP tool with approval prompts."],
+},
+```
+
+### Example: Declarative Workflow with External Loop
+
+```csharp
+new SampleDefinition
+{
+    Name = "Workflow_Declarative_FunctionTools",
+    ProjectPath = "samples/03-workflows/Declarative/FunctionTools",
+    RequiredEnvironmentVariables = ["AZURE_AI_PROJECT_ENDPOINT"],
+    OptionalEnvironmentVariables = ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+    Inputs = ["What are today's specials?", "EXIT"],
+    InputDelayMs = 8000,
+    ExpectedOutputDescription = ["The output should show a workflow calling function tools to answer a question about restaurant specials."],
+},
+```
+
+### Example: Skipped Sample
+
+```csharp
+new SampleDefinition
+{
+    Name = "Agent_MCP_Server",
+    ProjectPath = "samples/02-agents/ModelContextProtocol/Agent_MCP_Server",
+    RequiredEnvironmentVariables = ["AZURE_OPENAI_ENDPOINT"],
+    OptionalEnvironmentVariables = ["AZURE_OPENAI_DEPLOYMENT_NAME"],
+    SkipReason = "Runs as an MCP stdio server that does not exit on its own.",
+},
+```
@@ -29,13 +29,14 @@ using types like `IChatClient`, `FunctionInvokingChatClient`, `AITool`, `AIFunct

 ## Key Conventions

- **Encoding**: All new files must be saved with UTF-8 encoding with BOM (Byte Order Mark). This is required for `dotnet format` to work correctly.
+- **Command output capture**: When running `dotnet build`, `dotnet test`, `dotnet format`, or similar commands, redirect output to a temp file first (e.g., `dotnet build --tl:off 2>&1 | Out-File $env:TEMP\build.log`), then analyze the file as needed. This avoids re-running expensive commands when the initial analysis misses something.
+- **Encoding**: All new files must be saved with UTF-8 encoding with BOM (Byte Order Mark). This is required for `dotnet format` to work correctly. When using PowerShell `Set-Content`, always pass `-Encoding UTF8BOM` to preserve the BOM (e.g., `Set-Content $file $content -NoNewline -Encoding UTF8BOM`).
 - **Copyright header**: `// Copyright (c) Microsoft. All rights reserved.` at top of all `.cs` files
 - **XML docs**: Required for all public methods and classes
 - **Async**: Use `Async` suffix for methods returning `Task`/`ValueTask`
 - **Private classes**: Should be `sealed` unless subclassed
 - **Config**: Read from environment variables with `UPPER_SNAKE_CASE` naming
- **Tests**: Add Arrange/Act/Assert comments; use Moq for mocking
+- **Tests**: Add Arrange/Act/Assert comments; use Moq for mocking; test methods returning `Task`/`ValueTask` must use the `Async` suffix.

 ## Key Design Principles

@@ -17,7 +17,7 @@

  <PropertyGroup>
    <IsReleaseCandidate>false</IsReleaseCandidate>
-    <IsGenerallyAvailable>false</IsGenerallyAvailable>
+    <IsReleased>false</IsReleased>
  </PropertyGroup>
  
  <PropertyGroup>
@@ -11,7 +11,7 @@
  </PropertyGroup>
  <ItemGroup>
    <!-- Aspire.* -->
-    <PackageVersion Include="Anthropic" Version="12.8.0" />
+    <PackageVersion Include="Anthropic" Version="12.11.0" />
    <PackageVersion Include="Anthropic.Foundry" Version="0.4.2" />
    <PackageVersion Include="Aspire.Azure.AI.OpenAI" Version="13.0.0-preview.1.25560.3" />
    <PackageVersion Include="Aspire.Hosting.AppHost" Version="$(AspireAppHostSdkVersion)" />
@@ -19,13 +19,13 @@
    <PackageVersion Include="Aspire.Microsoft.Azure.Cosmos" Version="$(AspireAppHostSdkVersion)" />
    <PackageVersion Include="CommunityToolkit.Aspire.OllamaSharp" Version="13.0.0" />
    <!-- Azure.* -->
-    <PackageVersion Include="Azure.AI.Projects" Version="2.0.0-beta.2" />
+    <PackageVersion Include="Azure.AI.Projects" Version="2.0.0" />
    <PackageVersion Include="Azure.AI.Agents.Persistent" Version="1.2.0-beta.10" />
    <PackageVersion Include="Azure.AI.OpenAI" Version="2.9.0-beta.1" />
-    <PackageVersion Include="Azure.Identity" Version="1.19.0" />
+    <PackageVersion Include="Azure.Identity" Version="1.20.0" />
    <PackageVersion Include="Azure.Monitor.OpenTelemetry.Exporter" Version="1.4.0" />
    <!-- Google Gemini  -->
-    <PackageVersion Include="Google.GenAI" Version="0.11.0" />
+    <PackageVersion Include="Google.GenAI" Version="1.6.0" />
    <PackageVersion Include="Mscc.GenerativeAI.Microsoft" Version="2.9.3" />
    <!-- Microsoft.Azure.* -->
    <PackageVersion Include="Microsoft.Azure.Cosmos" Version="3.54.0" />
@@ -35,7 +35,7 @@
    <PackageVersion Include="Microsoft.Bcl.AsyncInterfaces" Version="10.0.4" />
    <PackageVersion Include="Microsoft.Bcl.HashCode" Version="6.0.0" />
    <PackageVersion Include="Microsoft.Bcl.Memory" Version="10.0.4" />
-    <PackageVersion Include="System.ClientModel" Version="1.9.0" />
+    <PackageVersion Include="System.ClientModel" Version="1.10.0" />
    <PackageVersion Include="System.CodeDom" Version="10.0.0" />
    <PackageVersion Include="System.Collections.Immutable" Version="10.0.1" />
    <PackageVersion Include="System.CommandLine" Version="2.0.0-rc.2.25502.107" />
@@ -7,6 +7,7 @@
  <Folder Name="/Samples/">
    <File Path="samples/AGENTS.md" />
    <File Path="samples/README.md" />
+    <Project Path="eng/verify-samples/verify-samples.csproj" />
  </Folder>
  <Folder Name="/Samples/01-get-started/">
    <Project Path="samples/01-get-started/01_hello_agent/01_hello_agent.csproj" />
@@ -33,7 +34,6 @@
    <Project Path="samples/02-agents/AgentProviders/Agent_With_GoogleGemini/Agent_With_GoogleGemini.csproj" />
    <Project Path="samples/02-agents/AgentProviders/Agent_With_Ollama/Agent_With_Ollama.csproj" />
    <Project Path="samples/02-agents/AgentProviders/Agent_With_ONNX/Agent_With_ONNX.csproj" />
-    <Project Path="samples/02-agents/AgentProviders/Agent_With_OpenAIAssistants/Agent_With_OpenAIAssistants.csproj" />
    <Project Path="samples/02-agents/AgentProviders/Agent_With_OpenAIChatCompletion/Agent_With_OpenAIChatCompletion.csproj" />
    <Project Path="samples/02-agents/AgentProviders/Agent_With_OpenAIResponses/Agent_With_OpenAIResponses.csproj" />
  </Folder>
@@ -106,6 +106,9 @@
    <File Path="samples/02-agents/AgentSkills/README.md" />
    <Project Path="samples/02-agents/AgentSkills/Agent_Step01_FileBasedSkills/Agent_Step01_FileBasedSkills.csproj" />
    <Project Path="samples/02-agents/AgentSkills/Agent_Step02_CodeDefinedSkills/Agent_Step02_CodeDefinedSkills.csproj" />
+    <Project Path="samples/02-agents/AgentSkills/Agent_Step03_ClassBasedSkills/Agent_Step03_ClassBasedSkills.csproj" />
+    <Project Path="samples/02-agents/AgentSkills/Agent_Step04_MixedSkills/Agent_Step04_MixedSkills.csproj" />
+    <Project Path="samples/02-agents/AgentSkills/Agent_Step05_SkillsWithDI/Agent_Step05_SkillsWithDI.csproj" />
  </Folder>
  <Folder Name="/Samples/02-agents/AGUI/Step05_StateManagement/">
    <Project Path="samples/02-agents/AGUI/Step05_StateManagement/Client/Client.csproj" />
@@ -171,6 +174,7 @@
    <Project Path="samples/02-agents/AgentWithRAG/AgentWithRAG_Step02_CustomVectorStoreRAG/AgentWithRAG_Step02_CustomVectorStoreRAG.csproj" />
    <Project Path="samples/02-agents/AgentWithRAG/AgentWithRAG_Step03_CustomRAGDataSource/AgentWithRAG_Step03_CustomRAGDataSource.csproj" />
    <Project Path="samples/02-agents/AgentWithRAG/AgentWithRAG_Step04_FoundryServiceRAG/AgentWithRAG_Step04_FoundryServiceRAG.csproj" />
+    <Project Path="samples/02-agents/AgentWithRAG/AgentWithRAG_Step05_Neo4jGraphRAG/AgentWithRAG_Step05_Neo4jGraphRAG.csproj" />
  </Folder>
  <Folder Name="/Samples/02-agents/ModelContextProtocol/">
    <File Path="samples/02-agents/ModelContextProtocol/README.md" />
@@ -212,12 +216,12 @@
    <Project Path="samples/03-workflows/Declarative/ToolApproval/ToolApproval.csproj" />
  </Folder>
  <Folder Name="/Samples/03-workflows/Declarative/Examples/">
-    <File Path="../workflow-samples/CustomerSupport.yaml" />
-    <File Path="../workflow-samples/DeepResearch.yaml" />
-    <File Path="../workflow-samples/Marketing.yaml" />
-    <File Path="../workflow-samples/MathChat.yaml" />
-    <File Path="../workflow-samples/README.md" />
-    <File Path="../workflow-samples/wttr.json" />
+    <File Path="../declarative-agents/workflow-samples/CustomerSupport.yaml" />
+    <File Path="../declarative-agents/workflow-samples/DeepResearch.yaml" />
+    <File Path="../declarative-agents/workflow-samples/Marketing.yaml" />
+    <File Path="../declarative-agents/workflow-samples/MathChat.yaml" />
+    <File Path="../declarative-agents/workflow-samples/README.md" />
+    <File Path="../declarative-agents/workflow-samples/wttr.json" />
  </Folder>
  <Folder Name="/Samples/03-workflows/SharedStates/">
    <Project Path="samples/03-workflows/SharedStates/SharedStates.csproj" />
@@ -476,13 +480,13 @@
    <Project Path="src/Microsoft.Agents.AI.AGUI/Microsoft.Agents.AI.AGUI.csproj" />
    <Project Path="src/Microsoft.Agents.AI.Anthropic/Microsoft.Agents.AI.Anthropic.csproj" />
    <Project Path="src/Microsoft.Agents.AI.AzureAI.Persistent/Microsoft.Agents.AI.AzureAI.Persistent.csproj" />
-    <Project Path="src/Microsoft.Agents.AI.AzureAI/Microsoft.Agents.AI.AzureAI.csproj" />
+    <Project Path="src/Microsoft.Agents.AI.Foundry/Microsoft.Agents.AI.Foundry.csproj" />
    <Project Path="src/Microsoft.Agents.AI.CopilotStudio/Microsoft.Agents.AI.CopilotStudio.csproj" />
    <Project Path="src/Microsoft.Agents.AI.CosmosNoSql/Microsoft.Agents.AI.CosmosNoSql.csproj" />
    <Project Path="src/Microsoft.Agents.AI.Declarative/Microsoft.Agents.AI.Declarative.csproj" />
    <Project Path="src/Microsoft.Agents.AI.DevUI/Microsoft.Agents.AI.DevUI.csproj" />
    <Project Path="src/Microsoft.Agents.AI.DurableTask/Microsoft.Agents.AI.DurableTask.csproj" />
-    <Project Path="src/Microsoft.Agents.AI.FoundryMemory/Microsoft.Agents.AI.FoundryMemory.csproj" />
+
    <Project Path="src/Microsoft.Agents.AI.GitHub.Copilot/Microsoft.Agents.AI.GitHub.Copilot.csproj" />
    <Project Path="src/Microsoft.Agents.AI.Hosting.A2A.AspNetCore/Microsoft.Agents.AI.Hosting.A2A.AspNetCore.csproj" />
    <Project Path="src/Microsoft.Agents.AI.Hosting.A2A/Microsoft.Agents.AI.Hosting.A2A.csproj" />
@@ -493,7 +497,7 @@
    <Project Path="src/Microsoft.Agents.AI.Mem0/Microsoft.Agents.AI.Mem0.csproj" />
    <Project Path="src/Microsoft.Agents.AI.OpenAI/Microsoft.Agents.AI.OpenAI.csproj" />
    <Project Path="src/Microsoft.Agents.AI.Purview/Microsoft.Agents.AI.Purview.csproj" />
-    <Project Path="src/Microsoft.Agents.AI.Workflows.Declarative.AzureAI/Microsoft.Agents.AI.Workflows.Declarative.AzureAI.csproj" />
+    <Project Path="src/Microsoft.Agents.AI.Workflows.Declarative.Foundry/Microsoft.Agents.AI.Workflows.Declarative.Foundry.csproj" />
    <Project Path="src/Microsoft.Agents.AI.Workflows.Declarative.Mcp/Microsoft.Agents.AI.Workflows.Declarative.Mcp.csproj" />
    <Project Path="src/Microsoft.Agents.AI.Workflows.Declarative/Microsoft.Agents.AI.Workflows.Declarative.csproj" />
    <Project Path="src/Microsoft.Agents.AI.Workflows.Generators/Microsoft.Agents.AI.Workflows.Generators.csproj" />
@@ -504,11 +508,11 @@
  <Folder Name="/Tests/IntegrationTests/">
    <Project Path="tests/AgentConformance.IntegrationTests/AgentConformance.IntegrationTests.csproj" />
    <Project Path="tests/AnthropicChatCompletion.IntegrationTests/AnthropicChatCompletion.IntegrationTests.csproj" />
-    <Project Path="tests/AzureAI.IntegrationTests/AzureAI.IntegrationTests.csproj" />
+    <Project Path="tests/Foundry.IntegrationTests/Foundry.IntegrationTests.csproj" />
    <Project Path="tests/AzureAIAgentsPersistent.IntegrationTests/AzureAIAgentsPersistent.IntegrationTests.csproj" />
    <Project Path="tests/CopilotStudio.IntegrationTests/CopilotStudio.IntegrationTests.csproj" />
    <Project Path="tests/Microsoft.Agents.AI.DurableTask.IntegrationTests/Microsoft.Agents.AI.DurableTask.IntegrationTests.csproj" />
-    <Project Path="tests/Microsoft.Agents.AI.FoundryMemory.IntegrationTests/Microsoft.Agents.AI.FoundryMemory.IntegrationTests.csproj" />
+
    <Project Path="tests/Microsoft.Agents.AI.GitHub.Copilot.IntegrationTests/Microsoft.Agents.AI.GitHub.Copilot.IntegrationTests.csproj" />
    <Project Path="tests/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.IntegrationTests/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.IntegrationTests.csproj" />
    <Project Path="tests/Microsoft.Agents.AI.Hosting.AzureFunctions.IntegrationTests/Microsoft.Agents.AI.Hosting.AzureFunctions.IntegrationTests.csproj" />
@@ -524,12 +528,12 @@
    <Project Path="tests/Microsoft.Agents.AI.AGUI.UnitTests/Microsoft.Agents.AI.AGUI.UnitTests.csproj" />
    <Project Path="tests/Microsoft.Agents.AI.Anthropic.UnitTests/Microsoft.Agents.AI.Anthropic.UnitTests.csproj" />
    <Project Path="tests/Microsoft.Agents.AI.AzureAI.Persistent.UnitTests/Microsoft.Agents.AI.AzureAI.Persistent.UnitTests.csproj" />
-    <Project Path="tests/Microsoft.Agents.AI.AzureAI.UnitTests/Microsoft.Agents.AI.AzureAI.UnitTests.csproj" />
+    <Project Path="tests/Microsoft.Agents.AI.Foundry.UnitTests/Microsoft.Agents.AI.Foundry.UnitTests.csproj" />
    <Project Path="tests/Microsoft.Agents.AI.CosmosNoSql.UnitTests/Microsoft.Agents.AI.CosmosNoSql.UnitTests.csproj" />
    <Project Path="tests/Microsoft.Agents.AI.Declarative.UnitTests/Microsoft.Agents.AI.Declarative.UnitTests.csproj" />
    <Project Path="tests/Microsoft.Agents.AI.DevUI.UnitTests/Microsoft.Agents.AI.DevUI.UnitTests.csproj" />
    <Project Path="tests/Microsoft.Agents.AI.DurableTask.UnitTests/Microsoft.Agents.AI.DurableTask.UnitTests.csproj" />
-    <Project Path="tests/Microsoft.Agents.AI.FoundryMemory.UnitTests/Microsoft.Agents.AI.FoundryMemory.UnitTests.csproj" />
+
    <Project Path="tests/Microsoft.Agents.AI.GitHub.Copilot.UnitTests/Microsoft.Agents.AI.GitHub.Copilot.UnitTests.csproj" />
    <Project Path="tests/Microsoft.Agents.AI.Hosting.A2A.UnitTests/Microsoft.Agents.AI.Hosting.A2A.UnitTests.csproj" />
    <Project Path="tests/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.UnitTests/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.UnitTests.csproj" />
@@ -8,13 +8,13 @@
      "src\\Microsoft.Agents.AI.Anthropic\\Microsoft.Agents.AI.Anthropic.csproj",
      "src\\Microsoft.Agents.AI.GitHub.Copilot\\Microsoft.Agents.AI.GitHub.Copilot.csproj",
      "src\\Microsoft.Agents.AI.AzureAI.Persistent\\Microsoft.Agents.AI.AzureAI.Persistent.csproj",
-      "src\\Microsoft.Agents.AI.AzureAI\\Microsoft.Agents.AI.AzureAI.csproj",
+      "src\\Microsoft.Agents.AI.Foundry\\Microsoft.Agents.AI.Foundry.csproj",
      "src\\Microsoft.Agents.AI.CopilotStudio\\Microsoft.Agents.AI.CopilotStudio.csproj",
      "src\\Microsoft.Agents.AI.CosmosNoSql\\Microsoft.Agents.AI.CosmosNoSql.csproj",
      "src\\Microsoft.Agents.AI.Declarative\\Microsoft.Agents.AI.Declarative.csproj",
      "src\\Microsoft.Agents.AI.DevUI\\Microsoft.Agents.AI.DevUI.csproj",
      "src\\Microsoft.Agents.AI.DurableTask\\Microsoft.Agents.AI.DurableTask.csproj",
-      "src\\Microsoft.Agents.AI.FoundryMemory\\Microsoft.Agents.AI.FoundryMemory.csproj",
+
      "src\\Microsoft.Agents.AI.Hosting.A2A.AspNetCore\\Microsoft.Agents.AI.Hosting.A2A.AspNetCore.csproj",
      "src\\Microsoft.Agents.AI.Hosting.A2A\\Microsoft.Agents.AI.Hosting.A2A.csproj",
      "src\\Microsoft.Agents.AI.Hosting.AGUI.AspNetCore\\Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.csproj",
@@ -24,7 +24,7 @@
      "src\\Microsoft.Agents.AI.Mem0\\Microsoft.Agents.AI.Mem0.csproj",
      "src\\Microsoft.Agents.AI.OpenAI\\Microsoft.Agents.AI.OpenAI.csproj",
      "src\\Microsoft.Agents.AI.Purview\\Microsoft.Agents.AI.Purview.csproj",
-      "src\\Microsoft.Agents.AI.Workflows.Declarative.AzureAI\\Microsoft.Agents.AI.Workflows.Declarative.AzureAI.csproj",
+      "src\\Microsoft.Agents.AI.Workflows.Declarative.Foundry\\Microsoft.Agents.AI.Workflows.Declarative.Foundry.csproj",
      "src\\Microsoft.Agents.AI.Workflows.Declarative\\Microsoft.Agents.AI.Workflows.Declarative.csproj",
      "src\\Microsoft.Agents.AI.Workflows.Generators\\Microsoft.Agents.AI.Workflows.Generators.csproj",
      "src\\Microsoft.Agents.AI.Workflows\\Microsoft.Agents.AI.Workflows.csproj",
@@ -0,0 +1,95 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+namespace VerifySamples;
+
+/// <summary>
+/// Thread-safe console output with sample-name prefixes and colored status.
+/// </summary>
+internal sealed class ConsoleReporter
+{
+    private readonly object _lock = new();
+
+    /// <summary>
+    /// Writes a complete prefixed line atomically to the console.
+    /// </summary>
+    public void WriteLineWithPrefix(string sampleName, string message, ConsoleColor? color = null)
+    {
+        lock (this._lock)
+        {
+            Console.ForegroundColor = ConsoleColor.Cyan;
+            Console.Write($"[{sampleName}] ");
+            if (color.HasValue)
+            {
+                Console.ForegroundColor = color.Value;
+            }
+            else
+            {
+                Console.ResetColor();
+            }
+
+            Console.WriteLine(message);
+            Console.ResetColor();
+        }
+    }
+
+    /// <summary>
+    /// Prints the final summary table and elapsed time to the console.
+    /// </summary>
+    public void PrintSummary(
+        IReadOnlyList<VerificationResult> orderedResults,
+        IReadOnlyList<(string Name, string Reason)> skipped,
+        TimeSpan elapsed)
+    {
+        var passCount = orderedResults.Count(r => r.Passed);
+        var failCount = orderedResults.Count(r => !r.Passed);
+
+        Console.WriteLine();
+        Console.WriteLine(new string('─', 60));
+        Console.ForegroundColor = ConsoleColor.White;
+        Console.WriteLine("SUMMARY");
+        Console.ResetColor();
+
+        foreach (var result in orderedResults)
+        {
+            Console.ForegroundColor = result.Passed ? ConsoleColor.Green : ConsoleColor.Red;
+            Console.Write(result.Passed ? "  ✓ " : "  ✗ ");
+            Console.ResetColor();
+            Console.WriteLine($"{result.SampleName}: {result.Summary}");
+        }
+
+        foreach (var (name, reason) in skipped)
+        {
+            Console.ForegroundColor = ConsoleColor.Yellow;
+            Console.Write("  ○ ");
+            Console.ResetColor();
+            Console.WriteLine($"{name}: Skipped — {reason}");
+        }
+
+        Console.WriteLine();
+        Console.Write("Results: ");
+        Console.ForegroundColor = ConsoleColor.Green;
+        Console.Write($"{passCount} passed");
+        Console.ResetColor();
+
+        if (failCount > 0)
+        {
+            Console.Write(", ");
+            Console.ForegroundColor = ConsoleColor.Red;
+            Console.Write($"{failCount} failed");
+            Console.ResetColor();
+        }
+
+        if (skipped.Count > 0)
+        {
+            Console.Write(", ");
+            Console.ForegroundColor = ConsoleColor.Yellow;
+            Console.Write($"{skipped.Count} skipped");
+            Console.ResetColor();
+        }
+
+        Console.WriteLine();
+        Console.ForegroundColor = ConsoleColor.DarkGray;
+        Console.WriteLine($"Elapsed: {elapsed.Hours:D2}:{elapsed.Minutes:D2}:{elapsed.Seconds:D2}");
+        Console.ResetColor();
+    }
+}
@@ -0,0 +1,56 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using System.Text;
+
+namespace VerifySamples;
+
+/// <summary>
+/// Writes a CSV summary of sample verification results.
+/// </summary>
+internal static class CsvResultWriter
+{
+    /// <summary>
+    /// Writes the results to a CSV file at the specified path.
+    /// </summary>
+    public static async Task WriteAsync(
+        string path,
+        IReadOnlyList<VerificationResult> orderedResults,
+        IReadOnlyList<(string Name, string Reason)> skipped,
+        IReadOnlyList<SampleDefinition> samples)
+    {
+        var pathLookup = samples.ToDictionary(s => s.Name, s => s.ProjectPath);
+
+        var sb = new StringBuilder();
+        sb.AppendLine("Sample,ProjectPath,Status,FailedChecks,Failures");
+
+        foreach (var result in orderedResults)
+        {
+            var status = result.Passed ? "PASSED" : "FAILED";
+            var failedChecks = result.Failures.Count;
+            var failures = string.Join("; ", result.Failures);
+            pathLookup.TryGetValue(result.SampleName, out var projectPath);
+            sb.AppendLine($"{CsvEscape(result.SampleName)},{CsvEscape(projectPath ?? "")},{status},{failedChecks},{CsvEscape(failures)}");
+        }
+
+        foreach (var (name, reason) in skipped)
+        {
+            pathLookup.TryGetValue(name, out var projectPath);
+            sb.AppendLine($"{CsvEscape(name)},{CsvEscape(projectPath ?? "")},SKIPPED,0,{CsvEscape(reason)}");
+        }
+
+        await File.WriteAllTextAsync(path, sb.ToString());
+    }
+
+    /// <summary>
+    /// Escapes a value for CSV: wraps in quotes if it contains commas, quotes, or newlines.
+    /// </summary>
+    private static string CsvEscape(string value)
+    {
+        if (value.Contains('"') || value.Contains(',') || value.Contains('\n') || value.Contains('\r'))
+        {
+            return $"\"{value.Replace("\"", "\"\"")}\"";
+        }
+
+        return value;
+    }
+}
@@ -0,0 +1,105 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+namespace VerifySamples;
+
+/// <summary>
+/// Defines the expected behavior for each sample in 01-get-started.
+/// </summary>
+internal static class GetStartedSamples
+{
+    public static IReadOnlyList<SampleDefinition> All { get; } =
+    [
+        new SampleDefinition
+        {
+            Name = "05_first_workflow",
+            ProjectPath = "samples/01-get-started/05_first_workflow",
+            RequiredEnvironmentVariables = [],
+            IsDeterministic = true,
+            MustContain =
+            [
+                "UppercaseExecutor: HELLO, WORLD!",
+                "ReverseTextExecutor: !DLROW ,OLLEH",
+            ],
+        },
+
+        new SampleDefinition
+        {
+            Name = "01_hello_agent",
+            ProjectPath = "samples/01-get-started/01_hello_agent",
+            RequiredEnvironmentVariables = ["AZURE_OPENAI_ENDPOINT"],
+            OptionalEnvironmentVariables = ["AZURE_OPENAI_DEPLOYMENT_NAME"],
+            ExpectedOutputDescription =
+            [
+                "The output should contain a joke about a pirate.",
+                "There should be two separate joke responses — one from a non-streaming call and one from a streaming call.",
+                "The output should not contain error messages or stack traces.",
+            ],
+        },
+
+        new SampleDefinition
+        {
+            Name = "02_add_tools",
+            ProjectPath = "samples/01-get-started/02_add_tools",
+            RequiredEnvironmentVariables = ["AZURE_OPENAI_ENDPOINT"],
+            OptionalEnvironmentVariables = ["AZURE_OPENAI_DEPLOYMENT_NAME"],
+            MustContain = [],
+            ExpectedOutputDescription =
+            [
+                "The output should contain information about the weather in Amsterdam.",
+                "The response should mention that it is cloudy with a high of 15°C (or equivalent), since this comes from a tool that returns a canned response.",
+                "There should be two responses — one from a non-streaming call and one from a streaming call.",
+                "The output should not contain error messages or stack traces.",
+            ],
+        },
+
+        new SampleDefinition
+        {
+            Name = "03_multi_turn",
+            ProjectPath = "samples/01-get-started/03_multi_turn",
+            RequiredEnvironmentVariables = ["AZURE_OPENAI_ENDPOINT"],
+            OptionalEnvironmentVariables = ["AZURE_OPENAI_DEPLOYMENT_NAME"],
+            ExpectedOutputDescription =
+            [
+                "The output should contain a joke about a pirate.",
+                "After the initial joke, there should be a modified version that includes emojis and is told in the voice of a pirate's parrot.",
+                "The pattern repeats: first a non-streaming pirate joke + parrot version, then a streaming pirate joke + parrot version.",
+                "The output should not contain error messages or stack traces.",
+            ],
+        },
+
+        new SampleDefinition
+        {
+            Name = "04_memory",
+            ProjectPath = "samples/01-get-started/04_memory",
+            RequiredEnvironmentVariables = ["AZURE_OPENAI_ENDPOINT"],
+            OptionalEnvironmentVariables = ["AZURE_OPENAI_DEPLOYMENT_NAME"],
+            MustContain =
+            [
+                ">> Use session with blank memory",
+                ">> Use deserialized session with previously created memories",
+                ">> Read memories using memory component",
+                "MEMORY - User Name:",
+                "MEMORY - User Age:",
+                ">> Use new session with previously created memories",
+            ],
+            ExpectedOutputDescription =
+            [
+                "In the 'Use session with blank memory' section, the agent should respond to the user's messages. It may ask for the user's name or age if not yet known.",
+                "In the 'Use deserialized session with previously created memories' section, the agent should correctly recall that the user's name is Ruaidhrí and age is 20.",
+                "The 'MEMORY - User Name:' line should show 'Ruaidhrí' (or a close transliteration).",
+                "The 'MEMORY - User Age:' line should show '20'.",
+                "In the 'Use new session with previously created memories' section, the agent should know the user's name and age from the transferred memory.",
+                "The output should not contain error messages or stack traces.",
+            ],
+        },
+
+        new SampleDefinition
+        {
+            Name = "06_host_your_agent",
+            ProjectPath = "samples/01-get-started/06_host_your_agent",
+            RequiredEnvironmentVariables = ["AZURE_OPENAI_ENDPOINT"],
+            OptionalEnvironmentVariables = ["AZURE_OPENAI_DEPLOYMENT_NAME"],
+            SkipReason = "Requires Azure Functions Core Tools runtime and starts a web server.",
+        },
+    ];
+}
@@ -0,0 +1,153 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using System.Text;
+
+namespace VerifySamples;
+
+/// <summary>
+/// Incrementally writes a sequential (non-interleaved) log file, appending after each sample completes.
+/// Thread-safe: multiple parallel tasks may call write methods concurrently.
+/// </summary>
+internal sealed class LogFileWriter : IDisposable
+{
+    private readonly string _path;
+    private readonly SemaphoreSlim _writeLock = new(1, 1);
+
+    public LogFileWriter(string path)
+    {
+        this._path = path;
+    }
+
+    /// <inheritdoc />
+    public void Dispose()
+    {
+        this._writeLock.Dispose();
+    }
+
+    /// <summary>
+    /// Writes the log file header. Call once at the start of the run.
+    /// </summary>
+    public async Task WriteHeaderAsync()
+    {
+        var sb = new StringBuilder();
+        sb.AppendLine($"Sample Verification Log — {DateTime.UtcNow:yyyy-MM-dd HH:mm:ss} UTC");
+        sb.AppendLine(new string('═', 72));
+        sb.AppendLine();
+
+        await File.WriteAllTextAsync(this._path, sb.ToString());
+    }
+
+    /// <summary>
+    /// Appends a skipped-sample entry to the log file.
+    /// </summary>
+    public async Task WriteSkippedAsync(string name, string reason)
+    {
+        var sb = new StringBuilder();
+        sb.AppendLine($"── {name} ──");
+        sb.AppendLine($"Status: SKIPPED — {reason}");
+        sb.AppendLine();
+
+        await this.AppendAsync(sb.ToString());
+    }
+
+    /// <summary>
+    /// Appends a completed sample's full output section to the log file.
+    /// </summary>
+    public async Task WriteSampleResultAsync(VerificationResult result)
+    {
+        var sb = new StringBuilder();
+        sb.AppendLine(new string('─', 72));
+        sb.AppendLine($"── {result.SampleName} ──");
+        sb.AppendLine($"Status: {(result.Passed ? "PASSED" : "FAILED")}");
+        sb.AppendLine();
+
+        foreach (var line in result.LogLines)
+        {
+            sb.AppendLine(line);
+        }
+
+        sb.AppendLine();
+
+        if (!string.IsNullOrWhiteSpace(result.Stdout))
+        {
+            sb.AppendLine("--- stdout ---");
+            sb.AppendLine(result.Stdout.TrimEnd());
+            sb.AppendLine("--- end stdout ---");
+            sb.AppendLine();
+        }
+
+        if (!string.IsNullOrWhiteSpace(result.Stderr))
+        {
+            sb.AppendLine("--- stderr ---");
+            sb.AppendLine(result.Stderr.TrimEnd());
+            sb.AppendLine("--- end stderr ---");
+            sb.AppendLine();
+        }
+
+        if (result.Failures.Count > 0)
+        {
+            sb.AppendLine("Failures:");
+            foreach (var failure in result.Failures)
+            {
+                sb.AppendLine($"  ✗ {failure}");
+            }
+
+            sb.AppendLine();
+        }
+
+        if (result.AIReasoning is not null)
+        {
+            sb.AppendLine("AI Reasoning:");
+            sb.AppendLine(result.AIReasoning);
+            sb.AppendLine();
+        }
+
+        await this.AppendAsync(sb.ToString());
+    }
+
+    /// <summary>
+    /// Appends the final summary section and elapsed time to the log file.
+    /// </summary>
+    public async Task WriteSummaryAsync(
+        IReadOnlyList<VerificationResult> orderedResults,
+        IReadOnlyList<(string Name, string Reason)> skipped,
+        TimeSpan elapsed)
+    {
+        var passCount = orderedResults.Count(r => r.Passed);
+        var failCount = orderedResults.Count(r => !r.Passed);
+
+        var sb = new StringBuilder();
+        sb.AppendLine(new string('═', 72));
+        sb.AppendLine("SUMMARY");
+        sb.AppendLine();
+
+        foreach (var result in orderedResults)
+        {
+            sb.AppendLine($"  {(result.Passed ? "✓" : "✗")} {result.SampleName}: {result.Summary}");
+        }
+
+        foreach (var (name, reason) in skipped)
+        {
+            sb.AppendLine($"  ○ {name}: Skipped — {reason}");
+        }
+
+        sb.AppendLine();
+        sb.AppendLine($"Results: {passCount} passed{(failCount > 0 ? $", {failCount} failed" : "")}{(skipped.Count > 0 ? $", {skipped.Count} skipped" : "")}");
+        sb.AppendLine($"Elapsed: {elapsed.Hours:D2}:{elapsed.Minutes:D2}:{elapsed.Seconds:D2}");
+
+        await this.AppendAsync(sb.ToString());
+    }
+
+    private async Task AppendAsync(string text)
+    {
+        await this._writeLock.WaitAsync();
+        try
+        {
+            await File.AppendAllTextAsync(this._path, text);
+        }
+        finally
+        {
+            this._writeLock.Release();
+        }
+    }
+}
@@ -0,0 +1,98 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using System.Text;
+
+namespace VerifySamples;
+
+/// <summary>
+/// Writes a Markdown summary of sample verification results.
+/// </summary>
+internal static class MarkdownResultWriter
+{
+    /// <summary>
+    /// Writes the results to a Markdown file at the specified path.
+    /// </summary>
+    public static async Task WriteAsync(
+        string path,
+        IReadOnlyList<VerificationResult> orderedResults,
+        IReadOnlyList<(string Name, string Reason)> skipped,
+        TimeSpan elapsed)
+    {
+        var passCount = orderedResults.Count(r => r.Passed);
+        var failCount = orderedResults.Count(r => !r.Passed);
+
+        var sb = new StringBuilder();
+        sb.AppendLine("# Sample Verification Results");
+        sb.AppendLine();
+        sb.AppendLine($"**{passCount} passed, {failCount} failed, {skipped.Count} skipped** | Elapsed: {elapsed.Hours:D2}:{elapsed.Minutes:D2}:{elapsed.Seconds:D2}");
+        sb.AppendLine();
+
+        // Results table
+        sb.AppendLine("| Sample | Status | Failed Checks | Failures |");
+        sb.AppendLine("|--------|--------|---------------|----------|");
+
+        foreach (var result in orderedResults)
+        {
+            var status = result.Passed ? "✅ PASSED" : "❌ FAILED";
+            var failedChecks = result.Failures.Count;
+            var failures = MdEscape(string.Join("; ", result.Failures));
+            sb.AppendLine($"| {MdEscape(result.SampleName)} | {status} | {failedChecks} | {failures} |");
+        }
+
+        foreach (var (name, reason) in skipped)
+        {
+            sb.AppendLine($"| {MdEscape(name)} | ⏭️ SKIPPED | 0 | {MdEscape(reason)} |");
+        }
+
+        // Collapsible AI reasoning details for failures
+        var failures2 = orderedResults.Where(r => !r.Passed && !string.IsNullOrEmpty(r.AIReasoning)).ToList();
+        if (failures2.Count > 0)
+        {
+            sb.AppendLine();
+            sb.AppendLine("## Failure Details");
+            sb.AppendLine();
+
+            foreach (var result in failures2)
+            {
+                sb.AppendLine($"<details><summary><strong>{HtmlEscape(result.SampleName)}</strong></summary>");
+                sb.AppendLine();
+                if (result.Failures.Count > 0)
+                {
+                    foreach (var failure in result.Failures)
+                    {
+                        sb.AppendLine($"- {MdEscape(failure)}");
+                    }
+
+                    sb.AppendLine();
+                }
+
+                sb.AppendLine("**AI Reasoning:**");
+                sb.AppendLine();
+                sb.AppendLine("```");
+                sb.AppendLine(result.AIReasoning);
+                sb.AppendLine("```");
+                sb.AppendLine();
+                sb.AppendLine("</details>");
+                sb.AppendLine();
+            }
+        }
+
+        await File.WriteAllTextAsync(path, sb.ToString());
+    }
+
+    /// <summary>
+    /// Escapes pipe characters and newlines for use inside Markdown table cells.
+    /// </summary>
+    private static string MdEscape(string value)
+    {
+        return value.Replace("|", "\\|").Replace("\n", " ").Replace("\r", "");
+    }
+
+    /// <summary>
+    /// Escapes HTML special characters for use inside HTML tags.
+    /// </summary>
+    private static string HtmlEscape(string value)
+    {
+        return value.Replace("&", "&amp;").Replace("<", "&lt;").Replace(">", "&gt;").Replace("\"", "&quot;");
+    }
+}
@@ -0,0 +1,109 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This tool runs the 01-get-started, 02-agents, and 03-workflows samples and verifies their output.
+// Deterministic samples are verified with exact string matching.
+// Non-deterministic (LLM) samples are verified using an agent-framework agent.
+//
+// Usage:
+//   dotnet run                                          # Run all samples
+//   dotnet run -- 01_hello_agent 05_first_workflow      # Run specific samples by name
+//   dotnet run -- --category 01-get-started             # Run the 01-get-started category
+//   dotnet run -- --category 02-agents                  # Run the 02-agents category
+//   dotnet run -- --category 03-workflows               # Run the 03-workflows category
+//   dotnet run -- --parallel 16                         # Run up to 16 samples concurrently
+//   dotnet run -- --log results.log                     # Write sequential log to file
+//   dotnet run -- --csv results.csv                     # Write CSV summary to file
+//   dotnet run -- --md results.md                       # Write Markdown summary to file
+//   dotnet run -- --build                                # Build samples during run (default: --no-build)
+// Note: By default, this tool expects sample build outputs to already exist.
+// Pre-build the solution before running, or pass --build to avoid missing build output failures.
+//
+// Required environment variables (for AI-powered samples):
+//   AZURE_OPENAI_ENDPOINT
+//   AZURE_OPENAI_DEPLOYMENT_NAME (optional, defaults to gpt-5-mini)
+
+using System.Diagnostics;
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using VerifySamples;
+
+var options = VerifyOptions.Parse(args);
+if (options is null)
+{
+    return 1;
+}
+
+var stopwatch = Stopwatch.StartNew();
+
+// Resolve the dotnet/ root directory (verify-samples is at dotnet/eng/verify-samples/)
+var dotnetRoot = Path.GetFullPath(Path.Combine(AppContext.BaseDirectory, "..", "..", "..", "..", ".."));
+if (!File.Exists(Path.Combine(dotnetRoot, "agent-framework-dotnet.slnx")))
+{
+    dotnetRoot = Path.GetFullPath(Path.Combine(Directory.GetCurrentDirectory(), "..", ".."));
+}
+
+// Set up the AI verifier
+var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5-mini";
+
+OpenAI.Chat.ChatClient? chatClient = null;
+if (!string.IsNullOrEmpty(endpoint))
+{
+    chatClient = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential())
+        .GetChatClient(deploymentName);
+}
+
+// Set up optional log file writer
+LogFileWriter? logWriter = null;
+if (options.LogFilePath is not null)
+{
+    logWriter = new LogFileWriter(options.LogFilePath);
+    await logWriter.WriteHeaderAsync();
+}
+
+try
+{
+    // Run all samples
+    var reporter = new ConsoleReporter();
+    var verifier = new SampleVerifier(chatClient);
+    var orchestrator = new VerificationOrchestrator(verifier, reporter, dotnetRoot, TimeSpan.FromMinutes(3), logWriter, buildSamples: options.BuildSamples);
+
+    var run = await orchestrator.RunAllAsync(options.Samples, options.MaxParallelism);
+
+    stopwatch.Stop();
+
+    // Print summary
+    var orderedResults = run.SampleOrder
+        .Where(run.Results.ContainsKey)
+        .Select(name => run.Results[name])
+        .ToList();
+
+    reporter.PrintSummary(orderedResults, run.Skipped, stopwatch.Elapsed);
+
+    // Write log file summary
+    if (logWriter is not null)
+    {
+        await logWriter.WriteSummaryAsync(orderedResults, run.Skipped, stopwatch.Elapsed);
+        Console.WriteLine($"Log written to: {options.LogFilePath}");
+    }
+
+    // Write CSV summary
+    if (options.CsvFilePath is not null)
+    {
+        await CsvResultWriter.WriteAsync(options.CsvFilePath, orderedResults, run.Skipped, options.Samples);
+        Console.WriteLine($"CSV written to: {options.CsvFilePath}");
+    }
+
+    // Write Markdown summary
+    if (options.MarkdownFilePath is not null)
+    {
+        await MarkdownResultWriter.WriteAsync(options.MarkdownFilePath, orderedResults, run.Skipped, stopwatch.Elapsed);
+        Console.WriteLine($"Markdown written to: {options.MarkdownFilePath}");
+    }
+
+    return orderedResults.Any(r => !r.Passed) ? 1 : 0;
+}
+finally
+{
+    logWriter?.Dispose();
+}
@@ -0,0 +1,79 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+namespace VerifySamples;
+
+/// <summary>
+/// Describes a sample to verify, including its expected output.
+/// </summary>
+internal sealed class SampleDefinition
+{
+    /// <summary>
+    /// Display name for the sample (e.g., "01_hello_agent").
+    /// </summary>
+    public required string Name { get; init; }
+
+    /// <summary>
+    /// Relative path from the dotnet/ directory to the sample project directory.
+    /// </summary>
+    public required string ProjectPath { get; init; }
+
+    /// <summary>
+    /// Environment variables that the sample requires for a meaningful run.
+    /// The runner checks these before running and will skip the sample if any are unset,
+    /// recording a skip reason that indicates which required variables are missing.
+    /// </summary>
+    public string[] RequiredEnvironmentVariables { get; init; } = [];
+
+    /// <summary>
+    /// Environment variables that the sample can use but typically has fallbacks or defaults for.
+    /// If these are not set, the sample might prompt or behave interactively, which could cause
+    /// automated verification to hang. The runner checks these and skips the sample if they are unset
+    /// to avoid non-deterministic or blocking behavior in automated runs.
+    /// </summary>
+    public string[] OptionalEnvironmentVariables { get; init; } = [];
+
+    /// <summary>
+    /// If set, the sample is skipped with this reason.
+    /// Use only for structural reasons (e.g., web server, multi-process, needs external service).
+    /// Do NOT use for missing environment variables — those are checked dynamically.
+    /// </summary>
+    public string? SkipReason { get; init; }
+
+    /// <summary>
+    /// Substrings that must appear in stdout for the sample to pass.
+    /// Used for deterministic verification.
+    /// </summary>
+    public string[] MustContain { get; init; } = [];
+
+    /// <summary>
+    /// Substrings that must not appear in stdout for the sample to pass.
+    /// </summary>
+    public string[] MustNotContain { get; init; } = [];
+
+    /// <summary>
+    /// If true, <see cref="MustContain"/> entries cover the entire expected output —
+    /// no AI verification is needed.
+    /// </summary>
+    public bool IsDeterministic { get; init; }
+
+    /// <summary>
+    /// Natural-language description of what the sample output should look like.
+    /// Used by the AI verifier for non-deterministic samples.
+    /// Each entry describes one aspect of the expected output that should be verified.
+    /// </summary>
+    public string[] ExpectedOutputDescription { get; init; } = [];
+
+    /// <summary>
+    /// Sequence of stdin inputs to feed to the sample process.
+    /// Each entry is written as a line (followed by newline) to the process stdin.
+    /// A <c>null</c> entry inserts a delay without writing anything.
+    /// Inputs are sent with a short delay between each to allow the process to prompt.
+    /// </summary>
+    public string?[] Inputs { get; init; } = [];
+
+    /// <summary>
+    /// Delay in milliseconds between each input line. Default is 2000ms.
+    /// Increase for samples that need more time between prompts (e.g., LLM calls between inputs).
+    /// </summary>
+    public int InputDelayMs { get; init; } = 2000;
+}
@@ -0,0 +1,141 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using System.Diagnostics;
+
+namespace VerifySamples;
+
+/// <summary>
+/// Result of running a sample process.
+/// </summary>
+internal sealed record SampleRunResult(
+    string Stdout,
+    string Stderr,
+    int ExitCode,
+    TimeSpan Elapsed);
+
+/// <summary>
+/// Runs a sample project via <c>dotnet run</c> and captures its output.
+/// </summary>
+internal static class SampleRunner
+{
+    /// <summary>
+    /// Runs <c>dotnet run --framework net10.0</c> in the given project directory.
+    /// When <paramref name="build"/> is false (the default), <c>--no-build</c> is passed
+    /// to skip building, assuming the project was pre-built.
+    /// </summary>
+    public static Task<SampleRunResult> RunAsync(
+        string projectPath,
+        TimeSpan timeout,
+        bool build = false,
+        CancellationToken cancellationToken = default)
+        => RunAsync(projectPath, DotnetRunArgs(build), timeout, inputs: null, inputDelayMs: 0, cancellationToken: cancellationToken);
+
+    /// <summary>
+    /// Runs <c>dotnet run --framework net10.0</c> with stdin inputs.
+    /// When <paramref name="build"/> is false (the default), <c>--no-build</c> is passed
+    /// to skip building, assuming the project was pre-built.
+    /// </summary>
+    public static Task<SampleRunResult> RunAsync(
+        string projectPath,
+        TimeSpan timeout,
+        string?[]? inputs,
+        int inputDelayMs = 2000,
+        bool build = false,
+        CancellationToken cancellationToken = default)
+        => RunAsync(projectPath, DotnetRunArgs(build), timeout, inputs, inputDelayMs, cancellationToken);
+
+    private static string DotnetRunArgs(bool build) =>
+        $"run {(build ? "" : "--no-build")} --framework net10.0";
+
+    /// <summary>
+    /// Runs an arbitrary <c>dotnet</c> command in the given working directory.
+    /// </summary>
+    public static async Task<SampleRunResult> RunAsync(
+        string workingDirectory,
+        string dotnetArgs,
+        TimeSpan timeout,
+        string?[]? inputs = null,
+        int inputDelayMs = 0,
+        CancellationToken cancellationToken = default)
+    {
+        var psi = new ProcessStartInfo
+        {
+            FileName = "dotnet",
+            Arguments = dotnetArgs,
+            WorkingDirectory = workingDirectory,
+            RedirectStandardOutput = true,
+            RedirectStandardError = true,
+            RedirectStandardInput = inputs is { Length: > 0 },
+            UseShellExecute = false,
+            CreateNoWindow = true,
+        };
+
+        var sw = Stopwatch.StartNew();
+
+        using var process = new Process { StartInfo = psi };
+        process.Start();
+
+        var stdoutTask = process.StandardOutput.ReadToEndAsync(cancellationToken);
+        var stderrTask = process.StandardError.ReadToEndAsync(cancellationToken);
+
+        // Feed stdin inputs with delays if configured
+        if (inputs is { Length: > 0 })
+        {
+            _ = Task.Run(async () =>
+            {
+                try
+                {
+                    foreach (var input in inputs)
+                    {
+                        await Task.Delay(inputDelayMs, cancellationToken);
+                        if (input is not null)
+                        {
+                            await process.StandardInput.WriteLineAsync(input.AsMemory(), cancellationToken);
+                            await process.StandardInput.FlushAsync(cancellationToken);
+                        }
+                    }
+
+                    process.StandardInput.Close();
+                }
+                catch (Exception ex) when (ex is IOException or ObjectDisposedException or OperationCanceledException)
+                {
+                    // Process may have exited before all inputs were sent
+                }
+            }, cancellationToken);
+        }
+
+        using var cts = CancellationTokenSource.CreateLinkedTokenSource(cancellationToken);
+        cts.CancelAfter(timeout);
+
+        try
+        {
+            await process.WaitForExitAsync(cts.Token);
+        }
+        catch (OperationCanceledException) when (!cancellationToken.IsCancellationRequested)
+        {
+            // Timeout — kill the process
+            try
+            {
+                process.Kill(entireProcessTree: true);
+            }
+            catch
+            {
+                // Best effort
+            }
+
+            sw.Stop();
+            return new SampleRunResult(
+                Stdout: await stdoutTask,
+                Stderr: $"TIMEOUT: Sample did not complete within {timeout.TotalSeconds}s.\n{await stderrTask}",
+                ExitCode: -1,
+                Elapsed: sw.Elapsed);
+        }
+
+        sw.Stop();
+        return new SampleRunResult(
+            Stdout: await stdoutTask,
+            Stderr: await stderrTask,
+            ExitCode: process.ExitCode,
+            Elapsed: sw.Elapsed);
+    }
+}
@@ -0,0 +1,229 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using System.ComponentModel;
+using System.Text.Json.Serialization;
+using Microsoft.Agents.AI;
+using Microsoft.Extensions.AI;
+using OpenAI.Chat;
+
+namespace VerifySamples;
+
+/// <summary>
+/// Verifies sample output using deterministic checks and an AI agent
+/// for non-deterministic output validation.
+/// </summary>
+internal sealed class SampleVerifier
+{
+    private readonly AIAgent? _verifierAgent;
+
+    /// <summary>
+    /// Creates a verifier. If <paramref name="chatClient"/> is provided,
+    /// AI-based verification is available for non-deterministic samples.
+    /// </summary>
+    public SampleVerifier(ChatClient? chatClient = null)
+    {
+        if (chatClient is not null)
+        {
+            this._verifierAgent = chatClient.AsAIAgent(
+                instructions: """
+                    You are a test output verifier. You will be given:
+                    1. The actual stdout output of a program
+                    2. The stderr output (if any)
+                    3. A list of expectations about what the output should contain or demonstrate
+
+                    Your job is to determine whether the actual output satisfies each expectation.
+                    Be reasonable — the output comes from an LLM so exact wording won't match, but the
+                    semantic intent should be clearly satisfied.
+
+                    In your response, you MUST:
+                    - Always provide ai_reasoning with a brief overall assessment.
+                    - Always provide exactly one entry in expectation_results for each expectation,
+                      in the same order as the input list.
+                    - For each expectation_results entry, echo the expectation text in the expectation
+                      field and explain your assessment in the detail field, citing evidence from the output.
+                    """,
+                name: "OutputVerifier");
+        }
+    }
+
+    /// <summary>
+    /// Verifies the output of a sample run against its definition.
+    /// </summary>
+    public async Task<VerificationResult> VerifyAsync(SampleDefinition sample, SampleRunResult run)
+    {
+        var failures = new List<string>();
+
+        // 1. Exit code check
+        if (run.ExitCode != 0)
+        {
+            failures.Add($"Exit code was {run.ExitCode}, expected 0. Stderr: {Truncate(run.Stderr, 500)}");
+        }
+
+        // 2. Must-contain checks
+        foreach (var expected in sample.MustContain)
+        {
+            if (!run.Stdout.Contains(expected, StringComparison.Ordinal))
+            {
+                failures.Add($"Output missing expected substring: \"{expected}\"");
+            }
+        }
+
+        // 3. Must-not-contain checks
+        foreach (var unexpected in sample.MustNotContain)
+        {
+            if (run.Stdout.Contains(unexpected, StringComparison.Ordinal))
+            {
+                failures.Add($"Output contains unexpected substring: \"{unexpected}\"");
+            }
+        }
+
+        // 4. AI verification for non-deterministic samples
+        string? aiReasoning = null;
+        if (!sample.IsDeterministic && sample.ExpectedOutputDescription.Length > 0)
+        {
+            if (this._verifierAgent is null)
+            {
+                failures.Add("AI verification required but no AI agent configured (missing AZURE_OPENAI_ENDPOINT).");
+            }
+            else
+            {
+                var aiResult = await this.VerifyWithAIAsync(run.Stdout, run.Stderr, sample.ExpectedOutputDescription);
+                aiReasoning = aiResult.Reasoning;
+
+                foreach (var unmet in aiResult.UnmetExpectations)
+                {
+                    failures.Add($"AI expectation not met: {unmet}");
+                }
+            }
+        }
+
+        bool passed = failures.Count == 0;
+        return new VerificationResult
+        {
+            SampleName = sample.Name,
+            Passed = passed,
+            Summary = passed ? "All checks passed" : $"{failures.Count} check(s) failed",
+            Failures = failures,
+            AIReasoning = aiReasoning,
+        };
+    }
+
+    private async Task<(string Reasoning, List<string> UnmetExpectations)> VerifyWithAIAsync(
+        string stdout,
+        string stderr,
+        string[] expectations)
+    {
+        var expectationList = string.Join("\n", expectations.Select((e, i) => $"  {i + 1}. {e}"));
+
+        var stderrSection = string.IsNullOrWhiteSpace(stderr)
+            ? ""
+            : $"""
+
+                Stderr output:
+                ---
+                {Truncate(stderr, 2000)}
+                ---
+                """;
+
+        var prompt = $"""
+            Actual program output:
+            ---
+            {Truncate(stdout, 4000)}
+            ---
+            {stderrSection}
+            Expectations to verify:
+            {expectationList}
+
+            Does the output satisfy all expectations?
+            """;
+
+        try
+        {
+            var response = await this._verifierAgent!.RunAsync<AIVerificationResponse>(prompt);
+            var result = response.Result;
+
+            if (result is null)
+            {
+                return ($"AI verification returned null result. Raw: {response.Text}", ["AI verification returned null result."]);
+            }
+
+            var reasoning = string.IsNullOrWhiteSpace(result.AIReasoning)
+                ? "(no reasoning provided)"
+                : result.AIReasoning;
+
+            // Collect unmet expectations as individual failures
+            var unmet = new List<string>();
+            if (result.ExpectationResults is { Count: > 0 })
+            {
+                foreach (var er in result.ExpectationResults.Where(er => !er.Met))
+                {
+                    var detail = string.IsNullOrWhiteSpace(er.Detail) ? er.Expectation : $"{er.Expectation} — {er.Detail}";
+                    unmet.Add(detail ?? "Unknown expectation");
+                }
+
+                // If the model flagged overall failure but all individual expectations were met,
+                // still treat as failure using the overall reasoning.
+                if (unmet.Count == 0 && !result.Pass)
+                {
+                    unmet.Add(reasoning);
+                }
+            }
+            else if (!result.Pass)
+            {
+                // Fallback: no per-expectation detail but overall pass is false
+                unmet.Add(reasoning);
+            }
+
+            return (reasoning, unmet);
+        }
+        catch (Exception ex)
+        {
+            return ($"AI verification error: {ex.Message}", [$"AI verification error: {ex.Message}"]);
+        }
+    }
+
+    private static string Truncate(string text, int maxLength)
+        => text.Length <= maxLength ? text : text[..maxLength] + "... (truncated)";
+}
+
+/// <summary>
+/// Structured response from the AI verification agent.
+/// </summary>
+[System.Diagnostics.CodeAnalysis.SuppressMessage("Performance", "CA1812:Avoid uninstantiated internal classes", Justification = "Instantiated by JSON deserialization via RunAsync<T>.")]
+internal sealed class AIVerificationResponse
+{
+    /// <summary>Whether all expectations were met.</summary>
+    [JsonPropertyName("pass")]
+    public bool Pass { get; set; }
+
+    /// <summary>Brief explanation of the overall assessment.</summary>
+    [JsonPropertyName("ai_reasoning")]
+    [Description("Always required. Brief explanation of the overall assessment, covering all expectations.")]
+    public string AIReasoning { get; set; } = string.Empty;
+
+    /// <summary>Per-expectation results.</summary>
+    [JsonPropertyName("expectation_results")]
+    [Description("Always required. One entry per expectation, in the same order as the input list.")]
+    public List<ExpectationResult> ExpectationResults { get; set; } = [];
+}
+
+/// <summary>
+/// Result for an individual expectation check.
+/// </summary>
+[System.Diagnostics.CodeAnalysis.SuppressMessage("Performance", "CA1812:Avoid uninstantiated internal classes", Justification = "Instantiated by JSON deserialization via RunAsync<T>.")]
+internal sealed class ExpectationResult
+{
+    /// <summary>The expectation text that was evaluated.</summary>
+    [JsonPropertyName("expectation")]
+    [Description("Echo back the expectation text being evaluated.")]
+    public string Expectation { get; set; } = string.Empty;
+
+    /// <summary>Whether this expectation was met.</summary>
+    [JsonPropertyName("met")]
+    public bool Met { get; set; }
+
+    /// <summary>Detail about how the expectation was or was not met.</summary>
+    [JsonPropertyName("detail")]
+    [Description("Explain how the expectation was or was not met, citing specific evidence from the output.")]
+    public string Detail { get; set; } = string.Empty;
+}
@@ -0,0 +1,200 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using System.Collections.Concurrent;
+
+namespace VerifySamples;
+
+/// <summary>
+/// Orchestrates sample verification: filters, runs in parallel, and collects results.
+/// </summary>
+internal sealed class VerificationOrchestrator
+{
+    private readonly SampleVerifier _verifier;
+    private readonly ConsoleReporter _reporter;
+    private readonly LogFileWriter? _logWriter;
+    private readonly string _dotnetRoot;
+    private readonly TimeSpan _timeout;
+    private readonly bool _buildSamples;
+
+    public VerificationOrchestrator(
+        SampleVerifier verifier,
+        ConsoleReporter reporter,
+        string dotnetRoot,
+        TimeSpan timeout,
+        LogFileWriter? logWriter = null,
+        bool buildSamples = false)
+    {
+        this._verifier = verifier;
+        this._reporter = reporter;
+        this._logWriter = logWriter;
+        this._dotnetRoot = dotnetRoot;
+        this._timeout = timeout;
+        this._buildSamples = buildSamples;
+    }
+
+    /// <summary>
+    /// The result of running all samples through the orchestrator.
+    /// </summary>
+    internal sealed record RunAllResult(
+        ConcurrentDictionary<string, VerificationResult> Results,
+        List<(string Name, string Reason)> Skipped,
+        List<string> SampleOrder);
+
+    /// <summary>
+    /// Filters samples, runs the runnable ones in parallel, and returns all results.
+    /// </summary>
+    public async Task<RunAllResult> RunAllAsync(
+        IReadOnlyList<SampleDefinition> samples,
+        int maxParallelism)
+    {
+        var skipped = new List<(string Name, string Reason)>();
+        var runnableSamples = new List<SampleDefinition>();
+        var sampleOrder = new List<string>();
+
+        // Separate samples into skipped and runnable
+        foreach (var sample in samples)
+        {
+            sampleOrder.Add(sample.Name);
+
+            if (sample.SkipReason is not null)
+            {
+                skipped.Add((sample.Name, sample.SkipReason));
+                this._reporter.WriteLineWithPrefix(sample.Name, $"SKIPPED — {sample.SkipReason}", ConsoleColor.Yellow);
+
+                if (this._logWriter is not null)
+                {
+                    await this._logWriter.WriteSkippedAsync(sample.Name, sample.SkipReason);
+                }
+
+                continue;
+            }
+
+            var missingRequired = sample.RequiredEnvironmentVariables
+                .Where(v => string.IsNullOrEmpty(Environment.GetEnvironmentVariable(v)))
+                .ToList();
+
+            var missingOptional = sample.OptionalEnvironmentVariables
+                .Where(v => string.IsNullOrEmpty(Environment.GetEnvironmentVariable(v)))
+                .ToList();
+
+            if (missingRequired.Count > 0 || missingOptional.Count > 0)
+            {
+                var reasons = new List<string>();
+                if (missingRequired.Count > 0)
+                {
+                    reasons.Add($"Missing required: {string.Join(", ", missingRequired)}");
+                }
+
+                if (missingOptional.Count > 0)
+                {
+                    reasons.Add($"Missing optional (would cause console prompt hang): {string.Join(", ", missingOptional)}");
+                }
+
+                var skipReason = string.Join("; ", reasons);
+                skipped.Add((sample.Name, skipReason));
+                this._reporter.WriteLineWithPrefix(sample.Name, $"SKIPPED — {skipReason}", ConsoleColor.Yellow);
+
+                if (this._logWriter is not null)
+                {
+                    await this._logWriter.WriteSkippedAsync(sample.Name, skipReason);
+                }
+
+                continue;
+            }
+
+            runnableSamples.Add(sample);
+        }
+
+        // Run samples in parallel
+        var results = new ConcurrentDictionary<string, VerificationResult>();
+        var semaphore = new SemaphoreSlim(maxParallelism);
+
+        this._reporter.WriteLineWithPrefix(
+            "runner", $"Running {runnableSamples.Count} samples (max {maxParallelism} parallel)...");
+
+        try
+        {
+            var tasks = runnableSamples.Select(sample => this.RunSingleAsync(sample, results, semaphore)).ToArray();
+            await Task.WhenAll(tasks);
+        }
+        finally
+        {
+            semaphore.Dispose();
+        }
+
+        return new RunAllResult(results, skipped, sampleOrder);
+    }
+
+    private async Task RunSingleAsync(
+        SampleDefinition sample,
+        ConcurrentDictionary<string, VerificationResult> results,
+        SemaphoreSlim semaphore)
+    {
+        await semaphore.WaitAsync();
+        try
+        {
+            var log = new List<string>();
+            log.Add($"[{sample.Name}] Running...");
+            this._reporter.WriteLineWithPrefix(sample.Name, "Running...");
+
+            var projectPath = Path.Combine(this._dotnetRoot, sample.ProjectPath);
+            var run = sample.Inputs.Length > 0
+                ? await SampleRunner.RunAsync(projectPath, this._timeout, sample.Inputs, sample.InputDelayMs, build: this._buildSamples)
+                : await SampleRunner.RunAsync(projectPath, this._timeout, build: this._buildSamples);
+
+            log.Add($"[{sample.Name}] Completed ({run.Elapsed.TotalSeconds:F1}s, exit={run.ExitCode})");
+            this._reporter.WriteLineWithPrefix(
+                sample.Name, $"Completed ({run.Elapsed.TotalSeconds:F1}s, exit={run.ExitCode}). Verifying...");
+
+            var result = await this._verifier.VerifyAsync(sample, run);
+
+            if (result.Passed)
+            {
+                log.Add($"[{sample.Name}] PASSED");
+                this._reporter.WriteLineWithPrefix(sample.Name, "PASSED", ConsoleColor.Green);
+            }
+            else
+            {
+                log.Add($"[{sample.Name}] FAILED");
+                this._reporter.WriteLineWithPrefix(sample.Name, "FAILED", ConsoleColor.Red);
+                foreach (var failure in result.Failures)
+                {
+                    log.Add($"[{sample.Name}]   ✗ {failure}");
+                    this._reporter.WriteLineWithPrefix(sample.Name, $"  ✗ {failure}", ConsoleColor.Red);
+                }
+            }
+
+            if (result.AIReasoning is not null)
+            {
+                log.Add($"[{sample.Name}]   AI: {result.AIReasoning}");
+                this._reporter.WriteLineWithPrefix(
+                    sample.Name, $"  AI: {Truncate(result.AIReasoning, 300)}", ConsoleColor.DarkGray);
+            }
+
+            var verificationResult = new VerificationResult
+            {
+                SampleName = result.SampleName,
+                Passed = result.Passed,
+                Summary = result.Summary,
+                Failures = result.Failures,
+                AIReasoning = result.AIReasoning,
+                Stdout = run.Stdout,
+                Stderr = run.Stderr,
+                LogLines = log,
+            };
+            results[sample.Name] = verificationResult;
+
+            if (this._logWriter is not null)
+            {
+                await this._logWriter.WriteSampleResultAsync(verificationResult);
+            }
+        }
+        finally
+        {
+            semaphore.Release();
+        }
+    }
+
+    private static string Truncate(string text, int maxLength)
+        => text.Length <= maxLength ? text : text[..maxLength] + "...";
+}
@@ -0,0 +1,31 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+namespace VerifySamples;
+
+/// <summary>
+/// The result of verifying a single sample.
+/// </summary>
+internal sealed class VerificationResult
+{
+    public required string SampleName { get; init; }
+    public required bool Passed { get; init; }
+    public required string Summary { get; init; }
+    public List<string> Failures { get; init; } = [];
+    public string? AIReasoning { get; init; }
+
+    /// <summary>
+    /// The sample's stdout output, captured for log file output.
+    /// </summary>
+    public string? Stdout { get; init; }
+
+    /// <summary>
+    /// The sample's stderr output, captured for log file output.
+    /// </summary>
+    public string? Stderr { get; init; }
+
+    /// <summary>
+    /// Per-sample log lines, buffered during parallel execution
+    /// and written sequentially to the log file.
+    /// </summary>
+    public List<string> LogLines { get; init; } = [];
+}
@@ -0,0 +1,151 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+namespace VerifySamples;
+
+/// <summary>
+/// Parsed command-line options for the sample verification tool.
+/// </summary>
+internal sealed class VerifyOptions
+{
+    /// <summary>
+    /// Maximum number of samples to run concurrently.
+    /// </summary>
+    public int MaxParallelism { get; init; } = 8;
+
+    /// <summary>
+    /// Path to write a CSV summary file, or <c>null</c> to skip.
+    /// </summary>
+    public string? CsvFilePath { get; init; }
+
+    /// <summary>
+    /// Path to write a Markdown summary file, or <c>null</c> to skip.
+    /// </summary>
+    public string? MarkdownFilePath { get; init; }
+
+    /// <summary>
+    /// Path to write a sequential log file, or <c>null</c> to skip.
+    /// </summary>
+    public string? LogFilePath { get; init; }
+
+    /// <summary>
+    /// When true, samples are built as part of <c>dotnet run</c>.
+    /// When false (the default), <c>--no-build</c> is passed, assuming a prior build step.
+    /// </summary>
+    public bool BuildSamples { get; init; }
+
+    /// <summary>
+    /// The filtered list of samples to process.
+    /// </summary>
+    public required IReadOnlyList<SampleDefinition> Samples { get; init; }
+
+    /// <summary>
+    /// All known sample set registries, keyed by category name.
+    /// </summary>
+    private static readonly Dictionary<string, IReadOnlyList<SampleDefinition>> s_sampleSets =
+        new(StringComparer.OrdinalIgnoreCase)
+        {
+            ["01-get-started"] = GetStartedSamples.All,
+            ["02-agents"] = AgentsSamples.All,
+            ["03-workflows"] = WorkflowSamples.All,
+        };
+
+    /// <summary>
+    /// Parses command-line arguments and resolves the sample list.
+    /// Returns <c>null</c> and writes to stderr if the arguments are invalid.
+    /// </summary>
+    public static VerifyOptions? Parse(string[] args)
+    {
+        var argList = args.ToList();
+
+        var categoryFilter = ExtractArg(argList, "--category");
+        var logFilePath = ExtractArg(argList, "--log");
+        var csvFilePath = ExtractArg(argList, "--csv");
+        var markdownFilePath = ExtractArg(argList, "--md");
+        var buildSamples = ExtractFlag(argList, "--build");
+
+        int maxParallelism = 8;
+        var parallelArg = ExtractArg(argList, "--parallel");
+        if (parallelArg is not null && int.TryParse(parallelArg, out var p) && p > 0)
+        {
+            maxParallelism = p;
+        }
+
+        HashSet<string>? nameFilter = null;
+        if (argList.Count > 0)
+        {
+            nameFilter = argList.ToHashSet(StringComparer.OrdinalIgnoreCase);
+        }
+
+        // Build the sample list
+        IReadOnlyList<SampleDefinition> samples;
+        if (categoryFilter is not null)
+        {
+            if (!s_sampleSets.TryGetValue(categoryFilter, out var categoryList))
+            {
+                Console.Error.WriteLine(
+                    $"Unknown category '{categoryFilter}'. Available: {string.Join(", ", s_sampleSets.Keys)}");
+                return null;
+            }
+
+            samples = categoryList;
+        }
+        else
+        {
+            samples = s_sampleSets.Values.SelectMany(s => s).ToList();
+        }
+
+        if (nameFilter is not null)
+        {
+            samples = samples.Where(s => nameFilter.Contains(s.Name)).ToList();
+        }
+
+        if (samples.Count == 0)
+        {
+            var allNames = s_sampleSets.Values.SelectMany(s => s).Select(s => s.Name);
+            Console.Error.WriteLine($"No matching samples found. Available: {string.Join(", ", allNames)}");
+            return null;
+        }
+
+        return new VerifyOptions
+        {
+            MaxParallelism = maxParallelism,
+            LogFilePath = logFilePath,
+            CsvFilePath = csvFilePath,
+            MarkdownFilePath = markdownFilePath,
+            BuildSamples = buildSamples,
+            Samples = samples,
+        };
+    }
+
+    private static string? ExtractArg(List<string> list, string flag)
+    {
+        var idx = list.IndexOf(flag);
+        if (idx < 0)
+        {
+            return null;
+        }
+
+        if (idx + 1 >= list.Count)
+        {
+            Console.Error.WriteLine($"Missing value for {flag}.");
+            list.RemoveAt(idx);
+            return null;
+        }
+
+        var value = list[idx + 1];
+        list.RemoveRange(idx, 2);
+        return value;
+    }
+
+    private static bool ExtractFlag(List<string> list, string flag)
+    {
+        var idx = list.IndexOf(flag);
+        if (idx < 0)
+        {
+            return false;
+        }
+
+        list.RemoveAt(idx);
+        return true;
+    }
+}
@@ -0,0 +1,525 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+namespace VerifySamples;
+
+/// <summary>
+/// Defines the expected behavior for each sample in 03-workflows.
+/// </summary>
+internal static class WorkflowSamples
+{
+    public static IReadOnlyList<SampleDefinition> All { get; } =
+    [
+        // ───────────────────────────────────────────────────────────────────
+        // _StartHere
+        // ───────────────────────────────────────────────────────────────────
+
+        new SampleDefinition
+        {
+            Name = "Workflow_StartHere_01_Streaming",
+            ProjectPath = "samples/03-workflows/_StartHere/01_Streaming",
+            RequiredEnvironmentVariables = [],
+            IsDeterministic = true,
+            MustContain =
+            [
+                "UppercaseExecutor: HELLO, WORLD!",
+                "ReverseTextExecutor: !DLROW ,OLLEH",
+            ],
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_StartHere_02_AgentsInWorkflows",
+            ProjectPath = "samples/03-workflows/_StartHere/02_AgentsInWorkflows",
+            RequiredEnvironmentVariables = ["AZURE_OPENAI_ENDPOINT"],
+            OptionalEnvironmentVariables = ["AZURE_OPENAI_DEPLOYMENT_NAME"],
+            ExpectedOutputDescription =
+            [
+                "The output should show agent responses from a translation workflow.",
+                "The output should not contain error messages or stack traces.",
+            ],
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_StartHere_03_AgentWorkflowPatterns",
+            ProjectPath = "samples/03-workflows/_StartHere/03_AgentWorkflowPatterns",
+            RequiredEnvironmentVariables = ["AZURE_OPENAI_ENDPOINT"],
+            OptionalEnvironmentVariables = ["AZURE_OPENAI_DEPLOYMENT_NAME"],
+            Inputs = ["sequential"],
+            InputDelayMs = 3000,
+            ExpectedOutputDescription =
+            [
+                "The output should show a sequential workflow pattern with multiple agents executing tasks in order.",
+                "The output should not contain error messages or stack traces.",
+            ],
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_StartHere_04_MultiModelService",
+            ProjectPath = "samples/03-workflows/_StartHere/04_MultiModelService",
+            RequiredEnvironmentVariables = ["BEDROCK_ACCESS_KEY", "BEDROCK_SECRET_KEY", "ANTHROPIC_API_KEY", "OPENAI_API_KEY"],
+            SkipReason = "Requires multiple external provider API keys (Bedrock, Anthropic, OpenAI).",
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_StartHere_05_SubWorkflows",
+            ProjectPath = "samples/03-workflows/_StartHere/05_SubWorkflows",
+            RequiredEnvironmentVariables = [],
+            IsDeterministic = true,
+            MustContain =
+            [
+                "=== Sub-Workflow Demonstration ===",
+                "Final Output:",
+                "=== Main Workflow Completed ===",
+                "Sample Complete: Workflows can be composed hierarchically using sub-workflows",
+            ],
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_StartHere_06_MixedWorkflowAgentsAndExecutors",
+            ProjectPath = "samples/03-workflows/_StartHere/06_MixedWorkflowAgentsAndExecutors",
+            RequiredEnvironmentVariables = ["AZURE_OPENAI_ENDPOINT"],
+            OptionalEnvironmentVariables = ["AZURE_OPENAI_DEPLOYMENT_NAME"],
+            Inputs = ["What is 2 plus 2?"],
+            InputDelayMs = 3000,
+            ExpectedOutputDescription =
+            [
+                "The output should show agents and executors working together to process a user question.",
+                "The output should not contain error messages or stack traces.",
+            ],
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_StartHere_07_WriterCriticWorkflow",
+            ProjectPath = "samples/03-workflows/_StartHere/07_WriterCriticWorkflow",
+            RequiredEnvironmentVariables = ["AZURE_OPENAI_ENDPOINT"],
+            OptionalEnvironmentVariables = ["AZURE_OPENAI_DEPLOYMENT_NAME"],
+            MustContain = ["=== Writer-Critic Iteration Workflow ==="],
+            ExpectedOutputDescription =
+            [
+                "The output should show a writer-critic iteration workflow with writer and critic sections.",
+                "The critic should either approve or request revisions.",
+                "The output should not contain error messages or stack traces.",
+            ],
+        },
+
+        // ───────────────────────────────────────────────────────────────────
+        // Agents
+        // ───────────────────────────────────────────────────────────────────
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Agents_CustomAgentExecutors",
+            ProjectPath = "samples/03-workflows/Agents/CustomAgentExecutors",
+            RequiredEnvironmentVariables = ["AZURE_OPENAI_ENDPOINT"],
+            OptionalEnvironmentVariables = ["AZURE_OPENAI_DEPLOYMENT_NAME"],
+            ExpectedOutputDescription =
+            [
+                "The output should show custom workflow events including slogan generation and feedback.",
+                "The output should not contain error messages or stack traces.",
+            ],
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Agents_FoundryAgent",
+            ProjectPath = "samples/03-workflows/Agents/FoundryAgent",
+            RequiredEnvironmentVariables = ["AZURE_AI_PROJECT_ENDPOINT"],
+            OptionalEnvironmentVariables = ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+            SkipReason = "Requires Azure AI Foundry project endpoint.",
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Agents_GroupChatToolApproval",
+            ProjectPath = "samples/03-workflows/Agents/GroupChatToolApproval",
+            RequiredEnvironmentVariables = ["AZURE_OPENAI_ENDPOINT"],
+            OptionalEnvironmentVariables = ["AZURE_OPENAI_DEPLOYMENT_NAME"],
+            MustContain = ["Starting group chat workflow for software deployment..."],
+            ExpectedOutputDescription =
+            [
+                "The output should show a group chat workflow with QA and DevOps agents for software deployment.",
+                "There should be approval requests for tool calls.",
+                "The workflow should show interaction between QA and DevOps agents toward deployment.",
+                "The output should not contain error messages or stack traces.",
+            ],
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Agents_WorkflowAsAnAgent",
+            ProjectPath = "samples/03-workflows/Agents/WorkflowAsAnAgent",
+            RequiredEnvironmentVariables = ["AZURE_OPENAI_ENDPOINT"],
+            OptionalEnvironmentVariables = ["AZURE_OPENAI_DEPLOYMENT_NAME"],
+            Inputs = ["hello", "exit"],
+            InputDelayMs = 5000,
+            ExpectedOutputDescription =
+            [
+                "The output should show a conversational workflow responding to the user's hello message.",
+                "The output should not contain error messages or stack traces.",
+            ],
+        },
+
+        // ───────────────────────────────────────────────────────────────────
+        // Checkpoint
+        // ───────────────────────────────────────────────────────────────────
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Checkpoint_CheckpointAndRehydrate",
+            ProjectPath = "samples/03-workflows/Checkpoint/CheckpointAndRehydrate",
+            RequiredEnvironmentVariables = [],
+            IsDeterministic = true,
+            MustContain =
+            [
+                "Workflow completed with result:",
+                "Number of checkpoints created:",
+                "Hydrating a new workflow instance from the 6th checkpoint.",
+            ],
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Checkpoint_CheckpointAndResume",
+            ProjectPath = "samples/03-workflows/Checkpoint/CheckpointAndResume",
+            RequiredEnvironmentVariables = [],
+            IsDeterministic = true,
+            MustContain =
+            [
+                "Workflow completed with result:",
+                "Number of checkpoints created:",
+                "Restoring from the 6th checkpoint.",
+            ],
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Checkpoint_CheckpointWithHumanInTheLoop",
+            ProjectPath = "samples/03-workflows/Checkpoint/CheckpointWithHumanInTheLoop",
+            RequiredEnvironmentVariables = [],
+            Inputs = ["50", "25", "40", "45", "42", "50", "25", "40", "45", "42"],
+            InputDelayMs = 1000,
+            MustContain = ["found in"],
+            ExpectedOutputDescription =
+            [
+                "The output should show a number guessing game with higher/lower hints that eventually reaches the correct number.",
+                "The output should demonstrate checkpoint save and restore behavior.",
+            ],
+        },
+
+        // ───────────────────────────────────────────────────────────────────
+        // Concurrent
+        // ───────────────────────────────────────────────────────────────────
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Concurrent_Concurrent",
+            ProjectPath = "samples/03-workflows/Concurrent/Concurrent",
+            RequiredEnvironmentVariables = ["AZURE_OPENAI_ENDPOINT"],
+            OptionalEnvironmentVariables = ["AZURE_OPENAI_DEPLOYMENT_NAME"],
+            ExpectedOutputDescription =
+            [
+                "The output should show results from concurrent agent processing.",
+                "The output should not contain error messages or stack traces.",
+            ],
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Concurrent_MapReduce",
+            ProjectPath = "samples/03-workflows/Concurrent/MapReduce",
+            RequiredEnvironmentVariables = [],
+            MustContain =
+            [
+                "=== RUNNING WORKFLOW ===",
+            ],
+        },
+
+        // ───────────────────────────────────────────────────────────────────
+        // ConditionalEdges
+        // ───────────────────────────────────────────────────────────────────
+
+        new SampleDefinition
+        {
+            Name = "Workflow_ConditionalEdges_01_EdgeCondition",
+            ProjectPath = "samples/03-workflows/ConditionalEdges/01_EdgeCondition",
+            RequiredEnvironmentVariables = ["AZURE_OPENAI_ENDPOINT"],
+            OptionalEnvironmentVariables = ["AZURE_OPENAI_DEPLOYMENT_NAME"],
+            ExpectedOutputDescription =
+            [
+                "The output should show an email being classified as spam or not spam and processed accordingly.",
+                "The output should not contain error messages or stack traces.",
+            ],
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_ConditionalEdges_02_SwitchCase",
+            ProjectPath = "samples/03-workflows/ConditionalEdges/02_SwitchCase",
+            RequiredEnvironmentVariables = ["AZURE_OPENAI_ENDPOINT"],
+            OptionalEnvironmentVariables = ["AZURE_OPENAI_DEPLOYMENT_NAME"],
+            ExpectedOutputDescription =
+            [
+                "The output should show an ambiguous email being classified as spam, not spam, or uncertain.",
+                "The output should not contain error messages or stack traces.",
+            ],
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_ConditionalEdges_03_MultiSelection",
+            ProjectPath = "samples/03-workflows/ConditionalEdges/03_MultiSelection",
+            RequiredEnvironmentVariables = ["AZURE_OPENAI_ENDPOINT"],
+            OptionalEnvironmentVariables = ["AZURE_OPENAI_DEPLOYMENT_NAME"],
+            ExpectedOutputDescription =
+            [
+                "The output should show an email being classified and potentially routed to multiple handlers.",
+                "The output should not contain error messages or stack traces.",
+            ],
+        },
+
+        // ───────────────────────────────────────────────────────────────────
+        // HumanInTheLoop
+        // ───────────────────────────────────────────────────────────────────
+
+        new SampleDefinition
+        {
+            Name = "Workflow_HumanInTheLoop_Basic",
+            ProjectPath = "samples/03-workflows/HumanInTheLoop/HumanInTheLoopBasic",
+            RequiredEnvironmentVariables = [],
+            Inputs = ["50", "25", "40", "45", "42"],
+            InputDelayMs = 1000,
+            MustContain = ["found in"],
+            ExpectedOutputDescription =
+            [
+                "The output should show a number guessing game with higher/lower hints that eventually reaches the correct number 42.",
+            ],
+        },
+
+        // ───────────────────────────────────────────────────────────────────
+        // Loop
+        // ───────────────────────────────────────────────────────────────────
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Loop",
+            ProjectPath = "samples/03-workflows/Loop",
+            RequiredEnvironmentVariables = [],
+            MustContain = ["Result:"],
+        },
+
+        // ───────────────────────────────────────────────────────────────────
+        // SharedStates
+        // ───────────────────────────────────────────────────────────────────
+
+        new SampleDefinition
+        {
+            Name = "Workflow_SharedStates",
+            ProjectPath = "samples/03-workflows/SharedStates",
+            RequiredEnvironmentVariables = [],
+            IsDeterministic = true,
+            MustContain =
+            [
+                "Total Paragraphs:",
+                "Total Words:",
+            ],
+        },
+
+        // ───────────────────────────────────────────────────────────────────
+        // Visualization
+        // ───────────────────────────────────────────────────────────────────
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Visualization",
+            ProjectPath = "samples/03-workflows/Visualization",
+            RequiredEnvironmentVariables = [],
+            IsDeterministic = true,
+            MustContain =
+            [
+                "Generating workflow visualization...",
+                "Mermaid string:",
+                "DiGraph string:",
+            ],
+        },
+
+        // ───────────────────────────────────────────────────────────────────
+        // Observability
+        // ───────────────────────────────────────────────────────────────────
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Observability_ApplicationInsights",
+            ProjectPath = "samples/03-workflows/Observability/ApplicationInsights",
+            RequiredEnvironmentVariables = ["APPLICATIONINSIGHTS_CONNECTION_STRING"],
+            SkipReason = "Requires Application Insights connection string.",
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Observability_AspireDashboard",
+            ProjectPath = "samples/03-workflows/Observability/AspireDashboard",
+            RequiredEnvironmentVariables = [],
+            SkipReason = "Requires Aspire Dashboard / OTLP endpoint.",
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Observability_WorkflowAsAnAgent",
+            ProjectPath = "samples/03-workflows/Observability/WorkflowAsAnAgent",
+            RequiredEnvironmentVariables = ["AZURE_OPENAI_ENDPOINT"],
+            OptionalEnvironmentVariables = ["AZURE_OPENAI_DEPLOYMENT_NAME"],
+            SkipReason = "Interactive console with ReadLine loop; requires OTLP endpoint.",
+        },
+
+        // ───────────────────────────────────────────────────────────────────
+        // Declarative
+        // ───────────────────────────────────────────────────────────────────
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Declarative_ConfirmInput",
+            ProjectPath = "samples/03-workflows/Declarative/ConfirmInput",
+            RequiredEnvironmentVariables = ["AZURE_AI_PROJECT_ENDPOINT"],
+            Inputs = ["hello", "hello"],
+            InputDelayMs = 8000,
+            ExpectedOutputDescription = ["The output should show a confirmation prompt and a user response."],
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Declarative_CustomerSupport",
+            ProjectPath = "samples/03-workflows/Declarative/CustomerSupport",
+            RequiredEnvironmentVariables = ["AZURE_AI_PROJECT_ENDPOINT"],
+            OptionalEnvironmentVariables = ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+            Inputs = ["My laptop won't start"],
+            InputDelayMs = 3000,
+            ExpectedOutputDescription = ["The output should show a customer support workflow processing a laptop issue, with agent responses providing troubleshooting or support."],
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Declarative_DeepResearch",
+            ProjectPath = "samples/03-workflows/Declarative/DeepResearch",
+            RequiredEnvironmentVariables = ["AZURE_AI_PROJECT_ENDPOINT"],
+            OptionalEnvironmentVariables = ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+            SkipReason = "Requires external weather API (wttr.in).",
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Declarative_ExecuteCode",
+            ProjectPath = "samples/03-workflows/Declarative/ExecuteCode",
+            RequiredEnvironmentVariables = ["AZURE_AI_PROJECT_ENDPOINT"],
+            Inputs = ["What is 12 * 34?"],
+            InputDelayMs = 5000,
+            ExpectedOutputDescription = ["The output should show a declarative workflow executing generated code, processing a math question and producing a result."],
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Declarative_ExecuteWorkflow",
+            ProjectPath = "samples/03-workflows/Declarative/ExecuteWorkflow",
+            RequiredEnvironmentVariables = ["AZURE_AI_PROJECT_ENDPOINT"],
+            SkipReason = "Requires a workflow file path as a CLI argument.",
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Declarative_FunctionTools",
+            ProjectPath = "samples/03-workflows/Declarative/FunctionTools",
+            RequiredEnvironmentVariables = ["AZURE_AI_PROJECT_ENDPOINT"],
+            OptionalEnvironmentVariables = ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+            Inputs = ["What are today's specials?", "EXIT"],
+            InputDelayMs = 8000,
+            ExpectedOutputDescription = ["The output should show a workflow calling function tools (e.g. a menu plugin) to answer a question about restaurant specials."],
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Declarative_GenerateCode",
+            ProjectPath = "samples/03-workflows/Declarative/GenerateCode",
+            IsDeterministic = true,
+            MustContain = ["WORKFLOW: Parsing", "WORKFLOW: Defined"],
+            ExpectedOutputDescription = ["The output should show a YAML workflow being parsed and C# code being generated from it."],
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Declarative_HostedWorkflow",
+            ProjectPath = "samples/03-workflows/Declarative/HostedWorkflow",
+            RequiredEnvironmentVariables = ["AZURE_AI_PROJECT_ENDPOINT"],
+            SkipReason = "Hosts a persistent workflow server that does not exit.",
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Declarative_InputArguments",
+            ProjectPath = "samples/03-workflows/Declarative/InputArguments",
+            RequiredEnvironmentVariables = ["AZURE_AI_PROJECT_ENDPOINT"],
+            OptionalEnvironmentVariables = ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+            Inputs = ["I'd like to visit Seattle", "EXIT"],
+            InputDelayMs = 8000,
+            ExpectedOutputDescription = ["The output should show a workflow capturing location input and providing travel-related information about Seattle."],
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Declarative_InvokeFunctionTool",
+            ProjectPath = "samples/03-workflows/Declarative/InvokeFunctionTool",
+            RequiredEnvironmentVariables = ["AZURE_AI_PROJECT_ENDPOINT"],
+            OptionalEnvironmentVariables = ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+            Inputs = ["What's the soup of the day?", "EXIT"],
+            InputDelayMs = 8000,
+            ExpectedOutputDescription = ["The output should show a workflow invoking a function tool (e.g. a menu plugin) to answer a question about the soup of the day."],
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Declarative_InvokeMcpTool",
+            ProjectPath = "samples/03-workflows/Declarative/InvokeMcpTool",
+            RequiredEnvironmentVariables = ["AZURE_AI_PROJECT_ENDPOINT"],
+            OptionalEnvironmentVariables = ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+            Inputs = ["Search for .NET tutorials on Microsoft Learn"],
+            InputDelayMs = 3000,
+            ExpectedOutputDescription = ["The output should show a workflow using MCP tools to search Microsoft Learn documentation and provide a summary of results."],
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Declarative_Marketing",
+            ProjectPath = "samples/03-workflows/Declarative/Marketing",
+            RequiredEnvironmentVariables = ["AZURE_AI_PROJECT_ENDPOINT"],
+            OptionalEnvironmentVariables = ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+            Inputs = ["A smart water bottle that tracks hydration"],
+            InputDelayMs = 3000,
+            ExpectedOutputDescription = ["The output should show a marketing workflow generating content about a smart water bottle product."],
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Declarative_StudentTeacher",
+            ProjectPath = "samples/03-workflows/Declarative/StudentTeacher",
+            RequiredEnvironmentVariables = ["AZURE_AI_PROJECT_ENDPOINT"],
+            OptionalEnvironmentVariables = ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+            Inputs = ["What is 18 + 27?"],
+            InputDelayMs = 3000,
+            ExpectedOutputDescription = ["The output should show a student-teacher workflow where a student asks a math question and a teacher provides the answer."],
+        },
+
+        new SampleDefinition
+        {
+            Name = "Workflow_Declarative_ToolApproval",
+            ProjectPath = "samples/03-workflows/Declarative/ToolApproval",
+            RequiredEnvironmentVariables = ["AZURE_AI_PROJECT_ENDPOINT"],
+            OptionalEnvironmentVariables = ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+            Inputs = ["Search for .NET tutorials", "EXIT"],
+            InputDelayMs = 8000,
+            ExpectedOutputDescription = ["The output should show a workflow using an MCP tool with approval to search Microsoft Learn, followed by an exit from the input loop."],
+        },
+    ];
+}
@@ -0,0 +1,24 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFrameworks>net10.0</TargetFrameworks>
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <IsPackable>false</IsPackable>
+    <IsAotCompatible>false</IsAotCompatible>
+    <!-- This is a top-level console app; ConfigureAwait is unnecessary -->
+    <NoWarn>$(NoWarn);CA2007</NoWarn>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
+  </ItemGroup>
+
+</Project>
@@ -1,20 +1,21 @@
 <Project>
  <PropertyGroup>
    <!-- Central version prefix - applies to all nuget packages. -->
-    <VersionPrefix>1.0.0</VersionPrefix>
-    <RCNumber>5</RCNumber>
+    <VersionPrefix>1.1.0</VersionPrefix>
+    <RCNumber>1</RCNumber>
    <PackageVersion Condition="'$(IsReleaseCandidate)' == 'true'">$(VersionPrefix)-rc$(RCNumber)</PackageVersion>
-    <PackageVersion Condition="'$(IsReleaseCandidate)' != 'true' AND '$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).260330.1</PackageVersion>
-    <PackageVersion Condition="'$(IsReleaseCandidate)' != 'true' AND '$(VersionSuffix)' == ''">$(VersionPrefix)-preview.260330.1</PackageVersion>
-    <GitTag>1.0.0-rc5</GitTag>
+    <PackageVersion Condition="'$(IsReleaseCandidate)' != 'true' AND '$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).260410.1</PackageVersion>
+    <PackageVersion Condition="'$(IsReleaseCandidate)' != 'true' AND '$(VersionSuffix)' == ''">$(VersionPrefix)-preview.260410.1</PackageVersion>
+    <PackageVersion Condition="'$(IsReleased)' == 'true'">$(VersionPrefix)</PackageVersion>
+    <GitTag>1.1.0</GitTag>

    <Configurations>Debug;Release;Publish</Configurations>
    <IsPackable>true</IsPackable>

    <!-- Package validation. Baseline Version should be the latest version available on NuGet. -->
-    <PackageValidationBaselineVersion>1.0.0-rc4</PackageValidationBaselineVersion>
-    <!-- Enable validation for RC packages and GA packages -->
-    <EnablePackageValidation Condition="'$(IsReleaseCandidate)' == 'true' OR '$(IsGenerallyAvailable)' == 'true'">true</EnablePackageValidation>
+    <PackageValidationBaselineVersion>1.0.0</PackageValidationBaselineVersion>
+    <!-- Enable validation for GA packages -->
+    <EnablePackageValidation Condition="'$(IsReleased)' == 'true'">true</EnablePackageValidation>
    <!-- Validate assembly attributes only for Publish builds -->
    <NoWarn Condition="'$(Configuration)' != 'Publish'">$(NoWarn);CP0003</NoWarn>
    <!-- Do not validate reference assemblies -->
@@ -8,7 +8,7 @@ using Microsoft.Agents.AI;
 using OpenAI.Chat;

 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";

 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
@@ -11,7 +11,7 @@ using Microsoft.Extensions.AI;
 using OpenAI.Chat;

 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";

 [Description("Get the weather for a given location.")]
 static string GetWeather([Description("The location to get the weather for.")] string location)
@@ -8,7 +8,7 @@ using Microsoft.Agents.AI;
 using OpenAI.Chat;

 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";

 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
@@ -16,7 +16,7 @@ using OpenAI.Chat;
 using SampleApp;

 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";

 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
@@ -8,7 +8,7 @@
 //
 // Environment variables:
 //   AZURE_OPENAI_ENDPOINT
-//   AZURE_OPENAI_DEPLOYMENT_NAME (defaults to "gpt-4o-mini")
+//   AZURE_OPENAI_DEPLOYMENT_NAME (defaults to "gpt-5.4-mini")
 //
 // Run with: func start
 // Then call: POST http://localhost:7071/api/agents/HostedAgent/run
@@ -23,7 +23,7 @@ using OpenAI.Chat;

 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")
    ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";

 // Set up an AI agent following the standard Microsoft Agent Framework pattern.
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
@@ -15,7 +15,7 @@ All samples require the following environment variables:

 ```bash
 export AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/"
-export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"
+export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"
 ```

 For the client samples, you can optionally set:
@@ -23,7 +23,7 @@ const string SourceName = "OpenTelemetryAspire.ConsoleApp";
 const string ServiceName = "AgentOpenTelemetry";

 // Configure OpenTelemetry for Aspire dashboard
-var otlpEndpoint = Environment.GetEnvironmentVariable("OTEL_EXPORTER_OTLP_ENDPOINT") ?? "http://localhost:4318";
+var otlpEndpoint = Environment.GetEnvironmentVariable("OTEL_EXPORTER_OTLP_ENDPOINT") ?? "http://localhost:4317";

 var applicationInsightsConnectionString = Environment.GetEnvironmentVariable("APPLICATIONINSIGHTS_CONNECTION_STRING");

@@ -97,7 +97,7 @@ Console.WriteLine("""
    """);

 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT environment variable is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";

 // Log application startup
 appLogger.LogInformation("OpenTelemetry Aspire Demo application started");
@@ -34,7 +34,7 @@ graph TD
 Set the following environment variables:
 ```powershell
 $env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/"
-$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
 ```

 **Note**: This demo uses Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Azure OpenAI resource.
@@ -5,8 +5,8 @@ This sample demonstrates how to create an AIAgent using Anthropic Claude models
 The sample supports three deployment scenarios:

 1. **Anthropic Public API** - Direct connection to Anthropic's public API
-2. **Azure Foundry with API Key** - Anthropic models deployed through Azure Foundry using API key authentication
-3. **Azure Foundry with Azure CLI** - Anthropic models deployed through Azure Foundry using Azure CLI credentials
+2. **Microsoft Foundry with API Key** - Anthropic models deployed through Microsoft Foundry using API key authentication
+3. **Microsoft Foundry with Azure CLI** - Anthropic models deployed through Microsoft Foundry using Azure CLI credentials

 ## Prerequisites

@@ -25,29 +25,29 @@ $env:ANTHROPIC_API_KEY="your-anthropic-api-key"  # Replace with your Anthropic A
 $env:ANTHROPIC_CHAT_MODEL_NAME="claude-haiku-4-5"  # Optional, defaults to claude-haiku-4-5
 ```

-### For Azure Foundry with API Key
+### For Microsoft Foundry with API Key

- Azure Foundry service endpoint and deployment configured
+- Microsoft Foundry service endpoint and deployment configured
 - Anthropic API key

 Set the following environment variables:

 ```powershell
-$env:ANTHROPIC_RESOURCE="your-foundry-resource-name"  # Replace with your Azure Foundry resource name (subdomain before .services.ai.azure.com)
+$env:ANTHROPIC_RESOURCE="your-foundry-resource-name"  # Replace with your Microsoft Foundry resource name (subdomain before .services.ai.azure.com)
 $env:ANTHROPIC_API_KEY="your-anthropic-api-key"  # Replace with your Anthropic API key
 $env:ANTHROPIC_CHAT_MODEL_NAME="claude-haiku-4-5"  # Optional, defaults to claude-haiku-4-5
 ```

-### For Azure Foundry with Azure CLI
+### For Microsoft Foundry with Azure CLI

- Azure Foundry service endpoint and deployment configured
+- Microsoft Foundry service endpoint and deployment configured
 - Azure CLI installed and authenticated (for Azure credential authentication)

 Set the following environment variables:

 ```powershell
-$env:ANTHROPIC_RESOURCE="your-foundry-resource-name"  # Replace with your Azure Foundry resource name (subdomain before .services.ai.azure.com)
+$env:ANTHROPIC_RESOURCE="your-foundry-resource-name"  # Replace with your Microsoft Foundry resource name (subdomain before .services.ai.azure.com)
 $env:ANTHROPIC_CHAT_MODEL_NAME="claude-haiku-4-5"  # Optional, defaults to claude-haiku-4-5
 ```

-**Note**: When using Azure Foundry with Azure CLI, make sure you're logged in with `az login` and have access to the Azure Foundry resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
+**Note**: When using Microsoft Foundry with Azure CLI, make sure you're logged in with `az login` and have access to the Microsoft Foundry resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
@@ -2,14 +2,14 @@

 #pragma warning disable CS0618 // Type or member is obsolete - sample uses deprecated PersistentAgentsClientExtensions

-// This sample shows how to create and use a simple AI agent with Azure Foundry Agents as the backend.
+// This sample shows how to create and use a simple AI agent with Microsoft Foundry Agents as the backend.

 using Azure.AI.Agents.Persistent;
 using Azure.Identity;
 using Microsoft.Agents.AI;

 var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";

 const string JokerName = "Joker";
 const string JokerInstructions = "You are good at telling jokes.";
@@ -13,14 +13,14 @@ Below is a comparison between the classic and new Foundry Agents approaches:
 Before you begin, ensure you have the following prerequisites:

 - .NET 10 SDK or later
- Azure Foundry service endpoint and deployment configured
+- Microsoft Foundry service endpoint and deployment configured
 - Azure CLI installed and authenticated (for Azure credential authentication)

-**Note**: This demo uses Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Azure Foundry resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
+**Note**: This demo uses Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Microsoft Foundry resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).

 Set the following environment variables:

 ```powershell
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project" # Replace with your Azure Foundry resource endpoint
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project" # Replace with your Microsoft Foundry resource endpoint
+$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
 ```
@@ -15,7 +15,7 @@
  </ItemGroup>

  <ItemGroup>
-    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.Foundry\Microsoft.Agents.AI.Foundry.csproj" />
  </ItemGroup>

 </Project>
@@ -1,29 +1,29 @@
 // Copyright (c) Microsoft. All rights reserved.

-// This sample shows how to create and use a AI agents with Azure Foundry Agents as the backend.
+// This sample shows how to create and use AI agents with Microsoft Foundry Agents as the backend.

 using Azure.AI.Projects;
 using Azure.AI.Projects.Agents;
 using Azure.Identity;
 using Microsoft.Agents.AI;
-using Microsoft.Agents.AI.AzureAI;
+using Microsoft.Agents.AI.Foundry;

 var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";

 const string JokerName = "JokerAgent";

-// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
+// Get a client to create/retrieve/delete server side agents with Microsoft Foundry Agents.
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
 // latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 var aiProjectClient = new AIProjectClient(new Uri(endpoint), new DefaultAzureCredential());

 // Define the agent you want to create. (Prompt Agent in this case)
-var agentVersionCreationOptions = new AgentVersionCreationOptions(new PromptAgentDefinition(model: deploymentName) { Instructions = "You are good at telling jokes." });
+var agentVersionCreationOptions = new ProjectsAgentVersionCreationOptions(new DeclarativeAgentDefinition(model: deploymentName) { Instructions = "You are good at telling jokes." });
 // Azure.AI.Agents SDK creates and manages agent by name and versions.
 // You can create a server side agent version with the Azure.AI.Agents SDK client below.
-var createdAgentVersion = aiProjectClient.Agents.CreateAgentVersion(agentName: JokerName, options: agentVersionCreationOptions);
+var createdAgentVersion = aiProjectClient.AgentAdministrationClient.CreateAgentVersion(agentName: JokerName, options: agentVersionCreationOptions);

 // Note:
 //      agentVersion.Id = "<agentName>:<versionNumber>",
@@ -34,15 +34,15 @@ var createdAgentVersion = aiProjectClient.Agents.CreateAgentVersion(agentName: J
 FoundryAgent existingJokerAgent = aiProjectClient.AsAIAgent(createdAgentVersion);

 // You can also create another AIAgent version by providing the same name with a different definition.
-AgentVersion newJokerAgentVersion = await aiProjectClient.Agents.CreateAgentVersionAsync(
+ProjectsAgentVersion newJokerAgentVersion = await aiProjectClient.AgentAdministrationClient.CreateAgentVersionAsync(
    JokerName,
-    new AgentVersionCreationOptions(new PromptAgentDefinition(model: deploymentName) { Instructions = "You are extremely hilarious at telling jokes." }));
+    new ProjectsAgentVersionCreationOptions(new DeclarativeAgentDefinition(model: deploymentName) { Instructions = "You are extremely hilarious at telling jokes." }));
 FoundryAgent newJokerAgent = aiProjectClient.AsAIAgent(newJokerAgentVersion);

 // You can also get the AIAgent latest version just providing its name.
-AgentRecord jokerAgentRecord = await aiProjectClient.Agents.GetAgentAsync(JokerName);
+ProjectsAgentRecord jokerAgentRecord = await aiProjectClient.AgentAdministrationClient.GetAgentAsync(JokerName);
 FoundryAgent jokerAgentLatest = aiProjectClient.AsAIAgent(jokerAgentRecord);
-AgentVersion latestAgentVersion = jokerAgentRecord.GetLatestVersion();
+ProjectsAgentVersion latestAgentVersion = jokerAgentRecord.GetLatestVersion();

 // The AIAgent version can be accessed via the GetService method.
 Console.WriteLine($"Latest agent version id: {latestAgentVersion.Id}");
@@ -55,4 +55,4 @@ Console.WriteLine(await jokerAgentLatest.RunAsync("Tell me a joke about a pirate
 Console.WriteLine(await jokerAgentLatest.RunAsync("Now tell me a joke about a cat and a dog using last joke as the anchor.", session));

 // Cleanup by agent name removes both agent versions created.
-aiProjectClient.Agents.DeleteAgent(existingJokerAgent.Name);
+aiProjectClient.AgentAdministrationClient.DeleteAgent(existingJokerAgent.Name);
@@ -13,14 +13,14 @@ Below is a comparison between the classic and new Foundry Agents approaches:
 Before you begin, ensure you have the following prerequisites:

 - .NET 10 SDK or later
- Azure Foundry service endpoint and deployment configured
+- Microsoft Foundry service endpoint and deployment configured
 - Azure CLI installed and authenticated (for Azure credential authentication)

-**Note**: This demo uses Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Azure Foundry resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
+**Note**: This demo uses Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Microsoft Foundry resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).

 Set the following environment variables:

 ```powershell
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project" # Replace with your Azure Foundry resource endpoint
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project" # Replace with your Microsoft Foundry resource endpoint
+$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
 ```
@@ -1,7 +1,7 @@
 // Copyright (c) Microsoft. All rights reserved.

-// This sample shows how to use the OpenAI SDK to create and use a simple AI agent with any model hosted in Azure AI Foundry.
-// You could use models from Microsoft, OpenAI, DeepSeek, Hugging Face, Meta, xAI or any other model you have deployed in your Azure AI Foundry resource.
+// This sample shows how to use the OpenAI SDK to create and use a simple AI agent with any model hosted in Microsoft Foundry.
+// You could use models from Microsoft, OpenAI, DeepSeek, Hugging Face, Meta, xAI or any other model you have deployed in your Microsoft Foundry resource.
 // Note: Ensure that you pick a model that suits your needs. For example, if you want to use function calling, ensure that the model you pick supports function calling.

 using System.ClientModel;
@@ -15,7 +15,7 @@ var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? th
 var apiKey = Environment.GetEnvironmentVariable("AZURE_OPENAI_API_KEY");
 var model = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "Phi-4-mini-instruct";

-// Since we are using the OpenAI Client SDK, we need to override the default endpoint to point to Azure Foundry.
+// Since we are using the OpenAI Client SDK, we need to override the default endpoint to point to Microsoft Foundry.
 var clientOptions = new OpenAIClientOptions() { Endpoint = new Uri(endpoint) };

 // Create the OpenAI client with either an API key or Azure CLI credential.
@@ -1,8 +1,8 @@
 ## Overview

-This sample shows how to use the OpenAI SDK to create and use a simple AI agent with any model hosted in Azure AI Foundry.
+This sample shows how to use the OpenAI SDK to create and use a simple AI agent with any model hosted in Microsoft Foundry.

-You could use models from Microsoft, OpenAI, DeepSeek, Hugging Face, Meta, xAI or any other model you have deployed in Azure AI Foundry.
+You could use models from Microsoft, OpenAI, DeepSeek, Hugging Face, Meta, xAI or any other model you have deployed in Microsoft Foundry.

 **Note**: Ensure that you pick a model that suits your needs. For example, if you want to use function calling, ensure that the model you pick supports function calling.

@@ -11,19 +11,19 @@ You could use models from Microsoft, OpenAI, DeepSeek, Hugging Face, Meta, xAI o
 Before you begin, ensure you have the following prerequisites:

 - .NET 10 SDK or later
- Azure AI Foundry resource
- A model deployment in your Azure AI Foundry resource. This example defaults to using the `Phi-4-mini-instruct` model,
+- Microsoft Foundry resource
+- A model deployment in your Microsoft Foundry resource. This example defaults to using the `Phi-4-mini-instruct` model,
 so if you want to use a different model, ensure that you set your `AZURE_AI_MODEL_DEPLOYMENT_NAME` environment
 variable to the name of your deployed model.
- An API key or role based authentication to access the Azure AI Foundry resource
+- An API key or role based authentication to access the Microsoft Foundry resource

 See [here](https://learn.microsoft.com/en-us/azure/ai-foundry/quickstarts/get-started-code?tabs=csharp) for more info on setting up these prerequisites

 Set the following environment variables:

 ```powershell
-# Replace with your Azure AI Foundry resource endpoint
-# Ensure that you have the "/openai/v1/" path in the URL, since this is required when using the OpenAI SDK to access Azure Foundry models.
+# Replace with your Microsoft Foundry resource endpoint
+# Ensure that you have the "/openai/v1/" path in the URL, since this is required when using the OpenAI SDK to access Microsoft Foundry models.
 $env:AZURE_OPENAI_ENDPOINT="https://ai-foundry-<myresourcename>.services.ai.azure.com/openai/v1/"

 # Optional, defaults to using Azure CLI for authentication if not provided
@@ -8,7 +8,7 @@ using Microsoft.Agents.AI;
 using OpenAI.Chat;

 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";

 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
@@ -12,5 +12,5 @@ Set the following environment variables:

 ```powershell
 $env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI resource endpoint
-$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
 ```
@@ -9,7 +9,7 @@ using Microsoft.Extensions.AI;
 using OpenAI.Responses;

 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";

 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
@@ -12,5 +12,5 @@ Set the following environment variables:

 ```powershell
 $env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI resource endpoint
-$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
 ```
@@ -1,41 +0,0 @@
-// Copyright (c) Microsoft. All rights reserved.
-
-// This sample shows how to create and use a simple AI agent with OpenAI Assistants as the backend.
-
-// WARNING: The Assistants API is deprecated and will be shut down.
-// For more information see the OpenAI documentation: https://platform.openai.com/docs/assistants/migration
-
-#pragma warning disable CS0618 // Type or member is obsolete - OpenAI Assistants API is deprecated but still used in this sample
-
-using Microsoft.Agents.AI;
-using OpenAI;
-using OpenAI.Assistants;
-
-var apiKey = Environment.GetEnvironmentVariable("OPENAI_API_KEY") ?? throw new InvalidOperationException("OPENAI_API_KEY is not set.");
-var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-4o-mini";
-
-const string JokerName = "Joker";
-const string JokerInstructions = "You are good at telling jokes.";
-
-// Get a client to create/retrieve server side agents with.
-var assistantClient = new OpenAIClient(apiKey).GetAssistantClient();
-
-// You can create a server side assistant with the OpenAI SDK.
-var createResult = await assistantClient.CreateAssistantAsync(model, new() { Name = JokerName, Instructions = JokerInstructions });
-
-// You can retrieve an already created server side assistant as an AIAgent.
-AIAgent agent1 = await assistantClient.GetAIAgentAsync(createResult.Value.Id);
-
-// You can also create a server side assistant and return it as an AIAgent directly.
-AIAgent agent2 = await assistantClient.CreateAIAgentAsync(
-    model: model,
-    name: JokerName,
-    instructions: JokerInstructions);
-
-// You can invoke the agent like any other AIAgent.
-AgentSession session = await agent1.CreateSessionAsync();
-Console.WriteLine(await agent1.RunAsync("Tell me a joke about a pirate.", session));
-
-// Cleanup for sample purposes.
-await assistantClient.DeleteAssistantAsync(agent1.Id);
-await assistantClient.DeleteAssistantAsync(agent2.Id);
@@ -1,16 +0,0 @@
-# Prerequisites
-
-WARNING: The Assistants API is deprecated and will be shut down.
-For more information see the OpenAI documentation: https://platform.openai.com/docs/assistants/migration
-
-Before you begin, ensure you have the following prerequisites:
-
- .NET 10 SDK or later
- OpenAI API key
-
-Set the following environment variables:
-
-```powershell
-$env:OPENAI_API_KEY="*****" # Replace with your OpenAI API key
-$env:OPENAI_CHAT_MODEL_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
-```
@@ -8,7 +8,7 @@ using OpenAI;
 using OpenAI.Chat;

 var apiKey = Environment.GetEnvironmentVariable("OPENAI_API_KEY") ?? throw new InvalidOperationException("OPENAI_API_KEY is not set.");
-var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-4o-mini";
+var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-5.4-mini";

 AIAgent agent = new OpenAIClient(
    apiKey)
@@ -9,5 +9,5 @@ Set the following environment variables:

 ```powershell
 $env:OPENAI_API_KEY="*****" # Replace with your OpenAI api key
-$env:OPENAI_CHAT_MODEL_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+$env:OPENAI_CHAT_MODEL_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
 ```
@@ -7,7 +7,7 @@ using OpenAI;
 using OpenAI.Responses;

 var apiKey = Environment.GetEnvironmentVariable("OPENAI_API_KEY") ?? throw new InvalidOperationException("OPENAI_API_KEY is not set.");
-var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-4o-mini";
+var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-5.4-mini";

 AIAgent agent = new OpenAIClient(
    apiKey)
@@ -9,5 +9,5 @@ Set the following environment variables:

 ```powershell
 $env:OPENAI_API_KEY="*****" # Replace with your OpenAI api key
-$env:OPENAI_CHAT_MODEL_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+$env:OPENAI_CHAT_MODEL_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
 ```
@@ -18,14 +18,13 @@ See the README.md for each sample for the prerequisites for that sample.
 |[Creating an AIAgent with Anthropic](./Agent_With_Anthropic/)|This sample demonstrates how to create an AIAgent using Anthropic Claude models as the underlying inference service|
 |[Creating an AIAgent with Foundry Agents using Azure.AI.Agents.Persistent](./Agent_With_AzureAIAgentsPersistent/)|This sample demonstrates how to create a Foundry Persistent agent and expose it as an AIAgent using the Azure.AI.Agents.Persistent SDK|
 |[Creating an AIAgent with Foundry Agents using Azure.AI.Project](./Agent_With_AzureAIProject/)|This sample demonstrates how to create an Foundry Project agent and expose it as an AIAgent using the Azure.AI.Project SDK|
-|[Creating an AIAgent with AzureFoundry Model](./Agent_With_AzureFoundryModel/)|This sample demonstrates how to use any model deployed to Azure Foundry to create an AIAgent|
+|[Creating an AIAgent with Foundry Model](./Agent_With_AzureFoundryModel/)|This sample demonstrates how to use any model deployed to Microsoft Foundry to create an AIAgent|
 |[Creating an AIAgent with Azure OpenAI ChatCompletion](./Agent_With_AzureOpenAIChatCompletion/)|This sample demonstrates how to create an AIAgent using Azure OpenAI ChatCompletion as the underlying inference service|
 |[Creating an AIAgent with Azure OpenAI Responses](./Agent_With_AzureOpenAIResponses/)|This sample demonstrates how to create an AIAgent using Azure OpenAI Responses as the underlying inference service|
 |[Creating an AIAgent with a custom implementation](./Agent_With_CustomImplementation/)|This sample demonstrates how to create an AIAgent with a custom implementation|
 |[Creating an AIAgent with GitHub Copilot](./Agent_With_GitHubCopilot/)|This sample demonstrates how to create an AIAgent using GitHub Copilot SDK as the underlying inference service|
 |[Creating an AIAgent with Ollama](./Agent_With_Ollama/)|This sample demonstrates how to create an AIAgent using Ollama as the underlying inference service|
 |[Creating an AIAgent with ONNX](./Agent_With_ONNX/)|This sample demonstrates how to create an AIAgent using ONNX as the underlying inference service|
-|[Creating an AIAgent with OpenAI Assistants](./Agent_With_OpenAIAssistants/)|This sample demonstrates how to create an AIAgent using OpenAI Assistants as the underlying inference service.</br>WARNING: The Assistants API is deprecated and will be shut down. For more information see the OpenAI documentation: https://platform.openai.com/docs/assistants/migration|
 |[Creating an AIAgent with OpenAI ChatCompletion](./Agent_With_OpenAIChatCompletion/)|This sample demonstrates how to create an AIAgent using OpenAI ChatCompletion as the underlying inference service|
 |[Creating an AIAgent with OpenAI Responses](./Agent_With_OpenAIResponses/)|This sample demonstrates how to create an AIAgent using OpenAI Responses as the underlying inference service|

@@ -16,7 +16,7 @@ using OpenAI.Responses;

 // --- Configuration ---
 string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";

 // --- Skills Provider ---
 // Discovers skills from the 'skills' directory containing SKILL.md files.
@@ -6,7 +6,7 @@ This sample demonstrates how to use **file-based Agent Skills** with a `ChatClie

 - Discovering skills from `SKILL.md` files on disk via `AgentFileSkillsSource`
 - The progressive disclosure pattern: advertise → load → read resources → run scripts
- Using the `AgentSkillsProvider` constructor with a skill directory path and script executor
+- Using the `AgentSkillsProvider` constructor with a skill directory path and script runner
 - Running file-based scripts (Python) via a subprocess-based executor

 ## Skills Included
@@ -30,7 +30,7 @@ Converts between common units (miles↔km, pounds↔kg) using a multiplication f

 ```bash
 export AZURE_OPENAI_ENDPOINT="https://your-endpoint.openai.azure.com/"
-export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"
+export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"
 ```

 ### Run
@@ -16,7 +16,7 @@ using OpenAI.Responses;

 // --- Configuration ---
 string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";

 // --- Build the code-defined skill ---
 var unitConverterSkill = new AgentInlineSkill(
@@ -31,7 +31,7 @@ Converts between common units using multiplication factors. Defined entirely in

 ```bash
 export AZURE_OPENAI_ENDPOINT="https://your-endpoint.openai.azure.com/"
-export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"
+export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"
 ```

 ### Run
@@ -6,8 +6,14 @@

    <Nullable>enable</Nullable>
    <ImplicitUsings>enable</ImplicitUsings>
+    <NoWarn>$(NoWarn);MAAI001;IDE0051</NoWarn>
  </PropertyGroup>

+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+  </ItemGroup>
+
  <ItemGroup>
    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
  </ItemGroup>
@@ -0,0 +1,111 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates how to define Agent Skills as C# classes using AgentClassSkill
+// with attributes for automatic script and resource discovery.
+
+using System.ComponentModel;
+using System.Text.Json;
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using OpenAI.Responses;
+
+// --- Configuration ---
+string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+
+// --- Class-Based Skill ---
+// Instantiate the skill class.
+var unitConverter = new UnitConverterSkill();
+
+// --- Skills Provider ---
+var skillsProvider = new AgentSkillsProvider(unitConverter);
+
+// --- Agent Setup ---
+AIAgent agent = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential())
+    .GetResponsesClient()
+    .AsAIAgent(new ChatClientAgentOptions
+    {
+        Name = "UnitConverterAgent",
+        ChatOptions = new()
+        {
+            Instructions = "You are a helpful assistant that can convert units.",
+        },
+        AIContextProviders = [skillsProvider],
+    },
+    model: deploymentName);
+
+// --- Example: Unit conversion ---
+Console.WriteLine("Converting units with class-based skills");
+Console.WriteLine(new string('-', 60));
+
+AgentResponse response = await agent.RunAsync(
+    "How many kilometers is a marathon (26.2 miles)? And how many pounds is 75 kilograms?");
+
+Console.WriteLine($"Agent: {response.Text}");
+
+/// <summary>
+/// A unit-converter skill defined as a C# class using attributes for discovery.
+/// </summary>
+/// <remarks>
+/// Properties annotated with <see cref="AgentSkillResourceAttribute"/> are automatically
+/// discovered as skill resources, and methods annotated with <see cref="AgentSkillScriptAttribute"/>
+/// are automatically discovered as skill scripts. Alternatively,
+/// <see cref="AgentSkill.Resources"/> and <see cref="AgentSkill.Scripts"/> can be overridden.
+/// </remarks>
+internal sealed class UnitConverterSkill : AgentClassSkill<UnitConverterSkill>
+{
+    /// <inheritdoc/>
+    public override AgentSkillFrontmatter Frontmatter { get; } = new(
+        "unit-converter",
+        "Convert between common units using a multiplication factor. Use when asked to convert miles, kilometers, pounds, or kilograms.");
+
+    /// <inheritdoc/>
+    protected override string Instructions => """
+        Use this skill when the user asks to convert between units.
+
+        1. Review the conversion-table resource to find the factor for the requested conversion.
+        2. Use the convert script, passing the value and factor from the table.
+        3. Present the result clearly with both units.
+        """;
+
+    /// <summary>
+    /// Gets the <see cref="JsonSerializerOptions"/> used to marshal parameters and return values
+    /// for scripts and resources.
+    /// </summary>
+    /// <remarks>
+    /// This override is not necessary for this sample, but can be used to provide custom
+    /// serialization options, for example a source-generated <c>JsonTypeInfoResolver</c>
+    /// for Native AOT compatibility.
+    /// </remarks>
+    protected override JsonSerializerOptions? SerializerOptions => null;
+
+    /// <summary>
+    /// A conversion table resource providing multiplication factors.
+    /// </summary>
+    [AgentSkillResource("conversion-table")]
+    [Description("Lookup table of multiplication factors for common unit conversions.")]
+    public string ConversionTable => """
+        # Conversion Tables
+
+        Formula: **result = value × factor**
+
+        | From        | To          | Factor   |
+        |-------------|-------------|----------|
+        | miles       | kilometers  | 1.60934  |
+        | kilometers  | miles       | 0.621371 |
+        | pounds      | kilograms   | 0.453592 |
+        | kilograms   | pounds      | 2.20462  |
+        """;
+
+    /// <summary>
+    /// Converts a value by the given factor.
+    /// </summary>
+    [AgentSkillScript("convert")]
+    [Description("Multiplies a value by a conversion factor and returns the result as JSON.")]
+    private static string ConvertUnits(double value, double factor)
+    {
+        double result = Math.Round(value * factor, 4);
+        return JsonSerializer.Serialize(new { value, factor, result });
+    }
+}
@@ -0,0 +1,53 @@
+# Class-Based Agent Skills Sample
+
+This sample demonstrates how to define **Agent Skills as C# classes** using `AgentClassSkill`
+with **attributes** for automatic script and resource discovery.
+
+## What it demonstrates
+
+- Creating skills as classes that extend `AgentClassSkill`
+- Using `[AgentSkillResource]` on properties to define resources
+- Using `[AgentSkillScript]` on methods to define scripts
+- Automatic discovery (no need to override `Resources`/`Scripts`)
+- Using the `AgentSkillsProvider` constructor with class-based skills
+- Overriding `SerializerOptions` for Native AOT compatibility
+
+## Skills Included
+
+### unit-converter (class-based)
+
+A `UnitConverterSkill` class that converts between common units. Defined in `Program.cs`:
+
+- `conversion-table` — Static resource with factor table
+- `convert` — Script that performs `value × factor` conversion
+
+## Running the Sample
+
+### Prerequisites
+
+- .NET 10.0 SDK
+- Azure OpenAI endpoint with a deployed model
+
+### Setup
+
+```bash
+export AZURE_OPENAI_ENDPOINT="https://your-endpoint.openai.azure.com/"
+export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"
+```
+
+### Run
+
+```bash
+dotnet run
+```
+
+### Expected Output
+
+```
+Converting units with class-based skills
+------------------------------------------------------------
+Agent: Here are your conversions:
+
+1. **26.2 miles → 42.16 km** (a marathon distance)
+2. **75 kg → 165.35 lbs**
+```
@@ -0,0 +1,32 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFrameworks>net10.0</TargetFrameworks>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <NoWarn>$(NoWarn);MAAI001;IDE0051</NoWarn>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <Compile Include="..\SubprocessScriptRunner.cs" Link="SubprocessScriptRunner.cs" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
+  </ItemGroup>
+
+  <!-- Copy skills directory to output -->
+  <ItemGroup>
+    <None Include="skills\**\*.*">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+    </None>
+  </ItemGroup>
+
+</Project>
@@ -0,0 +1,150 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates an advanced scenario: combining multiple skill types in a single agent
+// using AgentSkillsProviderBuilder. The builder is designed for cases where the simple
+// AgentSkillsProvider constructors are insufficient — for example, when you need to mix skill
+// sources, apply filtering, or configure cross-cutting options in one place.
+//
+// Three different skill sources are registered here:
+// 1. File-based: unit-converter (miles↔km, pounds↔kg) from SKILL.md on disk
+// 2. Code-defined: volume-converter (gallons↔liters) using AgentInlineSkill
+// 3. Class-based: temperature-converter (°F↔°C↔K) using AgentClassSkill with attributes
+//
+// For simpler, single-source scenarios, see the earlier steps in this sample series
+// (e.g., Step01 for file-based, Step02 for code-defined, Step03 for class-based).
+
+using System.ComponentModel;
+using System.Text.Json;
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using OpenAI.Responses;
+
+// --- Configuration ---
+string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")
+    ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+
+// --- 1. Code-Defined Skill: volume-converter ---
+var volumeConverterSkill = new AgentInlineSkill(
+    name: "volume-converter",
+    description: "Convert between gallons and liters using a multiplication factor.",
+    instructions: """
+        Use this skill when the user asks to convert between gallons and liters.
+
+        1. Review the volume-conversion-table resource to find the correct factor.
+        2. Use the convert-volume script, passing the value and factor.
+        """)
+    .AddResource("volume-conversion-table",
+        """
+        # Volume Conversion Table
+
+        Formula: **result = value × factor**
+
+        | From    | To      | Factor  |
+        |---------|---------|---------|
+        | gallons | liters  | 3.78541 |
+        | liters  | gallons | 0.264172|
+        """)
+    .AddScript("convert-volume", (double value, double factor) =>
+    {
+        double result = Math.Round(value * factor, 4);
+        return JsonSerializer.Serialize(new { value, factor, result });
+    });
+
+// --- 2. Class-Based Skill: temperature-converter ---
+var temperatureConverter = new TemperatureConverterSkill();
+
+// --- 3. Build provider combining all three source types ---
+var skillsProvider = new AgentSkillsProviderBuilder()
+    .UseFileSkill(Path.Combine(AppContext.BaseDirectory, "skills"))    // File-based: unit-converter
+    .UseSkill(volumeConverterSkill)                                    // Code-defined: volume-converter
+    .UseSkill(temperatureConverter)                                     // Class-based: temperature-converter
+    .UseFileScriptRunner(SubprocessScriptRunner.RunAsync)
+    .Build();
+
+// --- Agent Setup ---
+AIAgent agent = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential())
+    .GetResponsesClient()
+    .AsAIAgent(new ChatClientAgentOptions
+    {
+        Name = "MultiConverterAgent",
+        ChatOptions = new()
+        {
+            Instructions = "You are a helpful assistant that can convert units, volumes, and temperatures.",
+        },
+        AIContextProviders = [skillsProvider],
+    },
+    model: deploymentName);
+
+// --- Example: Use all three skills ---
+Console.WriteLine("Converting with mixed skills (file + code + class)");
+Console.WriteLine(new string('-', 60));
+
+AgentResponse response = await agent.RunAsync(
+    "I need three conversions: " +
+    "1) How many kilometers is a marathon (26.2 miles)? " +
+    "2) How many liters is a 5-gallon bucket? " +
+    "3) What is 98.6°F in Celsius?");
+
+Console.WriteLine($"Agent: {response.Text}");
+
+/// <summary>
+/// A temperature-converter skill defined as a C# class using attributes for discovery.
+/// </summary>
+/// <remarks>
+/// Properties annotated with <see cref="AgentSkillResourceAttribute"/> are automatically
+/// discovered as skill resources, and methods annotated with <see cref="AgentSkillScriptAttribute"/>
+/// are automatically discovered as skill scripts.
+/// </remarks>
+internal sealed class TemperatureConverterSkill : AgentClassSkill<TemperatureConverterSkill>
+{
+    /// <inheritdoc/>
+    public override AgentSkillFrontmatter Frontmatter { get; } = new(
+        "temperature-converter",
+        "Convert between temperature scales (Fahrenheit, Celsius, Kelvin).");
+
+    /// <inheritdoc/>
+    protected override string Instructions => """
+        Use this skill when the user asks to convert temperatures.
+
+        1. Review the temperature-conversion-formulas resource for the correct formula.
+        2. Use the convert-temperature script, passing the value, source scale, and target scale.
+        3. Present the result clearly with both temperature scales.
+        """;
+
+    /// <summary>
+    /// A reference table of temperature conversion formulas.
+    /// </summary>
+    [AgentSkillResource("temperature-conversion-formulas")]
+    [Description("Formulas for converting between Fahrenheit, Celsius, and Kelvin.")]
+    public string ConversionFormulas => """
+        # Temperature Conversion Formulas
+
+        | From        | To          | Formula                   |
+        |-------------|-------------|---------------------------|
+        | Fahrenheit  | Celsius     | °C = (°F − 32) × 5/9     |
+        | Celsius     | Fahrenheit  | °F = (°C × 9/5) + 32     |
+        | Celsius     | Kelvin      | K = °C + 273.15           |
+        | Kelvin      | Celsius     | °C = K − 273.15           |
+        """;
+
+    /// <summary>
+    /// Converts a temperature value between scales.
+    /// </summary>
+    [AgentSkillScript("convert-temperature")]
+    [Description("Converts a temperature value from one scale to another.")]
+    private static string ConvertTemperature(double value, string from, string to)
+    {
+        double result = (from.ToUpperInvariant(), to.ToUpperInvariant()) switch
+        {
+            ("FAHRENHEIT", "CELSIUS") => Math.Round((value - 32) * 5.0 / 9.0, 2),
+            ("CELSIUS", "FAHRENHEIT") => Math.Round(value * 9.0 / 5.0 + 32, 2),
+            ("CELSIUS", "KELVIN") => Math.Round(value + 273.15, 2),
+            ("KELVIN", "CELSIUS") => Math.Round(value - 273.15, 2),
+            _ => throw new ArgumentException($"Unsupported conversion: {from} → {to}")
+        };
+
+        return JsonSerializer.Serialize(new { value, from, to, result });
+    }
+}
@@ -0,0 +1,67 @@
+# Mixed Agent Skills Sample (Advanced)
+
+This sample demonstrates an **advanced scenario**: combining multiple skill types in a single agent using `AgentSkillsProviderBuilder`.
+
+> **Tip:** For simpler, single-source scenarios, use the `AgentSkillsProvider` constructors directly — see [Step01](../Agent_Step01_FileBasedSkills/) (file-based), [Step02](../Agent_Step02_CodeDefinedSkills/) (code-defined), or [Step03](../Agent_Step03_ClassBasedSkills/) (class-based).
+
+## What it demonstrates
+
+- Combining file-based, code-defined, and class-based skills in one provider
+- Using `UseFileSkill` and `UseSkill` on the builder to register different skill types
+- Aggregating skills from all sources into a single provider with automatic deduplication
+
+## When to use `AgentSkillsProviderBuilder`
+
+The builder is intended for advanced scenarios where the simple `AgentSkillsProvider` constructors are insufficient:
+
+| Scenario | Builder method |
+|----------|---------------|
+| **Mixed skill types** — combine file-based, code-defined, and class-based skills | `UseFileSkill` + `UseSkill` / `UseSkills` |
+| **Multiple file script runners** — use different script runners for different file skill directories | `UseFileSkill` / `UseFileSkills` with per-source `scriptRunner` |
+| **Skill filtering** — include/exclude skills using a predicate | `UseFilter(predicate)` |
+
+## Skills Included
+
+### unit-converter (file-based)
+
+Discovered from `skills/unit-converter/SKILL.md` on disk. Converts miles↔km, pounds↔kg.
+
+### volume-converter (code-defined)
+
+Defined as `AgentInlineSkill` in `Program.cs`. Converts gallons↔liters.
+
+### temperature-converter (class-based)
+
+Defined as `TemperatureConverterSkill` class in `Program.cs`. Converts °F↔°C↔K.
+
+## Running the Sample
+
+### Prerequisites
+
+- .NET 10.0 SDK
+- Azure OpenAI endpoint with a deployed model
+
+### Setup
+
+```bash
+export AZURE_OPENAI_ENDPOINT="https://your-endpoint.openai.azure.com/"
+export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"
+```
+
+### Run
+
+```bash
+dotnet run
+```
+
+### Expected Output
+
+```
+Converting with mixed skills (file + code + class)
+------------------------------------------------------------
+Agent: Here are your conversions:
+
+1. **26.2 miles → 42.16 km** (a marathon distance)
+2. **5 gallons → 18.93 liters**
+3. **98.6°F → 37.0°C**
+```
@@ -0,0 +1,11 @@
+---
+name: unit-converter
+description: Convert between common units using a multiplication factor. Use when asked to convert miles, kilometers, pounds, or kilograms.
+---
+
+## Usage
+
+When the user requests a unit conversion:
+1. First, review `references/unit-conversion-table.md` to find the correct factor
+2. Run the `scripts/convert-units.py` script with `--value <number> --factor <factor>` (e.g. `--value 26.2 --factor 1.60934`)
+3. Present the converted value clearly with both units
@@ -0,0 +1,10 @@
+# Conversion Tables
+
+Formula: **result = value × factor**
+
+| From        | To          | Factor   |
+|-------------|-------------|----------|
+| miles       | kilometers  | 1.60934  |
+| kilometers  | miles       | 0.621371 |
+| pounds      | kilograms   | 0.453592 |
+| kilograms   | pounds      | 2.20462  |
@@ -0,0 +1,29 @@
+# Unit conversion script
+# Converts a value using a multiplication factor: result = value × factor
+#
+# Usage:
+#   python scripts/convert-units.py --value 26.2 --factor 1.60934
+#   python scripts/convert-units.py --value 75 --factor 2.20462
+
+import argparse
+import json
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(
+        description="Convert a value using a multiplication factor.",
+        epilog="Examples:\n"
+        "  python scripts/convert-units.py --value 26.2 --factor 1.60934\n"
+        "  python scripts/convert-units.py --value 75 --factor 2.20462",
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+    )
+    parser.add_argument("--value", type=float, required=True, help="The numeric value to convert.")
+    parser.add_argument("--factor", type=float, required=True, help="The conversion factor from the table.")
+    args = parser.parse_args()
+
+    result = round(args.value * args.factor, 4)
+    print(json.dumps({"value": args.value, "factor": args.factor, "result": result}))
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,22 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFrameworks>net10.0</TargetFrameworks>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <NoWarn>$(NoWarn);MAAI001;CA1812;IDE0051</NoWarn>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Extensions.DependencyInjection" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
+  </ItemGroup>
+
+</Project>
@@ -0,0 +1,210 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates how to use Dependency Injection (DI) with Agent Skills.
+// It shows two approaches side-by-side, each handling a different conversion domain:
+//
+// 1. Code-defined skill (AgentInlineSkill) — converts distances (miles ↔ kilometers).
+//    Resources and scripts are inline delegates that resolve services from IServiceProvider.
+//
+// 2. Class-based skill (AgentClassSkill) — converts weights (pounds ↔ kilograms).
+//    Resources and scripts are encapsulated in a class, also resolving services from IServiceProvider.
+//
+// Both skills share the same ConversionService registered in the DI container,
+// showing that DI works identically regardless of how the skill is defined.
+// When prompted with a question spanning both domains, the agent uses both skills.
+
+using System.ComponentModel;
+using System.Text.Json;
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Extensions.DependencyInjection;
+using OpenAI.Responses;
+
+// --- Configuration ---
+string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+
+// --- DI Container ---
+// Register application services that skill resources and scripts can resolve at execution time.
+ServiceCollection services = new();
+services.AddSingleton<ConversionService>();
+
+IServiceProvider serviceProvider = services.BuildServiceProvider();
+
+// =====================================================================
+// Approach 1: Code-Defined Skill with DI (AgentInlineSkill)
+// =====================================================================
+// Handles distance conversions (miles ↔ kilometers).
+// Resources and scripts are inline delegates. Each delegate can declare
+// an IServiceProvider parameter that the framework injects automatically.
+
+var distanceSkill = new AgentInlineSkill(
+    name: "distance-converter",
+    description: "Convert between distance units. Use when asked to convert miles to kilometers or kilometers to miles.",
+    instructions: """
+        Use this skill when the user asks to convert between distance units (miles and kilometers).
+
+        1. Review the distance-table resource to find the factor for the requested conversion.
+        2. Use the convert script, passing the value and factor from the table.
+        """)
+    .AddResource("distance-table", (IServiceProvider serviceProvider) =>
+    {
+        var service = serviceProvider.GetRequiredService<ConversionService>();
+        return service.GetDistanceTable();
+    })
+    .AddScript("convert", (double value, double factor, IServiceProvider serviceProvider) =>
+    {
+        var service = serviceProvider.GetRequiredService<ConversionService>();
+        return service.Convert(value, factor);
+    });
+
+// =====================================================================
+// Approach 2: Class-Based Skill with DI (AgentClassSkill)
+// =====================================================================
+// Handles weight conversions (pounds ↔ kilograms).
+// Resources and scripts are discovered via reflection using attributes.
+// Methods with an IServiceProvider parameter receive DI automatically.
+//
+// Alternatively, class-based skills can accept dependencies through their
+// constructor. Register the skill class itself in the ServiceCollection and
+// resolve it from the container:
+//
+//   services.AddSingleton<WeightConverterSkill>();
+//   var weightSkill = serviceProvider.GetRequiredService<WeightConverterSkill>();
+
+var weightSkill = new WeightConverterSkill();
+
+// --- Skills Provider ---
+// Both skills are registered with the same provider so the agent can use either one.
+var skillsProvider = new AgentSkillsProvider(distanceSkill, weightSkill);
+
+// --- Agent Setup ---
+AIAgent agent = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential())
+    .GetResponsesClient()
+    .AsAIAgent(
+        options: new ChatClientAgentOptions
+        {
+            Name = "UnitConverterAgent",
+            ChatOptions = new()
+            {
+                Instructions = "You are a helpful assistant that can convert units.",
+            },
+            AIContextProviders = [skillsProvider],
+        },
+        model: deploymentName,
+        services: serviceProvider);
+
+// --- Example: Unit conversion ---
+// This prompt spans both domains, so the agent will use both skills.
+Console.WriteLine("Converting units with DI-powered skills");
+Console.WriteLine(new string('-', 60));
+
+AgentResponse response = await agent.RunAsync(
+    "How many kilometers is a marathon (26.2 miles)? And how many pounds is 75 kilograms?");
+
+Console.WriteLine($"Agent: {response.Text}");
+
+// ---------------------------------------------------------------------------
+// Class-Based Skill
+// ---------------------------------------------------------------------------
+
+/// <summary>
+/// A weight-converter skill defined as a C# class that uses Dependency Injection.
+/// </summary>
+/// <remarks>
+/// This skill resolves <see cref="ConversionService"/> from the DI container
+/// in both its resource and script methods. Methods with an <see cref="IServiceProvider"/>
+/// parameter are automatically injected by the framework. Properties and methods annotated
+/// with <see cref="AgentSkillResourceAttribute"/> and <see cref="AgentSkillScriptAttribute"/>
+/// are automatically discovered via reflection.
+/// </remarks>
+internal sealed class WeightConverterSkill : AgentClassSkill<WeightConverterSkill>
+{
+    /// <inheritdoc/>
+    public override AgentSkillFrontmatter Frontmatter { get; } = new(
+        "weight-converter",
+        "Convert between weight units. Use when asked to convert pounds to kilograms or kilograms to pounds.");
+
+    /// <inheritdoc/>
+    protected override string Instructions => """
+        Use this skill when the user asks to convert between weight units (pounds and kilograms).
+
+        1. Review the weight-table resource to find the factor for the requested conversion.
+        2. Use the convert script, passing the value and factor from the table.
+        3. Present the result clearly with both units.
+        """;
+
+    /// <summary>
+    /// Returns the weight conversion table from the DI-registered <see cref="ConversionService"/>.
+    /// </summary>
+    [AgentSkillResource("weight-table")]
+    [Description("Lookup table of multiplication factors for weight conversions.")]
+    private static string GetWeightTable(IServiceProvider serviceProvider)
+    {
+        var service = serviceProvider.GetRequiredService<ConversionService>();
+        return service.GetWeightTable();
+    }
+
+    /// <summary>
+    /// Converts a value by the given factor using the DI-registered <see cref="ConversionService"/>.
+    /// </summary>
+    [AgentSkillScript("convert")]
+    [Description("Multiplies a value by a conversion factor and returns the result as JSON.")]
+    private static string Convert(double value, double factor, IServiceProvider serviceProvider)
+    {
+        var service = serviceProvider.GetRequiredService<ConversionService>();
+        return service.Convert(value, factor);
+    }
+}
+
+// ---------------------------------------------------------------------------
+// Services
+// ---------------------------------------------------------------------------
+
+/// <summary>
+/// Provides conversion rates between units.
+/// In a real application this could call an external API, read from a database,
+/// or apply time-varying exchange rates.
+/// </summary>
+internal sealed class ConversionService
+{
+    /// <summary>
+    /// Returns a markdown table of supported distance conversions.
+    /// </summary>
+    public string GetDistanceTable() =>
+        """
+        # Distance Conversions
+
+        Formula: **result = value × factor**
+
+        | From        | To          | Factor   |
+        |-------------|-------------|----------|
+        | miles       | kilometers  | 1.60934  |
+        | kilometers  | miles       | 0.621371 |
+        """;
+
+    /// <summary>
+    /// Returns a markdown table of supported weight conversions.
+    /// </summary>
+    public string GetWeightTable() =>
+        """
+        # Weight Conversions
+
+        Formula: **result = value × factor**
+
+        | From        | To          | Factor   |
+        |-------------|-------------|----------|
+        | pounds      | kilograms   | 0.453592 |
+        | kilograms   | pounds      | 2.20462  |
+        """;
+
+    /// <summary>
+    /// Converts a value by the given factor and returns a JSON result.
+    /// </summary>
+    public string Convert(double value, double factor)
+    {
+        double result = Math.Round(value * factor, 4);
+        return JsonSerializer.Serialize(new { value, factor, result });
+    }
+}
@@ -0,0 +1,65 @@
+# Agent Skills with Dependency Injection
+
+This sample demonstrates how to use **Dependency Injection (DI)** with Agent Skills. It shows two approaches side-by-side, each handling a different conversion domain:
+
+1. **Code-defined skill** (`AgentInlineSkill`) — converts **distances** (miles ↔ kilometers)
+2. **Class-based skill** (`AgentClassSkill`) — converts **weights** (pounds ↔ kilograms)
+
+Both skills resolve the same `ConversionService` from the DI container. When prompted with a question spanning both domains, the agent uses both skills.
+
+## What It Shows
+
+- Registering application services in a `ServiceCollection`
+- Defining a **code-defined** skill (distance converter) with resources and scripts that resolve services from `IServiceProvider`
+- Defining a **class-based** skill (weight converter) with resources and scripts that resolve services from `IServiceProvider`
+- Passing the built `IServiceProvider` to the agent so skills can access DI services at execution time
+- Running a single prompt that exercises both skills to show they work together
+
+## How It Works
+
+1. A `ConversionService` is registered as a singleton in the DI container
+2. **Code-defined skill**: An `AgentInlineSkill` for distance conversions declares `IServiceProvider` as a parameter in its `AddResource` and `AddScript` delegates — the framework injects it automatically
+3. **Class-based skill**: A `WeightConverterSkill` class extends `AgentClassSkill` for weight conversions and uses `CreateResource`/`CreateScript` factory methods with `IServiceProvider` parameters
+4. Both skills resolve `ConversionService` from the provider — one for distance tables, the other for weight tables
+5. A single agent is created with both skills registered, and the service provider flows through to skill execution
+
+> **Tip:** Class-based skills can also accept dependencies through their **constructor**. Register the skill class in the `ServiceCollection` and resolve it from the container instead of calling `new` directly. This is useful when the skill itself needs injected services beyond what the resource/script delegates use.
+
+## How It Differs from Other Samples
+
+| Sample | Skill Type | DI Support |
+|--------|------------|------------|
+| [Step02](../Agent_Step02_CodeDefinedSkills/) | Code-defined (`AgentInlineSkill`) | No — static resources |
+| [Step03](../Agent_Step03_ClassBasedSkills/) | Class-based (`AgentClassSkill`) | No — static resources |
+| **Step05 (this)** | **Both code-defined and class-based** | **Yes — DI via `IServiceProvider`** |
+
+## Prerequisites
+
+- .NET 10
+- An Azure OpenAI deployment
+
+## Configuration
+
+Set the following environment variables:
+
+| Variable | Description |
+|---|---|
+| `AZURE_OPENAI_ENDPOINT` | Your Azure OpenAI endpoint URL |
+| `AZURE_OPENAI_DEPLOYMENT_NAME` | Model deployment name (defaults to `gpt-5.4-mini`) |
+
+## Running the Sample
+
+```bash
+dotnet run
+```
+
+### Expected Output
+
+```
+Converting units with DI-powered skills
+------------------------------------------------------------
+Agent: Here are your conversions:
+
+1. **26.2 miles → 42.16 km** (a marathon distance)
+2. **75 kg → 165.35 lbs**
+```
@@ -6,19 +6,32 @@ Samples demonstrating Agent Skills capabilities. Each sample shows a different w
 |--------|-------------|
 | [Agent_Step01_FileBasedSkills](Agent_Step01_FileBasedSkills/) | Define skills as `SKILL.md` files on disk with reference documents. Uses a unit-converter skill. |
 | [Agent_Step02_CodeDefinedSkills](Agent_Step02_CodeDefinedSkills/) | Define skills entirely in C# code using `AgentInlineSkill`, with static/dynamic resources and scripts. |
+| [Agent_Step03_ClassBasedSkills](Agent_Step03_ClassBasedSkills/) | Define skills as C# classes using `AgentClassSkill`. |
+| [Agent_Step04_MixedSkills](Agent_Step04_MixedSkills/) | **(Advanced)** Combine file-based, code-defined, and class-based skills using `AgentSkillsProviderBuilder`. |
+| [Agent_Step05_SkillsWithDI](Agent_Step05_SkillsWithDI/) | Use Dependency Injection with both code-defined (`AgentInlineSkill`) and class-based (`AgentClassSkill`) skills. |

 ## Key Concepts

-### File-Based vs Code-Defined Skills
+### Skill Types

-| Aspect | File-Based | Code-Defined |
-|--------|-----------|--------------|
-| Definition | `SKILL.md` files on disk | `AgentInlineSkill` instances in C# |
-| Resources | All files in skill directory (filtered by extension) | `AddResource` (static value or delegate-backed) |
-| Scripts | Supported via script executor delegate | `AddScript` delegates |
-| Discovery | Automatic from directory path | Explicit via constructor |
-| Dynamic content | No (static files only) | Yes (factory delegates) |
-| Reusability | Copy skill directory | Inline or shared instances |
+| Aspect | File-Based | Code-Defined | Class-Based |
+|--------|-----------|--------------|-------------|
+| Definition | `SKILL.md` files on disk | `AgentInlineSkill` instances in C# | Classes extending `AgentClassSkill` |
+| Resources | All files in skill directory (filtered by extension) | `AddResource` (static value or delegate-backed) | `CreateResource` factory methods |
+| Scripts | Supported via script runner delegate | `AddScript` delegates | `CreateScript` factory methods |
+| Discovery | Automatic from directory path | Explicit via constructor | Explicit via constructor |
+| Dynamic content | No (static files only) | Yes (factory delegates) | Yes (factory delegates) |
+| Sharing pattern | Copy skill directory | Inline or shared instances | Package in shared assemblies/NuGet |
+| DI support | No | Yes (via `IServiceProvider` parameter) | Yes (via `IServiceProvider` parameter) |

-For single-source scenarios, use the `AgentSkillsProvider` constructors directly. To combine multiple skill types, use the `AgentSkillsProviderBuilder`.
+### `AgentSkillsProvider` vs `AgentSkillsProviderBuilder`

+For single-source scenarios, use the `AgentSkillsProvider` constructors directly — they accept a skill directory path, a set of skills, or a custom source.
+
+Use `AgentSkillsProviderBuilder` for advanced scenarios where simple constructors are insufficient:
+
+- **Mixed skill types** — combine file-based, code-defined, and class-based skills in one provider
+- **Multiple file script runners** — use different script runners for different file skill directories
+- **Skill filtering** — include or exclude skills using a predicate
+
+See [Agent_Step04_MixedSkills](Agent_Step04_MixedSkills/) for a working example.
@@ -18,9 +18,9 @@ Before you begin, ensure you have the following prerequisites:

 **Note**: These samples use Anthropic Claude models. For more information, see [Anthropic documentation](https://docs.anthropic.com/).

-## Using Anthropic with Azure Foundry
+## Using Anthropic with Microsoft Foundry

-To use Anthropic with Azure Foundry, you can check the sample [AgentProviders/Agent_With_Anthropic](../AgentProviders/Agent_With_Anthropic/README.md) for more details.
+To use Anthropic with Microsoft Foundry, you can check the sample [AgentProviders/Agent_With_Anthropic](../AgentProviders/Agent_With_Anthropic/README.md) for more details.

 ## Samples

--- a/Show More
+++ b/Show More