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# Directory Structure
```
├── .devcontainer
│ ├── .vscode
│ │ └── settings.json
│ ├── devcontainer.json
│ ├── OPTIMIZING_FOR_CODESPACES.md
│ ├── POST_SETUP_README.md
│ └── README.md
├── .dockerignore
├── .gitattributes
├── .github
│ ├── policheck.yml
│ └── workflows
│ ├── assistants-codespace-assistant.yml
│ ├── assistants-document-assistant.yml
│ ├── assistants-explorer-assistant.yml
│ ├── assistants-guided-conversation-assistant.yml
│ ├── assistants-knowledge-transfer-assistant.yml
│ ├── assistants-navigator-assistant.yml
│ ├── assistants-project-assistant.yml
│ ├── assistants-prospector-assistant.yml
│ ├── assistants-skill-assistant.yml
│ ├── libraries.yml
│ ├── mcp-server-giphy.yml
│ ├── mcp-server-memory-filesystem-edit.yml
│ ├── mcp-server-memory-user-bio.yml
│ ├── mcp-server-memory-whiteboard.yml
│ ├── mcp-server-open-deep-research-clone.yml
│ ├── mcp-server-web-research.yml
│ ├── workbench-app.yml
│ └── workbench-service.yml
├── .gitignore
├── .multi-root-tools
│ ├── Makefile
│ └── README.md
├── .vscode
│ ├── extensions.json
│ ├── launch.json
│ └── settings.json
├── ai_context
│ └── generated
│ ├── ASPIRE_ORCHESTRATOR.md
│ ├── ASSISTANT_CODESPACE.md
│ ├── ASSISTANT_DOCUMENT.md
│ ├── ASSISTANT_NAVIGATOR.md
│ ├── ASSISTANT_PROJECT.md
│ ├── ASSISTANT_PROSPECTOR.md
│ ├── ASSISTANTS_OTHER.md
│ ├── ASSISTANTS_OVERVIEW.md
│ ├── CONFIGURATION.md
│ ├── DOTNET_LIBRARIES.md
│ ├── EXAMPLES.md
│ ├── MCP_SERVERS.md
│ ├── PYTHON_LIBRARIES_AI_CLIENTS.md
│ ├── PYTHON_LIBRARIES_CORE.md
│ ├── PYTHON_LIBRARIES_EXTENSIONS.md
│ ├── PYTHON_LIBRARIES_SKILLS.md
│ ├── PYTHON_LIBRARIES_SPECIALIZED.md
│ ├── TOOLS.md
│ ├── WORKBENCH_FRONTEND.md
│ └── WORKBENCH_SERVICE.md
├── aspire-orchestrator
│ ├── .editorconfig
│ ├── Aspire.AppHost
│ │ ├── .gitignore
│ │ ├── appsettings.json
│ │ ├── Aspire.AppHost.csproj
│ │ ├── Program.cs
│ │ └── Properties
│ │ └── launchSettings.json
│ ├── Aspire.Extensions
│ │ ├── Aspire.Extensions.csproj
│ │ ├── Dashboard.cs
│ │ ├── DockerFileExtensions.cs
│ │ ├── PathNormalizer.cs
│ │ ├── UvAppHostingExtensions.cs
│ │ ├── UvAppResource.cs
│ │ ├── VirtualEnvironment.cs
│ │ └── WorkbenchServiceHostingExtensions.cs
│ ├── Aspire.ServiceDefaults
│ │ ├── Aspire.ServiceDefaults.csproj
│ │ └── Extensions.cs
│ ├── README.md
│ ├── run.sh
│ ├── SemanticWorkbench.Aspire.sln
│ └── SemanticWorkbench.Aspire.sln.DotSettings
├── assistants
│ ├── codespace-assistant
│ │ ├── .claude
│ │ │ └── settings.local.json
│ │ ├── .env.example
│ │ ├── .vscode
│ │ │ ├── extensions.json
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── assistant
│ │ │ ├── __init__.py
│ │ │ ├── assets
│ │ │ │ ├── icon_context_transfer.svg
│ │ │ │ └── icon.svg
│ │ │ ├── chat.py
│ │ │ ├── config.py
│ │ │ ├── helpers.py
│ │ │ ├── response
│ │ │ │ ├── __init__.py
│ │ │ │ ├── completion_handler.py
│ │ │ │ ├── models.py
│ │ │ │ ├── request_builder.py
│ │ │ │ ├── response.py
│ │ │ │ ├── step_handler.py
│ │ │ │ └── utils
│ │ │ │ ├── __init__.py
│ │ │ │ ├── abbreviations.py
│ │ │ │ ├── formatting_utils.py
│ │ │ │ ├── message_utils.py
│ │ │ │ └── openai_utils.py
│ │ │ ├── text_includes
│ │ │ │ ├── card_content_context_transfer.md
│ │ │ │ ├── card_content.md
│ │ │ │ ├── codespace_assistant_info.md
│ │ │ │ ├── context_transfer_assistant_info.md
│ │ │ │ ├── guardrails_prompt.txt
│ │ │ │ ├── guidance_prompt_context_transfer.txt
│ │ │ │ ├── guidance_prompt.txt
│ │ │ │ ├── instruction_prompt_context_transfer.txt
│ │ │ │ └── instruction_prompt.txt
│ │ │ └── whiteboard
│ │ │ ├── __init__.py
│ │ │ ├── _inspector.py
│ │ │ └── _whiteboard.py
│ │ ├── assistant.code-workspace
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── document-assistant
│ │ ├── .env.example
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── assistant
│ │ │ ├── __init__.py
│ │ │ ├── assets
│ │ │ │ └── icon.svg
│ │ │ ├── chat.py
│ │ │ ├── config.py
│ │ │ ├── context_management
│ │ │ │ ├── __init__.py
│ │ │ │ └── inspector.py
│ │ │ ├── filesystem
│ │ │ │ ├── __init__.py
│ │ │ │ ├── _convert.py
│ │ │ │ ├── _file_sources.py
│ │ │ │ ├── _filesystem.py
│ │ │ │ ├── _inspector.py
│ │ │ │ ├── _model.py
│ │ │ │ ├── _prompts.py
│ │ │ │ └── _tasks.py
│ │ │ ├── guidance
│ │ │ │ ├── __init__.py
│ │ │ │ ├── dynamic_ui_inspector.py
│ │ │ │ ├── guidance_config.py
│ │ │ │ ├── guidance_prompts.py
│ │ │ │ └── README.md
│ │ │ ├── response
│ │ │ │ ├── __init__.py
│ │ │ │ ├── completion_handler.py
│ │ │ │ ├── models.py
│ │ │ │ ├── prompts.py
│ │ │ │ ├── responder.py
│ │ │ │ └── utils
│ │ │ │ ├── __init__.py
│ │ │ │ ├── formatting_utils.py
│ │ │ │ ├── message_utils.py
│ │ │ │ ├── openai_utils.py
│ │ │ │ ├── tokens_tiktoken.py
│ │ │ │ └── workbench_messages.py
│ │ │ ├── text_includes
│ │ │ │ └── document_assistant_info.md
│ │ │ ├── types.py
│ │ │ └── whiteboard
│ │ │ ├── __init__.py
│ │ │ ├── _inspector.py
│ │ │ └── _whiteboard.py
│ │ ├── assistant.code-workspace
│ │ ├── CLAUDE.md
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── tests
│ │ │ ├── __init__.py
│ │ │ ├── test_convert.py
│ │ │ └── test_data
│ │ │ ├── blank_image.png
│ │ │ ├── Formatting Test.docx
│ │ │ ├── sample_data.csv
│ │ │ ├── sample_data.xlsx
│ │ │ ├── sample_page.html
│ │ │ ├── sample_presentation.pptx
│ │ │ └── simple_pdf.pdf
│ │ └── uv.lock
│ ├── explorer-assistant
│ │ ├── .env.example
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── assistant
│ │ │ ├── __init__.py
│ │ │ ├── chat.py
│ │ │ ├── config.py
│ │ │ ├── helpers.py
│ │ │ ├── response
│ │ │ │ ├── __init__.py
│ │ │ │ ├── model.py
│ │ │ │ ├── response_anthropic.py
│ │ │ │ ├── response_openai.py
│ │ │ │ └── response.py
│ │ │ └── text_includes
│ │ │ └── guardrails_prompt.txt
│ │ ├── assistant.code-workspace
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── guided-conversation-assistant
│ │ ├── .env.example
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── assistant
│ │ │ ├── __init__.py
│ │ │ ├── agents
│ │ │ │ ├── guided_conversation
│ │ │ │ │ ├── config.py
│ │ │ │ │ ├── definition.py
│ │ │ │ │ └── definitions
│ │ │ │ │ ├── er_triage.py
│ │ │ │ │ ├── interview.py
│ │ │ │ │ ├── patient_intake.py
│ │ │ │ │ └── poem_feedback.py
│ │ │ │ └── guided_conversation_agent.py
│ │ │ ├── chat.py
│ │ │ ├── config.py
│ │ │ └── text_includes
│ │ │ └── guardrails_prompt.txt
│ │ ├── assistant.code-workspace
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── knowledge-transfer-assistant
│ │ ├── .claude
│ │ │ └── settings.local.json
│ │ ├── .env.example
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── assistant
│ │ │ ├── __init__.py
│ │ │ ├── agentic
│ │ │ │ ├── __init__.py
│ │ │ │ ├── analysis.py
│ │ │ │ ├── coordinator_support.py
│ │ │ │ └── team_welcome.py
│ │ │ ├── assets
│ │ │ │ ├── icon-knowledge-transfer.svg
│ │ │ │ └── icon.svg
│ │ │ ├── assistant.py
│ │ │ ├── common.py
│ │ │ ├── config.py
│ │ │ ├── conversation_clients.py
│ │ │ ├── conversation_share_link.py
│ │ │ ├── data.py
│ │ │ ├── domain
│ │ │ │ ├── __init__.py
│ │ │ │ ├── audience_manager.py
│ │ │ │ ├── information_request_manager.py
│ │ │ │ ├── knowledge_brief_manager.py
│ │ │ │ ├── knowledge_digest_manager.py
│ │ │ │ ├── learning_objectives_manager.py
│ │ │ │ └── share_manager.py
│ │ │ ├── files.py
│ │ │ ├── logging.py
│ │ │ ├── notifications.py
│ │ │ ├── respond.py
│ │ │ ├── storage_models.py
│ │ │ ├── storage.py
│ │ │ ├── string_utils.py
│ │ │ ├── text_includes
│ │ │ │ ├── assistant_info.md
│ │ │ │ ├── card_content.md
│ │ │ │ ├── coordinator_instructions.txt
│ │ │ │ ├── coordinator_role.txt
│ │ │ │ ├── knowledge_digest_instructions.txt
│ │ │ │ ├── knowledge_digest_prompt.txt
│ │ │ │ ├── share_information_request_detection.txt
│ │ │ │ ├── team_instructions.txt
│ │ │ │ ├── team_role.txt
│ │ │ │ └── welcome_message_generation.txt
│ │ │ ├── tools
│ │ │ │ ├── __init__.py
│ │ │ │ ├── base.py
│ │ │ │ ├── information_requests.py
│ │ │ │ ├── learning_objectives.py
│ │ │ │ ├── learning_outcomes.py
│ │ │ │ ├── progress_tracking.py
│ │ │ │ └── share_setup.py
│ │ │ ├── ui_tabs
│ │ │ │ ├── __init__.py
│ │ │ │ ├── brief.py
│ │ │ │ ├── common.py
│ │ │ │ ├── debug.py
│ │ │ │ ├── learning.py
│ │ │ │ └── sharing.py
│ │ │ └── utils.py
│ │ ├── CLAUDE.md
│ │ ├── docs
│ │ │ ├── design
│ │ │ │ ├── actions.md
│ │ │ │ └── inference.md
│ │ │ ├── DEV_GUIDE.md
│ │ │ ├── how-kta-works.md
│ │ │ ├── JTBD.md
│ │ │ ├── knowledge-transfer-goals.md
│ │ │ ├── learning_assistance.md
│ │ │ ├── notable_claude_conversations
│ │ │ │ ├── clarifying_quad_modal_design.md
│ │ │ │ ├── CLAUDE_PROMPTS.md
│ │ │ │ ├── transfer_state.md
│ │ │ │ └── trying_the_context_agent.md
│ │ │ └── opportunities-of-knowledge-transfer.md
│ │ ├── knowledge-transfer-assistant.code-workspace
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── tests
│ │ │ ├── __init__.py
│ │ │ ├── test_artifact_loading.py
│ │ │ ├── test_inspector.py
│ │ │ ├── test_share_manager.py
│ │ │ ├── test_share_storage.py
│ │ │ ├── test_share_tools.py
│ │ │ └── test_team_mode.py
│ │ └── uv.lock
│ ├── Makefile
│ ├── navigator-assistant
│ │ ├── .env.example
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── assistant
│ │ │ ├── __init__.py
│ │ │ ├── assets
│ │ │ │ ├── card_content.md
│ │ │ │ └── icon.svg
│ │ │ ├── chat.py
│ │ │ ├── config.py
│ │ │ ├── helpers.py
│ │ │ ├── response
│ │ │ │ ├── __init__.py
│ │ │ │ ├── completion_handler.py
│ │ │ │ ├── completion_requestor.py
│ │ │ │ ├── local_tool
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── add_assistant_to_conversation.py
│ │ │ │ │ ├── list_assistant_services.py
│ │ │ │ │ └── model.py
│ │ │ │ ├── models.py
│ │ │ │ ├── prompt.py
│ │ │ │ ├── request_builder.py
│ │ │ │ ├── response.py
│ │ │ │ ├── step_handler.py
│ │ │ │ └── utils
│ │ │ │ ├── __init__.py
│ │ │ │ ├── formatting_utils.py
│ │ │ │ ├── message_utils.py
│ │ │ │ ├── openai_utils.py
│ │ │ │ └── tools.py
│ │ │ ├── text_includes
│ │ │ │ ├── guardrails_prompt.md
│ │ │ │ ├── guidance_prompt.md
│ │ │ │ ├── instruction_prompt.md
│ │ │ │ ├── navigator_assistant_info.md
│ │ │ │ └── semantic_workbench_features.md
│ │ │ └── whiteboard
│ │ │ ├── __init__.py
│ │ │ ├── _inspector.py
│ │ │ └── _whiteboard.py
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── project-assistant
│ │ ├── .cspell
│ │ │ └── custom-dictionary-workspace.txt
│ │ ├── .env.example
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── assistant
│ │ │ ├── __init__.py
│ │ │ ├── agentic
│ │ │ │ ├── __init__.py
│ │ │ │ ├── act.py
│ │ │ │ ├── coordinator_next_action.py
│ │ │ │ ├── create_invitation.py
│ │ │ │ ├── detect_audience_and_takeaways.py
│ │ │ │ ├── detect_coordinator_actions.py
│ │ │ │ ├── detect_information_request_needs.py
│ │ │ │ ├── detect_knowledge_package_gaps.py
│ │ │ │ ├── focus.py
│ │ │ │ ├── respond.py
│ │ │ │ ├── team_welcome.py
│ │ │ │ └── update_digest.py
│ │ │ ├── assets
│ │ │ │ ├── icon-knowledge-transfer.svg
│ │ │ │ └── icon.svg
│ │ │ ├── assistant.py
│ │ │ ├── common.py
│ │ │ ├── config.py
│ │ │ ├── conversation_clients.py
│ │ │ ├── data.py
│ │ │ ├── domain
│ │ │ │ ├── __init__.py
│ │ │ │ ├── audience_manager.py
│ │ │ │ ├── conversation_preferences_manager.py
│ │ │ │ ├── information_request_manager.py
│ │ │ │ ├── knowledge_brief_manager.py
│ │ │ │ ├── knowledge_digest_manager.py
│ │ │ │ ├── learning_objectives_manager.py
│ │ │ │ ├── share_manager.py
│ │ │ │ ├── tasks_manager.py
│ │ │ │ └── transfer_manager.py
│ │ │ ├── errors.py
│ │ │ ├── files.py
│ │ │ ├── logging.py
│ │ │ ├── notifications.py
│ │ │ ├── prompt_utils.py
│ │ │ ├── storage.py
│ │ │ ├── string_utils.py
│ │ │ ├── text_includes
│ │ │ │ ├── actor_instructions.md
│ │ │ │ ├── assistant_info.md
│ │ │ │ ├── card_content.md
│ │ │ │ ├── coordinator_instructions copy.md
│ │ │ │ ├── coordinator_instructions.md
│ │ │ │ ├── create_invitation.md
│ │ │ │ ├── detect_audience.md
│ │ │ │ ├── detect_coordinator_actions.md
│ │ │ │ ├── detect_information_request_needs.md
│ │ │ │ ├── detect_knowledge_package_gaps.md
│ │ │ │ ├── focus.md
│ │ │ │ ├── knowledge_digest_instructions.txt
│ │ │ │ ├── team_instructions.txt
│ │ │ │ ├── to_do.md
│ │ │ │ ├── update_knowledge_brief.md
│ │ │ │ ├── update_knowledge_digest.md
│ │ │ │ └── welcome_message_generation.txt
│ │ │ ├── tools
│ │ │ │ ├── __init__.py
│ │ │ │ ├── base.py
│ │ │ │ ├── conversation_preferences.py
│ │ │ │ ├── information_requests.py
│ │ │ │ ├── learning_objectives.py
│ │ │ │ ├── learning_outcomes.py
│ │ │ │ ├── progress_tracking.py
│ │ │ │ ├── share_setup.py
│ │ │ │ ├── system_reminders.py
│ │ │ │ ├── tasks.py
│ │ │ │ └── todo.py
│ │ │ ├── ui_tabs
│ │ │ │ ├── __init__.py
│ │ │ │ ├── brief.py
│ │ │ │ ├── common.py
│ │ │ │ ├── debug.py
│ │ │ │ ├── learning.py
│ │ │ │ └── sharing.py
│ │ │ └── utils.py
│ │ ├── CLAUDE.md
│ │ ├── docs
│ │ │ ├── design
│ │ │ │ ├── actions.md
│ │ │ │ ├── control_options.md
│ │ │ │ ├── design.md
│ │ │ │ ├── inference.md
│ │ │ │ └── PXL_20250814_190140267.jpg
│ │ │ ├── DEV_GUIDE.md
│ │ │ ├── how-kta-works.md
│ │ │ ├── JTBD.md
│ │ │ ├── knowledge-transfer-goals.md
│ │ │ ├── learning_assistance.md
│ │ │ ├── notable_claude_conversations
│ │ │ │ ├── clarifying_quad_modal_design.md
│ │ │ │ ├── CLAUDE_PROMPTS.md
│ │ │ │ ├── transfer_state.md
│ │ │ │ └── trying_the_context_agent.md
│ │ │ └── opportunities-of-knowledge-transfer.md
│ │ ├── knowledge-transfer-assistant.code-workspace
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── tests
│ │ │ ├── __init__.py
│ │ │ ├── test_artifact_loading.py
│ │ │ ├── test_inspector.py
│ │ │ ├── test_share_manager.py
│ │ │ ├── test_share_storage.py
│ │ │ └── test_team_mode.py
│ │ └── uv.lock
│ ├── prospector-assistant
│ │ ├── .env.example
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── assistant
│ │ │ ├── __init__.py
│ │ │ ├── agents
│ │ │ │ ├── artifact_agent.py
│ │ │ │ ├── document
│ │ │ │ │ ├── config.py
│ │ │ │ │ ├── gc_draft_content_feedback_config.py
│ │ │ │ │ ├── gc_draft_outline_feedback_config.py
│ │ │ │ │ ├── guided_conversation.py
│ │ │ │ │ └── state.py
│ │ │ │ └── document_agent.py
│ │ │ ├── artifact_creation_extension
│ │ │ │ ├── __init__.py
│ │ │ │ ├── _llm.py
│ │ │ │ ├── config.py
│ │ │ │ ├── document.py
│ │ │ │ ├── extension.py
│ │ │ │ ├── store.py
│ │ │ │ ├── test
│ │ │ │ │ ├── conftest.py
│ │ │ │ │ ├── evaluation.py
│ │ │ │ │ ├── test_completion_with_tools.py
│ │ │ │ │ └── test_extension.py
│ │ │ │ └── tools.py
│ │ │ ├── chat.py
│ │ │ ├── config.py
│ │ │ ├── form_fill_extension
│ │ │ │ ├── __init__.py
│ │ │ │ ├── config.py
│ │ │ │ ├── extension.py
│ │ │ │ ├── inspector.py
│ │ │ │ ├── state.py
│ │ │ │ └── steps
│ │ │ │ ├── __init__.py
│ │ │ │ ├── _guided_conversation.py
│ │ │ │ ├── _llm.py
│ │ │ │ ├── acquire_form_step.py
│ │ │ │ ├── extract_form_fields_step.py
│ │ │ │ ├── fill_form_step.py
│ │ │ │ └── types.py
│ │ │ ├── helpers.py
│ │ │ ├── legacy.py
│ │ │ └── text_includes
│ │ │ ├── artifact_agent_enabled.md
│ │ │ ├── guardrails_prompt.txt
│ │ │ ├── guided_conversation_agent_enabled.md
│ │ │ └── skills_agent_enabled.md
│ │ ├── assistant.code-workspace
│ │ ├── gc_learnings
│ │ │ ├── gc_learnings.md
│ │ │ └── images
│ │ │ ├── gc_conversation_plan_fcn.png
│ │ │ ├── gc_conversation_plan_template.png
│ │ │ ├── gc_execute_plan_callstack.png
│ │ │ ├── gc_functions.png
│ │ │ ├── gc_generate_plan_callstack.png
│ │ │ ├── gc_get_resource_instructions.png
│ │ │ ├── gc_get_termination_instructions.png
│ │ │ ├── gc_kernel_arguments.png
│ │ │ ├── gc_plan_calls.png
│ │ │ ├── gc_termination_instructions.png
│ │ │ ├── sk_get_chat_message_contents.png
│ │ │ ├── sk_inner_get_chat_message_contents.png
│ │ │ ├── sk_send_request_prep.png
│ │ │ └── sk_send_request.png
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ └── skill-assistant
│ ├── .env.example
│ ├── .vscode
│ │ ├── launch.json
│ │ └── settings.json
│ ├── assistant
│ │ ├── __init__.py
│ │ ├── config.py
│ │ ├── logging.py
│ │ ├── skill_assistant.py
│ │ ├── skill_engine_registry.py
│ │ ├── skill_event_mapper.py
│ │ ├── text_includes
│ │ │ └── guardrails_prompt.txt
│ │ └── workbench_helpers.py
│ ├── assistant.code-workspace
│ ├── Makefile
│ ├── pyproject.toml
│ ├── README.md
│ ├── tests
│ │ └── test_setup.py
│ └── uv.lock
├── CLAUDE.md
├── CODE_OF_CONDUCT.md
├── CONTRIBUTING.md
├── docs
│ ├── .vscode
│ │ └── settings.json
│ ├── ASSISTANT_CONFIG.md
│ ├── ASSISTANT_DEVELOPMENT_GUIDE.md
│ ├── CUSTOM_APP_REGISTRATION.md
│ ├── HOSTED_ASSISTANT_WITH_LOCAL_MCP_SERVERS.md
│ ├── images
│ │ ├── architecture-animation.gif
│ │ ├── configure_assistant.png
│ │ ├── conversation_canvas_open.png
│ │ ├── conversation_duplicate.png
│ │ ├── conversation_export.png
│ │ ├── conversation_share_dialog.png
│ │ ├── conversation_share_link.png
│ │ ├── dashboard_configured_view.png
│ │ ├── dashboard_view.png
│ │ ├── license_agreement.png
│ │ ├── message_bar.png
│ │ ├── message_inspection.png
│ │ ├── message_link.png
│ │ ├── new_prospector_assistant_dialog.png
│ │ ├── open_conversation_canvas.png
│ │ ├── prospector_example.png
│ │ ├── readme1.png
│ │ ├── readme2.png
│ │ ├── readme3.png
│ │ ├── rewind.png
│ │ ├── signin_page.png
│ │ └── splash_screen.png
│ ├── LOCAL_ASSISTANT_WITH_REMOTE_WORKBENCH.md
│ ├── SETUP_DEV_ENVIRONMENT.md
│ └── WORKBENCH_APP.md
├── examples
│ ├── dotnet
│ │ ├── .editorconfig
│ │ ├── dotnet-01-echo-bot
│ │ │ ├── appsettings.json
│ │ │ ├── dotnet-01-echo-bot.csproj
│ │ │ ├── MyAgent.cs
│ │ │ ├── MyAgentConfig.cs
│ │ │ ├── MyWorkbenchConnector.cs
│ │ │ ├── Program.cs
│ │ │ └── README.md
│ │ ├── dotnet-02-message-types-demo
│ │ │ ├── appsettings.json
│ │ │ ├── ConnectorExtensions.cs
│ │ │ ├── docs
│ │ │ │ ├── abc.png
│ │ │ │ ├── code.png
│ │ │ │ ├── config.png
│ │ │ │ ├── echo.png
│ │ │ │ ├── markdown.png
│ │ │ │ ├── mermaid.png
│ │ │ │ ├── reverse.png
│ │ │ │ └── safety-check.png
│ │ │ ├── dotnet-02-message-types-demo.csproj
│ │ │ ├── MyAgent.cs
│ │ │ ├── MyAgentConfig.cs
│ │ │ ├── MyWorkbenchConnector.cs
│ │ │ ├── Program.cs
│ │ │ └── README.md
│ │ └── dotnet-03-simple-chatbot
│ │ ├── appsettings.json
│ │ ├── ConnectorExtensions.cs
│ │ ├── dotnet-03-simple-chatbot.csproj
│ │ ├── MyAgent.cs
│ │ ├── MyAgentConfig.cs
│ │ ├── MyWorkbenchConnector.cs
│ │ ├── Program.cs
│ │ └── README.md
│ ├── Makefile
│ └── python
│ ├── python-01-echo-bot
│ │ ├── .env.example
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── assistant
│ │ │ ├── __init__.py
│ │ │ ├── chat.py
│ │ │ └── config.py
│ │ ├── assistant.code-workspace
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── python-02-simple-chatbot
│ │ ├── .env.example
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── assistant
│ │ │ ├── __init__.py
│ │ │ ├── chat.py
│ │ │ ├── config.py
│ │ │ └── text_includes
│ │ │ └── guardrails_prompt.txt
│ │ ├── assistant.code-workspace
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ └── python-03-multimodel-chatbot
│ ├── .env.example
│ ├── .vscode
│ │ ├── launch.json
│ │ └── settings.json
│ ├── assistant
│ │ ├── __init__.py
│ │ ├── chat.py
│ │ ├── config.py
│ │ ├── model_adapters.py
│ │ └── text_includes
│ │ └── guardrails_prompt.txt
│ ├── assistant.code-workspace
│ ├── Makefile
│ ├── pyproject.toml
│ ├── README.md
│ └── uv.lock
├── KNOWN_ISSUES.md
├── libraries
│ ├── dotnet
│ │ ├── .editorconfig
│ │ ├── pack.sh
│ │ ├── README.md
│ │ ├── SemanticWorkbench.sln
│ │ ├── SemanticWorkbench.sln.DotSettings
│ │ └── WorkbenchConnector
│ │ ├── AgentBase.cs
│ │ ├── AgentConfig
│ │ │ ├── AgentConfigBase.cs
│ │ │ ├── AgentConfigPropertyAttribute.cs
│ │ │ └── ConfigUtils.cs
│ │ ├── Constants.cs
│ │ ├── IAgentBase.cs
│ │ ├── icon.png
│ │ ├── Models
│ │ │ ├── Command.cs
│ │ │ ├── Conversation.cs
│ │ │ ├── ConversationEvent.cs
│ │ │ ├── DebugInfo.cs
│ │ │ ├── Insight.cs
│ │ │ ├── Message.cs
│ │ │ ├── MessageMetadata.cs
│ │ │ ├── Participant.cs
│ │ │ ├── Sender.cs
│ │ │ └── ServiceInfo.cs
│ │ ├── Storage
│ │ │ ├── AgentInfo.cs
│ │ │ ├── AgentServiceStorage.cs
│ │ │ └── IAgentServiceStorage.cs
│ │ ├── StringLoggingExtensions.cs
│ │ ├── Webservice.cs
│ │ ├── WorkbenchConfig.cs
│ │ ├── WorkbenchConnector.cs
│ │ └── WorkbenchConnector.csproj
│ ├── Makefile
│ └── python
│ ├── anthropic-client
│ │ ├── .vscode
│ │ │ └── settings.json
│ │ ├── anthropic_client
│ │ │ ├── __init__.py
│ │ │ ├── client.py
│ │ │ ├── config.py
│ │ │ └── messages.py
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── assistant-data-gen
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── assistant_data_gen
│ │ │ ├── __init__.py
│ │ │ ├── assistant_api.py
│ │ │ ├── config.py
│ │ │ ├── gce
│ │ │ │ ├── __init__.py
│ │ │ │ ├── gce_agent.py
│ │ │ │ └── prompts.py
│ │ │ └── pydantic_ai_utils.py
│ │ ├── configs
│ │ │ └── document_assistant_example_config.yaml
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── scripts
│ │ │ ├── gce_simulation.py
│ │ │ └── generate_scenario.py
│ │ └── uv.lock
│ ├── assistant-drive
│ │ ├── .gitignore
│ │ ├── .vscode
│ │ │ ├── extensions.json
│ │ │ └── settings.json
│ │ ├── assistant_drive
│ │ │ ├── __init__.py
│ │ │ ├── drive.py
│ │ │ └── tests
│ │ │ └── test_basic.py
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── pytest.ini
│ │ ├── README.md
│ │ ├── usage.ipynb
│ │ └── uv.lock
│ ├── assistant-extensions
│ │ ├── .vscode
│ │ │ └── settings.json
│ │ ├── assistant_extensions
│ │ │ ├── __init__.py
│ │ │ ├── ai_clients
│ │ │ │ └── config.py
│ │ │ ├── artifacts
│ │ │ │ ├── __init__.py
│ │ │ │ ├── _artifacts.py
│ │ │ │ ├── _inspector.py
│ │ │ │ └── _model.py
│ │ │ ├── attachments
│ │ │ │ ├── __init__.py
│ │ │ │ ├── _attachments.py
│ │ │ │ ├── _convert.py
│ │ │ │ ├── _model.py
│ │ │ │ ├── _shared.py
│ │ │ │ └── _summarizer.py
│ │ │ ├── chat_context_toolkit
│ │ │ │ ├── __init__.py
│ │ │ │ ├── _config.py
│ │ │ │ ├── archive
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── _archive.py
│ │ │ │ │ └── _summarizer.py
│ │ │ │ ├── message_history
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── _history.py
│ │ │ │ │ └── _message.py
│ │ │ │ └── virtual_filesystem
│ │ │ │ ├── __init__.py
│ │ │ │ ├── _archive_file_source.py
│ │ │ │ └── _attachments_file_source.py
│ │ │ ├── dashboard_card
│ │ │ │ ├── __init__.py
│ │ │ │ └── _dashboard_card.py
│ │ │ ├── document_editor
│ │ │ │ ├── __init__.py
│ │ │ │ ├── _extension.py
│ │ │ │ ├── _inspector.py
│ │ │ │ └── _model.py
│ │ │ ├── mcp
│ │ │ │ ├── __init__.py
│ │ │ │ ├── _assistant_file_resource_handler.py
│ │ │ │ ├── _client_utils.py
│ │ │ │ ├── _devtunnel.py
│ │ │ │ ├── _model.py
│ │ │ │ ├── _openai_utils.py
│ │ │ │ ├── _sampling_handler.py
│ │ │ │ ├── _tool_utils.py
│ │ │ │ └── _workbench_file_resource_handler.py
│ │ │ ├── navigator
│ │ │ │ ├── __init__.py
│ │ │ │ └── _navigator.py
│ │ │ └── workflows
│ │ │ ├── __init__.py
│ │ │ ├── _model.py
│ │ │ ├── _workflows.py
│ │ │ └── runners
│ │ │ └── _user_proxy.py
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── test
│ │ │ └── attachments
│ │ │ └── test_attachments.py
│ │ └── uv.lock
│ ├── chat-context-toolkit
│ │ ├── .claude
│ │ │ └── settings.local.json
│ │ ├── .env.sample
│ │ ├── .vscode
│ │ │ └── settings.json
│ │ ├── assets
│ │ │ ├── archive_v1.png
│ │ │ ├── history_v1.png
│ │ │ └── vfs_v1.png
│ │ ├── chat_context_toolkit
│ │ │ ├── __init__.py
│ │ │ ├── archive
│ │ │ │ ├── __init__.py
│ │ │ │ ├── _archive_reader.py
│ │ │ │ ├── _archive_task_queue.py
│ │ │ │ ├── _state.py
│ │ │ │ ├── _types.py
│ │ │ │ └── summarization
│ │ │ │ ├── __init__.py
│ │ │ │ └── _summarizer.py
│ │ │ ├── history
│ │ │ │ ├── __init__.py
│ │ │ │ ├── _budget.py
│ │ │ │ ├── _decorators.py
│ │ │ │ ├── _history.py
│ │ │ │ ├── _prioritize.py
│ │ │ │ ├── _types.py
│ │ │ │ └── tool_abbreviations
│ │ │ │ ├── __init__.py
│ │ │ │ └── _tool_abbreviations.py
│ │ │ └── virtual_filesystem
│ │ │ ├── __init__.py
│ │ │ ├── _types.py
│ │ │ ├── _virtual_filesystem.py
│ │ │ ├── README.md
│ │ │ └── tools
│ │ │ ├── __init__.py
│ │ │ ├── _ls_tool.py
│ │ │ ├── _tools.py
│ │ │ └── _view_tool.py
│ │ ├── CLAUDE.md
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── test
│ │ │ ├── archive
│ │ │ │ └── test_archive_reader.py
│ │ │ ├── history
│ │ │ │ ├── test_abbreviate_messages.py
│ │ │ │ ├── test_history.py
│ │ │ │ ├── test_pair_and_order_tool_messages.py
│ │ │ │ ├── test_prioritize.py
│ │ │ │ └── test_truncate_messages.py
│ │ │ └── virtual_filesystem
│ │ │ ├── test_virtual_filesystem.py
│ │ │ └── tools
│ │ │ ├── test_ls_tool.py
│ │ │ ├── test_tools.py
│ │ │ └── test_view_tool.py
│ │ └── uv.lock
│ ├── content-safety
│ │ ├── .vscode
│ │ │ └── settings.json
│ │ ├── content_safety
│ │ │ ├── __init__.py
│ │ │ ├── evaluators
│ │ │ │ ├── __init__.py
│ │ │ │ ├── azure_content_safety
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── config.py
│ │ │ │ │ └── evaluator.py
│ │ │ │ ├── config.py
│ │ │ │ ├── evaluator.py
│ │ │ │ └── openai_moderations
│ │ │ │ ├── __init__.py
│ │ │ │ ├── config.py
│ │ │ │ └── evaluator.py
│ │ │ └── README.md
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── events
│ │ ├── .vscode
│ │ │ └── settings.json
│ │ ├── events
│ │ │ ├── __init__.py
│ │ │ └── events.py
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── guided-conversation
│ │ ├── .vscode
│ │ │ └── settings.json
│ │ ├── guided_conversation
│ │ │ ├── __init__.py
│ │ │ ├── functions
│ │ │ │ ├── __init__.py
│ │ │ │ ├── conversation_plan.py
│ │ │ │ ├── execution.py
│ │ │ │ └── final_update_plan.py
│ │ │ ├── guided_conversation_agent.py
│ │ │ ├── plugins
│ │ │ │ ├── __init__.py
│ │ │ │ ├── agenda.py
│ │ │ │ └── artifact.py
│ │ │ └── utils
│ │ │ ├── __init__.py
│ │ │ ├── base_model_llm.py
│ │ │ ├── conversation_helpers.py
│ │ │ ├── openai_tool_calling.py
│ │ │ ├── plugin_helpers.py
│ │ │ └── resources.py
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── llm-client
│ │ ├── .vscode
│ │ │ └── settings.json
│ │ ├── llm_client
│ │ │ ├── __init__.py
│ │ │ └── model.py
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── Makefile
│ ├── mcp-extensions
│ │ ├── .vscode
│ │ │ └── settings.json
│ │ ├── Makefile
│ │ ├── mcp_extensions
│ │ │ ├── __init__.py
│ │ │ ├── _client_session.py
│ │ │ ├── _model.py
│ │ │ ├── _sampling.py
│ │ │ ├── _server_extensions.py
│ │ │ ├── _tool_utils.py
│ │ │ ├── llm
│ │ │ │ ├── __init__.py
│ │ │ │ ├── chat_completion.py
│ │ │ │ ├── helpers.py
│ │ │ │ ├── llm_types.py
│ │ │ │ ├── mcp_chat_completion.py
│ │ │ │ └── openai_chat_completion.py
│ │ │ └── server
│ │ │ ├── __init__.py
│ │ │ └── storage.py
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── tests
│ │ │ └── test_tool_utils.py
│ │ └── uv.lock
│ ├── mcp-tunnel
│ │ ├── .vscode
│ │ │ └── settings.json
│ │ ├── Makefile
│ │ ├── mcp_tunnel
│ │ │ ├── __init__.py
│ │ │ ├── _devtunnel.py
│ │ │ ├── _dir.py
│ │ │ └── _main.py
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── openai-client
│ │ ├── .vscode
│ │ │ └── settings.json
│ │ ├── Makefile
│ │ ├── openai_client
│ │ │ ├── __init__.py
│ │ │ ├── chat_driver
│ │ │ │ ├── __init__.py
│ │ │ │ ├── chat_driver.ipynb
│ │ │ │ ├── chat_driver.py
│ │ │ │ ├── message_history_providers
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── in_memory_message_history_provider.py
│ │ │ │ │ ├── local_message_history_provider.py
│ │ │ │ │ ├── message_history_provider.py
│ │ │ │ │ └── tests
│ │ │ │ │ └── formatted_instructions_test.py
│ │ │ │ └── README.md
│ │ │ ├── client.py
│ │ │ ├── completion.py
│ │ │ ├── config.py
│ │ │ ├── errors.py
│ │ │ ├── logging.py
│ │ │ ├── messages.py
│ │ │ ├── tokens.py
│ │ │ └── tools.py
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── tests
│ │ │ ├── test_command_parsing.py
│ │ │ ├── test_formatted_messages.py
│ │ │ ├── test_messages.py
│ │ │ └── test_tokens.py
│ │ └── uv.lock
│ ├── semantic-workbench-api-model
│ │ ├── .vscode
│ │ │ └── settings.json
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── semantic_workbench_api_model
│ │ │ ├── __init__.py
│ │ │ ├── assistant_model.py
│ │ │ ├── assistant_service_client.py
│ │ │ ├── workbench_model.py
│ │ │ └── workbench_service_client.py
│ │ └── uv.lock
│ ├── semantic-workbench-assistant
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── semantic_workbench_assistant
│ │ │ ├── __init__.py
│ │ │ ├── assistant_app
│ │ │ │ ├── __init__.py
│ │ │ │ ├── assistant.py
│ │ │ │ ├── config.py
│ │ │ │ ├── content_safety.py
│ │ │ │ ├── context.py
│ │ │ │ ├── error.py
│ │ │ │ ├── export_import.py
│ │ │ │ ├── protocol.py
│ │ │ │ └── service.py
│ │ │ ├── assistant_service.py
│ │ │ ├── auth.py
│ │ │ ├── canonical.py
│ │ │ ├── command.py
│ │ │ ├── config.py
│ │ │ ├── logging_config.py
│ │ │ ├── settings.py
│ │ │ ├── start.py
│ │ │ └── storage.py
│ │ ├── tests
│ │ │ ├── conftest.py
│ │ │ ├── test_assistant_app.py
│ │ │ ├── test_canonical.py
│ │ │ ├── test_config.py
│ │ │ └── test_storage.py
│ │ └── uv.lock
│ └── skills
│ ├── .vscode
│ │ └── settings.json
│ ├── Makefile
│ ├── README.md
│ └── skill-library
│ ├── .vscode
│ │ └── settings.json
│ ├── docs
│ │ └── vs-recipe-tool.md
│ ├── Makefile
│ ├── pyproject.toml
│ ├── README.md
│ ├── skill_library
│ │ ├── __init__.py
│ │ ├── chat_driver_helpers.py
│ │ ├── cli
│ │ │ ├── azure_openai.py
│ │ │ ├── conversation_history.py
│ │ │ ├── README.md
│ │ │ ├── run_routine.py
│ │ │ ├── settings.py
│ │ │ └── skill_logger.py
│ │ ├── engine.py
│ │ ├── llm_info.txt
│ │ ├── logging.py
│ │ ├── README.md
│ │ ├── routine_stack.py
│ │ ├── skill.py
│ │ ├── skills
│ │ │ ├── common
│ │ │ │ ├── __init__.py
│ │ │ │ ├── common_skill.py
│ │ │ │ └── routines
│ │ │ │ ├── bing_search.py
│ │ │ │ ├── consolidate.py
│ │ │ │ ├── echo.py
│ │ │ │ ├── gather_context.py
│ │ │ │ ├── get_content_from_url.py
│ │ │ │ ├── gpt_complete.py
│ │ │ │ ├── select_user_intent.py
│ │ │ │ └── summarize.py
│ │ │ ├── eval
│ │ │ │ ├── __init__.py
│ │ │ │ ├── eval_skill.py
│ │ │ │ └── routines
│ │ │ │ └── eval.py
│ │ │ ├── fabric
│ │ │ │ ├── __init__.py
│ │ │ │ ├── fabric_skill.py
│ │ │ │ ├── patterns
│ │ │ │ │ ├── agility_story
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── ai
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_answers
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_candidates
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── analyze_cfp_submission
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_claims
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── analyze_comments
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_debate
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_email_headers
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── analyze_incident
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── analyze_interviewer_techniques
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_logs
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_malware
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_military_strategy
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_mistakes
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_paper
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── analyze_patent
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_personality
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_presentation
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_product_feedback
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_proposition
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── analyze_prose
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── analyze_prose_json
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── analyze_prose_pinker
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_risk
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_sales_call
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_spiritual_text
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── analyze_tech_impact
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── analyze_threat_report
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── analyze_threat_report_cmds
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_threat_report_trends
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── answer_interview_question
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── ask_secure_by_design_questions
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── ask_uncle_duke
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── capture_thinkers_work
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── check_agreement
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── clean_text
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── coding_master
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── compare_and_contrast
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── convert_to_markdown
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_5_sentence_summary
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_academic_paper
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_ai_jobs_analysis
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_aphorisms
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── create_art_prompt
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_better_frame
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── create_coding_project
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_command
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── create_cyber_summary
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_design_document
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_diy
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_formal_email
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_git_diff_commit
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_graph_from_input
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_hormozi_offer
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_idea_compass
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_investigation_visualization
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_keynote
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_logo
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── create_markmap_visualization
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_mermaid_visualization
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_mermaid_visualization_for_github
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_micro_summary
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_network_threat_landscape
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── create_newsletter_entry
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── create_npc
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── create_pattern
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_prd
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_prediction_block
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_quiz
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_reading_plan
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_recursive_outline
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_report_finding
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── create_rpg_summary
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_security_update
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── create_show_intro
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_sigma_rules
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_story_explanation
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_stride_threat_model
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_summary
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_tags
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_threat_scenarios
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_ttrc_graph
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_ttrc_narrative
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_upgrade_pack
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_user_story
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_video_chapters
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── create_visualization
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── dialog_with_socrates
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── enrich_blog_post
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── explain_code
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── explain_docs
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── explain_math
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── explain_project
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── explain_terms
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── export_data_as_csv
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_algorithm_update_recommendations
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── extract_article_wisdom
│ │ │ │ │ │ ├── dmiessler
│ │ │ │ │ │ │ └── extract_wisdom-1.0.0
│ │ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ │ └── user.md
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── extract_book_ideas
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_book_recommendations
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_business_ideas
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_controversial_ideas
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_core_message
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_ctf_writeup
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_domains
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_extraordinary_claims
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_ideas
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_insights
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_insights_dm
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_instructions
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_jokes
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_latest_video
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_main_idea
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_most_redeeming_thing
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_patterns
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_poc
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── extract_predictions
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_primary_problem
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_primary_solution
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_product_features
│ │ │ │ │ │ ├── dmiessler
│ │ │ │ │ │ │ └── extract_wisdom-1.0.0
│ │ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ │ └── user.md
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_questions
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_recipe
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_recommendations
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── extract_references
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── extract_skills
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_song_meaning
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_sponsors
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_videoid
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── extract_wisdom
│ │ │ │ │ │ ├── dmiessler
│ │ │ │ │ │ │ └── extract_wisdom-1.0.0
│ │ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ │ └── user.md
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_wisdom_agents
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_wisdom_dm
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_wisdom_nometa
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── find_hidden_message
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── find_logical_fallacies
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── get_wow_per_minute
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── get_youtube_rss
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── humanize
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── identify_dsrp_distinctions
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── identify_dsrp_perspectives
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── identify_dsrp_relationships
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── identify_dsrp_systems
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── identify_job_stories
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── improve_academic_writing
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── improve_prompt
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── improve_report_finding
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── improve_writing
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── judge_output
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── label_and_rate
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── loaded
│ │ │ │ │ ├── md_callout
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── official_pattern_template
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── pattern_explanations.md
│ │ │ │ │ ├── prepare_7s_strategy
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── provide_guidance
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── rate_ai_response
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── rate_ai_result
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── rate_content
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── rate_value
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── raw_query
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── raycast
│ │ │ │ │ │ ├── capture_thinkers_work
│ │ │ │ │ │ ├── create_story_explanation
│ │ │ │ │ │ ├── extract_primary_problem
│ │ │ │ │ │ ├── extract_wisdom
│ │ │ │ │ │ └── yt
│ │ │ │ │ ├── recommend_artists
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── recommend_pipeline_upgrades
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── recommend_talkpanel_topics
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── refine_design_document
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── review_design
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── sanitize_broken_html_to_markdown
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── show_fabric_options_markmap
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── solve_with_cot
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── stringify
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── suggest_pattern
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── summarize
│ │ │ │ │ │ ├── dmiessler
│ │ │ │ │ │ │ └── summarize
│ │ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ │ └── user.md
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── summarize_debate
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── summarize_git_changes
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── summarize_git_diff
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── summarize_lecture
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── summarize_legislation
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── summarize_meeting
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── summarize_micro
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── summarize_newsletter
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── summarize_paper
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── summarize_prompt
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── summarize_pull-requests
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── summarize_rpg_session
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_analyze_challenge_handling
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_check_metrics
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_create_h3_career
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_create_opening_sentences
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_describe_life_outlook
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_extract_intro_sentences
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_extract_panel_topics
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_find_blindspots
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_find_negative_thinking
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_find_neglected_goals
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_give_encouragement
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_red_team_thinking
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_threat_model_plans
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_visualize_mission_goals_projects
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_year_in_review
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── to_flashcards
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── transcribe_minutes
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── translate
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── tweet
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── write_essay
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── write_hackerone_report
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── write_latex
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── write_micro_essay
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── write_nuclei_template_rule
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── write_pull-request
│ │ │ │ │ │ └── system.md
│ │ │ │ │ └── write_semgrep_rule
│ │ │ │ │ ├── system.md
│ │ │ │ │ └── user.md
│ │ │ │ └── routines
│ │ │ │ ├── list.py
│ │ │ │ ├── run.py
│ │ │ │ └── show.py
│ │ │ ├── guided_conversation
│ │ │ │ ├── __init__.py
│ │ │ │ ├── agenda.py
│ │ │ │ ├── artifact_helpers.py
│ │ │ │ ├── chat_completions
│ │ │ │ │ ├── fix_agenda_error.py
│ │ │ │ │ ├── fix_artifact_error.py
│ │ │ │ │ ├── generate_agenda.py
│ │ │ │ │ ├── generate_artifact_updates.py
│ │ │ │ │ ├── generate_final_artifact.py
│ │ │ │ │ └── generate_message.py
│ │ │ │ ├── conversation_guides
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── acrostic_poem.py
│ │ │ │ │ ├── er_triage.py
│ │ │ │ │ ├── interview.py
│ │ │ │ │ └── patient_intake.py
│ │ │ │ ├── guide.py
│ │ │ │ ├── guided_conversation_skill.py
│ │ │ │ ├── logging.py
│ │ │ │ ├── message.py
│ │ │ │ ├── resources.py
│ │ │ │ ├── routines
│ │ │ │ │ └── guided_conversation.py
│ │ │ │ └── tests
│ │ │ │ ├── conftest.py
│ │ │ │ ├── test_artifact_helpers.py
│ │ │ │ ├── test_generate_agenda.py
│ │ │ │ ├── test_generate_artifact_updates.py
│ │ │ │ ├── test_generate_final_artifact.py
│ │ │ │ └── test_resource.py
│ │ │ ├── meta
│ │ │ │ ├── __init__.py
│ │ │ │ ├── meta_skill.py
│ │ │ │ ├── README.md
│ │ │ │ └── routines
│ │ │ │ └── generate_routine.py
│ │ │ ├── posix
│ │ │ │ ├── __init__.py
│ │ │ │ ├── posix_skill.py
│ │ │ │ ├── routines
│ │ │ │ │ ├── append_file.py
│ │ │ │ │ ├── cd.py
│ │ │ │ │ ├── ls.py
│ │ │ │ │ ├── make_home_dir.py
│ │ │ │ │ ├── mkdir.py
│ │ │ │ │ ├── mv.py
│ │ │ │ │ ├── pwd.py
│ │ │ │ │ ├── read_file.py
│ │ │ │ │ ├── rm.py
│ │ │ │ │ ├── touch.py
│ │ │ │ │ └── write_file.py
│ │ │ │ └── sandbox_shell.py
│ │ │ ├── README.md
│ │ │ ├── research
│ │ │ │ ├── __init__.py
│ │ │ │ ├── README.md
│ │ │ │ ├── research_skill.py
│ │ │ │ └── routines
│ │ │ │ ├── answer_question_about_content.py
│ │ │ │ ├── evaluate_answer.py
│ │ │ │ ├── generate_research_plan.py
│ │ │ │ ├── generate_search_query.py
│ │ │ │ ├── update_research_plan.py
│ │ │ │ ├── web_research.py
│ │ │ │ └── web_search.py
│ │ │ ├── research2
│ │ │ │ ├── __init__.py
│ │ │ │ ├── README.md
│ │ │ │ ├── research_skill.py
│ │ │ │ └── routines
│ │ │ │ ├── facts.py
│ │ │ │ ├── make_final_report.py
│ │ │ │ ├── research.py
│ │ │ │ ├── search_plan.py
│ │ │ │ ├── search.py
│ │ │ │ └── visit_pages.py
│ │ │ └── web_research
│ │ │ ├── __init__.py
│ │ │ ├── README.md
│ │ │ ├── research_skill.py
│ │ │ └── routines
│ │ │ ├── facts.py
│ │ │ ├── make_final_report.py
│ │ │ ├── research.py
│ │ │ ├── search_plan.py
│ │ │ ├── search.py
│ │ │ └── visit_pages.py
│ │ ├── tests
│ │ │ ├── test_common_skill.py
│ │ │ ├── test_integration.py
│ │ │ ├── test_routine_stack.py
│ │ │ ├── tst_skill
│ │ │ │ ├── __init__.py
│ │ │ │ └── routines
│ │ │ │ ├── __init__.py
│ │ │ │ └── a_routine.py
│ │ │ └── utilities
│ │ │ ├── test_find_template_vars.py
│ │ │ ├── test_make_arg_set.py
│ │ │ ├── test_paramspec.py
│ │ │ ├── test_parse_command_string.py
│ │ │ └── test_to_string.py
│ │ ├── types.py
│ │ ├── usage.py
│ │ └── utilities.py
│ └── uv.lock
├── LICENSE
├── Makefile
├── mcp-servers
│ ├── ai-assist-content
│ │ ├── .vscode
│ │ │ └── settings.json
│ │ ├── mcp-example-brave-search.md
│ │ ├── mcp-fastmcp-typescript-README.md
│ │ ├── mcp-llms-full.txt
│ │ ├── mcp-metadata-tips.md
│ │ ├── mcp-python-sdk-README.md
│ │ ├── mcp-typescript-sdk-README.md
│ │ ├── pydanticai-documentation.md
│ │ ├── pydanticai-example-question-graph.md
│ │ ├── pydanticai-example-weather.md
│ │ ├── pydanticai-tutorial.md
│ │ └── README.md
│ ├── Makefile
│ ├── mcp-server-bing-search
│ │ ├── .env.example
│ │ ├── .gitignore
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── Makefile
│ │ ├── mcp_server_bing_search
│ │ │ ├── __init__.py
│ │ │ ├── config.py
│ │ │ ├── prompts
│ │ │ │ ├── __init__.py
│ │ │ │ ├── clean_website.py
│ │ │ │ └── filter_links.py
│ │ │ ├── server.py
│ │ │ ├── start.py
│ │ │ ├── tools.py
│ │ │ ├── types.py
│ │ │ ├── utils.py
│ │ │ └── web
│ │ │ ├── __init__.py
│ │ │ ├── get_content.py
│ │ │ ├── llm_processing.py
│ │ │ ├── process_website.py
│ │ │ └── search_bing.py
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── tests
│ │ │ └── test_tools.py
│ │ └── uv.lock
│ ├── mcp-server-bundle
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── Makefile
│ │ ├── mcp_server_bundle
│ │ │ ├── __init__.py
│ │ │ └── main.py
│ │ ├── pyinstaller.spec
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── mcp-server-filesystem
│ │ ├── .env.example
│ │ ├── .github
│ │ │ └── workflows
│ │ │ └── ci.yml
│ │ ├── .gitignore
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── Makefile
│ │ ├── mcp_server_filesystem
│ │ │ ├── __init__.py
│ │ │ ├── config.py
│ │ │ ├── server.py
│ │ │ └── start.py
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── tests
│ │ │ └── test_filesystem.py
│ │ └── uv.lock
│ ├── mcp-server-filesystem-edit
│ │ ├── .env.example
│ │ ├── .gitignore
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── data
│ │ │ ├── attachments
│ │ │ │ ├── Daily Game Ideas.txt
│ │ │ │ ├── Frontend Framework Proposal.txt
│ │ │ │ ├── ReDoodle.txt
│ │ │ │ └── Research Template.tex
│ │ │ ├── test_cases.yaml
│ │ │ └── transcripts
│ │ │ ├── transcript_research_simple.md
│ │ │ ├── transcript_Startup_Idea_1_202503031513.md
│ │ │ ├── transcript_Startup_Idea_2_202503031659.md
│ │ │ └── transcript_Web_Frontends_202502281551.md
│ │ ├── Makefile
│ │ ├── mcp_server_filesystem_edit
│ │ │ ├── __init__.py
│ │ │ ├── app_handling
│ │ │ │ ├── __init__.py
│ │ │ │ ├── excel.py
│ │ │ │ ├── miktex.py
│ │ │ │ ├── office_common.py
│ │ │ │ ├── powerpoint.py
│ │ │ │ └── word.py
│ │ │ ├── config.py
│ │ │ ├── evals
│ │ │ │ ├── __init__.py
│ │ │ │ ├── common.py
│ │ │ │ ├── run_comments.py
│ │ │ │ ├── run_edit.py
│ │ │ │ └── run_ppt_edit.py
│ │ │ ├── prompts
│ │ │ │ ├── __init__.py
│ │ │ │ ├── add_comments.py
│ │ │ │ ├── analyze_comments.py
│ │ │ │ ├── latex_edit.py
│ │ │ │ ├── markdown_draft.py
│ │ │ │ ├── markdown_edit.py
│ │ │ │ └── powerpoint_edit.py
│ │ │ ├── server.py
│ │ │ ├── start.py
│ │ │ ├── tools
│ │ │ │ ├── __init__.py
│ │ │ │ ├── add_comments.py
│ │ │ │ ├── edit_adapters
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── common.py
│ │ │ │ │ ├── latex.py
│ │ │ │ │ └── markdown.py
│ │ │ │ ├── edit.py
│ │ │ │ └── helpers.py
│ │ │ └── types.py
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── tests
│ │ │ ├── app_handling
│ │ │ │ ├── test_excel.py
│ │ │ │ ├── test_miktext.py
│ │ │ │ ├── test_office_common.py
│ │ │ │ ├── test_powerpoint.py
│ │ │ │ └── test_word.py
│ │ │ ├── conftest.py
│ │ │ └── tools
│ │ │ └── edit_adapters
│ │ │ ├── test_latex.py
│ │ │ └── test_markdown.py
│ │ └── uv.lock
│ ├── mcp-server-fusion
│ │ ├── .gitignore
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── AddInIcon.svg
│ │ ├── config.py
│ │ ├── FusionMCPServerAddIn.manifest
│ │ ├── FusionMCPServerAddIn.py
│ │ ├── mcp_server_fusion
│ │ │ ├── __init__.py
│ │ │ ├── fusion_mcp_server.py
│ │ │ ├── fusion_utils
│ │ │ │ ├── __init__.py
│ │ │ │ ├── event_utils.py
│ │ │ │ ├── general_utils.py
│ │ │ │ └── tool_utils.py
│ │ │ ├── mcp_tools
│ │ │ │ ├── __init__.py
│ │ │ │ ├── fusion_3d_operation.py
│ │ │ │ ├── fusion_geometry.py
│ │ │ │ ├── fusion_pattern.py
│ │ │ │ └── fusion_sketch.py
│ │ │ └── vendor
│ │ │ └── README.md
│ │ ├── README.md
│ │ └── requirements.txt
│ ├── mcp-server-giphy
│ │ ├── .env.example
│ │ ├── .gitignore
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── Makefile
│ │ ├── mcp_server
│ │ │ ├── __init__.py
│ │ │ ├── config.py
│ │ │ ├── giphy_search.py
│ │ │ ├── sampling.py
│ │ │ ├── server.py
│ │ │ ├── start.py
│ │ │ └── utils.py
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── mcp-server-memory-user-bio
│ │ ├── .env.example
│ │ ├── .gitignore
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── Makefile
│ │ ├── mcp_server_memory_user_bio
│ │ │ ├── __init__.py
│ │ │ ├── config.py
│ │ │ ├── server.py
│ │ │ └── start.py
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── mcp-server-memory-whiteboard
│ │ ├── .env.example
│ │ ├── .gitignore
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── Makefile
│ │ ├── mcp_server_memory_whiteboard
│ │ │ ├── __init__.py
│ │ │ ├── config.py
│ │ │ ├── server.py
│ │ │ └── start.py
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── mcp-server-office
│ │ ├── .env.example
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── build.sh
│ │ ├── data
│ │ │ ├── attachments
│ │ │ │ ├── Daily Game Ideas.txt
│ │ │ │ ├── Frontend Framework Proposal.txt
│ │ │ │ └── ReDoodle.txt
│ │ │ └── word
│ │ │ ├── test_cases.yaml
│ │ │ └── transcripts
│ │ │ ├── transcript_Startup_Idea_1_202503031513.md
│ │ │ ├── transcript_Startup_Idea_2_202503031659.md
│ │ │ └── transcript_Web_Frontends_202502281551.md
│ │ ├── Makefile
│ │ ├── mcp_server
│ │ │ ├── __init__.py
│ │ │ ├── app_interaction
│ │ │ │ ├── __init__.py
│ │ │ │ ├── excel_editor.py
│ │ │ │ ├── powerpoint_editor.py
│ │ │ │ └── word_editor.py
│ │ │ ├── config.py
│ │ │ ├── constants.py
│ │ │ ├── evals
│ │ │ │ ├── __init__.py
│ │ │ │ ├── common.py
│ │ │ │ ├── run_comment_analysis.py
│ │ │ │ ├── run_feedback.py
│ │ │ │ └── run_markdown_edit.py
│ │ │ ├── helpers.py
│ │ │ ├── markdown_edit
│ │ │ │ ├── __init__.py
│ │ │ │ ├── comment_analysis.py
│ │ │ │ ├── feedback_step.py
│ │ │ │ ├── markdown_edit.py
│ │ │ │ └── utils.py
│ │ │ ├── prompts
│ │ │ │ ├── __init__.py
│ │ │ │ ├── comment_analysis.py
│ │ │ │ ├── feedback.py
│ │ │ │ ├── markdown_draft.py
│ │ │ │ └── markdown_edit.py
│ │ │ ├── server.py
│ │ │ ├── start.py
│ │ │ └── types.py
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── tests
│ │ │ └── test_word_editor.py
│ │ └── uv.lock
│ ├── mcp-server-open-deep-research
│ │ ├── .env.example
│ │ ├── .gitignore
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── Makefile
│ │ ├── mcp_server
│ │ │ ├── __init__.py
│ │ │ ├── config.py
│ │ │ ├── libs
│ │ │ │ └── open_deep_research
│ │ │ │ ├── cookies.py
│ │ │ │ ├── mdconvert.py
│ │ │ │ ├── run_agents.py
│ │ │ │ ├── text_inspector_tool.py
│ │ │ │ ├── text_web_browser.py
│ │ │ │ └── visual_qa.py
│ │ │ ├── open_deep_research.py
│ │ │ ├── server.py
│ │ │ └── start.py
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── mcp-server-open-deep-research-clone
│ │ ├── .env.example
│ │ ├── .gitignore
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── Makefile
│ │ ├── mcp_server_open_deep_research_clone
│ │ │ ├── __init__.py
│ │ │ ├── azure_openai.py
│ │ │ ├── config.py
│ │ │ ├── logging.py
│ │ │ ├── sampling.py
│ │ │ ├── server.py
│ │ │ ├── start.py
│ │ │ ├── utils.py
│ │ │ └── web_research.py
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── test
│ │ │ └── test_open_deep_research_clone.py
│ │ └── uv.lock
│ ├── mcp-server-template
│ │ ├── .taplo.toml
│ │ ├── .vscode
│ │ │ └── settings.json
│ │ ├── copier.yml
│ │ ├── README.md
│ │ └── template
│ │ └── {{ project_slug }}
│ │ ├── .env.example.jinja
│ │ ├── .gitignore
│ │ ├── .vscode
│ │ │ ├── launch.json.jinja
│ │ │ └── settings.json
│ │ ├── {{ module_name }}
│ │ │ ├── __init__.py
│ │ │ ├── config.py.jinja
│ │ │ ├── server.py.jinja
│ │ │ └── start.py.jinja
│ │ ├── Makefile.jinja
│ │ ├── pyproject.toml.jinja
│ │ └── README.md.jinja
│ ├── mcp-server-vscode
│ │ ├── .eslintrc.cjs
│ │ ├── .gitignore
│ │ ├── .npmrc
│ │ ├── .vscode
│ │ │ ├── extensions.json
│ │ │ ├── launch.json
│ │ │ ├── settings.json
│ │ │ └── tasks.json
│ │ ├── .vscode-test.mjs
│ │ ├── .vscodeignore
│ │ ├── ASSISTANT_BOOTSTRAP.md
│ │ ├── eslint.config.mjs
│ │ ├── images
│ │ │ └── icon.png
│ │ ├── LICENSE
│ │ ├── Makefile
│ │ ├── out
│ │ │ ├── extension.d.ts
│ │ │ ├── extension.js
│ │ │ ├── test
│ │ │ │ ├── extension.test.d.ts
│ │ │ │ └── extension.test.js
│ │ │ ├── tools
│ │ │ │ ├── code_checker.d.ts
│ │ │ │ ├── code_checker.js
│ │ │ │ ├── debug_tools.d.ts
│ │ │ │ ├── debug_tools.js
│ │ │ │ ├── focus_editor.d.ts
│ │ │ │ ├── focus_editor.js
│ │ │ │ ├── search_symbol.d.ts
│ │ │ │ └── search_symbol.js
│ │ │ └── utils
│ │ │ ├── port.d.ts
│ │ │ └── port.js
│ │ ├── package.json
│ │ ├── pnpm-lock.yaml
│ │ ├── prettier.config.cjs
│ │ ├── README.md
│ │ ├── src
│ │ │ ├── extension.d.ts
│ │ │ ├── extension.ts
│ │ │ ├── test
│ │ │ │ ├── extension.test.d.ts
│ │ │ │ └── extension.test.ts
│ │ │ ├── tools
│ │ │ │ ├── code_checker.d.ts
│ │ │ │ ├── code_checker.ts
│ │ │ │ ├── debug_tools.d.ts
│ │ │ │ ├── debug_tools.ts
│ │ │ │ ├── focus_editor.d.ts
│ │ │ │ ├── focus_editor.ts
│ │ │ │ ├── search_symbol.d.ts
│ │ │ │ └── search_symbol.ts
│ │ │ └── utils
│ │ │ ├── port.d.ts
│ │ │ └── port.ts
│ │ ├── tsconfig.json
│ │ ├── tsconfig.tsbuildinfo
│ │ ├── vsc-extension-quickstart.md
│ │ └── webpack.config.js
│ └── mcp-server-web-research
│ ├── .env.example
│ ├── .gitignore
│ ├── .vscode
│ │ ├── launch.json
│ │ └── settings.json
│ ├── Makefile
│ ├── mcp_server_web_research
│ │ ├── __init__.py
│ │ ├── azure_openai.py
│ │ ├── config.py
│ │ ├── logging.py
│ │ ├── sampling.py
│ │ ├── server.py
│ │ ├── start.py
│ │ ├── utils.py
│ │ └── web_research.py
│ ├── pyproject.toml
│ ├── README.md
│ ├── test
│ │ └── test_web_research.py
│ └── uv.lock
├── README.md
├── RESPONSIBLE_AI_FAQ.md
├── ruff.toml
├── SECURITY.md
├── semantic-workbench.code-workspace
├── SUPPORT.md
├── tools
│ ├── build_ai_context_files.py
│ ├── collect_files.py
│ ├── docker
│ │ ├── azure_website_sshd.conf
│ │ ├── docker-entrypoint.sh
│ │ ├── Dockerfile.assistant
│ │ └── Dockerfile.mcp-server
│ ├── makefiles
│ │ ├── docker-assistant.mk
│ │ ├── docker-mcp-server.mk
│ │ ├── docker.mk
│ │ ├── python.mk
│ │ ├── recursive.mk
│ │ └── shell.mk
│ ├── reset-service-data.ps1
│ ├── reset-service-data.sh
│ ├── run-app.ps1
│ ├── run-app.sh
│ ├── run-canonical-agent.ps1
│ ├── run-canonical-agent.sh
│ ├── run-dotnet-examples-with-aspire.sh
│ ├── run-python-example1.sh
│ ├── run-python-example2.ps1
│ ├── run-python-example2.sh
│ ├── run-service.ps1
│ ├── run-service.sh
│ ├── run-workbench-chatbot.ps1
│ └── run-workbench-chatbot.sh
├── workbench-app
│ ├── .dockerignore
│ ├── .env.example
│ ├── .eslintrc.cjs
│ ├── .gitignore
│ ├── .vscode
│ │ ├── launch.json
│ │ └── settings.json
│ ├── docker-entrypoint.sh
│ ├── Dockerfile
│ ├── docs
│ │ ├── APP_DEV_GUIDE.md
│ │ ├── MESSAGE_METADATA.md
│ │ ├── MESSAGE_TYPES.md
│ │ ├── README.md
│ │ └── STATE_INSPECTORS.md
│ ├── index.html
│ ├── Makefile
│ ├── nginx.conf
│ ├── package.json
│ ├── pnpm-lock.yaml
│ ├── prettier.config.cjs
│ ├── public
│ │ └── assets
│ │ ├── background-1-upscaled.jpg
│ │ ├── background-1-upscaled.png
│ │ ├── background-1.jpg
│ │ ├── background-1.png
│ │ ├── background-2.jpg
│ │ ├── background-2.png
│ │ ├── experimental-feature.jpg
│ │ ├── favicon.svg
│ │ ├── workflow-designer-1.jpg
│ │ ├── workflow-designer-outlets.jpg
│ │ ├── workflow-designer-states.jpg
│ │ └── workflow-designer-transitions.jpg
│ ├── README.md
│ ├── run.sh
│ ├── src
│ │ ├── components
│ │ │ ├── App
│ │ │ │ ├── AppFooter.tsx
│ │ │ │ ├── AppHeader.tsx
│ │ │ │ ├── AppMenu.tsx
│ │ │ │ ├── AppView.tsx
│ │ │ │ ├── CodeLabel.tsx
│ │ │ │ ├── CommandButton.tsx
│ │ │ │ ├── ConfirmLeave.tsx
│ │ │ │ ├── ContentExport.tsx
│ │ │ │ ├── ContentImport.tsx
│ │ │ │ ├── CopyButton.tsx
│ │ │ │ ├── DialogControl.tsx
│ │ │ │ ├── DynamicIframe.tsx
│ │ │ │ ├── ErrorListFromAppState.tsx
│ │ │ │ ├── ErrorMessageBar.tsx
│ │ │ │ ├── ExperimentalNotice.tsx
│ │ │ │ ├── FormWidgets
│ │ │ │ │ ├── BaseModelEditorWidget.tsx
│ │ │ │ │ ├── CustomizedArrayFieldTemplate.tsx
│ │ │ │ │ ├── CustomizedFieldTemplate.tsx
│ │ │ │ │ ├── CustomizedObjectFieldTemplate.tsx
│ │ │ │ │ └── InspectableWidget.tsx
│ │ │ │ ├── LabelWithDescription.tsx
│ │ │ │ ├── Loading.tsx
│ │ │ │ ├── MenuItemControl.tsx
│ │ │ │ ├── MiniControl.tsx
│ │ │ │ ├── MyAssistantServiceRegistrations.tsx
│ │ │ │ ├── MyItemsManager.tsx
│ │ │ │ ├── OverflowMenu.tsx
│ │ │ │ ├── PresenceMotionList.tsx
│ │ │ │ ├── ProfileSettings.tsx
│ │ │ │ └── TooltipWrapper.tsx
│ │ │ ├── Assistants
│ │ │ │ ├── ApplyConfigButton.tsx
│ │ │ │ ├── AssistantAdd.tsx
│ │ │ │ ├── AssistantConfigExportButton.tsx
│ │ │ │ ├── AssistantConfigImportButton.tsx
│ │ │ │ ├── AssistantConfiguration.tsx
│ │ │ │ ├── AssistantConfigure.tsx
│ │ │ │ ├── AssistantCreate.tsx
│ │ │ │ ├── AssistantDelete.tsx
│ │ │ │ ├── AssistantDuplicate.tsx
│ │ │ │ ├── AssistantExport.tsx
│ │ │ │ ├── AssistantImport.tsx
│ │ │ │ ├── AssistantRemove.tsx
│ │ │ │ ├── AssistantRename.tsx
│ │ │ │ ├── AssistantServiceInfo.tsx
│ │ │ │ ├── AssistantServiceMetadata.tsx
│ │ │ │ └── MyAssistants.tsx
│ │ │ ├── AssistantServiceRegistrations
│ │ │ │ ├── AssistantServiceRegistrationApiKey.tsx
│ │ │ │ ├── AssistantServiceRegistrationApiKeyReset.tsx
│ │ │ │ ├── AssistantServiceRegistrationCreate.tsx
│ │ │ │ └── AssistantServiceRegistrationRemove.tsx
│ │ │ ├── Conversations
│ │ │ │ ├── Canvas
│ │ │ │ │ ├── AssistantCanvas.tsx
│ │ │ │ │ ├── AssistantCanvasList.tsx
│ │ │ │ │ ├── AssistantInspector.tsx
│ │ │ │ │ ├── AssistantInspectorList.tsx
│ │ │ │ │ └── ConversationCanvas.tsx
│ │ │ │ ├── ChatInputPlugins
│ │ │ │ │ ├── ClearEditorPlugin.tsx
│ │ │ │ │ ├── LexicalMenu.ts
│ │ │ │ │ ├── ParticipantMentionsPlugin.tsx
│ │ │ │ │ ├── TypeaheadMenuPlugin.css
│ │ │ │ │ └── TypeaheadMenuPlugin.tsx
│ │ │ │ ├── ContentRenderers
│ │ │ │ │ ├── CodeContentRenderer.tsx
│ │ │ │ │ ├── ContentListRenderer.tsx
│ │ │ │ │ ├── ContentRenderer.tsx
│ │ │ │ │ ├── DiffRenderer.tsx
│ │ │ │ │ ├── HtmlContentRenderer.tsx
│ │ │ │ │ ├── JsonSchemaContentRenderer.tsx
│ │ │ │ │ ├── MarkdownContentRenderer.tsx
│ │ │ │ │ ├── MarkdownEditorRenderer.tsx
│ │ │ │ │ ├── MermaidContentRenderer.tsx
│ │ │ │ │ ├── MusicABCContentRenderer.css
│ │ │ │ │ └── MusicABCContentRenderer.tsx
│ │ │ │ ├── ContextWindow.tsx
│ │ │ │ ├── ConversationCreate.tsx
│ │ │ │ ├── ConversationDuplicate.tsx
│ │ │ │ ├── ConversationExport.tsx
│ │ │ │ ├── ConversationFileIcon.tsx
│ │ │ │ ├── ConversationRemove.tsx
│ │ │ │ ├── ConversationRename.tsx
│ │ │ │ ├── ConversationShare.tsx
│ │ │ │ ├── ConversationShareCreate.tsx
│ │ │ │ ├── ConversationShareList.tsx
│ │ │ │ ├── ConversationShareView.tsx
│ │ │ │ ├── ConversationsImport.tsx
│ │ │ │ ├── ConversationTranscript.tsx
│ │ │ │ ├── DebugInspector.tsx
│ │ │ │ ├── FileItem.tsx
│ │ │ │ ├── FileList.tsx
│ │ │ │ ├── InputAttachmentList.tsx
│ │ │ │ ├── InputOptionsControl.tsx
│ │ │ │ ├── InteractHistory.tsx
│ │ │ │ ├── InteractInput.tsx
│ │ │ │ ├── Message
│ │ │ │ │ ├── AttachmentSection.tsx
│ │ │ │ │ ├── ContentRenderer.tsx
│ │ │ │ │ ├── ContentSafetyNotice.tsx
│ │ │ │ │ ├── InteractMessage.tsx
│ │ │ │ │ ├── MessageActions.tsx
│ │ │ │ │ ├── MessageBase.tsx
│ │ │ │ │ ├── MessageBody.tsx
│ │ │ │ │ ├── MessageContent.tsx
│ │ │ │ │ ├── MessageFooter.tsx
│ │ │ │ │ ├── MessageHeader.tsx
│ │ │ │ │ ├── NotificationAccordion.tsx
│ │ │ │ │ └── ToolResultMessage.tsx
│ │ │ │ ├── MessageDelete.tsx
│ │ │ │ ├── MessageLink.tsx
│ │ │ │ ├── MyConversations.tsx
│ │ │ │ ├── MyShares.tsx
│ │ │ │ ├── ParticipantAvatar.tsx
│ │ │ │ ├── ParticipantAvatarGroup.tsx
│ │ │ │ ├── ParticipantItem.tsx
│ │ │ │ ├── ParticipantList.tsx
│ │ │ │ ├── ParticipantStatus.tsx
│ │ │ │ ├── RewindConversation.tsx
│ │ │ │ ├── ShareRemove.tsx
│ │ │ │ ├── SpeechButton.tsx
│ │ │ │ └── ToolCalls.tsx
│ │ │ └── FrontDoor
│ │ │ ├── Chat
│ │ │ │ ├── AssistantDrawer.tsx
│ │ │ │ ├── CanvasDrawer.tsx
│ │ │ │ ├── Chat.tsx
│ │ │ │ ├── ChatCanvas.tsx
│ │ │ │ ├── ChatControls.tsx
│ │ │ │ └── ConversationDrawer.tsx
│ │ │ ├── Controls
│ │ │ │ ├── AssistantCard.tsx
│ │ │ │ ├── AssistantSelector.tsx
│ │ │ │ ├── AssistantServiceSelector.tsx
│ │ │ │ ├── ConversationItem.tsx
│ │ │ │ ├── ConversationList.tsx
│ │ │ │ ├── ConversationListOptions.tsx
│ │ │ │ ├── NewConversationButton.tsx
│ │ │ │ ├── NewConversationForm.tsx
│ │ │ │ └── SiteMenuButton.tsx
│ │ │ ├── GlobalContent.tsx
│ │ │ └── MainContent.tsx
│ │ ├── Constants.ts
│ │ ├── global.d.ts
│ │ ├── index.css
│ │ ├── libs
│ │ │ ├── AppStorage.ts
│ │ │ ├── AuthHelper.ts
│ │ │ ├── EventSubscriptionManager.ts
│ │ │ ├── Theme.ts
│ │ │ ├── useAssistantCapabilities.ts
│ │ │ ├── useChatCanvasController.ts
│ │ │ ├── useConversationEvents.ts
│ │ │ ├── useConversationUtility.ts
│ │ │ ├── useCreateConversation.ts
│ │ │ ├── useDebugComponentLifecycle.ts
│ │ │ ├── useDragAndDrop.ts
│ │ │ ├── useEnvironment.ts
│ │ │ ├── useExportUtility.ts
│ │ │ ├── useHistoryUtility.ts
│ │ │ ├── useKeySequence.ts
│ │ │ ├── useMediaQuery.ts
│ │ │ ├── useMicrosoftGraph.ts
│ │ │ ├── useNotify.tsx
│ │ │ ├── useParticipantUtility.tsx
│ │ │ ├── useSiteUtility.ts
│ │ │ ├── useWorkbenchEventSource.ts
│ │ │ ├── useWorkbenchService.ts
│ │ │ └── Utility.ts
│ │ ├── main.tsx
│ │ ├── models
│ │ │ ├── Assistant.ts
│ │ │ ├── AssistantCapability.ts
│ │ │ ├── AssistantServiceInfo.ts
│ │ │ ├── AssistantServiceRegistration.ts
│ │ │ ├── Config.ts
│ │ │ ├── Conversation.ts
│ │ │ ├── ConversationFile.ts
│ │ │ ├── ConversationMessage.ts
│ │ │ ├── ConversationMessageDebug.ts
│ │ │ ├── ConversationParticipant.ts
│ │ │ ├── ConversationShare.ts
│ │ │ ├── ConversationShareRedemption.ts
│ │ │ ├── ConversationState.ts
│ │ │ ├── ConversationStateDescription.ts
│ │ │ ├── ServiceEnvironment.ts
│ │ │ └── User.ts
│ │ ├── redux
│ │ │ ├── app
│ │ │ │ ├── hooks.ts
│ │ │ │ ├── rtkQueryErrorLogger.ts
│ │ │ │ └── store.ts
│ │ │ └── features
│ │ │ ├── app
│ │ │ │ ├── appSlice.ts
│ │ │ │ └── AppState.ts
│ │ │ ├── chatCanvas
│ │ │ │ ├── chatCanvasSlice.ts
│ │ │ │ └── ChatCanvasState.ts
│ │ │ ├── localUser
│ │ │ │ ├── localUserSlice.ts
│ │ │ │ └── LocalUserState.ts
│ │ │ └── settings
│ │ │ ├── settingsSlice.ts
│ │ │ └── SettingsState.ts
│ │ ├── Root.tsx
│ │ ├── routes
│ │ │ ├── AcceptTerms.tsx
│ │ │ ├── AssistantEditor.tsx
│ │ │ ├── AssistantServiceRegistrationEditor.tsx
│ │ │ ├── Dashboard.tsx
│ │ │ ├── ErrorPage.tsx
│ │ │ ├── FrontDoor.tsx
│ │ │ ├── Login.tsx
│ │ │ ├── Settings.tsx
│ │ │ ├── ShareRedeem.tsx
│ │ │ └── Shares.tsx
│ │ ├── services
│ │ │ └── workbench
│ │ │ ├── assistant.ts
│ │ │ ├── assistantService.ts
│ │ │ ├── conversation.ts
│ │ │ ├── file.ts
│ │ │ ├── index.ts
│ │ │ ├── participant.ts
│ │ │ ├── share.ts
│ │ │ ├── state.ts
│ │ │ └── workbench.ts
│ │ └── vite-env.d.ts
│ ├── tools
│ │ └── filtered-ts-prune.cjs
│ ├── tsconfig.json
│ └── vite.config.ts
└── workbench-service
├── .env.example
├── .vscode
│ ├── extensions.json
│ ├── launch.json
│ └── settings.json
├── alembic.ini
├── devdb
│ ├── docker-compose.yaml
│ └── postgresql-init.sh
├── Dockerfile
├── Makefile
├── migrations
│ ├── env.py
│ ├── README
│ ├── script.py.mako
│ └── versions
│ ├── 2024_09_19_000000_69dcda481c14_init.py
│ ├── 2024_09_19_190029_dffb1d7e219a_file_version_filename.py
│ ├── 2024_09_20_204130_b29524775484_share.py
│ ├── 2024_10_30_231536_039bec8edc33_index_message_type.py
│ ├── 2024_11_04_204029_5149c7fb5a32_conversationmessagedebug.py
│ ├── 2024_11_05_015124_245baf258e11_double_check_debugs.py
│ ├── 2024_11_25_191056_a106de176394_drop_workflow.py
│ ├── 2025_03_19_140136_aaaf792d4d72_set_user_title_set.py
│ ├── 2025_03_21_153250_3763629295ad_add_assistant_template_id.py
│ ├── 2025_05_19_163613_b2f86e981885_delete_context_transfer_assistants.py
│ └── 2025_06_18_174328_503c739152f3_delete_knowlege_transfer_assistants.py
├── pyproject.toml
├── README.md
├── semantic_workbench_service
│ ├── __init__.py
│ ├── api.py
│ ├── assistant_api_key.py
│ ├── auth.py
│ ├── azure_speech.py
│ ├── config.py
│ ├── controller
│ │ ├── __init__.py
│ │ ├── assistant_service_client_pool.py
│ │ ├── assistant_service_registration.py
│ │ ├── assistant.py
│ │ ├── conversation_share.py
│ │ ├── conversation.py
│ │ ├── convert.py
│ │ ├── exceptions.py
│ │ ├── export_import.py
│ │ ├── file.py
│ │ ├── participant.py
│ │ └── user.py
│ ├── db.py
│ ├── event.py
│ ├── files.py
│ ├── logging_config.py
│ ├── middleware.py
│ ├── query.py
│ ├── service_user_principals.py
│ ├── service.py
│ └── start.py
├── tests
│ ├── __init__.py
│ ├── conftest.py
│ ├── docker-compose.yaml
│ ├── test_assistant_api_key.py
│ ├── test_files.py
│ ├── test_integration.py
│ ├── test_middleware.py
│ ├── test_migrations.py
│ ├── test_workbench_service.py
│ └── types.py
└── uv.lock
```
# Files
--------------------------------------------------------------------------------
/mcp-servers/mcp-server-filesystem-edit/data/transcripts/transcript_research_simple.md:
--------------------------------------------------------------------------------
```markdown
### [Monday, March 3 3:01 PM] User:
notice: User created the conversation
----------------------------------
### [Monday, March 3 3:01 PM] User:
notice: Codespace Assistant 2-26 added to conversation
----------------------------------
### [Monday, March 3 3:01 PM] Assistant:
Hello! I am an assistant that can help you with coding projects within the context of the Semantic Workbench.Let's get started by having a conversation about your project. You can ask me questions, request code snippets, or ask for help with debugging. I can also help you with markdown, code snippets, and other types of content. You can also attach .docx, text, and image files to your chat messages to help me better understand the context of our conversation. Where would you like to start?
----------------------------------
### [Monday, March 3 3:05 PM] User:
Hello! I am writing a research paper in LaTeX on the history of asteroids.
----------------------------------
### [Monday, March 3 3:06 PM] Assistant:
That sounds great! What specific topic or question do you need help with regarding your research paper in LaTeX?
----------------------------------
```
--------------------------------------------------------------------------------
/workbench-app/src/components/App/ErrorMessageBar.tsx:
--------------------------------------------------------------------------------
```typescript
// Copyright (c) Microsoft. All rights reserved.
import { Button, MessageBar, MessageBarActions, MessageBarBody, MessageBarTitle } from '@fluentui/react-components';
import { DismissRegular } from '@fluentui/react-icons';
import React from 'react';
import { Utility } from '../../libs/Utility';
interface ErrorMessageBarProps {
title?: string;
error?: Record<string, any> | string;
onDismiss?: () => void;
}
export const ErrorMessageBar: React.FC<ErrorMessageBarProps> = (props) => {
const { title, error, onDismiss } = props;
let message = Utility.errorToMessageString(error);
if (!title && !message) {
message = 'An unknown error occurred';
}
return (
<MessageBar intent="error" layout="multiline">
<MessageBarBody>
<MessageBarTitle>{title ?? 'Error'}:</MessageBarTitle>
{message}
</MessageBarBody>
{onDismiss && (
<MessageBarActions
containerAction={<Button appearance="transparent" icon={<DismissRegular />} onClick={onDismiss} />}
/>
)}
</MessageBar>
);
};
```
--------------------------------------------------------------------------------
/mcp-servers/mcp-server-filesystem-edit/pyproject.toml:
--------------------------------------------------------------------------------
```toml
[project]
name = "mcp-server-filesystem-edit"
version = "0.1.0"
description = "Allows for robust editing of files like Markdown and LaTeX"
authors = [{ name = "Semantic Workbench Team" }]
readme = "README.md"
requires-python = ">=3.11,<3.13"
dependencies = [
"mcp-extensions[llm,openai]>=0.1.0",
"pendulum>=3.0,<4.0",
"pydantic>=2.10,<3.0",
"python-dotenv>=1.0.1,<2.0",
"pyyaml>=6.0,<7.0",
"pywin32==308; platform_system == 'Windows'",
"rich>=13.9,<14.0",
"tiktoken>=0.9,<1.0",
]
[dependency-groups]
dev = [
"pyinstaller>=6.11",
"pyright>=1.1.389",
"pytest>=8.0",
"pytest-asyncio>=0.25",
]
[tool.uv]
package = true
[tool.uv.sources]
mcp-extensions = { path = "../../libraries/python/mcp-extensions", editable = true }
[project.scripts]
mcp-server-filesystem-edit = "mcp_server_filesystem_edit.start:main"
[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[tool.pytest.ini_options]
addopts = "-vv"
log_cli = true
log_cli_level = "WARNING"
log_cli_format = "%(asctime)s | %(levelname)-7s | %(name)s | %(message)s"
asyncio_mode = "auto"
asyncio_default_fixture_loop_scope = "function"
```
--------------------------------------------------------------------------------
/workbench-app/src/index.css:
--------------------------------------------------------------------------------
```css
:root {
text-rendering: optimizeLegibility;
-webkit-font-smoothing: antialiased;
-moz-osx-font-smoothing: grayscale;
-webkit-text-size-adjust: 100%;
}
body {
margin: 0;
overscroll-behavior: none;
background-size: cover;
background-repeat: no-repeat;
background-position: center;
}
html,
body,
#root,
#root > .app-container {
height: 100%;
background-color: rgba(255, 255, 255, 0.3);
}
::-webkit-scrollbar {
width: 1em;
}
::-webkit-scrollbar-track {
-webkit-box-shadow: inset 0 0 6px rgba(0, 0, 0, 0.2);
}
::-webkit-scrollbar-thumb {
background-color: rgba(0, 0, 0, 0.1);
outline: 1px solid rgba(0, 0, 0, 0.1);
border-radius: 2px;
}
/* Themed scroll bars - make sure to update the colors to match your theme brands */
.brand-scrollbar-light::-webkit-scrollbar-thumb {
background-color: '#1D6BB9';
}
.brand-scrollbar-orange::-webkit-scrollbar-thumb {
background-color: '#C02D09';
}
.brand-scrollbar-purple::-webkit-scrollbar-thumb {
background-color: '#AB12D9';
}
.user-avatar .fui-Avatar {
margin-right: unset;
}
#root .fui-Card {
overflow: visible;
margin: 2px 0;
}
```
--------------------------------------------------------------------------------
/tools/run-app.sh:
--------------------------------------------------------------------------------
```bash
#!/usr/bin/env bash
set -e
ROOT="$(cd "$(dirname "${BASH_SOURCE[0]:-$0}")" && cd .. && pwd)"
cd $ROOT
# ================================================================
cd workbench-app
# Check node version, it must be major version 20 (any minor), otherwise show an error and exit
NODE_VERSION=$(node -v)
if [[ ! $NODE_VERSION =~ ^v(1[8-9]|[2-9][0-9]).* ]]; then
echo "Node version is $NODE_VERSION, expected 18.x.x or higher."
# Attempt to source nvm
if [ -s "$NVM_DIR/nvm.sh" ]; then
. "$NVM_DIR/nvm.sh"
elif [ -s "$HOME/.nvm/nvm.sh" ]; then
export NVM_DIR="$HOME/.nvm"
. "$NVM_DIR/nvm.sh"
else
echo "nvm not found. Please install Node 18 or higher manually."
echo "See also README.md for instructions."
exit 1
fi
echo "Installing latest LTS Node version via nvm..."
nvm install --lts
nvm use --lts
NODE_VERSION=$(node -v)
if [[ ! $NODE_VERSION =~ ^v(1[8-9]|[2-9][0-9]).* ]]; then
echo "Failed to switch to Node 18 or higher via nvm. You have $NODE_VERSION."
exit 1
fi
fi
echo "Starting the Semantic Workbench app, open https://localhost:4000 in your browser when ready"
pnpm install
pnpm start
```
--------------------------------------------------------------------------------
/assistants/project-assistant/assistant/tools/conversation_preferences.py:
--------------------------------------------------------------------------------
```python
"""
Project setup tools for Knowledge Transfer Assistant.
Tools for configuring knowledge shares.
"""
from assistant.domain.conversation_preferences_manager import ConversationPreferencesManager
from .base import ToolsBase
class ConversationPreferencesTools(ToolsBase):
async def update_preferred_communication_style(self, style: str) -> str:
"""
Update the preferred communication style for the conversation.
Args:
style: The preferred communication style to set. This should include all of the users instructions about how the assistant should communicate with the user. It is not just a single style, but a comprehensive set of instructions.
Returns:
A message indicating success or failure
""" # noqa: E501
try:
await ConversationPreferencesManager.update_preferred_communication_style(
context=self.context,
preferred_communication_style=style,
)
return "Preferred conversation style updated successfully"
except Exception as e:
return f"Failed to update preferred conversation style: {e!s}"
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/skills/fabric/patterns/extract_book_ideas/system.md:
--------------------------------------------------------------------------------
```markdown
# IDENTITY and PURPOSE
You take a book name as an input and output a full summary of the book's most important content using the steps and instructions below.
Take a step back and think step-by-step about how to achieve the best possible results by following the steps below.
# STEPS
- Scour your memory for everything you know about this book.
- Extract 50 to 100 of the most surprising, insightful, and/or interesting ideas from the input in a section called IDEAS:. If there are less than 50 then collect all of them. Make sure you extract at least 20.
# OUTPUT INSTRUCTIONS
- Only output Markdown.
- Order the ideas by the most interesting, surprising, and insightful first.
- Extract at least 50 IDEAS from the content.
- Extract up to 100 IDEAS.
- Limit each bullet to a maximum of 20 words.
- Do not give warnings or notes; only output the requested sections.
- You use bulleted lists for output, not numbered lists.
- Do not repeat IDEAS.
- Vary the wording of the IDEAS.
- Don't repeat the same IDEAS over and over, even if you're using different wording.
- Ensure you follow ALL these instructions when creating your output.
# INPUT
INPUT:
```
--------------------------------------------------------------------------------
/assistants/guided-conversation-assistant/assistant/agents/guided_conversation/config.py:
--------------------------------------------------------------------------------
```python
from typing import Annotated
from pydantic import BaseModel, Field
from semantic_workbench_assistant.config import UISchema
from .definition import GuidedConversationDefinition
from .definitions.er_triage import er_triage
from .definitions.interview import interview
from .definitions.patient_intake import patient_intake
from .definitions.poem_feedback import poem_feedback
#
# region Models
#
class GuidedConversationAgentConfigModel(BaseModel):
definition: Annotated[
GuidedConversationDefinition,
Field(
title="Definition",
description="The definition of the guided conversation agent.",
),
UISchema(
schema={
"ui:options": {
"configurations": {
"Poem Feedback": poem_feedback.model_dump(mode="json"),
"Interview": interview.model_dump(mode="json"),
"Patient Intake": patient_intake.model_dump(mode="json"),
"ER Triage": er_triage.model_dump(mode="json"),
},
},
},
),
] = poem_feedback
# endregion
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/skills/fabric/patterns/md_callout/system.md:
--------------------------------------------------------------------------------
```markdown
IDENTITY and GOAL:
You are an ultra-wise and brilliant classifier and judge of content. You create a markdown callout based on the provided text.
Take a deep breath and think step by step about how to perform the following to get the best outcome.
STEPS:
1. You determine which callout type is going to best identify the content you are working with.
CALLOUT OPTIONS TO SELECT FROM (Select one that applies best):
> [!NOTE]
> This is a note callout for general information.
> [!TIP]
> Here's a helpful tip for users.
> [!IMPORTANT]
> This information is crucial for success.
> [!WARNING]
> Be cautious! This action has potential risks.
> [!CAUTION]
> This action may have negative consequences.
END OF CALLOUT OPTIONS
2. Take the text I gave you and place it in the appropriate callout format.
OUTPUT:
The output should look like the following:
```md
> [!CHOSEN CALLOUT]
> The text I gave you goes here.
```
OUTPUT FORMAT:
```md
> [!CHOSEN CALLOUT]
> The text I gave you goes here.
```
OUTPUT INSTRUCTIONS
- ONLY generate the chosen callout
- ONLY OUTPUT THE MARKDOWN CALLOUT ABOVE.
- Do not output the ```md container. Just the markdown itself.
INPUT:
```
--------------------------------------------------------------------------------
/workbench-app/Dockerfile:
--------------------------------------------------------------------------------
```dockerfile
ARG VITE_SEMANTIC_WORKBENCH_AUTHORITY
ARG VITE_SEMANTIC_WORKBENCH_CLIENT_ID
# Stage 1: Build the React application
FROM node:18-alpine AS build
WORKDIR /app
ARG VITE_SEMANTIC_WORKBENCH_AUTHORITY
ARG VITE_SEMANTIC_WORKBENCH_CLIENT_ID
# Install pnpm
RUN npm install -g pnpm
# Copy package.json and pnpm-lock.yaml
COPY package.json pnpm-lock.yaml ./
# Install dependencies
RUN pnpm install
# Copy the rest of the application code
COPY . .
ENV VITE_SEMANTIC_WORKBENCH_AUTHORITY=${VITE_SEMANTIC_WORKBENCH_AUTHORITY}
ENV VITE_SEMANTIC_WORKBENCH_CLIENT_ID=${VITE_SEMANTIC_WORKBENCH_CLIENT_ID}
# Build the application
RUN NODE_OPTIONS=--max-old-space-size=4096 pnpm run build
# Stage 2: Serve the app with Nginx
FROM nginx:alpine
RUN apk add --no-cache gettext
WORKDIR /usr/share/nginx/html
# Remove default Nginx static files
RUN rm -rf ./*
# Copy build artifacts from the previous stage
COPY --from=build /app/build .
# Copy custom entrypoint script
COPY docker-entrypoint.sh /usr/bin/
RUN chmod +x /usr/bin/docker-entrypoint.sh
# Copy Nginx configuration
COPY nginx.conf /etc/nginx/conf.d/default.conf
ENTRYPOINT ["docker-entrypoint.sh"]
CMD ["nginx", "-g", "daemon off;"]
```
--------------------------------------------------------------------------------
/workbench-service/tests/test_migrations.py:
--------------------------------------------------------------------------------
```python
import pytest
import semantic_workbench_service
from alembic import command
from alembic.config import Config
from semantic_workbench_service import db
from semantic_workbench_service.config import DBSettings
@pytest.fixture
async def bootstrapped_db_settings(db_settings: DBSettings) -> DBSettings:
async with db.create_engine(db_settings) as engine:
await db.bootstrap_db(engine, settings=db_settings)
return db_settings
@pytest.fixture
def alembic_config(bootstrapped_db_settings: DBSettings, monkeypatch: pytest.MonkeyPatch) -> Config:
monkeypatch.setattr(semantic_workbench_service.settings, "db", bootstrapped_db_settings)
return Config(bootstrapped_db_settings.alembic_config_path)
def test_migration_cycle(alembic_config: Config) -> None:
"""Test that all migrations can downgrade and upgrade without error."""
# check that there are no schema differences from head
command.check(alembic_config)
# downgrade to base
command.downgrade(alembic_config, "base")
# and upgrade back to head
command.upgrade(alembic_config, "head")
# check that the current revision is head
command.check(
alembic_config,
)
```
--------------------------------------------------------------------------------
/assistants/guided-conversation-assistant/pyproject.toml:
--------------------------------------------------------------------------------
```toml
[project]
name = "assistant"
version = "0.1.0"
description = "An assistant that will guide users through a conversation towards a specific goal."
authors = [{ name = "Semantic Workbench Team" }]
readme = "README.md"
requires-python = ">=3.11"
dependencies = [
"deepmerge>=2.0",
"docx2txt>=0.8",
"html2docx>=1.6.0",
"markdown>=3.6",
"openai>=1.61.0",
"pdfplumber>=0.11.2",
"tiktoken>=0.8.0",
"semantic-workbench-assistant>=0.1.0",
"content-safety>=0.1.0",
"semantic-kernel>=1.11.0",
"guided-conversation>=0.1.0",
"openai-client>=0.1.0",
]
[tool.uv]
package = true
[tool.uv.sources]
semantic-workbench-assistant = { path = "../../libraries/python/semantic-workbench-assistant", editable = true }
content-safety = { path = "../../libraries/python/content-safety/", editable = true }
guided-conversation = { path = "../../libraries/python/guided-conversation", editable = true }
openai-client = { path = "../../libraries/python/openai-client", editable = true }
[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[dependency-groups]
dev = ["pyright>=1.1.389"]
[tool.pyright]
exclude = ["**/.venv", "**/.data", "**/__pycache__"]
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/skills/fabric/patterns/create_git_diff_commit/system.md:
--------------------------------------------------------------------------------
```markdown
# IDENTITY and PURPOSE
You are an expert project manager and developer, and you specialize in creating super clean updates for what changed in a Git diff.
# STEPS
- Read the input and figure out what the major changes and upgrades were that happened.
- Create the git commands needed to add the changes to the repo, and a git commit to reflect the changes
- If there are a lot of changes include more bullets. If there are only a few changes, be more terse.
# OUTPUT INSTRUCTIONS
- Use conventional commits - i.e. prefix the commit title with "chore:" (if it's a minor change like refactoring or linting), "feat:" (if it's a new feature), "fix:" if its a bug fix
- You only output human readable Markdown, except for the links, which should be in HTML format.
- The output should only be the shell commands needed to update git.
- Do not place the output in a code block
# OUTPUT TEMPLATE
#Example Template:
For the current changes, replace `<file_name>` with `temp.py` and `<commit_message>` with `Added --newswitch switch to temp.py to do newswitch behavior`:
git add temp.py
git commit -m "Added --newswitch switch to temp.py to do newswitch behavior"
#EndTemplate
# INPUT:
INPUT:
```
--------------------------------------------------------------------------------
/workbench-app/src/routes/ErrorPage.tsx:
--------------------------------------------------------------------------------
```typescript
// Copyright (c) Microsoft. All rights reserved.
import { MessageBar, MessageBarBody } from '@fluentui/react-components';
import React from 'react';
import { isRouteErrorResponse, useRouteError } from 'react-router-dom';
import { AppView } from '../components/App/AppView';
import { useSiteUtility } from '../libs/useSiteUtility';
export const ErrorPage: React.FC = () => {
const error = useRouteError();
const siteUtility = useSiteUtility();
siteUtility.setDocumentTitle('Error');
let errorMessage: string;
if (isRouteErrorResponse(error)) {
// error is type `ErrorResponse`
errorMessage = error.data || error.statusText;
} else if (error instanceof Error) {
// error is type `Error`
errorMessage = error.message;
} else if (typeof error === 'string') {
// error is type `string`
errorMessage = error;
} else {
// error is type `unknown`
errorMessage = 'Unknown error';
}
return (
<AppView title="Error">
<MessageBar intent="error" layout="multiline">
<MessageBarBody>{errorMessage}</MessageBarBody>
</MessageBar>
</AppView>
);
};
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/skills/fabric/patterns/analyze_threat_report_trends/system.md:
--------------------------------------------------------------------------------
```markdown
# IDENTITY and PURPOSE
You are a super-intelligent cybersecurity expert. You specialize in extracting the surprising, insightful, and interesting information from cybersecurity threat reports.
Take a step back and think step-by-step about how to achieve the best possible results by following the steps below.
# STEPS
- Read the entire threat report from an expert perspective, thinking deeply about what's new, interesting, and surprising in the report.
- Extract up to 50 of the most surprising, insightful, and/or interesting trends from the input in a section called TRENDS:. If there are less than 50 then collect all of them. Make sure you extract at least 20.
# OUTPUT INSTRUCTIONS
- Only output Markdown.
- Do not output the markdown code syntax, only the content.
- Do not use bold or italics formatting in the markdown output.
- Extract at least 20 TRENDS from the content.
- Do not give warnings or notes; only output the requested sections.
- You use bulleted lists for output, not numbered lists.
- Do not repeat ideas, quotes, facts, or resources.
- Do not start items with the same opening words.
- Ensure you follow ALL these instructions when creating your output.
# INPUT
INPUT:
```
--------------------------------------------------------------------------------
/workbench-app/src/routes/Shares.tsx:
--------------------------------------------------------------------------------
```typescript
// Copyright (c) Microsoft. All rights reserved.
import React from 'react';
import { AppView } from '../components/App/AppView';
import { Loading } from '../components/App/Loading';
import { MyShares } from '../components/Conversations/MyShares';
import { useSiteUtility } from '../libs/useSiteUtility';
import { useGetSharesQuery } from '../services/workbench/share';
export const Shares: React.FC = () => {
const {
data: conversationShares,
error: conversationSharesError,
isLoading: isLoadingConversationShares,
} = useGetSharesQuery({
conversationId: undefined,
includeUnredeemable: false,
});
const siteUtility = useSiteUtility();
siteUtility.setDocumentTitle('Shares');
if (conversationSharesError) {
throw new Error(`Error loading conversation shares: ${JSON.stringify(conversationSharesError)}`);
}
if (isLoadingConversationShares) {
return (
<AppView title="Shares">
<Loading />
</AppView>
);
}
return (
<AppView title="Shares">
<MyShares hideInstruction={true} shares={conversationShares ?? []} />
</AppView>
);
};
```
--------------------------------------------------------------------------------
/workbench-service/semantic_workbench_service/api.py:
--------------------------------------------------------------------------------
```python
import logging
from contextlib import AsyncExitStack, asynccontextmanager
from typing import AsyncContextManager, AsyncGenerator, Callable
from fastapi import FastAPI
logger = logging.getLogger(__name__)
class FastAPILifespan:
def __init__(self) -> None:
self._lifecycle_handlers: list[Callable[[], AsyncContextManager[None]]] = []
def register_handler(self, handler: Callable[[], AsyncContextManager[None]]) -> None:
self._lifecycle_handlers.append(handler)
@asynccontextmanager
async def lifespan(self, app: FastAPI) -> AsyncGenerator[None, None]:
async with AsyncExitStack() as stack:
logger.debug("app lifespan starting up; title: %s, version: %s", app.title, app.version)
for handler in self._lifecycle_handlers:
await stack.enter_async_context(handler())
logger.info("app lifespan started; title: %s, version: %s", app.title, app.version)
try:
yield
finally:
logger.debug("app lifespan shutting down; title: %s, version: %s", app.title, app.version)
logger.info("app lifespan shut down; title: %s, version: %s", app.title, app.version)
```
--------------------------------------------------------------------------------
/assistants/explorer-assistant/pyproject.toml:
--------------------------------------------------------------------------------
```toml
[project]
name = "explorer-assistant"
version = "0.1.0"
description = "A python Semantic Workbench OpenAI assistant for exploring capabilities."
authors = [{ name = "Semantic Workbench Team" }]
readme = "README.md"
requires-python = ">=3.11"
dependencies = [
"anthropic>=0.40.0",
"anthropic-client>=0.1.0",
"assistant-drive>=0.1.0",
"assistant-extensions[attachments]>=0.1.0",
"content-safety>=0.1.0",
"deepmerge>=2.0",
"html2docx>=1.6.0",
"markdown>=3.6",
"openai>=1.61.0",
"openai-client>=0.1.0",
]
[tool.hatch.build.targets.wheel]
packages = ["assistant"]
[tool.uv]
package = true
[tool.uv.sources]
anthropic-client = { path = "../../libraries/python/anthropic-client", editable = true }
assistant-drive = { path = "../../libraries/python/assistant-drive", editable = true }
assistant-extensions = { path = "../../libraries/python/assistant-extensions", editable = true }
content-safety = { path = "../../libraries/python/content-safety/", editable = true }
openai-client = { path = "../../libraries/python/openai-client", editable = true }
[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[dependency-groups]
dev = ["pyright>=1.1.389"]
```
--------------------------------------------------------------------------------
/libraries/python/assistant-data-gen/.vscode/settings.json:
--------------------------------------------------------------------------------
```json
{
"editor.bracketPairColorization.enabled": true,
"editor.codeActionsOnSave": {
"source.organizeImports": "explicit",
"source.fixAll": "explicit"
},
"editor.guides.bracketPairs": "active",
"editor.formatOnPaste": true,
"editor.formatOnType": true,
"editor.formatOnSave": true,
"files.eol": "\n",
"files.trimTrailingWhitespace": true,
"python.analysis.autoFormatStrings": true,
"python.analysis.autoImportCompletions": true,
"python.analysis.diagnosticMode": "workspace",
"python.analysis.fixAll": [
"source.unusedImports"
],
"python.analysis.inlayHints.functionReturnTypes": true,
"python.analysis.typeCheckingMode": "standard",
"python.defaultInterpreterPath": "${workspaceFolder}/.venv",
"python.testing.pytestEnabled": false,
"[python]": {
"editor.defaultFormatter": "charliermarsh.ruff",
"editor.formatOnSave": true,
"editor.codeActionsOnSave": {
"source.fixAll": "explicit",
"source.unusedImports": "explicit",
"source.organizeImports": "explicit",
"source.formatDocument": "explicit"
}
},
"ruff.nativeServer": "on",
"search.exclude": {
"**/.venv": true,
"**/.data": true,
"**/__pycache__": true
},
}
```
--------------------------------------------------------------------------------
/libraries/python/chat-context-toolkit/.vscode/settings.json:
--------------------------------------------------------------------------------
```json
{
"editor.bracketPairColorization.enabled": true,
"editor.codeActionsOnSave": {
"source.organizeImports": "explicit",
"source.fixAll": "explicit"
},
"editor.guides.bracketPairs": "active",
"editor.formatOnPaste": true,
"editor.formatOnType": true,
"editor.formatOnSave": true,
"files.eol": "\n",
"files.trimTrailingWhitespace": true,
"python.analysis.autoFormatStrings": true,
"python.analysis.autoImportCompletions": true,
"python.analysis.diagnosticMode": "workspace",
"python.analysis.fixAll": [
"source.unusedImports"
],
"python.analysis.inlayHints.functionReturnTypes": true,
"python.analysis.typeCheckingMode": "standard",
"python.defaultInterpreterPath": "${workspaceFolder}/.venv",
"python.testing.pytestEnabled": true,
"[python]": {
"editor.defaultFormatter": "charliermarsh.ruff",
"editor.formatOnSave": true,
"editor.codeActionsOnSave": {
"source.fixAll": "explicit",
"source.unusedImports": "explicit",
"source.organizeImports": "explicit",
"source.formatDocument": "explicit"
}
},
"ruff.nativeServer": "on",
"search.exclude": {
"**/.venv": true,
"**/.data": true,
"**/__pycache__": true
},
}
```
--------------------------------------------------------------------------------
/workbench-app/src/components/App/MenuItemControl.tsx:
--------------------------------------------------------------------------------
```typescript
// Copyright (c) Microsoft. All rights reserved.
import { ButtonProps, MenuItem } from '@fluentui/react-components';
import React from 'react';
import { TooltipWrapper } from './TooltipWrapper';
type MenuItemControlProps = ButtonProps & {
label?: string;
description?: string;
onClick?: () => void;
iconOnly?: boolean;
};
export const MenuItemControl: React.FC<MenuItemControlProps> = (props) => {
const { disabled, icon, label, description, onClick, iconOnly } = props;
let menuItem = null;
if (iconOnly) {
if (description) {
menuItem = (
<TooltipWrapper content={description}>
<MenuItem disabled={disabled} icon={icon} onClick={onClick} />
</TooltipWrapper>
);
} else {
menuItem = <MenuItem disabled={disabled} icon={icon} onClick={onClick} />;
}
} else {
menuItem = (
<MenuItem disabled={disabled} icon={icon} onClick={onClick}>
{label}
</MenuItem>
);
if (description) {
menuItem = <TooltipWrapper content={description}>{menuItem}</TooltipWrapper>;
}
}
return menuItem;
};
```
--------------------------------------------------------------------------------
/assistants/navigator-assistant/assistant/response/local_tool/model.py:
--------------------------------------------------------------------------------
```python
from typing import Any, Awaitable, Callable, Generic, TypeVar
from attr import dataclass
from pydantic import BaseModel, ValidationError
from semantic_workbench_assistant.assistant_app import ConversationContext
from ..utils import ExecutableTool
ToolArgumentModelT = TypeVar("ToolArgumentModelT", bound=BaseModel)
@dataclass
class LocalTool(Generic[ToolArgumentModelT]):
name: str
argument_model: type[ToolArgumentModelT]
func: Callable[[ToolArgumentModelT, ConversationContext], Awaitable[str]]
description: str = ""
def to_executable(self) -> ExecutableTool:
async def func(context: ConversationContext, arguments: dict[str, Any]) -> str:
try:
typed_argument = self.argument_model.model_validate(arguments)
except ValidationError as e:
content = f"Error validating local tool call arguments: {e}"
else:
content = await self.func(typed_argument, context)
return content
return ExecutableTool(
name=self.name,
description=self.description or self.func.__doc__ or "",
parameters=self.argument_model.model_json_schema(),
func=func,
)
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/skills/fabric/patterns/analyze_proposition/system.md:
--------------------------------------------------------------------------------
```markdown
# IDENTITY and PURPOSE
You are an AI assistant whose primary responsibility is to analyze a federal, state, or local ballot proposition. You will meticulously examine the proposition to identify key elements such as the purpose, potential impact, arguments for and against, and any relevant background information. Your goal is to provide a comprehensive analysis that helps users understand the implications of the ballot proposition.
Take a step back and think step-by-step about how to achieve the best possible results by following the steps below.
# STEPS
- Identify the key components of a federal, state, or local ballot propositions.
- Develop a framework for analyzing the purpose of the proposition.
- Assess the potential impact of the proposition if passed.
- Compile arguments for and against the proposition.
- Gather relevant background information and context.
- Organize the analysis in a clear and structured format.
# OUTPUT INSTRUCTIONS
- Only output Markdown.
- All sections should be Heading level 1.
- Subsections should be one Heading level higher than its parent section.
- All bullets should have their own paragraph.
- Ensure you follow ALL these instructions when creating your output.
# INPUT
INPUT:
```
--------------------------------------------------------------------------------
/workbench-app/src/components/Conversations/Message/AttachmentSection.tsx:
--------------------------------------------------------------------------------
```typescript
import { Attachment, AttachmentList } from '@fluentui-copilot/react-copilot';
import { makeStyles, mergeClasses, tokens } from '@fluentui/react-components';
import React from 'react';
import { TooltipWrapper } from '../../App/TooltipWrapper';
import { ConversationFileIcon } from '../ConversationFileIcon';
const useClasses = makeStyles({
root: {
display: 'flex',
flexDirection: 'column',
gap: tokens.spacingVerticalS,
},
});
interface AttachmentSectionProps {
filenames?: string[];
className?: string;
}
export const AttachmentSection: React.FC<AttachmentSectionProps> = (props) => {
const { filenames, className } = props;
const classes = useClasses();
const attachmentList =
filenames && filenames.length > 0 ? (
<AttachmentList>
{filenames.map((filename) => (
<TooltipWrapper content={filename} key={filename}>
<Attachment media={<ConversationFileIcon file={filename} />} content={filename} />
</TooltipWrapper>
))}
</AttachmentList>
) : null;
return <div className={mergeClasses(classes.root, className)}>{attachmentList}</div>;
};
```
--------------------------------------------------------------------------------
/mcp-servers/mcp-server-template/copier.yml:
--------------------------------------------------------------------------------
```yaml
_subdirectory: template
_tasks:
# format files after copying
- "make format"
short_name:
type: str
help: >
The short name for your MCP server, will have "MCP Server" appended in
README.md and other mentions.
default: Hello World
description:
type: str
help: A short description of your MCP server functionality.
project_slug:
type: str
help: The terminal-friendly and PyPi-friendly name for your project (dashes instead of spaces).
default: mcp-server-{{ short_name.lower().replace(' ', '-') }}
module_name:
type: str
help: The code-friendly name for your module (underscores instead of dashes or spaces).
default: "{{ project_slug.lower().replace('-', '_') }}"
author_name:
type: str
help: The person or entity to list as the author in the project package.
default: Semantic Workbench Team
default_port:
type: int
help: What is the default port to configure your MCP server to run on?
use_mcp_env_vars:
type: bool
help: >
Will your MCP server require env vars passed from MCP clients, such as
API keys or other client provided configuration values?
default: false
mcp_env_vars:
type: yaml
when: "{{ use_mcp_env_vars }}"
help: List the required env vars.
default: []
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/skills/fabric/patterns/summarize/dmiessler/summarize/system.md:
--------------------------------------------------------------------------------
```markdown
# IDENTITY and PURPOSE
You are a summarization system that extracts the most interesting, useful, and surprising aspects of an article.
Take a step back and think step by step about how to achieve the best result possible as defined in the steps below. You have a lot of freedom to make this work well.
## OUTPUT SECTIONS
1. You extract a summary of the content in 20 words or less, including who is presenting and the content being discussed into a section called SUMMARY.
2. You extract the top 20 ideas from the input in a section called IDEAS:.
3. You extract the 10 most insightful and interesting quotes from the input into a section called QUOTES:. Use the exact quote text from the input.
4. You extract the 20 most insightful and interesting recommendations that can be collected from the content into a section called RECOMMENDATIONS.
5. You combine all understanding of the article into a single, 20-word sentence in a section called ONE SENTENCE SUMMARY:.
## OUTPUT INSTRUCTIONS
1. You only output Markdown.
2. Do not give warnings or notes; only output the requested sections.
3. You use numbered lists, not bullets.
4. Do not repeat ideas, quotes, facts, or resources.
5. Do not start items with the same opening words.
```
--------------------------------------------------------------------------------
/workbench-app/src/components/Conversations/ConversationShareList.tsx:
--------------------------------------------------------------------------------
```typescript
// Copyright (c) Microsoft. All rights reserved.
import React from 'react';
import { Conversation } from '../../models/Conversation';
import { useGetSharesQuery } from '../../services/workbench/share';
import { Loading } from '../App/Loading';
import { MyShares } from './MyShares';
interface ConversationShareListProps {
conversation: Conversation;
}
export const ConversationShareList: React.FC<ConversationShareListProps> = (props) => {
const { conversation } = props;
const {
data: conversationShares,
error: conversationSharesError,
isLoading: conversationSharesLoading,
} = useGetSharesQuery({
conversationId: conversation.id,
includeUnredeemable: false,
});
if (!conversation) {
throw new Error('Conversation is required');
}
if (conversationSharesError) {
throw new Error(`Error loading conversation shares: ${JSON.stringify(conversationSharesError)}`);
}
if (conversationSharesLoading || !conversationShares) {
return <Loading />;
}
return (
<MyShares
conversation={conversation}
shares={conversationShares}
title={`Shares for "${conversation.title}"`}
/>
);
};
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/skills/fabric/patterns/extract_book_recommendations/system.md:
--------------------------------------------------------------------------------
```markdown
# IDENTITY and PURPOSE
You take a book name as an input and output a full summary of the book's most important content using the steps and instructions below.
Take a step back and think step-by-step about how to achieve the best possible results by following the steps below.
# STEPS
- Scour your memory for everything you know about this book.
- Extract 50 to 100 of the most practical RECOMMENDATIONS from the input in a section called RECOMMENDATIONS:. If there are less than 50 then collect all of them. Make sure you extract at least 20.
# OUTPUT INSTRUCTIONS
- Only output Markdown.
- Order the recommendations by the most powerful and important ones first.
- Write all recommendations as instructive advice, not abstract ideas.
- Extract at least 50 RECOMMENDATIONS from the content.
- Extract up to 100 RECOMMENDATIONS.
- Limit each bullet to a maximum of 20 words.
- Do not give warnings or notes; only output the requested sections.
- Do not repeat IDEAS.
- Vary the wording of the IDEAS.
- Don't repeat the same IDEAS over and over, even if you're using different wording.
- You use bulleted lists for output, not numbered lists.
- Ensure you follow ALL these instructions when creating your output.
# INPUT
INPUT:
```
--------------------------------------------------------------------------------
/workbench-app/src/components/Conversations/Message/MessageContent.tsx:
--------------------------------------------------------------------------------
```typescript
import React from 'react';
import { Conversation } from '../../../models/Conversation';
import { ConversationMessage } from '../../../models/ConversationMessage';
import { useCreateConversationMessageMutation } from '../../../services/workbench';
import { ContentRenderer } from '../ContentRenderers/ContentRenderer';
interface MessageContentProps {
conversation: Conversation;
message: ConversationMessage;
}
export const MessageContent: React.FC<MessageContentProps> = (props) => {
const { conversation, message } = props;
const [createConversationMessage] = useCreateConversationMessageMutation();
const onSubmit = async (data: string) => {
if (message.metadata?.command) {
await createConversationMessage({
conversationId: conversation.id,
content: JSON.stringify({
command: message.metadata.command,
parameters: data,
}),
messageType: 'command',
});
}
};
return (
<ContentRenderer
content={message.content}
contentType={message.contentType}
metadata={message.metadata}
onSubmit={onSubmit}
/>
);
};
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/skills/fabric/patterns/analyze_candidates/system.md:
--------------------------------------------------------------------------------
```markdown
# IDENTITY and PURPOSE
You are an AI assistant whose primary responsibility is to create a pattern that analyzes and compares two running candidates. You will meticulously examine each candidate's stances on key issues, highlight the pros and cons of their policies, and provide relevant background information. Your goal is to offer a comprehensive comparison that helps users understand the differences and similarities between the candidates.
Take a step back and think step-by-step about how to achieve the best possible results by following the steps below.
# STEPS
- Identify the key issues relevant to the election.
- Gather detailed information on each candidate's stance on these issues.
- Analyze the pros and cons of each candidate's policies.
- Compile background information that may influence their positions.
- Compare and contrast the candidates' stances and policy implications.
- Organize the analysis in a clear and structured format.
# OUTPUT INSTRUCTIONS
- Only output Markdown.
- All sections should be Heading level 1.
- Subsections should be one Heading level higher than its parent section.
- All bullets should have their own paragraph.
- Ensure you follow ALL these instructions when creating your output.
# INPUT
INPUT:
```
--------------------------------------------------------------------------------
/assistants/project-assistant/assistant/tools/todo.py:
--------------------------------------------------------------------------------
```python
import uuid
from enum import Enum
from pydantic import BaseModel, Field
class ToDoItemStatus(Enum):
"""
Enum for the status of a to-do item.
"""
PENDING = "pending"
IN_PROGRESS = "in_progress"
COMPLETED = "completed"
class ToDoItemPriority(Enum):
"""
Enum for the priority of a to-do item.
"""
HIGH = "high"
MEDIUM = "medium"
LOW = "low"
class ToDoItem(BaseModel):
"""
A class to represent a single to-do item.
"""
id: str = Field(default_factory=lambda: str(uuid.uuid4())) # Unique identifier
content: str
priority: str = "medium" # Default priority is 'medium'
status: str = "pending" # Default status is 'pending'
class ToDoList(BaseModel):
"""
A class to represent a to-do list.
"""
items: list[ToDoItem] = Field(default_factory=list)
def add(self, todo: ToDoItem) -> None:
"""
Add a new to-do item.
"""
self.items.append(todo)
def remove(self, id: str) -> None:
"""
Remove a to-do item.
"""
self.items = [item for item in self.items if item.id != id]
def list(self) -> list[ToDoItem]:
"""
List all to-do items.
"""
return self.items
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/skills/common/routines/get_content_from_url.py:
--------------------------------------------------------------------------------
```python
from typing import Any
import requests
from bs4 import BeautifulSoup
from skill_library import AskUserFn, EmitFn, RunContext, RunRoutineFn
from skill_library.logging import extra_data, logger
TIMEOUT_SECONDS = 5
async def main(
context: RunContext,
routine_state: dict[str, Any],
emit: EmitFn,
run: RunRoutineFn,
ask_user: AskUserFn,
url: str,
max_length: int | None = None,
) -> str:
"""Get the content from a webpage."""
try:
logger.debug("get_content_from_url", extra_data({"url": url}))
response = requests.get(url, timeout=TIMEOUT_SECONDS)
if response.status_code >= 200 and response.status_code < 300:
soup = BeautifulSoup(response.text, "html.parser")
content = soup.get_text(separator="\n", strip=True)
if max_length and len(content) > max_length:
return content[:max_length]
else:
return content
else:
return f"Error retrieving content from URL: `{response.status_code}`."
except requests.Timeout:
return f"Error retrieving content from URL: `Timeout` after {TIMEOUT_SECONDS} seconds."
except Exception as e:
return f"Error retrieving content from URL: `{e}`."
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/skills/fabric/patterns/coding_master/system.md:
--------------------------------------------------------------------------------
```markdown
**Expert coder**
You are an expert in understanding and digesting computer coding and computer languages.
Explain the concept of [insert specific coding concept or language here] as if you
were teaching it to a beginner. Use examples from reputable sources like Codeacademy (codeacademy.com) and NetworkChuck to illustrate your points.
**Coding output**
Please format the code in a markdown method using syntax
also please illustrate the code in this format:
``` your code
Your code here
```
**OUTPUT INSTRUCTIONS**
Only output Markdown.
Write the IDEAS bullets as exactly 16 words.
Write the RECOMMENDATIONS bullets as exactly 16 words.
Write the HABITS bullets as exactly 16 words.
Write the FACTS bullets as exactly 16 words.
Write the INSIGHTS bullets as exactly 16 words.
Extract at least 25 IDEAS from the content.
Extract at least 10 INSIGHTS from the content.
Extract at least 20 items for the other output sections.
Do not give warnings or notes; only output the requested sections.
You use bulleted lists for output, not numbered lists.
Do not repeat ideas, quotes, facts, or resources.
Do not start items with the same opening words.
Ensure you follow ALL these instructions when creating your output.
**INPUT**
INPUT:
```
--------------------------------------------------------------------------------
/assistants/knowledge-transfer-assistant/assistant/storage_models.py:
--------------------------------------------------------------------------------
```python
"""
Models for knowledge transfer share storage entities.
This module contains data models specific to storage operations,
separate from the core share data models.
"""
from datetime import datetime
from enum import Enum
from typing import List
from pydantic import BaseModel, Field
class ConversationRole(str, Enum):
"""
Enumeration of conversation roles in a knowledge transfer.
This enum represents the role that a conversation plays in a knowledge transfer,
either as a Coordinator (managing the knowledge transfer) or as a Team member
(participating in the knowledge transfer).
"""
COORDINATOR = "coordinator"
TEAM = "team"
class CoordinatorConversationMessage(BaseModel):
"""Model for storing a message from Coordinator conversation for Team access."""
message_id: str
content: str
sender_name: str
timestamp: datetime = Field(default_factory=datetime.utcnow)
is_assistant: bool = False
class CoordinatorConversationStorage(BaseModel):
"""Model for storing a collection of Coordinator conversation messages."""
knowledge_share_id: str
last_updated: datetime = Field(default_factory=datetime.utcnow)
messages: List[CoordinatorConversationMessage] = Field(default_factory=list)
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/skills/fabric/patterns/extract_core_message/system.md:
--------------------------------------------------------------------------------
```markdown
# IDENTITY
You are an expert at looking at a presentation, an essay, or a full body of lifetime work, and clearly and accurately articulating what the core message is.
# GOAL
- Produce a clear sentence that perfectly articulates the core message as presented in a given text or body of work.
# EXAMPLE
If the input is all of Victor Frankl's work, then the core message would be:
Finding meaning in suffering is key to human resilience, purpose, and enduring life’s challenges.
END EXAMPLE
# STEPS
- Fully digest the input.
- Determine if the input is a single text or a body of work.
- Based on which it is, parse the thing that's supposed to be parsed.
- Extract the core message from the parsed text into a single sentence.
# OUTPUT
- Output a single, 15-word sentence that perfectly articulates the core message as presented in the input.
# OUTPUT INSTRUCTIONS
- The sentence should be a single sentence that is 16 words or fewer, with no special formatting or anything else.
- Do not include any setup to the sentence, e.g., "The core message is to…", etc. Just list the core message and nothing else.
- ONLY OUTPUT THE CORE MESSAGE, not a setup to it, commentary on it, or anything else.
- Do not ask questions or complain in any way about the task.
```
--------------------------------------------------------------------------------
/examples/python/python-01-echo-bot/assistant/config.py:
--------------------------------------------------------------------------------
```python
from typing import Annotated
from pydantic import BaseModel, Field
from semantic_workbench_assistant.config import UISchema
# The semantic workbench app uses react-jsonschema-form for rendering
# dyanmic configuration forms based on the configuration model and UI schema
# See: https://rjsf-team.github.io/react-jsonschema-form/docs/
# Playground / examples: https://rjsf-team.github.io/react-jsonschema-form/
# The UI schema can be used to customize the appearance of the form. Use
# the UISchema class to define the UI schema for specific fields in the
# configuration model.
# the workbench app builds dynamic forms based on the configuration model and UI schema
class AssistantConfigModel(BaseModel):
enable_debug_output: Annotated[
bool,
Field(
title="Include Debug Output",
description="Include debug output on conversation messages.",
),
] = False
welcome_message: Annotated[
str,
Field(
title="Welcome Message",
description="The message to display when the conversation starts.",
),
UISchema(
widget="textarea",
),
] = "Hello! I am an echo example, I will repeat what you say."
# add any additional configuration fields
```
--------------------------------------------------------------------------------
/workbench-app/src/components/App/AppMenu.tsx:
--------------------------------------------------------------------------------
```typescript
// Copyright (c) Microsoft. All rights reserved.
import { Button, Menu, MenuItem, MenuList, MenuPopover, MenuTrigger } from '@fluentui/react-components';
import { MoreHorizontal24Regular, Settings24Regular, Share24Regular } from '@fluentui/react-icons';
import React from 'react';
import { useNavigate } from 'react-router-dom';
export const AppMenu: React.FC = () => {
const navigate = useNavigate();
return (
<Menu>
<MenuTrigger disableButtonEnhancement>
<Button icon={<MoreHorizontal24Regular />} />
</MenuTrigger>
<MenuPopover>
<MenuList>
<MenuItem
icon={<Share24Regular />}
onClick={() => {
navigate('/shares');
}}
>
Shares
</MenuItem>
<MenuItem
icon={<Settings24Regular />}
onClick={() => {
navigate('/settings');
}}
>
Settings
</MenuItem>
</MenuList>
</MenuPopover>
</Menu>
);
};
```
--------------------------------------------------------------------------------
/assistants/navigator-assistant/pyproject.toml:
--------------------------------------------------------------------------------
```toml
[project]
name = "navigator-assistant"
version = "0.1.0"
description = "A python Semantic Workbench OpenAI assistant for navigating the workbench and assistants."
authors = [{ name = "Semantic Workbench Team" }]
readme = "README.md"
requires-python = ">=3.11,<3.13"
dependencies = [
"assistant-drive>=0.1.0",
"assistant-extensions[attachments, mcp]>=0.1.0",
"mcp-extensions[openai]>=0.1.0",
"content-safety>=0.1.0",
"deepmerge>=2.0",
"openai>=1.61.0",
"openai-client>=0.1.0",
"tiktoken>=0.8.0",
]
[tool.hatch.build.targets.wheel]
packages = ["assistant"]
[tool.uv]
package = true
[tool.uv.sources]
anthropic-client = { path = "../../libraries/python/anthropic-client", editable = true }
assistant-drive = { path = "../../libraries/python/assistant-drive", editable = true }
assistant-extensions = { path = "../../libraries/python/assistant-extensions", editable = true }
mcp-extensions = { path = "../../libraries/python/mcp-extensions", editable = true }
content-safety = { path = "../../libraries/python/content-safety/", editable = true }
openai-client = { path = "../../libraries/python/openai-client", editable = true }
[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[dependency-groups]
dev = ["pyright>=1.1.389"]
```
--------------------------------------------------------------------------------
/mcp-servers/mcp-server-giphy/mcp_server/server.py:
--------------------------------------------------------------------------------
```python
from typing import Optional
from mcp.server.fastmcp import Context, FastMCP
from .config import settings
from .giphy_search import perform_search
# Set the name of the MCP server
server_name = "GIPHY MCP Server"
def create_mcp_server() -> FastMCP:
# Initialize FastMCP with debug logging.
mcp = FastMCP(name=server_name, log_level=settings.log_level)
@mcp.tool()
async def giphy_search(context: str, search_term: str, ctx: Context) -> Optional[dict]:
"""
A specialized team member that searches the GIPHY database for GIFs based on your search term.
Use them to find the perfect GIF to express your thoughts or feelings. Provide as much context
as possible to help them understand the context of your search. Your search term should be a
specific keyword or phrase that describes the GIF you're looking for. For context, pass as
much background as you can: if using this tool in a conversation, include the conversation
history; if in a broader context, include any relevant documents or details. If there is no
context, pass “None.”
"""
# Perform search using context and search term
return await perform_search(context=context, search_term=search_term, ctx=ctx)
return mcp
```
--------------------------------------------------------------------------------
/libraries/python/semantic-workbench-assistant/pyproject.toml:
--------------------------------------------------------------------------------
```toml
[project]
name = "semantic-workbench-assistant"
version = "0.1.0"
description = "Library for facilitating the implementation of FastAPI-based Semantic Workbench assistants."
authors = [{ name = "Semantic Workbench Team" }]
readme = "README.md"
requires-python = ">=3.11"
dependencies = [
"asgi-correlation-id>=4.3.1",
"backoff>=2.2.1",
"fastapi[standard]~=0.115.0",
"pydantic-settings>=2.2.0",
"python-json-logger>=2.0.7",
"rich>=13.7.0",
"deepmerge>=2.0",
"semantic-workbench-api-model>=0.1.0",
]
[dependency-groups]
dev = [
"asgi-lifespan>=2.1.0",
"pyright>=1.1.389",
"pytest>=7.4.3",
"pytest-asyncio>=0.23.5.post1",
"pytest-httpx>=0.30.0",
]
[tool.uv.sources]
semantic-workbench-api-model = { path = "../semantic-workbench-api-model", editable = true }
[project.scripts]
start-semantic-workbench-assistant = "semantic_workbench_assistant.start:main"
start-assistant = "semantic_workbench_assistant.start:main"
[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[tool.pytest.ini_options]
addopts = "-vv"
log_cli = true
log_cli_level = "WARNING"
log_cli_format = "%(asctime)s | %(levelname)-7s | %(name)s | %(message)s"
testpaths = ["tests"]
asyncio_mode = "auto"
asyncio_default_fixture_loop_scope = "function"
```
--------------------------------------------------------------------------------
/libraries/python/mcp-extensions/mcp_extensions/__init__.py:
--------------------------------------------------------------------------------
```python
from ._client_session import (
ExtendedClientSession,
ListResourcesFnT,
ReadResourceFnT,
WriteResourceFnT,
WriteResourceRequest,
WriteResourceRequestParams,
WriteResourceResult,
)
from ._model import ServerNotificationHandler, ToolCallFunction, ToolCallProgressMessage
from ._sampling import send_sampling_request
from ._server_extensions import list_client_resources, read_client_resource, write_client_resource
from ._tool_utils import (
convert_tools_to_openai_tools,
execute_tool_with_retries,
send_tool_call_progress,
)
# Exported utilities and models for external use.
# These components enhance interactions with MCP workflows by providing utilities for notifications,
# progress updates, and tool conversion specific to the MCP ecosystem.
__all__ = [
"convert_tools_to_openai_tools",
"execute_tool_with_retries",
"list_client_resources",
"read_client_resource",
"write_client_resource",
"send_sampling_request",
"send_tool_call_progress",
"ServerNotificationHandler",
"ToolCallFunction",
"ToolCallProgressMessage",
"ExtendedClientSession",
"ListResourcesFnT",
"ReadResourceFnT",
"WriteResourceFnT",
"WriteResourceRequest",
"WriteResourceRequestParams",
"WriteResourceResult",
]
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/docs/vs-recipe-tool.md:
--------------------------------------------------------------------------------
```markdown
# Comparison
## Comparing implementations
### Recipe Executor
- All input/output through context dict and files. Context mutation is opaque and buried in each step.
- Program flow through state machine flow diagram written in JSON. No Python available. Each step encodes its own.
- Sub-recipes through `execute_recipe` step.
- Control flow including `Loop` and `Conditional` steps.
- Packages recipes in sets (directories).
- No stack for running recipes (but one could be introduced to "see" where we are in control flow)
- "ask" handled by writing to files (how does resume work?)
- Interacts with the filesystem directly.
- Misc
- More directly focused on driving LLMs. Includes tools for handling prompts and prompt context.
### Routine Library
- Input/output through python args. Transparent.
- Program flow through program written in Python. All non-external functions are available. No separate "steps".
- Subroutines through `run` function.
- Control flow using Python.
- Packages routines in skills (dynamically-loaded Python packages)
- A stack for running subroutines with variable scope (vs. a general context bucket).
- "ask" handled by pausing control flow, resumes with answer
- uses `Drive` for interacting with the filesystem.
- Misc
- Focused on routines. LLM-agnostic.
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/skills/fabric/patterns/check_agreement/system.md:
--------------------------------------------------------------------------------
```markdown
# IDENTITY and PURPOSE
You are an expert at analyzing contracts and agreements and looking for gotchas. You take a document in and output a Markdown formatted summary using the format below.
Take a deep breath and think step by step about how to best accomplish this goal using the following steps.
# OUTPUT SECTIONS
- Combine all of your understanding of the content into a single, 30-word sentence in a section called DOCUMENT SUMMARY:.
- Output the 10 most important aspects, stipulations, and other types of gotchas in the content as a list with no more than 20 words per point into a section called CALLOUTS:.
- Output the 10 most important issues to be aware of before agreeing to the document, organized in three sections: CRITICAL:, IMPORTANT:, and OTHER:.
- For each of the CRITICAL and IMPORTANT items identified, write a request to be sent to the sending organization recommending it be changed or removed. Place this in a section called RESPONSES:.
# OUTPUT INSTRUCTIONS
- Create the output using the formatting above.
- You only output human readable Markdown.
- Output numbered lists, not bullets.
- Do not output warnings or notes—just the requested sections.
- Do not repeat items in the output sections.
- Do not start items with the same opening words.
# INPUT:
INPUT:
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/skills/fabric/patterns/recommend_artists/system.md:
--------------------------------------------------------------------------------
```markdown
# IDENTITY
You are an EDM expert who specializes in identifying artists that I will like based on the input of a list of artists at a festival. You output a list of artists and a proposed schedule based on the input of set times and artists.
# GOAL
- Recommend the perfect list of people and schedule to see at a festival that I'm most likely to enjoy.
# STEPS
- Look at the whole list of artists.
- Look at my list of favorite styles and artists below.
- Recommend similar artists, and the reason you think I will like them.
# MY FAVORITE STYLES AND ARTISTS
### Styles
- Dark menacing techno
- Hard techno
- Intricate minimal techno
- Hardstyle that sounds dangerous
### Artists
- Sarah Landry
- Fisher
- Boris Brejcha
- Technoboy
- Optimize your selections based on how much I'll love the artists, not anything else.
- If the artist themselves are playing, make sure you have them on the schedule.
# OUTPUT
- Output a schedule of where to be and when based on the best matched artists, along with the explanation of why them.
- Organize the output format by day, set time, then stage, then artist.
- Optimize your selections based on how much I'll love the artists, not anything else.
- Output in Markdown, but make it easy to read in text form, so no asterisks, bold or italic.
```
--------------------------------------------------------------------------------
/workbench-app/src/components/Conversations/ContentRenderers/CodeContentRenderer.tsx:
--------------------------------------------------------------------------------
```typescript
// Copyright (c) Microsoft. All rights reserved.
import { makeStyles, tokens } from '@fluentui/react-components';
import React from 'react';
import SyntaxHighlighter from 'react-syntax-highlighter';
import { stackoverflowLight as syntaxHighlighterStyle } from 'react-syntax-highlighter/dist/esm/styles/hljs';
import { CopyButton } from '../../App/CopyButton';
const useClasses = makeStyles({
root: {
position: 'relative',
},
copy: {
position: 'absolute',
right: tokens.spacingHorizontalXS,
top: tokens.spacingVerticalXS,
},
});
interface CodeContentRendererProps {
content: string;
language: string;
}
export const CodeContentRenderer: React.FC<CodeContentRendererProps> = (props) => {
const { content, language } = props;
const classes = useClasses();
return (
<div className={classes.root}>
<div className={classes.copy}>
<CopyButton data={content}></CopyButton>
</div>
<SyntaxHighlighter
PreTag="div"
language={language}
style={syntaxHighlighterStyle}
wrapLongLines
// eslint-disable-next-line react/no-children-prop
children={content}
/>
</div>
);
};
```
--------------------------------------------------------------------------------
/workbench-app/src/components/Conversations/ConversationsImport.tsx:
--------------------------------------------------------------------------------
```typescript
// Copyright (c) Microsoft. All rights reserved.
import React from 'react';
import { useWorkbenchService } from '../../libs/useWorkbenchService';
import { ContentImport } from '../App/ContentImport';
interface ConversationsImportProps {
disabled?: boolean;
iconOnly?: boolean;
asToolbarButton?: boolean;
appearance?: 'primary' | 'secondary' | 'outline' | 'subtle' | 'transparent';
size?: 'small' | 'medium' | 'large';
onImport?: (conversationIds: string[]) => void;
onError?: (error: Error) => void;
}
export const ConversationsImport: React.FC<ConversationsImportProps> = (props) => {
const { disabled, iconOnly, asToolbarButton, appearance, size, onImport, onError } = props;
const workbenchService = useWorkbenchService();
const importFile = async (file: File) => {
const result = await workbenchService.importConversationsAsync(file);
return result.conversationIds;
};
return (
<ContentImport
contentTypeLabel="conversations"
importFunction={importFile}
onImport={onImport}
onError={onError}
disabled={disabled}
iconOnly={iconOnly}
asToolbarButton={asToolbarButton}
appearance={appearance}
size={size}
/>
);
};
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/skills/fabric/patterns/extract_sponsors/system.md:
--------------------------------------------------------------------------------
```markdown
# IDENTITY and PURPOSE
You are an expert at extracting the sponsors and potential sponsors from a given transcript, such a from a podcast, video transcript, essay, or whatever.
# Steps
- Consume the whole transcript so you understand what is content, what is meta information, etc.
- Discern the difference between companies that were mentioned and companies that actually sponsored the podcast or video.
- Output the following:
## OFFICIAL SPONSORS
- $SOURCE_CHANNEL$ | $SPONSOR1$ | $SPONSOR1_DESCRIPTION$ | $SPONSOR1_LINK$
- $SOURCE_CHANNEL$ | $SPONSOR2$ | $SPONSOR2_DESCRIPTION$ | $SPONSOR2_LINK$
- $SOURCE_CHANNEL$ | $SPONSOR3$ | $SPONSOR3_DESCRIPTION$ | $SPONSOR3_LINK$
- And so on…
# EXAMPLE OUTPUT
## OFFICIAL SPONSORS
- Flair | Flair is a threat intel platform powered by AI. | https://flair.ai
- Weaviate | Weviate is an open-source knowledge graph powered by ML. | https://weaviate.com
- JunaAI | JunaAI is a platform for AI-powered content creation. | https://junaai.com
- JunaAI | JunaAI is a platform for AI-powered content creation. | https://junaai.com
## END EXAMPLE OUTPUT
# OUTPUT INSTRUCTIONS
- The official sponsor list should only include companies that officially sponsored the content in question.
- Do not output warnings or notes—just the requested sections.
# INPUT:
INPUT:
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/skills/fabric/patterns/solve_with_cot/system.md:
--------------------------------------------------------------------------------
```markdown
# IDENTITY
You are an AI assistant designed to provide detailed, step-by-step responses. Your outputs should follow this structure:
# STEPS
1. Begin with a <thinking> section.
2. Inside the thinking section:
- a. Briefly analyze the question and outline your approach.
- b. Present a clear plan of steps to solve the problem.
- c. Use a "Chain of Thought" reasoning process if necessary, breaking down your thought process into numbered steps.
3. Include a <reflection> section for each idea where you:
- a. Review your reasoning.
- b. Check for potential errors or oversights.
- c. Confirm or adjust your conclusion if necessary.
- Be sure to close all reflection sections.
- Close the thinking section with </thinking>.
- Provide your final answer in an <output> section.
Always use these tags in your responses. Be thorough in your explanations, showing each step of your reasoning process.
Aim to be precise and logical in your approach, and don't hesitate to break down complex problems into simpler components.
Your tone should be analytical and slightly formal, focusing on clear communication of your thought process.
Remember: Both <thinking> and <reflection> MUST be tags and must be closed at their conclusion.
Make sure all <tags> are on separate lines with no other text.
# INPUT
INPUT:
```
--------------------------------------------------------------------------------
/aspire-orchestrator/Aspire.Extensions/DockerFileExtensions.cs:
--------------------------------------------------------------------------------
```csharp
// Copyright (c) Microsoft. All rights reserved.
namespace Aspire.Hosting;
public static class DockerFileExtensions
{
public static IResourceBuilder<ExecutableResource> PublishAsDockerImage(this IResourceBuilder<ExecutableResource> builder,
string? dockerContext = null,
string? dockerFilePath = "Dockerfile",
Action<IResourceBuilder<ContainerResource>>? configure = null)
{
if (!builder.ApplicationBuilder.ExecutionContext.IsPublishMode)
{
return builder;
}
// Bait and switch the ExecutableResource with a ContainerResource
builder.ApplicationBuilder.Resources.Remove(builder.Resource);
var container = new ExecutableContainerResource(builder.Resource);
var cb = builder.ApplicationBuilder.AddResource(container);
cb.WithImage(builder.Resource.Name);
cb.WithDockerfile(contextPath: dockerContext ?? builder.Resource.WorkingDirectory, dockerfilePath: dockerFilePath);
// Clear the runtime args
cb.WithArgs(c => c.Args.Clear());
configure?.Invoke(cb);
return builder;
}
private sealed class ExecutableContainerResource(ExecutableResource er) : ContainerResource(er.Name)
{
public override ResourceAnnotationCollection Annotations => er.Annotations;
}
}
```
--------------------------------------------------------------------------------
/libraries/python/mcp-extensions/mcp_extensions/llm/chat_completion.py:
--------------------------------------------------------------------------------
```python
# Copyright (c) Microsoft. All rights reserved.
from typing import Any, Callable
from mcp.server.fastmcp import Context
from mcp_extensions.llm.llm_types import ChatCompletionRequest, ChatCompletionResponse
from mcp_extensions.llm.mcp_chat_completion import mcp_chat_completion
from mcp_extensions.llm.openai_chat_completion import openai_chat_completion
async def chat_completion(
request: ChatCompletionRequest,
provider: str,
client: Callable[..., Any] | Context,
) -> ChatCompletionResponse:
"""Get a chat completion response from the given provider. Currently supported providers:
- `azure_openai` - Azure OpenAI
- `mcp` - MCP Sampling
Args:
request: Request parameter object
provider: The supported provider name
client: Client information, see the provider's implementation for what can be provided
Returns:
ChatCompletionResponse: The chat completion response.
"""
if (provider == "openai" or provider == "azure_openai" or provider == "dev") and isinstance(client, Callable):
return openai_chat_completion(request, client)
elif provider == "mcp" and isinstance(client, Context):
return await mcp_chat_completion(request, client)
else:
raise ValueError(f"Provider {provider} not supported or client is of the wrong type")
```
--------------------------------------------------------------------------------
/assistants/knowledge-transfer-assistant/pyproject.toml:
--------------------------------------------------------------------------------
```toml
[project]
name = "assistant"
version = "0.1.0"
description = "A file-sharing mediator assistant for collaborative projects."
authors = [{ name = "Semantic Workbench Team" }]
readme = "README.md"
requires-python = ">=3.11"
dependencies = [
"assistant-extensions[attachments]>=0.1.0",
"content-safety>=0.1.0",
"openai>=1.61.0",
"openai-client>=0.1.0",
"semantic-workbench-assistant>=0.1.0",
]
[dependency-groups]
dev = [
"pytest>=8.3.1",
"pytest-asyncio>=0.23.8",
"pytest-repeat>=0.9.3",
"pyright>=1.1.389",
]
[tool.uv]
package = true
[tool.uv.sources]
assistant-extensions = { path = "../../libraries/python/assistant-extensions", editable = true }
content-safety = { path = "../../libraries/python/content-safety/", editable = true }
openai-client = { path = "../../libraries/python/openai-client", editable = true }
semantic-workbench-assistant = { path = "../../libraries/python/semantic-workbench-assistant", editable = true }
[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[tool.pyright]
exclude = ["**/.venv", "**/.data", "**/__pycache__"]
[tool.pytest.ini_options]
addopts = "-vv"
log_cli = true
log_cli_level = "WARNING"
log_cli_format = "%(asctime)s | %(levelname)-7s | %(name)s | %(message)s"
asyncio_mode = "auto"
asyncio_default_fixture_loop_scope = "function"
```
--------------------------------------------------------------------------------
/workbench-app/src/components/FrontDoor/GlobalContent.tsx:
--------------------------------------------------------------------------------
```typescript
// Copyright (c) Microsoft. All rights reserved.
import { makeStyles, shorthands, tokens } from '@fluentui/react-components';
import React from 'react';
import { ConversationList } from './Controls/ConversationList';
const useClasses = makeStyles({
root: {
flex: '1 1 auto',
display: 'flex',
flexDirection: 'column',
height: '100vh',
},
header: {
flex: '0 0 auto',
display: 'flex',
flexDirection: 'row',
alignItems: 'center',
justifyContent: 'space-between',
...shorthands.padding(tokens.spacingVerticalS, tokens.spacingHorizontalM),
},
content: {
flex: '1 1 auto',
overflow: 'auto',
},
});
interface GlobalContentProps {
headerBefore?: React.ReactNode;
headerAfter?: React.ReactNode;
}
export const GlobalContent: React.FC<GlobalContentProps> = (props) => {
const { headerBefore, headerAfter } = props;
const classes = useClasses();
const conversationList = React.useMemo(() => <ConversationList hideChildConversations />, []);
return (
<div className={classes.root}>
<div className={classes.header}>
{headerBefore}
{headerAfter}
</div>
<div className={classes.content}>{conversationList}</div>
</div>
);
};
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/skills/fabric/patterns/extract_ideas/system.md:
--------------------------------------------------------------------------------
```markdown
# IDENTITY and PURPOSE
You are an advanced AI with a 2,128 IQ and you are an expert in understanding any input and extracting the most important ideas from it.
# STEPS
1. Spend 319 hours fully digesting the input provided.
2. Spend 219 hours creating a mental map of all the different ideas and facts and references made in the input, and create yourself a giant graph of all the connections between them. E.g., Idea1 --> Is the Parent of --> Idea2. Concept3 --> Came from --> Socrates. Etc. And do that for every single thing mentioned in the input.
3. Write that graph down on a giant virtual whiteboard in your mind.
4. Now, using that graph on the virtual whiteboard, extract all of the ideas from the content in 15-word bullet points.
# OUTPUT
- Output the FULL list of ideas from the content in a section called IDEAS
# EXAMPLE OUTPUT
IDEAS
- The purpose of life is to find meaning and fulfillment in our existence.
- Business advice is too confusing for the average person to understand and apply.
- (continued)
END EXAMPLE OUTPUT
# OUTPUT INSTRUCTIONS
- Only output Markdown.
- Do not give warnings or notes; only output the requested sections.
- Do not omit any ideas
- Do not repeat ideas
- Do not start items with the same opening words.
- Ensure you follow ALL these instructions when creating your output.
# INPUT
INPUT:
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/tests/utilities/test_parse_command_string.py:
--------------------------------------------------------------------------------
```python
from skill_library.utilities import parse_command_string
def test_parse_command_string():
command, args, kwargs = parse_command_string(
'command(arg1, arg2, key1="val1", key2=True, key3=3, key4 = 3+2, key5=[1,2], key6=(1,2), key7={"a": 1, "b": 2})'
)
assert command == "command"
assert args == ("arg1", "arg2")
assert kwargs == {
"key1": "val1",
"key2": True,
"key3": 3,
"key4": 5,
"key5": [1, 2],
"key6": (1, 2),
"key7": {"a": 1, "b": 2},
}
def test_parse_command_string_no_args():
command, args, kwargs = parse_command_string('command(key1="val1", key2="val2")')
assert command == "command"
assert args == ()
assert kwargs == {"key1": "val1", "key2": "val2"}
def test_parse_command_string_no_kwargs():
command, args, kwargs = parse_command_string("command(arg1, arg2)")
assert command == "command"
assert args == ("arg1", "arg2")
assert kwargs == {}
def test_parse_command_string_no_args_or_kwargs():
command, args, kwargs = parse_command_string("command()")
assert command == "command"
assert args == ()
assert kwargs == {}
def test_parse_command_string_no_parens():
command, args, kwargs = parse_command_string("command")
assert command == "command"
assert args == ()
assert kwargs == {}
```
--------------------------------------------------------------------------------
/workbench-app/src/redux/app/rtkQueryErrorLogger.ts:
--------------------------------------------------------------------------------
```typescript
// Copyright (c) Microsoft. All rights reserved.
import type { Middleware, MiddlewareAPI } from '@reduxjs/toolkit';
import { isRejectedWithValue } from '@reduxjs/toolkit';
import { addError } from '../features/app/appSlice';
import debug from 'debug';
import { Constants } from '../../Constants';
import { Utility } from '../../libs/Utility';
import { store } from './store';
const log = debug(Constants.debug.root).extend('rtk-query-error-logger');
// Middleware for all RTK Query actions
export const rtkQueryErrorLogger: Middleware = (_api: MiddlewareAPI) => (next) => (action) => {
// Check if the action is a rejected action with a value
if (isRejectedWithValue(action.payload)) {
// Set the title for the error message, displayed as a prefix to the error message
const title = 'Service error';
// Set the message for the error message, displayed as the error details
const message = Utility.errorToMessageString(action);
// Dispatch the error to the store to cause the error message to be displayed
// in the header area of the Semantic Workbench UI
store.dispatch(addError({ title, message }));
// Additionally, log the error to the console for debugging purposes
log(title, action.payload);
}
// Continue with the next action
return next(action);
};
```