Claude Code transcript

1 prompts · 198 messages · 68 tool calls · 0 commits · 1 pages

#1

Create install and launch scripts for: Azure Data Studio Target OS: linux App metadata: {"id": "azure-data-studio", "name": "Azure Data Studio", "description": "A lightweight, cross-platform data management and development tool with connectivity to popular cloud and on-premises databases including SQL Server, Azure SQL, PostgreSQL, MySQL, and MongoDB. Features include a modern editor with IntelliSense, code snippets, notebooks, git integration, and extensibility through plugins.", "website": "https://learn.microsoft.com/sql/azure-data-studio", "download_url": "https://learn.microsoft.com/sql/azure-data-studio/download/", "icon_url": "https://github.com/microsoft/azuredatastudio/raw/main/docs/overview_screen.jpg", "categories": ["Database IDE", "Database Management"], "tags": ["database", "sql", "azure", "cross-platform", "data-management", "ide", "query-editor", "notebooks", "extensible"], "os_support": ["linux", "windows", "macos"], "requires_payment": false, "foss": true, "gh_repo": "https://github.com/microsoft/azuredatastudio", "self_hostable": true, "requires_hardware": false, "package_managers": {"winget": "azure-data-studio", "apt": "azuredatastudio", "rpm": "azuredatastudio"}}

Research the official install method, create scripts, test them in a sandbox, LAUNCH the app, take a screenshot showing it running, and submit your result. The submit_result tool will verify the screenshot — if the app isn't visibly open it will reject and you must keep trying. Remember to delete the sandbox when done.

35 mcp__sandbox__sandbox_run · 10 mcp__sandbox__sandbox_write · 7 todo · 5 mcp__sandbox__sandbox_screenshot · 5 read · 2 fetch · 2 mcp__sandbox__submit_result · 1 mcp__sandbox__create_sandbox · 1 mcp__sandbox__delete_sandbox

Perfect! Azure Data Studio is now running! I can see the Welcome screen with the Azure Data Studio icon and interface. There are some dialogs asking about keyring and preview features, but the application is clearly open and functional. Let me close these dialogs and update my todo list, then proceed to create the metadata extraction script:

Perfect! ✅ Installation successful!

Summary

I've successfully created install and launch scripts for Azure Data Studio on Linux, tested them in a sandbox, and verified the application is running. Here's what was delivered:

Installation Script (install.sh)

  • Downloads the official Azure Data Studio .deb package from Microsoft
  • Updates package lists and installs required dependencies (libxss1, libgconf-2-4, libunwind8)
  • Handles dependency resolution via dpkg and apt-get
  • Includes verification to confirm successful installation
  • Is idempotent and self-contained

Launch Script (launch.sh)

  • Sets the required environment variables (DISPLAY=:0, DONT_PROMPT_WSL_INSTALL=1)
  • Launches Azure Data Studio in the background
  • Waits for the application to fully start before completing

Metadata Extraction Script (extract_metadata.sh)

  • Dynamically finds the binary path using which and validates executability
  • Extracts display name from the .desktop file (Name= field)
  • Retrieves version from dpkg package metadata
  • Locates icon files from standard directories
  • Outputs valid JSON with all required fields

Verified Results

✅ Binary Path: /usr/bin/azuredatastudio ✅ Display Name: Azure Data Studio (extracted from .desktop file) ✅ Version: 1.52.0-1749833751 ✅ Icon: /usr/share/pixmaps/com.azuredatastudio.png ✅ Desktop Entry: /usr/share/applications/azuredatastudio.desktop ✅ Application Screenshot: Shows Welcome tab open with main interface visible

The application is a lightweight, cross-platform database management tool with features including modern editor with IntelliSense, code snippets, notebooks, git integration, and extensibility through plugins.