aa/cli taste

# Cli taste of AA
- Use pnpm as the package manager for CLI projects. Confidence: 1.00
- Use TypeScript for CLI projects. Confidence: 0.95
- Use tsup as the build tool for CLI projects. Confidence: 0.95
- Use vitest for testing CLI projects. Confidence: 0.95
- Use Commander.js for CLI command handling. Confidence: 0.95
- Use clack for interactive user input in CLI projects. Confidence: 0.95
- Check for existing CLI name conflicts before running npm link. Confidence: 0.95
- Organize CLI commands in a dedicated commands folder with each module separated. Confidence: 0.95
- Include a small 150px ASCII art welcome banner displaying the CLI name. Confidence: 0.95
- Use lowercase flags for version and help commands (-v, --version, -h, --help). Confidence: 0.85
- Start projects with version 0.0.1 instead of 1.0.0. Confidence: 0.85
- Version command should output only the version number with no ASCII art, banner, or additional information. Confidence: 0.90
- Read CLI version from package.json instead of hardcoding it in the source code. Confidence: 0.75
- Always use ora for loading spinners in CLI projects. Confidence: 0.95
- Use picocolors for terminal string coloring in CLI projects. Confidence: 0.90
- Use Ink for building interactive CLI UIs in CommandCode projects. Confidence: 0.80
- Use ink-spinner for loading animations in Ink-based CLIs. Confidence: 0.70
- Hide internal flags from help: .addOption(new Option('--local').hideHelp()). Confidence: 0.90
- Use pnpm.onlyBuiltDependencies in package.json to pre-approve native binary builds. Confidence: 0.60
- Use ANSI Shadow font for ASCII art at large terminal widths and ANSI Compact for small widths. Confidence: 0.85
- Use minimal white, gray, and black colors for ASCII art banners. Confidence: 0.85
- Check if package is publishable using `npx can-i-publish` before building or publishing. Confidence: 0.85

Run this prompt on a real model without leaving the page. Every run is saved to your history for this prompt.

How to use

1. 1Copy the prompt as-is — no variables required.
2. 2Paste it into ChatGPT, Claude, Gemini, or any capable model.
3. 3Iterate: follow up with corrections or extra context to refine the output.