Welcome to a deep dive into a fun project built live on Rubber Duck Thursdays by the GitHub team. This guide explains how we used the GitHub Copilot CLI to create an emoji list generator, a tool that automatically adds relevant emojis to bullet points and copies the result to your clipboard. Whether you're new to the Copilot CLI or looking for creative project ideas, you'll find step-by-step insights here.
What exactly is the Emoji List Generator and why was it created?
Social media launches often feature beautifully formatted bullet points with emojis, like “We shipped an amazing emoji list generator: works in the CLI, uses AI to convert bullet points to relevant emojis, and copies to clipboard.” But manually picking the perfect emoji slows down creators who want to “move fast and break things.” The Emoji List Generator solves this: it’s a terminal app where you paste or type a list, press Ctrl+S, and instantly get an emoji-enhanced list on your clipboard. The project was built during a live stream to demonstrate the power of the GitHub Copilot CLI and its AI capabilities, making tedious emoji selection effortless.
How did the GitHub team build this project on the stream?
The team started by opening the GitHub Copilot CLI in Plan mode using Claude Sonnet 4.6. They described their goal: “Create an AI-powered markdown emoji list generator that, when you paste bullet points, replaces them with relevant emojis and copies to clipboard.” Copilot asked clarifying questions about the tech stack and libraries, with community member Gabor suggesting OpenTUI for the terminal interface. From that dialogue, Copilot generated a detailed plan.md file. Then, using Autopilot mode with Claude Opus 4.7, they implemented the plan in minutes, resulting in a fully functional terminal UI. The entire process demonstrated how multi-model workflows and the Copilot CLI can accelerate prototyping.
What technologies were used to power the Emoji List Generator?
The project relied on three main components: @opentui/core for the terminal user interface, @github/copilot-sdk for the AI brain that intelligently matches emojis to bullet points, and clipboardy for clipboard access. Additionally, the GitHub Copilot CLI itself was used extensively, featuring Plan mode to design the solution, Autopilot mode to write the code, and a multi-model workflow (Claude Sonnet for planning, Opus for implementation). The team also enabled the allow-all flag and tapped the GitHub MCP server to streamline development. These tools together made building a polished CLI app quick and enjoyable.
How does the Emoji List Generator work step-by-step?
- Launch the app in your terminal. You see a simple input area.
- Paste or type a list of bullet points (e.g., “Works in the CLI” and “Copies to clipboard”).
- Press Ctrl+S to trigger processing. The app sends your lines to the GitHub Copilot SDK, which analyzes each line and selects the most relevant emoji (e.g., 💻 for CLI, 📋 for clipboard).
- The result is automatically copied to your clipboard via the clipboardy library.
- Paste anywhere – tweets, pull requests, documentation – to impress your audience with emoji-rich lists.
Behind the scenes, the AI brain uses natural language understanding to map concepts to emojis, making the tool both fast and accurate.
Can I build my own version and where can I find the code?
Absolutely! The Emoji List Generator is free and open source. You can find the complete code in the GitHub repository linked from the original post (available on the GitHub blog). To build your own, start by familiarizing yourself with the GitHub Copilot CLI documentation and the GitHub Copilot SDK. The project shows how easily you can create AI-powered CLI tools with these resources. Feel free to fork, modify, and adapt it for your own use cases – for example, adding support for different list formats or custom emoji mappings. Happy building!
What are some key features of the GitHub Copilot CLI used in this project?
The GitHub Copilot CLI offers several powerful modes and flags. Plan mode helps you design your application by asking clarifying questions and generating a structured plan file, as seen when the team described the emoji generator and received a detailed plan.md. Autopilot mode then executes that plan by writing actual code autonomously. The multi-model workflow allowed using Claude Sonnet for planning and Claude Opus for implementation, demonstrating flexibility. The allow-all flag gave the CLI access to system tools, while the GitHub MCP server integrated with other services. Together, these features let you go from idea to working prototype in minutes, especially for small, focused projects like this emoji list generator.