GitHub Labels CLI

Project Overview

GitHub Labels CLI is a powerful command-line tool designed to streamline label management across GitHub repositories. Built with TypeScript and the Octokit REST API, it provides an intuitive interface for organizing and maintaining repository labels at scale.

The tool features an interactive mode that guides users through common label management tasks, including fetching repository lists, adding/removing labels, and creating custom label templates. Users can save label configurations and reuse them across multiple repositories, ensuring consistency across projects.

One of the standout features is AI-powered label suggestions for pull requests. Using OpenAI API, the tool analyzes PR titles, descriptions, changed files, and code context to automatically suggest appropriate labels with confidence scores. It can also generate comprehensive PR descriptions, making it invaluable for large teams looking to automate workflow categorization and maintain consistent documentation.

Key Features

Interactive mode for guided label management

Fetch and list user repositories from GitHub

Add and remove labels from repositories

Create and save custom label templates

Reuse label templates across multiple repositories

AI-powered label suggestions for pull requests

Automatic PR description generation using AI

Analyze changed files and code context

Confidence scoring for label suggestions

Support for bulk label operations

Colored terminal output with Chalk

Loading spinners and progress indicators

Type-safe validation with Zod

Comprehensive testing with Vitest

Full VitePress documentation

Semantic versioning and automated releases

Technical Details

Technology Stack

TypeScript

Commander.js

@octokit/rest

OpenAI API

Inquirer

Chalk

Ora

Zod

Vitest

VitePress

tsup

Semantic Release

Husky

Commitizen

Architecture

GitHub Labels CLI follows a modular command-based architecture using Commander.js for command routing and argument parsing. The tool integrates with GitHub API via Octokit for repository and label operations, and OpenAI API for intelligent label suggestions. Interactive prompts are powered by Inquirer, providing a user-friendly CLI experience. The codebase uses Zod for runtime validation of API responses and user input, ensuring type safety throughout the application.

Challenges & Solutions

Challenge: Integrating AI for intelligent label suggestions
Solution: Implemented OpenAI API integration that analyzes PR context including title, description, changed files, and code diff to provide relevant label suggestions with confidence scores
Challenge: Managing complex GitHub API interactions
Solution: Used Octokit REST client with proper error handling and rate limiting, implementing retry logic for failed requests and clear error messages for users
Challenge: Creating reusable label templates
Solution: Built a template system that allows users to export labels from any repository and save them as JSON templates for quick application to other repositories
Challenge: Providing excellent user experience in the terminal
Solution: Combined Inquirer for interactive prompts, Chalk for colored output, and Ora for loading indicators to create an intuitive and visually appealing CLI interface