fuck-u-code is a code quality assessment tool that analyzes your codebase and produces a detailed report showing how poorly your code is structured.
The tool solves the problem of identifying code quality issues across large projects by performing static analysis on source files. It uses tree-sitter for accurate abstract syntax tree parsing and applies seven distinct quality checks: complexity, size, comments, error handling, naming conventions, duplication, and structure. Each file receives a "Shit-Gas Index" score, and the overall codebase gets a 0-100 quality score. The tool supports fourteen programming languages including Go, JavaScript, TypeScript, Python, Java, C, C++, Rust, C#, Lua, PHP, Ruby, and Swift. Analysis runs entirely offline on your machine, with code never transmitted externally. Optional AI-powered code review integrates with OpenAI-compatible APIs, Anthropic, DeepSeek, Gemini, or local Ollama instances.
Teams maintaining legacy codebases or those wanting to establish code quality baselines should consider this tool. It suits projects where developers need visibility into which files have the worst quality issues and want to prioritize refactoring efforts. The tool outputs results in multiple formats—colored terminal, Markdown, JSON, and HTML—making it easy to share reports with teams. Configuration is flexible through .fuckucoderc.json files at project or global scope, and the tool supports English, Chinese, and Russian locales. Concurrent analysis with configurable worker threads allows scanning large codebases efficiently.
Development activity shows consistent engagement with the codebase through regular commits and updates. The project maintains active support for multiple languages and output formats, indicating ongoing refinement of analysis capabilities. Configuration management features and internationalization support across three languages demonstrate attention to usability across different development environments. The tool receives updates to keep pace with dependency changes and user feedback.
