A curated list of awesome Common Lisp frameworks, libraries, and resources for developers.
Awesome Common Lisp is a curated directory of frameworks, libraries, and resources for the Common Lisp programming language. It helps developers discover high-quality tools across domains like artificial intelligence, databases, web development, and game programming by providing organized listings with quality indicators.
Common Lisp developers seeking libraries for specific tasks, newcomers exploring the ecosystem, and maintainers looking for established solutions to avoid reinventing the wheel.
It saves developers time by filtering the vast Common Lisp ecosystem into a trusted, organized resource with community-vetted recommendations, distinguishing between established standards and promising alternatives.
A curated list of awesome Common Lisp frameworks, libraries and other shiny stuff.
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
Marks community standards (⭐) and recommended libraries (👍) based on stability and adoption, helping users avoid unreliable tools and focus on proven solutions.
Organized into 50+ categories from AI to GUI toolkits, making it easy to discover libraries for niche domains like audio processing or cryptography without manual searching.
Prioritizes libraries available via Quicklisp for immediate use and emphasizes tools with real-world applications, as noted in the README's philosophy on balancing established standards with new libraries.
Regularly updated with new contributions and modern libraries, ensuring the list stays relevant, though it relies on volunteer efforts which can be a double-edged sword.
As a GitHub README, it lacks dynamic features like search filters, user ratings, or live updates, requiring manual browsing and limiting discoverability for complex queries.
Entries often provide only brief descriptions or links, missing in-depth tutorials, code samples, or comparison charts that would help developers evaluate libraries more effectively.
While actively maintained, the quality and timeliness of updates depend on community contributions, which can lead to gaps or outdated information in fast-moving areas like AI or web frameworks.