About
The Condensed Analytic Stacks skill provides a specialized framework for integrating advanced topological concepts—such as condensed sets, liquid vector spaces, and pyknotic objects—into computational learning systems. By leveraging 6-functor formalisms and categorical Künneth formulas, it allows Claude to model complex analytic stacks and bridge them to cellular sheaf neural networks. This skill is ideal for researchers and developers working on geometric deep learning, algebraic databases, and high-level categorical modeling where traditional topology fails to provide necessary algebraic completions.
