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The Article-to-Prototype skill bridges the gap between theoretical documentation and executable software by autonomously parsing technical content from diverse sources. Whether dealing with complex academic papers, technical blog posts, or Jupyter notebooks, this skill uses advanced semantic analysis to identify algorithms and architectural patterns. It intelligently selects the most appropriate programming language—such as Python for ML or Rust for systems—and generates a complete, documented repository including dependencies and unit tests, enabling developers to validate new concepts in minutes rather than days.
