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Implements a high-efficiency architecture for building Claude Code skills that maximizes token savings while maintaining full functionality. By utilizing YAML frontmatter for metadata-driven loading, this pattern achieves up to an 84% reduction in token usage and significantly faster response times. It provides a standardized framework for developing domain-specific expertise—such as PDF extraction or specialized protocols—ensuring that complex instructions are only loaded when triggered, leading to lower costs and more consistent outcomes across repetitive professional workflows.