virgiliojr94/book-to-skill
book-to-skill compiles books and document sets into on-demand agent skills, reducing repeated context loading while preserving chapter-level references and reusable decision rules.
book-to-skill converts PDFs, ebooks, document folders, or globs into a shared SKILL.md, a core index, and on-demand chapter files. Its tests report **24–51× fewer tokens** than repeatedly placing a full book in context.
Use this pattern for references you revisit: internal docs, standards, research clusters, or technical books. The generated structure front-loads mental models and loads only the relevant chapter, while the same skill format works in Claude Code, Amp, and GitHub Copilot CLI.
book-to-skill converts PDFs, ebooks, document folders, or globs into a shared SKILL.md, a core index, and on-demand chapter files. Its tests report **24–51× fewer tokens** than repeatedly placing a full book in context. Use this pattern for references you revisit: internal docs, standards, research clusters, or technical books. The generated structure front-loads mental models and loads only the relevant chapter, while the same skill format works in Claude Code, Amp, and GitHub Copilot CLI. The repository says conversion costs roughly **$1 per book**, and repeated use is where amortization helps. Chapter detection expects explicit numbered headings; one-off reading, broad library search, and poorly segmented sources may be better served by other approaches.
This makes the shared-context pattern concrete for stable, repeatedly consulted documents: preprocess them into a portable skill with a compact index and selectively loaded chapters. Unlike repository graphs, recursive inspection, or evidence replay, it pays an upfront conversion cost and depends on explicit document structure; its reported token savings therefore support repeated reference use, not general library search or one-off reading.