virgiliojr94/book-to-skill

Turn any technical book PDF into a Claude Code skill — ready to study, reference, and use while you work.

What it solves

Many technical books and long documents are difficult to query effectively with AI agents. Simply dumping a whole book into an LLM's context window is token-expensive and often leads to hallucinations or navigation errors. This tool converts these documents into a structured "skill" that an AI agent can load on-demand, allowing for precise, low-token queries without needing to search through PDFs manually.

How it works

The project uses a two-part process: a Python-based extractor that converts various file formats (PDF, EPUB, DOCX, etc.) into clean text and metadata, and a spec-driven generator that organizes this content into a structured skill format. Instead of a single large file, it creates a system of files including a core SKILL.md (mental models and index), individual chapter files for on-demand loading, a glossary, and a cheatsheet. This ensures the agent only reads the relevant sections of the book when needed.

Who it’s for

Developers and researchers who frequently reference technical books, internal company documentation, architecture decision records, or research papers and want to integrate that knowledge directly into their AI coding assistants (such as GitHub Copilot CLI, Claude Code, or OpenCode).

Highlights

  • Multi-format support: Extracts text from PDF, EPUB, DOCX, HTML, RTF, and MOBI.
  • Token efficiency: Reduces token usage by 24x to 51x compared to full-context dumping.
  • Cross-agent compatibility: Follows the Agent Skills open standard, making it compatible with multiple AI agent hosts.
  • Local processing: All extraction and analysis happen locally to maintain privacy.
  • Technical PDF handling: Uses specialized tools like docling to preserve markdown tables and code blocks in technical documents.

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