ebook-extractor_skill

Overview

This skill extracts plain text from EPUB, MOBI, and PDF ebooks so you can analyze, process, or read content in downstream tools. It is implemented in Python and performs local parsing and conversion—no external LLM calls. The tool focuses on reliable structure-aware extraction for EPUB, conversion-based handling for MOBI, and fast PDF text scraping.

How this skill works

The extractor auto-detects the input format and routes files to format-specific handlers. EPUB files are parsed with ebooklib and cleaned with BeautifulSoup to preserve reading order. MOBI files are converted to EPUB using Calibre's ebook-convert, then parsed like EPUB. PDFs are read with PyMuPDF (fitz) to pull text blocks quickly; image-only PDFs are not OCRed.

When to use it

• Convert EPUB, MOBI, or PDF ebooks to plain text for NLP, indexing, or summarization.
• Prepare books for readability in text-only environments or screen readers.
• Preprocess ebook content for search, topic modeling, or citation extraction.
• Batch-convert a library of ebooks into text files for archival or analysis.
• Quickly inspect the textual content of an ebook without opening a reader app.

Best practices

• Run the provided setup.sh or install requirements to ensure dependencies (ebooklib, BeautifulSoup, PyMuPDF) are present.
• Install Calibre if you need MOBI support; MOBI files are converted to EPUB before extraction.
• For large batches, pipe output to files rather than stdout to avoid console buffering issues.
• If a PDF returns garbled text, check if it is image-based; OCR is not included and needs a separate step.
• Trim or post-process extracted text (remove headers/footers) depending on downstream needs.

Example use cases

• Extract chapters from an EPUB to feed into a topic modeling pipeline.
• Convert a collection of MOBI novels to text files for full-text search indexing.
• Pull text from a PDF academic monograph to produce summaries or citation lists.
• Create plain-text versions of books for accessibility tools or e-readers that prefer raw text.
• Preprocess ebook text for training or evaluation of NLP models.