| name | pdf-reader |
| description | This skill should be used when the user asks to "read this PDF", "extract text from PDF", "what's in this PDF", or provides a PDF file path and wants to understand its contents. Extracts structured text from PDF files using PyMuPDF with pypdf fallback. |
PDF Reader
Extract text from PDF files using open-source tools. PyMuPDF (fitz) is the primary engine with pypdf as fallback.
When to use
- User provides a
.pdf file path and asks to read or extract its contents
- User asks to summarize a PDF
- User asks what a PDF document contains
- Academic papers, reports, or any PDF documents
When NOT to use
- URLs pointing to web pages (use
defuddle skill instead)
- Image files (use image analysis tools)
- Already-extracted text files
Workflow
1. Extract text
Run the extraction script:
python3 ~/.claude/skills/pdf-reader/scripts/extract_pdf.py <pdf_path>
Options:
-p, --pages — extract specific pages, e.g. 1-5 or 1,3,7-m, --method — force fitz or pypdf (default: auto)--json — output structured JSON with metadata--metadata-only — print only title, author, page count
2. For large PDFs
Extract in chunks to avoid token overflow:
- First run with
--metadata-only to check page count
- Then extract page ranges with
-p 1-10, -p 11-20, etc.
3. For scanned PDFs (image-based)
If extracted text is empty or garbled, the PDF is likely scanned. Inform the user that OCR is needed. Consider suggesting marker or ocrmypdf as next steps.
Quality notes
- PyMuPDF preserves font size and bold formatting as markdown headers and bold text
- pypdf is the fallback and produces plain text only
- Both handle multi-column layouts as single-column output (reading order)
- Tables are extracted as plain text, not as structured tables
