Extract pdf

extract-pdf — PDF and document extraction

Adapted from the Hermes Agent ocr-and-documents skill. Two extractors, one decision: pymupdf for speed, marker-pdf for hard cases.

For DOCX use python-docx (parses real document structure — better than OCR). For PPTX use a python-pptx-based flow. This skill is PDFs and scanned documents.

When this skill writes outputs (extracted markdown, tables, images), drop them under clients/{client}/pdf-extract-{YYYY-MM-DD}/ or apps/{app}/pdf-extract-{date}/. Never write to ~/.

Step 1: URL? Try web extract first

If the PDF has a URL, prefer a remote-fetch tool (e.g. WebFetch / Firecrawl) before installing local extractors. No deps, instant.

Use local extraction when: the file is local, the remote fetch fails, or you need batch/offline processing.

Step 2: Pick the extractor

Feature	pymupdf (~25 MB)	marker-pdf (~3–5 GB)
Text-based PDF	yes	yes
Scanned PDF (OCR)	no	yes (90+ languages)
Tables	basic	high accuracy
Equations / LaTeX	no	yes
Code blocks	no	yes
Forms	no	yes
Header/footer removal	no	yes
Reading-order detection	no	yes
Image extraction	embedded	with context
Image OCR	no	yes
EPUB	yes	yes
Markdown output	via pymupdf4llm	native, higher quality
Speed	instant	1–14 s/page CPU

Default to pymupdf. Reach for marker-pdf only when you actually need OCR, equations, forms, or layout analysis.

If the user needs marker capabilities but the system lacks ~5 GB free disk, escalate before installing. Tell them their options: free disk, supply a URL we can WebFetch, or accept pymupdf's text-only result.

---

pymupdf (lightweight)

pip install pymupdf pymupdf4llm

Helper script:

SKILL=.claude/skills/productivity/extract-pdf/scripts
python3 $SKILL/extract_pymupdf.py document.pdf              # plain text
python3 $SKILL/extract_pymupdf.py document.pdf --markdown   # markdown
python3 $SKILL/extract_pymupdf.py document.pdf --tables     # tables
python3 $SKILL/extract_pymupdf.py document.pdf --images out/ # extract images
python3 $SKILL/extract_pymupdf.py document.pdf --metadata   # title, author, pages
python3 $SKILL/extract_pymupdf.py document.pdf --pages 0-4  # specific pages

Inline:

python3 -c "
import pymupdf
doc = pymupdf.open('document.pdf')
for page in doc:
    print(page.get_text())
"

---

marker-pdf (high-quality OCR)

# Check disk space first
python3 .claude/skills/productivity/extract-pdf/scripts/extract_marker.py --check
pip install marker-pdf

Helper script:

SKILL=.claude/skills/productivity/extract-pdf/scripts
python3 $SKILL/extract_marker.py document.pdf              # markdown
python3 $SKILL/extract_marker.py document.pdf --json       # JSON + metadata
python3 $SKILL/extract_marker.py document.pdf --output_dir out/
python3 $SKILL/extract_marker.py scanned.pdf               # scanned PDF (OCR)
python3 $SKILL/extract_marker.py document.pdf --use_llm    # LLM-boosted accuracy

CLI (installed with marker-pdf):

marker_single document.pdf --output_dir ./output
marker /path/to/folder --workers 4    # batch

---

Split, merge, search

pymupdf covers these natively:

# Split: extract pages 1-5
import pymupdf
doc = pymupdf.open("report.pdf")
new = pymupdf.open()
for i in range(5):
    new.insert_pdf(doc, from_page=i, to_page=i)
new.save("pages_1-5.pdf")

# Merge multiple PDFs
result = pymupdf.open()
for path in ["a.pdf", "b.pdf", "c.pdf"]:
    result.insert_pdf(pymupdf.open(path))
result.save("merged.pdf")

# Search across pages
doc = pymupdf.open("report.pdf")
for i, page in enumerate(doc):
    if page.search_for("revenue"):
        print(f"Page {i+1} hit")

Notes

• WebFetch / remote extract first when a URL is available
• pymupdf is the safe default; install marker-pdf only when needed
• marker-pdf downloads ~2.5 GB to ~/.cache/huggingface/ on first use
• Both helper scripts accept --help
• For Word docs: pip install python-docx
• For PPT: use a python-pptx flow (separate skill)