🎁 Get the FREE AI Skills Starter Guide β€” Subscribe β†’
BytesAgainBytesAgain
πŸ¦€ ClawHub

academic-pdf-redaction

by @lnj22

Redact text from PDF documents for blind review anonymization

Versionv0.1.0
Downloads525
TERMINAL
clawhub install paper-anonymizer-academic-pdf-redaction

πŸ“– About This Skill


name: academic-pdf-redaction description: Redact text from PDF documents for blind review anonymization

PDF Redaction for Blind Review

Redact identifying information from academic papers for blind review.

CRITICAL RULES

1. PRESERVE References section - Self-citations MUST remain intact 2. ONLY redact specific text matches - Never redact entire pages/regions 3. VERIFY output - Check that 80%+ of original text remains

Common Pitfalls to AVOID

# ❌ WRONG - This removes ALL text from the page:
for block in page.get_text("blocks"):
    page.add_redact_annot(fitz.Rect(block[:4]))

❌ WRONG - Drawing rectangles over text:

page.draw_rect(fitz.Rect(0, 0, 600, 100), fill=(0,0,0))

βœ… CORRECT - Only redact specific search matches:

for rect in page.search_for("John Smith"): page.add_redact_annot(rect)

Patterns to Redact (Before References Only)

IMPORTANT: Use FULL names/phrases, not partial matches!

  • βœ… "John Smith" (full name)
  • ❌ "Smith" (partial - would incorrectly match "Smith et al." citations in References)
  • 1. Author names - FULL names only (e.g., "John Smith", not just "Smith") 2. Affiliations - Universities, companies (e.g., "Duke University") 3. Email addresses - Pattern: *@*.edu, *@*.com 4. Venue names - Conference/workshop names (e.g., "ICML 2024", "ICML Workshop") 5. arXiv identifiers - Pattern: arXiv:XXXX.XXXXX 6. DOIs - Pattern: 10.XXXX/... 7. Acknowledgement names - Names in "Acknowledgements" section 8. Equal contribution footnotes - e.g., "Equal contribution", "* Equal contribution"

    PyMuPDF (fitz) - Recommended Approach

    import fitz
    import os

    def redact_with_pymupdf(input_path: str, output_path: str, patterns: list[str]): """Redact specific patterns from PDF using PyMuPDF.""" doc = fitz.open(input_path) original_len = sum(len(p.get_text()) for p in doc)

    # Find References page - stop redacting there references_page = None for i, page in enumerate(doc): if "references" in page.get_text().lower(): references_page = i break

    for page_num, page in enumerate(doc): if references_page is not None and page_num >= references_page: continue # Skip References section

    for pattern in patterns: # ONLY redact exact search matches for rect in page.search_for(pattern): page.add_redact_annot(rect, fill=(0, 0, 0)) page.apply_redactions()

    os.makedirs(os.path.dirname(output_path), exist_ok=True) doc.save(output_path) doc.close()

    # MUST verify after saving verify_redaction(input_path, output_path)

    REQUIRED: Verification Function

    Always run this after ANY redaction to catch errors early:

    import fitz

    def verify_redaction(original_path, output_path): """Verify redaction didn't corrupt the PDF.""" orig = fitz.open(original_path) redc = fitz.open(output_path)

    orig_len = sum(len(p.get_text()) for p in orig) redc_len = sum(len(p.get_text()) for p in redc)

    print(f"Original: {len(orig)} pages, {orig_len} chars") print(f"Redacted: {len(redc)} pages, {redc_len} chars") print(f"Retained: {redc_len/orig_len:.1%}")

    # DEFENSIVE CHECKS - fail fast if something went wrong if len(redc) != len(orig): raise ValueError(f"Page count changed: {len(orig)} -> {len(redc)}") if redc_len < 1000: raise ValueError(f"PDF corrupted: only {redc_len} chars remain!") if redc_len < orig_len * 0.7: raise ValueError(f"Too much removed: kept only {redc_len/orig_len:.0%}")

    orig.close() redc.close() print("βœ“ Verification passed")