benchflow-ai/skillsbench/academic-pdf-redaction

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Redact text from PDF documents for blind review anonymization

Install

npx vskill@latest install benchflow-ai/skillsbench/academic-pdf-redaction

SKILL.md

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

python
# ❌ 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))
# ✅ 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!

  • ✅ "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

python
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:

python
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("✓ Verification passed")

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