academic-pdf-redaction

academic-pdf-redaction is a skill for Claude Code, Codex from xuansenpa1/skillrevise. It costs 17 tokens per session (966 once invoked), scanned A, a copy of academic-pdf-redaction, MIT.

A tool for removing identifying text from PDF research papers before blind review. Blind review is a process where reviewers should not know the authors or their institutions.

In plain words
What is it for?
Use it to redact author names, affiliations, email addresses, and venue names from academic PDFs before review.
Why use it?
It helps anonymize papers without accidentally removing citations, references, or large areas of content. It checks that only the intended text matches are redacted.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to redact author names, affiliations, email addresses, and venue names from academic PDFs before review.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/xuansenpa1/skillrevise/academic-pdf-redaction
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add xuansenpa1/skillrevise --skill academic-pdf-redaction
Clone the repo
git clone --depth 1 https://github.com/xuansenpa1/skillrevise

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for academic-pdf-redaction

README.md
[![agentmods](https://agentmods.dev/badge/skills/xuansenpa1/skillrevise/academic-pdf-redaction/github.svg)](https://agentmods.dev/skills/xuansenpa1/skillrevise/academic-pdf-redaction)
Your own site
<a href="https://agentmods.dev/skills/xuansenpa1/skillrevise/academic-pdf-redaction"><img src="https://agentmods.dev/badge/skills/xuansenpa1/skillrevise/academic-pdf-redaction/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for academic-pdf-redaction

Your own site · 80×15
<a href="https://agentmods.dev/skills/xuansenpa1/skillrevise/academic-pdf-redaction"><img src="https://agentmods.dev/badge/skills/xuansenpa1/skillrevise/academic-pdf-redaction.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 17 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 966 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00017 $0.00966
Opus 5 $0.00009 $0.00483
Sonnet 5 $0.00003 $0.00193
Haiku 4.5 $0.00002 $0.00097

Measured 8d ago against content hash 587dbb503749, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

academic-pdf-redaction scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to academic-pdf-redaction — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

data/skillsbench/tasks/paper-anonymizer/environment/skills/academic-pdf-redaction/SKILL.md · 113 lines

How it starts

The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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))

# ✅ 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"
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)

Read the full file on GitHub · 113 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 113 lines · 17 tokens per session scan A 587dbb503749

Subscribe to this mod's changes

academic-pdf-redaction is a skill published in the GitHub repository xuansenpa1/skillrevise (56 stars, last pushed 6d ago), licensed MIT. It adds 17 tokens to every session and 966 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to academic-pdf-redaction, differing in 0 lines, and is treated as a copy.

Related

Other skills, from other repositories

pydicom

Use pydicom to read, inspect, write, transform, and safely preflight local DICOM datasets and pixel data. Applies to DICOM metadata, transfer syntaxes, compression plugins, frames, private elements, JSON, and bounded de-identification review.

K-Dense-AI/scientific-agent-skills · 56 tokens

pptx-posters

Create and audit editable scientific posters in macro-free PowerPoint (.pptx) from author-approved local content and assets. Use when the requested deliverable is a PowerPoint research/conference poster and exact physical, printer, accessibility, provenance, and package-security checks are required.

K-Dense-AI/scientific-agent-skills · 59 tokens

extracting-lab-tables

Detects and extracts tabular laboratory panels from PDFs, scans, and images into structured rows ready for OpenMed and FHIR. Use when the user has a CBC, CMP, lipid panel, or other lab report as a scanned image / PDF / spreadsheet and needs the test name, value, unit, reference range, and abnormal flag as clean rows.…

maziyarpanahi/openmed · 210 tokens

paper-spine

Build, rewrite, audit, submit, revise, or transfer scholarly papers end to end, producing verified LaTeX/PDF/Word and target-specific publication packages.

WUBING2023/PaperSpine · 37 tokens

paper-compile

A build workflow that turns LaTeX source files into a PDF and checks whether the paper compiles correctly. LaTeX is a text-based system commonly used for academic papers.

wanshuiyin/Auto-claude-code-research-in-sleep · 53 tokens

nsfc-budget

A tool that creates an editable LaTeX budget justification and renders it as a PDF for an NSFC research-funding application. NSFC is China’s National Natural Science Foundation, and a budget justification explains why proposed costs are needed.

huangwb8/ChineseResearchLaTeX · 138 tokens