anonymize-paper

anonymize-paper is a skill for Claude Code from ShaishavMaisuria/research-paper-lifecycle-skills. It costs 219 tokens per session (1,980 once invoked), scanned A, original, Apache-2.0.

A document-checking guide for removing identifying details from LaTeX research papers submitted for double-blind review, then restoring them after acceptance. Double-blind review hides the authors' identities from the reviewers.

In plain words
What is it for?
Use it to anonymize or de-anonymize papers, check for identity leaks, rewrite self-citations, and prepare submissions for specific conferences.
Why use it?
It helps prevent author names, self-references, supplementary files, or links from revealing who wrote the paper. It also makes restoring the original details less error-prone for the final published version.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the paper-submission plugin — 12 skills shipped together

Good fit Use it to anonymize or de-anonymize papers, check for identity leaks, rewrite self-citations, and prepare submissions for specific conferences.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/shaishavmaisuria/research-paper-lifecycle-skills/anonymize-paper
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 ShaishavMaisuria/research-paper-lifecycle-skills --skill anonymize-paper
Clone the repo
git clone --depth 1 https://github.com/ShaishavMaisuria/research-paper-lifecycle-skills

Made for: Claude Code.

Or install paper-submission, the plugin that ships this one along with the rest of its 12 skills.

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 anonymize-paper

README.md
[![agentmods](https://agentmods.dev/badge/skills/shaishavmaisuria/research-paper-lifecycle-skills/anonymize-paper/github.svg)](https://agentmods.dev/skills/shaishavmaisuria/research-paper-lifecycle-skills/anonymize-paper)
Your own site
<a href="https://agentmods.dev/skills/shaishavmaisuria/research-paper-lifecycle-skills/anonymize-paper"><img src="https://agentmods.dev/badge/skills/shaishavmaisuria/research-paper-lifecycle-skills/anonymize-paper/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 anonymize-paper

Your own site · 80×15
<a href="https://agentmods.dev/skills/shaishavmaisuria/research-paper-lifecycle-skills/anonymize-paper"><img src="https://agentmods.dev/badge/skills/shaishavmaisuria/research-paper-lifecycle-skills/anonymize-paper.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 219 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,980 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 original No closer match found 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 $0.00219 $0.01980
Opus 5 $0.00110 $0.00990
Sonnet 5 $0.00044 $0.00396
Haiku 4.5 $0.00022 $0.00198

Measured 12d ago against content hash 195d8703da5f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

anonymize-paper 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 12d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/scan_anonymization.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/anonymize-paper/SKILL.md · 147 lines

How it starts

The opening of the file, as written. The whole thing — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Anonymize Paper

Make a LaTeX submission genuinely double-blind — then undo it cleanly after acceptance. Anonymization leaks are documented desk-reject grounds (CHI and NeurIPS state this explicitly, including leaks in supplementary material and linked repos), and de-anonymization done by hand routinely leaves placeholder authors or dead anonymous.4open.science links in the published PDF. This skill runs the deep sweep in both directions and records every change so the reversal is mechanical, not archaeological.

When to use

  • "Anonymize my paper for NeurIPS / CHI / ICML / KDD ..." / "blind this"
  • "Did I leak my identity anywhere?" / "double-blind check" before submission
  • "Rewrite my self-citations in third person"
  • "My code/data links identify me — what do I do?"
  • After acceptance: "de-anonymize", "restore the authors", "prepare the camera-ready author block"
  • Called from tailor-to-venue (anonymization sweep step) or before preflight-check (final gate).

Inputs

  1. The main .tex file (with \documentclass); \input/\include files are followed automatically.
  2. The venue profile venues/conferences/<venue>-<year>.yml (schema in venues/schema.yml) — supplies the blind level (single/double/triple) and the cfp_url. No profile? Ask the user for the blind level or create a profile with parse-cfp.
  3. Optional but recommended: the compiled PDF (metadata check), the supplementary directory, and the author/institution names to grep for.

Process — anonymize (submission)

  1. Resolve the blind level, then re-verify it live — mandatory. Read the venue profile; fetch the cfp_url and confirm the blind level and the venue's anonymization policy wording (what counts as a violation, whether acknowledgments must be removed, whether anonymized artifact links are allowed). Single-blind venues (e.g. SIGSPATIAL) need no anonymization — tell the user and stop instead of mangling a fine paper.

  2. Run the deep scan:

Read the full file on GitHub · 147 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 12d ago First seen · 147 lines · 219 tokens per session scan A 195d8703da5f

Subscribe to this mod's changes

anonymize-paper is a skill published in the GitHub repository ShaishavMaisuria/research-paper-lifecycle-skills (42 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 219 tokens to every session and 1,980 once invoked, about $0.0011 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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