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research-paper-integrity

Standards and audits for writing academic papers, especially ML/NLP submissions to NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL.

Install / Use

npx skills add Leanmcp/gateway-skills --skill research-paper-integrity

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

84/100

Supported Platforms

Universal

Our assessment of research-paper-integrity

research-paper-integrity scores 84/100 on our quality scale, 892nd of 1,188 Content & Media skills we index.

Its SKILL.md is 5.3 KB long, split into 7 sections with 1 code example: a solid amount of guidance for an agent.

With 2,111 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
15/20
Description
15/15
Adoption
14/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 16 days ago, so research-paper-integrity is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

research-paper-integrity compared with similar skills

All 4 of these similar skills score higher than research-paper-integrity; compare them before choosing.

SkillScoreStarsUpdatedFormat
research-paper-integrity (this skill)by Leanmcp842.1k16d agoSKILL.md
siyuanby siyuan-note10046.9ktodayMCP Server
algorithmic-artby anthropics100177.9k31d agoSKILL.md
pptxby anthropics100177.9k31d agoSKILL.md
designby nextlevelbuilder100137.2k9d agoSKILL.md

Frequently asked questions

How do I install research-paper-integrity?
Run npx skills add Leanmcp/gateway-skills --skill research-paper-integrity. The install tabs above show the steps for each supported agent.
Which AI agents does research-paper-integrity work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is research-paper-integrity safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is research-paper-integrity still maintained?
The repository was last updated 16 days ago, so research-paper-integrity is actively maintained.

name: research-paper-integrity description: Standards and audits for writing academic papers, especially ML/NLP submissions to NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL. Covers the author's house prose rules (zero em dashes, zero fluff, every sentence earns its place), verification of hallucinated claims and hallucinated or malformed bibliography entries, the ACL policy on AI writing assistance and what must be disclosed, and best practices for paper structure, experiments, reproducibility checklists, and rebuttals. Use this skill whenever the user is drafting, editing, polishing, restructuring, or reviewing a paper, abstract, intro, related work, rebuttal, or camera-ready; whenever they ask to "clean up" or "tighten" academic writing; whenever citations or a .bib file need checking; and whenever they ask what has to be disclosed about AI assistance. Reach for it even when the user only says "make this section better", "check my references", or "is this ready to submit".

Research paper integrity

This skill is the index. Each area below lives in its own reference file so you only load what the current task needs. Read the file before acting on that area, not after, because these rules change what you write rather than how you check it afterwards.

What lives where

| Area | File | Read it when | |---|---|---| | Prose rules: no em dashes, no fluff, necessity test | references/writing-style.md | Writing or editing any prose the user will submit | | Hallucination audit: unsupported claims, fake or wrong citations, bib hygiene | references/hallucination-audit.md | Any draft has claims or references that were not hand-verified | | AI assistance disclosure (ACL 2023 policy and its logic) | references/ai-writing-policy.md | The user asks what to disclose, fills a responsible-NLP checklist, or used a model for text, ideas, or code | | Conference craft: structure, experiments, figures, rebuttals, checklists | references/conference-writing.md | Planning a paper, restructuring sections, prepping a submission or rebuttal |

scripts/check_prose.py is a fast mechanical pass for em dashes, banned filler, hedge stacking, and suspicious bib entries. It catches the boring violations so your attention goes to the ones that need judgment. Per the user's global rule, do not run it yourself: write it into the relevant workspace if needed and hand over the exact command.

The three commitments

Everything in this skill reduces to three things the user cares about. Keep them in mind even when you have only loaded this index.

1. The text contains no em dashes and no filler. Not because em dashes are wrong in general, but because in this user's papers they signal a sentence that was never restructured, and filler signals a claim that was never sharpened. Replace an em dash with a period, a colon, a comma, or parentheses, whichever the actual logic calls for. Details and the filler list are in references/writing-style.md.

2. Every sentence has been asked twice whether it needs to exist. First pass: does this sentence carry information the reader does not already have? Second pass: if it does, is this the shortest honest form of it? A paragraph that survives both passes is usually a third shorter than the draft. Cutting is the main editing operation here, not rewording.

3. Nothing is asserted that has not been checked, and no reference is cited that has not been confirmed to exist. Fabricated citations and confidently wrong numbers are the two failure modes that end a paper's credibility, and both look completely normal in a draft. Treat every number, every "prior work shows", and every bib entry as unverified until you have traced it. Procedure in references/hallucination-audit.md.

Default workflow when handed a draft

Adapt this, do not perform it mechanically. If the user asked only for a citation check, do only that.

  1. Read the draft fully before changing anything. Local edits made without the whole argument in mind are how papers lose their thread.
  2. Run the hallucination audit first. There is no point polishing a sentence built on a claim that turns out to be unsupported, and finding a broken citation early changes what the surrounding paragraph should say.
  3. Then the prose pass: cut, de-fluff, remove em dashes, tighten.
  4. Then structure: does each section do the job references/conference-writing.md describes, in the order a reviewer reads.
  5. Report what you changed and, separately, what you could not verify. The second list matters more than the first. Never quietly leave an unverifiable claim in place without flagging it.

How to report

Give the user the edited text plus a short audit section. Something like:

## Changes
- Cut 4 sentences from the intro that restated the abstract
- Removed 11 em dashes, restructured the 3 sentences that needed it
- Section 4.2: "significantly improves" -> stated the actual delta and the test

## Could not verify (needs your call)
- [Smith 2021] claimed for the pretraining result: no paper by that name found in
  ACL Anthology or arXiv. Either the citation is wrong or the claim needs a source.
- Table 2 baseline number differs from the number quoted in Section 5.

Flagging honestly is the whole value here. A silent pass that leaves a fabricated citation in place is worse than no pass at all, because it launders the error.

Related Skills

View on GitHub
GitHub Stars2.1k
CategoryContent
Updated16d ago
Forks2.1k

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions