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What you can do with Game the LLM Reviewer

An agent skill that packages editing strategies for making small, meaning-preserving wording changes to a finished paper before submission, aimed at known LLM reviewer preferences.

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Michael-Jiahao-Zhang/game-the-llm-reviewer on GitHub

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Authorization notice. This tool is dual-use. Only use it on software, sites and systems you own or have explicit permission to test, and follow the relevant licenses and terms of service.

What do you want to do?

4 use cases

  • Run a meaning-preserving final pass on a finished paper

    Have an agent make small wording edits to a draft and log every change for review.

    View prompt
    Use the game-the-llm-reviewer skill from the repository Michael-Jiahao-Zhang/game-the-llm-reviewer on <path to finished manuscript>. Read the included sections first, apply small meaning-preserving edits, and save a revised copy and changes.md. Verify that every change note entry keeps the same claims, numbers, and citations as the original.

  • Tighten an abstract to 200 words without losing results

    Get replacement abstract prose and a short change note from one prompt.

    View prompt
    Use the game-the-llm-reviewer skill from Michael-Jiahao-Zhang/game-the-llm-reviewer on the abstract text in <path to abstract file>, keeping it under 200 words. Work only from the supplied text, preserve both positive and negative results, and return replacement prose with a short change note. Verify that no result, number, or limitation is missing from the new version.

  • Tune a theory paper's stance, keep theorems and assumptions

    Adjust contribution wording in a theory paper while leaving formal statements unchanged.

    View prompt
    Use the game-the-llm-reviewer skill from Michael-Jiahao-Zhang/game-the-llm-reviewer on paper/main.tex in <path to project>. Adjust contribution stance only, and preserve theorem assumptions, quantifiers, and the distinction between an upper bound and an optimal rate. Verify with a diff that no theorem, lemma, or assumption text changed.

  • Add this as the last pass after another writing skill

    Chain the skill after a drafting tool, reusing an existing claim-evidence map.

    View prompt
    The draft in <path to manuscript> is already polished. Use the game-the-llm-reviewer skill from Michael-Jiahao-Zhang/game-the-llm-reviewer as the final pass, reusing the attached claim-evidence map at <path to map>. Keep the meaning and scientific assessment unchanged, skip style-only rewrites, and return a revised copy and change note. Verify that every claim in the map still matches the revised text.

How to use Game the LLM Reviewer

  1. Check you have what it needs: A finished manuscript the agent can read and write, such as a LaTeX project; Git to clone the repository, or Node.js to run the Skills CLI installer; A file-capable agent that supports Agent Skills, such as Claude Code or Codex.
  2. Open Michael-Jiahao-Zhang/game-the-llm-reviewer on GitHub and read the README and license.
  3. Install the skill with npx skills add Michael-Jiahao-Zhang/game-the-llm-reviewer --skill game-the-llm-reviewer, or clone the repo and copy the whole skills/game-the-llm-reviewer/ folder.
  4. Read skills/game-the-llm-reviewer/SKILL.md and the included references before running the edit.
  5. Give the agent your finished manuscript path and ask for a revised copy and changes.md.
  6. Open changes.md and check that each entry keeps the same claims, numbers, citations, and limitations.

These steps come from our top use case, Run a meaning-preserving final pass on a finished paper, which also has a copy-paste agent prompt.

Game the LLM Reviewer alternatives · Best AI repos for Research

About this repo

Requirements

  • A finished manuscript the agent can read and write, such as a LaTeX project
  • Git to clone the repository, or Node.js to run the Skills CLI installer
  • A file-capable agent that supports Agent Skills, such as Claude Code or Codex
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Questions about Game the LLM Reviewer

What is Game the LLM Reviewer?

An agent skill that packages editing strategies for making small, meaning-preserving wording changes to a finished paper before submission, aimed at known LLM reviewer preferences. It is an open-source project on GitHub: https://github.com/Michael-Jiahao-Zhang/game-the-llm-reviewer.

Who is Game the LLM Reviewer for?

Researchers with a finished manuscript who want a file-capable AI agent to make a last editing pass before submission.

What can I do with Game the LLM Reviewer?

4 use cases so far, for example: Run a meaning-preserving final pass on a finished paper; Tighten an abstract to 200 words without losing results; Tune a theory paper's stance, keep theorems and assumptions. Each has steps and a copy-paste agent prompt.

What do I need to run Game the LLM Reviewer?

A finished manuscript the agent can read and write, such as a LaTeX project; Git to clone the repository, or Node.js to run the Skills CLI installer; A file-capable agent that supports Agent Skills, such as Claude Code or Codex.

What are alternatives to Game the LLM Reviewer?

Other hot AI repos in Research: Scientific Agent Skills, Speaker Mem R1, DSH Council, Evo Bot, AI Engineering Course.

Is Game the LLM Reviewer safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.