This repository provides a research-writing skills suite for academic paper lifecycle management. It offers two distinct AI-driven tools: one for comprehensive manuscript review and revision planning, and another for strategically responding to reviewer comments and crafting rebuttals. Researchers can leverage these skills to enhance paper quality and navigate the peer-review process more effectively.

How It Works

The suite comprises two core skills: review-revision and rebuttal-response. review-revision performs a reviewer-style diagnosis, assessing problem validity, insight defensibility, novelty, methodology, experimental support, and writing clarity for drafts or ideas. rebuttal-response transforms reviewer feedback into actionable evidence packages for Area Chairs, prioritizing concerns, identifying persuadable reviewers, and guiding the drafting of targeted responses and AC-facing summaries.

Quick Start & Requirements

Installation involves cloning the repository and linking the review-revision and rebuttal-response skills into the Codex skills directory. Specific commands are provided for Windows PowerShell and macOS/Linux. While designed for Codex, other agents can access the skills by reading the respective directory contents. No specific hardware or software prerequisites (e.g., GPU, CUDA, Python version) are detailed.

Highlighted Details

• Review Revision: Conducts audits on manuscript drafts (PDF, LaTeX, Word, Markdown), performing section-level revisions for introductions, related work, methods, and experiments. It also audits theory, statistics, reproducibility, figures, and tables.
• Rebuttal Response: Focuses on classifying review concerns, prioritizing issues impacting acceptance, and planning evidence to persuade reviewers. It aids in writing AC-facing executive summaries and per-reviewer responses, while also refining rebuttal tone to avoid excessive apologies or defensiveness.

Maintenance & Community

No information regarding maintainers, community channels (e.g., Discord, Slack), or project roadmap is present in the provided README.

Licensing & Compatibility

The README does not specify a software license. Consequently, compatibility for commercial use or closed-source linking cannot be determined from the provided text.

Limitations & Caveats

The repository is presented as a "skills suite" for AI agents, implying its functionality is dependent on the underlying agent's capabilities and interpretation. No specific technical limitations, alpha status, or known bugs are detailed in the README.