Parse reviewer comments into atomic issues with evidence mapping and rebuttal workspaces.
npx skills add https://github.com/Henryhe09/Review2Rebuttal --skill review2rebuttal
Please help me install this Agent Skill. Skill: review2rebuttal Source: https://github.com/Henryhe09/Review2Rebuttal/tree/main Command: npx skills add https://github.com/Henryhe09/Review2Rebuttal --skill review2rebuttal
Manually drafting academic paper rebuttals is time-consuming, prone to unsupported claims, and often leads to missed reviewer concerns and disorganized revision tracking. This Skill automates the end-to-end rebuttal workflow to keep responses grounded, traceable, and aligned with paper evidence.
Share your paper PDF, reviewer comments, and optional code repository with the AI, and ask it to use the review2rebuttal skill to generate a complete, evidence-backed rebuttal workspace for your paper submission.
High-intent search queries and answers about installing and using this skill.
To write an academic paper rebuttal, you can use automated workflows that parse raw reviewer comments into structured atomic issues and map each issue to specific paper facts. This ensures your rebuttal remains grounded, traceable, and aligned with verified paper evidence.
To ensure your peer review response is supported, evidence mapping links each reviewer issue to facts from your paper and optional code repository. This strict grounding keeps your rebuttal accurate and defensible by bounding claims to verified repository evidence.
Yes, you can draft rebuttals for machine learning conferences like ICLR or NeurIPS using a lightweight quick mode. This mode enables fast first-round rebuttal drafting by automatically breaking down reviewer comments into trackable issues for immediate response generation.
The best way to plan reviewer-requested experiments is using a rigorous full mode workflow that includes conservative feasibility assessment. This approach evaluates requested experiments for practical viability and integrates them into an auditable, reproducible rebuttal workspace.
No, providing a code repository is optional for generating grounded academic rebuttals. The workflow can map evidence strictly to paper facts, but supplying a repository allows deeper evidence grounding and more defensible responses to reviewer concerns.
To track and organize multiple reviewer concerns without missing issues, automated atomic issue breakdown splits raw comments into structured, trackable items. This creates an auditable on-disk artifact tracking system ensuring every concern is addressed in the final rebuttal.
Shallow-WGenerate venue-compliant rebuttals from reviewer feedback with provenance constraints.
TitoPrauseePlan and execute an end-to-end research paper pipeline for ML and AI conferences.
xiongqi123123Provision workspace-local rebuttal state and organize memory, reviews, and venue rules.
AlphaLab-USTCAutomate academic writing workflows from outline to rebuttal.
