Review Response
SkillDev toolsSystematic review response workflow from comment analysis to professional rebuttal writing. Use when the user asks to "write rebuttal", "respond to reviewers", "draft review response", or "analyze review comments". Improves paper acceptance rates.
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the Review Response skill
What this skill tells your AI
The instructions your AI receives, as published by brycewang-stanford/auto-empirical-research-skills in skills/33-Galaxy-Dawn-claude-scholar/skills/review-response/SKILL.md and read by ahel’s review.
A systematic review response workflow that helps researchers efficiently and professionally reply to reviewer comments.
Core Features
- Review Analysis - Parse and classify reviewer comments (Major/Minor/Typo/Misunderstanding)
- Response Strategy - Develop response strategies for different comment types (Accept/Defend/Clarify/Experiment)
- Rebuttal Writing - Write structured, professional rebuttal documents
- Tone Management - Optimize tone to maintain professionalism, respect, and evidence-based arguments
Workflow
Receive reviewer comments -> Parse and classify -> Develop strategy -> Write responses -> Tone check -> Final rebuttal
When to Use
Use this skill when you need to:
- "Help me write a rebuttal"
- "How to respond to reviewer comments"
- "Analyze these review comments"
- "Develop a review response strategy"
Usage Steps
- Provide reviewer comments - Share the reviewer comments text or file with Claude
- Analysis and classification - Claude automatically parses and classifies the comments
- Strategy recommendations - Receive response strategy suggestions for each comment
- Write rebuttal - Generate a structured rebuttal document based on the strategy
- Optimize tone - Review and optimize the professionalism and politeness of responses
Core Principles
- Professionalism - Maintain an academically professional tone and expression
- Respectfulness - Respect the reviewers' opinions and time
- Evidence-based - Support every response with sufficient reasoning and evidence
- Completeness - Ensure all reviewer comments receive a response
Success Factors (Based on ICLR Spotlight Paper Analysis)
Key lessons extracted from successful rebuttal cases:
1. Acknowledge Strengths, Respond Positively to Criticism
- Reviewers will first acknowledge the paper's strengths (novelty, impact, practical applicability)
- Even spotlight papers receive constructive criticism
- Strategy: Thank reviewers for acknowledged strengths first, then address criticism specifically
2. Provide Clarity and Intuitive Understanding
- Even high-quality papers may have clarity issues
- Need to provide intuition and detailed explanations for readers with different backgrounds
- Strategy: Expand key sections, move technical details to appendix, add step-by-step walkthroughs
3. Thorough Justification of Experimental Setup
- Need to justify experimental setup choices
- Consider and discuss alternative metrics
- Provide comprehensive experiments to support claims
- Strategy: Add ablation studies, explain why specific experimental setups were chosen
4. Emphasis on Ethical Considerations
- For research involving privacy, security, and other sensitive topics, ethical considerations are crucial
- Reviewers pay special attention to ethical implications
- Strategy: Proactively discuss ethical considerations, even if reviewers don't explicitly request it
5. Highlight Practical Application Value
- Reviewers value practical applicability and scalability of methods
- "Easily applicable" and "scalable" are important strengths
- Strategy: Emphasize practical benefits and scalability in the rebuttal
Integration with paper-miner global writing memory
When the rebuttal task involves:
- tone calibration,
- rebuttal phrasing,
- clarification language,
- structuring multi-point responses,
- or learning from strong prior paper/review writing,
read this file before drafting:
~/.claude/skills/ml-paper-writing/references/knowledge/paper-miner-writing-memory.md
Default read order for rebuttal work
- reviewer comments and paper context
paper-miner-writing-memory.mdreferences/response-strategies.mdreferences/rebuttal-templates.mdreferences/tone-guidelines.md
Read narrowly:
- start with
How this helps our writing, - then inspect
Reusable phrasing, - then inspect
Venue-specific signalsif the rebuttal is venue-sensitive, - use
Writing patterns minedonly when the response needs stronger rhetorical structure.
Do not quote the memory mechanically. Use it to improve structure, clarity, restraint, and professionalism.
Reference Documents
For detailed guides, refer to:
references/review-classification.md- Review comment classification criteriareferences/response-strategies.md- Response strategy libraryreferences/rebuttal-templates.md- Rebuttal templates and examplesreferences/tone-guidelines.md- Tone and expression guidelines
Related Tools
- Agent:
rebuttal-writer- Dedicated agent for rebuttal writing and optimization - Command:
/rebuttal <review_file>- Quick-start the rebuttal workflow
Signals
- GitHub stars
- 4k
- Forks
- 531
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
review-response-brycewang-stanford- Source
- github.com/brycewang-stanford/auto-empirical-research-skills
github.com/brycewang-stanford/auto-empirical-research-skills
Related picks
Skill · brycewang-stanford
The pick for Academic03-academic-writing
Skill · 24kchengye
The pick for Academicteach
Skill · mattpocock
More in Dev toolsimplement
Skill · mattpocock
More in Dev toolsponytail
Skill · dietrichgebert
More in Dev toolscaveman
Skill · juliusbrussee
More in Dev tools