
Rebuttal Writing
Turns peer review comments into structured, evidence-based rebuttals with proper academic formatting. It parses reviewer concerns, categorizes them by severity, then generates responses that cite specific sections, equations, and experimental results from your paper. The workflow enforces good rebuttal practices: acknowledge the point, respond with concrete evidence, and write in past tense ("We have added" not "We will add"). Outputs in standard rebuttal format with reviewer-by-reviewer responses and a summary of changes at the top. Useful after getting reviews back, especially when you're staring at three pages of criticism and need to organize your responses methodically. Saves you from the tedious work of extracting and numbering each concern manually.
- skills.sh installs
- 1.7K
- GitHub stars
- 459
- last updated
- Aug 21, 2026
Install
$ npx -y skills add lingzhi227/agent-research-skills --skill rebuttal-writing --agent claude-codeInstalls into .claude/skills of the current project.
Files
Rebuttal Writing
Generate structured, evidence-based rebuttals to peer review comments.
Input
$0— Reviewer comments (text file, or pasted directly)- Optional: current paper draft for reference
References
- Rebuttal prompts and format templates:
~/.claude/skills/rebuttal-writing/references/rebuttal-prompts.md
Workflow
Step 1: Parse Review Comments
For each reviewer:
- Extract individual concerns/questions/weaknesses
- Categorize each: major concern, minor concern, question, suggestion
- Identify the core issue behind each concern
Step 2: Generate Responses
For each concern:
- Acknowledge the reviewer's point
- Respond with evidence — cite specific sections, equations, experiments, or results from the paper
- Describe what was done (not what will be done) — "We have added...", "Our experiments show..."
- If additional experiments are needed, describe the new results concretely
Step 3: Format Rebuttal
Use the standard rebuttal format:
# Response to Reviewers
We thank all reviewers for their constructive feedback. We address each concern below.
## Reviewer #1
Sponsors
Details
- Repository
- github.com/lingzhi227/agent-research-skills
- Categories
- Git & Pull Requests, Documentation, Code Review & Quality, AI & Agent Building, Data Science & ML
- First seen
- Jun 3, 2026
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