paper-revision
Revise papers based on reviewer feedback. Map reviewer concerns to specific sections, apply targeted edits, run additional experiments if needed, and verify improvements. Use after receiving peer review with revision requests.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/lingzhi227/agent-research-skills --skill paper-revision- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads paper-revision automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Paper Revision
Systematically revise papers based on reviewer feedback.
Input
$0— Reviewer comments/feedback$1— Current paper draft (main.tex or paper directory)
References
- Revision workflow and prompts:
~/.claude/skills/paper-revision/references/revision-prompts.md
Workflow
Step 1: Parse and Prioritize Concerns
For each reviewer comment:
- Extract the specific concern
- Classify: major revision, minor revision, question, suggestion
- Map to affected paper section(s)
- Prioritize: address major concerns first
Step 2: Plan Revisions
Create a revision plan:
Concern → Affected Section → Required Action → New Content/Experiment
Categories of actions:
- Clarification: Rewrite text for clarity
- Additional experiment: Run new experiment, add results
- New analysis: Add ablation, statistical test, or comparison
- Structural change: Move, merge, or split sections
- Citation: Add missing references
Step 3: Execute Revisions
For each planned revision:
- Read the current section
- Apply targeted edits (preserve surrounding structure)
- If new experiments needed: use experiment-code skill
- If new figures/tables needed: use figure-generation / table-generation skills
- Mark changes (use
\textcolor{blue}{...}for revised text)
Step 4: Verify Improvements
- Re-run self-review skill to check if scores improved
- Verify all reviewer concerns are addressed
- Check that revisions don't introduce new issues
- Ensure page count still fits venue requirements
Step 5: Write Revision Summary
Generate a diff summary:
- List all changes made with section references
- Note any new experiments, figures, or tables added
- Cross-reference each change to the reviewer concern it addresses
Rules
- Address EVERY reviewer concern — do not skip any
- Preserve paper structure unless structural change is explicitly needed
- New results must come from actual experiments, not hallucinated
- Mark all revised text clearly for the reviewers
- Keep a copy of the previous version before revising
- Compare new scores vs previous scores after revision
Related Skills
- Upstream: self-review
- Downstream: paper-compilation
- See also: rebuttal-writing, paper-writing-section
FAQ
What does the paper-revision skill do?
Revise papers based on reviewer feedback. Map reviewer concerns to specific sections, apply targeted edits, run additional experiments if needed, and verify improvements. Use after receiving peer review with revision requests.
How do I install paper-revision?
Run npx skills add https://github.com/lingzhi227/agent-research-skills --skill paper-revision in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/paper-revision/ (personal) or .claude/skills/paper-revision/ (project).
Which AI agents can use paper-revision?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is paper-revision safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains paper-revision?
It is published by lingzhi227 in lingzhi227/agent-research-skills. It has 1,791 recorded installs.
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