yzxoi/paperly-codex/review-response

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Use when the user wants to draft structured responses to peer review comments, supported by evidence and relevant literature.

Install

npx vskill@latest install yzxoi/paperly-codex/review-response

SKILL.md

Review Response

Overview

Drafts structured, evidence-backed responses to peer reviewer comments. Grounds rebuttals in the team's literature base, surfaces relevant papers to cite in response, and calibrates tone appropriately — firm where warranted, concise throughout.

When to Use

  • User pastes reviewer comments and asks for a response draft
  • User asks "how should we respond to reviewer 2?"
  • Lab has a revise-and-resubmit and needs to draft the response letter
  • User wants to find papers that address a reviewer's concern
  • User needs help deciding which reviewer concerns to push back on vs. accept

Key Capabilities

  • Parse reviewer comment threads and categorize by type: factual concern, missing citation, methodology critique, scope request, clarity issue
  • Draft point-by-point response for each comment
  • Search team corpus and external literature for papers addressing reviewer concerns
  • Recommend response strategy: concede / address / push back / defer
  • Generate revision summary letter (cover letter for resubmission)
  • Calibrate tone: firm scientific disagreement vs. gracious acknowledgment

Usage Examples

Draft response to reviewer comments
python
review_response.draft(
reviewer_comments="[paste full review here]",
manuscript_abstract="[paste abstract]",
corpus=review.get_papers(),
tone="firm_but_respectful",
include_literature_search=True
)
Categorize and triage reviewer concerns
python
review_response.triage(
reviewer_comments="[paste full review]",
output=["category", "effort_estimate", "recommended_strategy"]
)
Find papers that address a specific reviewer concern
python
review_response.find_supporting_literature(
concern="The authors do not address out-of-distribution generalization",
corpus=review.get_papers(),
search_external=True
)
Generate cover letter for resubmission
python
review_response.cover_letter(
original_reviews=["R1 text", "R2 text", "R3 text"],
changes_made=["Added ablation study in Section 4.2", "Clarified limitation in Discussion"],
target_journal="Nature Methods"
)

Output Format

Response draft is structured as: summary paragraph + numbered point-by-point responses. Each response includes: reviewer quote, response text, and any new citations to add. Triage output is a prioritized table. Cover letter is formatted prose ready to submit.

Notes

  • This skill does not decide what experiments to run — it drafts the prose around decisions made by the authors
  • Tone calibration: "firm" = disagree with evidence; "gracious" = accept and thank; default is balanced
  • Combine with evidence-grading to assess whether a reviewer's concern has strong literature support

Security

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