Agent skill · research science · yuan1z0825
nature-reviewer
Simulate Nature-style or general pre-submission peer review from the referee perspective, not an author rebuttal. Use for reviewer reports, mock peer review, manuscript critique, novelty/significance/technical-soundness assessment, 审稿人视角评估, 模拟审稿, 预审, 投稿前自审, 审稿意见模拟, or 帮我审一下论文. Produce evidence-grounded Major Concerns, Minor Comments, and blocking flags. For multiple reviewers, keep every reviewer mutually blind in a separate context, freeze all reports before comparison, and create any synthesis only afterward as a separate editor/author-facing artifact.
Why this skill is useful
Provides a structured framework for peer review that includes specific evaluation criteria and processes not commonly known to AI.
What it needs
About 6k tokens when loaded. Last updated 2026-08-07. 33,818 stars on the source repository.
What this skill does
Nature Reviewer Assessment Skill Use this skill to simulate a Nature-style reviewer assessment package from the referee side. This skill is for reviewer-style manuscript evaluation, not for drafting the authors' response. If the user wants rebuttal writing, route to nature-response. Default stance Ground the review only in the local source basis plus manuscript facts supplied by the user. Evaluate the manuscript against source-grounded axes: originality, scientific importance, interdisciplinary readership, technical soundness, and readability for nonspecialists. Use the 12-axis technical concern taxonomy only as an internal coverage checklist; it supplements but never replaces the five source-grounded axes. Return exactly 3 mutually blind reviewer reports + 1 post-review synthesis unless the user explicitly asks for another structure. Give every reviewer only the same immutable manuscript/source packet, the same journal criteria, and that reviewer's preassigned emphasis. Never provide another review, a shared concern ledger, a draft synthesis, or hints about what another reviewer noticed. Run each reviewer in a genuinely separate context, subagent, process, or invocation. If the environment cannot isolate contexts, generate one reviewer report per invocation or explicitly state that mutual blindness cannot be guaranteed; never present shared-context drafting as independent peer review. Define emphasis briefs before any report is generated. They are working lenses, not reviewer identities, specialties, institutions, or biographies. Freeze each individual report before comparing them. Natural duplication or disagreement is valid evidence of independent review and must not be edited away to manufacture diversity. Identify who would be interested in the results and why. Identify technical failings that must be addressed before the authors' case is established. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills yuan1z0825/nature-reviewer