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Nature Reviewer

  • 1 installs
  • 33.4k repo stars
  • Updated August 4, 2026
  • yuan1z0825/nature-skill

This is a copy of nature-reviewer by yuan1z0825 - installs and ranking accrue to the original listing.

Helps with ai & agent building tasks during AI-assisted development.

About

nature-reviewer is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted coding.

  • nature-reviewer
  • AI & Agent Building
  • AI-coding skill

Nature Reviewer by the numbers

  • 1 all-time installs (skills.sh)
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/yuan1z0825/nature-skill --skill nature-reviewer

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Listed on Skillselion
Installs1
repo stars33.4k
Last updatedAugust 4, 2026
Repositoryyuan1z0825/nature-skill

What it does

Helps with ai & agent building tasks during AI-assisted development.

Files

SKILL.mdMarkdownGitHub ↗

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.
  • Return exactly 3 reviewer reports + 1 cross-review synthesis unless the user explicitly asks for another structure.
  • The three reviewers may differ only in emphasis; do not invent reviewer identities, specialties, institutions, or biographies.
  • Identify who would be interested in the results and why.
  • Identify technical failings that must be addressed before the authors' case is established.
  • Distinguish clearly between what is supported, what is weak, and what is not assessable from the provided material.
  • Do not claim the editor's final decision or certainty about fit to Nature.

Accepted inputs

The skill may receive:

  • full manuscript draft
  • abstract, summary paragraph, or cover-summary style text
  • introduction, results, discussion, or methods excerpts
  • figure legends, selected figures, or result notes
  • author notes in Chinese or English describing the claimed contribution
  • pre-submission positioning notes

If the provided material is partial, perform a bounded review and mark the assessment boundary explicitly.

Workflow

1. Identify the input scope and whether the job is a reviewer-style assessment rather than rebuttal drafting. 2. Extract a shared manuscript fact base: main claim, visible evidence, claimed significance, likely readership, and visible limitations. 3. Check readiness and label missing evidence or missing sections instead of inventing them. 4. Assess the manuscript using the source-grounded axes. 5. Generate Reviewer 1, Reviewer 2, and Reviewer 3 using shared facts but different emphasis. 6. Generate a Cross-review synthesis that captures consensus and weighting differences. 7. Run QA for groundedness, coverage, role boundaries, and non-invention.

Output format

Unless the user asks for another format, return:

Review setup
- Input scope:
- Assessment boundary:
- Shared manuscript claim summary:
- Visible evidence base:
- Missing materials affecting confidence:

Reviewer 1
- Overall assessment:
- Who would be interested in the results, and why:
- Major strengths:
- Major concerns:
- Technical failings that need to be addressed before the case is established:
- Assessment against Nature-style criteria:
- Recommendation posture:

Reviewer 2
[Same structure]

Reviewer 3
[Same structure]

Cross-review synthesis
- Consensus strengths:
- Consensus technical risks:
- Where emphasis differs across reviewers:
- Broad-interest / significance readout:
- Most important issues to resolve before a strong Nature-style case is established:

Risk / unsupported claims
- [specific unsupported or not-assessable items]

Red lines

  • Do not invent reviewer identities, specialty roles, or selection history.
  • Do not invent experiments, validations, controls, citations, figure details, line numbers, or prior-work distinctions not present in the input.
  • Do not silently turn reviewer assessment into author rebuttal drafting.
  • Do not present the review as an editorial decision letter.
  • Do not state that the manuscript belongs in Nature as a settled fact.
  • Do not omit technical failings when the provided evidence does not establish the authors' case.

Related files

FileOpen when
references/source-basis.mdYou need source provenance, local rule summaries, or source-vs-implementation boundaries
references/reviewer-workflow.mdYou need the invocation order, fact-base extraction flow, or synthesis rules
references/review-axes.mdYou need the evaluation axes or reviewer weighting logic
references/report-structure.mdYou need the default output contract or section anatomy
references/role-boundaries.mdYou need constraints on reviewer differences and editor-versus-reviewer boundaries
references/qa-checklist.mdYou are finalizing an output and need groundedness / non-invention checks
[references/editorial criteria and processes.md](references/editorial criteria and processes.md)You need the primary local Nature source text

Source hierarchy

Use sources in this order:

1. references/editorial criteria and processes.md 2. manuscript facts supplied by the user 3. conservative local implementation rules documented in references/source-basis.md

If a user asks for policy-level certainty beyond this local source, state the limit instead of improvising broader journal policy.

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