MCPInstall

nature-response

Draft, audit, or revise responses to peer review, revision cover letters, and marked-manuscript or LaTeX revision packages. Use for 审稿意见回复、逐点回复、返修信、 rebuttals and edits to existing response drafts. Initial-submission materials belong to nature-writing; simulated peer review belongs to nature-reviewer.

Installs
15.3K
Last 24h
+93
Trending rank
#2086
Security
Pass

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/yuan1z0825/nature-skills --skill nature-response
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads nature-response automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

Security audits

Independent scans of the skill's instructions and bundled files.

Gen Agent Trust Hub PassSAFE ·The skill is designed to help researchers draft and manage responses to scientific peer review. It includes a Python utility for verifying LaTeX document consistency and provides structured workflows for handling reviewer feedback. No malicious patterns, obfuscation, or unauthorized data exfiltration were detected.
Socket PassNo alerts
Snyk PassLOW ·Risk: LOW · No issues

SKILL.md

The instructions your agent reads when the skill is triggered.

Nature Reviewer Response — Router

Routing protocol

For a new task, load the core and matching resources below. Reuse already loaded guidance on follow-ups; load more only when the task needs it.

1. Load the manifest and the core layer

Read manifest.yaml. Then read every file listed under always_load:

  • static/core/stance.md — the editor-facing purpose, the default stance, the red lines, and the source hierarchy that apply to every response job.
  • static/core/workflow.md — accepted inputs, the revision correspondence workflow, and the output package format.

2. No content axis — identify mode and language inline

Unlike nature-writing or nature-figure, nature-response has no fragment axis. Its variation is identified at runtime, not by loading different content bodies:

  • task mode — draft / audit / revise / triage-only / cover-letter / revision-package / latex-template / appeal-like.
  • decision type — minor revision, major revision, revise-and-resubmit, transfer after review, or unclear.
  • user language — if the user writes Chinese, also produce the 中文核对 block.

Decision type is required for a new package-level revision strategy or complete response package. First extract it from the editor letter or task context. If it remains unclear, ask whether this is a Major Revision or Minor Revision and pause only decision-dependent work. A local wording edit, audit of an existing reply, or comment-level triage may proceed with decision type marked unknown. Do not infer the decision from the number, tone, or difficulty of reviewer comments.

Use references/intake-and-routing.md to fix the task mode, minimum inputs, and readiness state before drafting. Route appeal-like cases separately; do not draft an appeal as the default path.

For a local edit or bounded audit, return the revised passage or findings and relevant missing facts. Do not expand it into a master tracker, cover letter, or complete revision package unless requested. Apply the package workflow below only to the parts needed for the requested output.

3. Run the workflow

Follow the workflow in core/workflow.md: if the user pasted a journal email, first parse manuscript metadata, decision type, editor instructions, reviewer reports, required files, deadlines, and reviewer-visibility rules from the email; identify mode and pass the decision-type gate; apply the Major- or Minor-Revision strategy without downgrading the severity of individual comments; extract editor instructions (IDs E.1) then reviewer comments (R1.1, R2.1) when present; classify each item by response action and independently verified work status; build an internal/editor master strategy and tracker; draft a standalone privacy-filtered response for each mutually blind reviewer; when a reviewer missed material already present in the manuscript, treat that as a clarity signal and revise the presentation instead of replying that the point was already stated; draft a revision cover letter when required; map every claimed change to a manuscript location or explicit placeholder; mark changed manuscript text in red on a backed-up copy when editing; format quoted revised manuscript text in the response letter in italics; flag missing author input; run QA; and derive package readiness from the per-item statuses and blocking state.

Whenever a response proposes or performs a manuscript main-text edit, also load ../nature-shared/core/main-text-discipline.md. Answer the reviewer completely in the letter, but keep the manuscript change to the shortest text needed for the reader. Prefer replacement or compression over appending, and route non-central robustness or reconciliation detail to SI unless it changes the central interpretation.

Never invent experiments, citations, line numbers, figure panels, supplementary items, editor instructions, or manuscript changes. Mark anything the author must supply as AUTHOR_INPUT_NEEDED.

4. Reach for references only when needed

The files under references/ and templates/ are deep resources, not defaults. Open them on demand per the references.on_demand table in the manifest — for example references/comment-taxonomy.md to classify comments, references/action-mapping.md for tracker fields, references/tone-and-stance.md for disagreement wording, references/difficult-cases.md for impossible experiments / conflicting reviewers / appeal-like cases, references/chinese-author-alignment.md for Chinese author notes, references/latex-templates.md for .tex cover/response/redline outputs, ../nature-shared/core/main-text-discipline.md for reviewer-driven manuscript additions and evidence relocation, references/package-consistency-audit.md whenever the manuscript is edited alongside the letter or the package is about to be compiled and delivered, and references/qa-checklist.md before finalizing.

qa-checklist.md and package-consistency-audit.md are complementary and both apply to a final package: the first asks whether the response is complete, honest, and well-toned; the second asks whether the marked manuscript, the clean manuscript, and the letter actually agree with each other after editing. For a LaTeX package, run scripts/check_package_consistency.py after the first complete draft, after every manuscript edit, and immediately before delivery. Any manuscript edit invalidates the letter's verbatim quotes and page references, so re-run the audit rather than treating it as a one-time final check.

FAQ

What does the nature-response skill do?

Draft, audit, or revise responses to peer review, revision cover letters, and marked-manuscript or LaTeX revision packages. Use for 审稿意见回复、逐点回复、返修信、 rebuttals and edits to existing response drafts. Initial-submission materials belong to nature-writing; simulated peer review belongs to nature-reviewer.

How do I install nature-response?

Run npx skills add https://github.com/yuan1z0825/nature-skills --skill nature-response 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/nature-response/ (personal) or .claude/skills/nature-response/ (project).

Which AI agents can use nature-response?

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 nature-response safe to install?

Security partners have reviewed it: Gen Agent Trust Hub passed; Socket passed; Snyk passed. As with any skill, read the SKILL.md and bundled scripts before installing.

Who maintains nature-response?

It is published by yuan1z0825 in yuan1z0825/nature-skills. It has 15,280 recorded installs.

More from yuan1z0825/nature-skills

View all →

nature-figure

yuan1z0825/nature-skills

Create, revise, audit, and export manuscript scientific figures in Python or R. Use for 论文配图、科研绘图、多面板图 and submission-ready plots, or explicitly requested AI-generated graphical abstracts and mechanism schematics. Not for interactive dashboards, data cleaning, or statistics-only analysis.

Security18.9K installs

nature-polishing

yuan1z0825/nature-skills

Polish, translate, or tighten existing academic prose while preserving facts, terminology, and evidence boundaries. Use for 论文润色、学术翻译、正文精简, or manuscript LaTeX layout fixes. Use nature-writing when the main task is drafting new sections or rebuilding the manuscript argument.

Docs & Writing17.6K installs

nature-paper2ppt

yuan1z0825/nature-skills

Create or improve a Chinese academic PPTX from a scientific paper or research reading notes, with source figures and speaker notes. Use for 论文做PPT、文献汇报、组会PPT and paper-based conference or defense presentations.

Education & Science16.2K installs

nature-writing

yuan1z0825/nature-skills

Draft or restructure scientific manuscript arguments, sections, and initial-submission materials from author-provided evidence. Use for 论文写作、章节起草、论证重构、正文压缩、首次投稿材料. Use nature-polishing for language-only edits to existing prose and nature-response for post-decision correspondence.

Docs & Writing15.8K installs

nature-citation

yuan1z0825/nature-skills

Find and verify Nature/CNS-family literature supporting manuscript claims, with claim-to-source mapping and reference-manager export. Use for Nature系列引用、CNS支撑文献、分段补引用 when this journal scope is requested; use broader literature search for unrestricted sources.

15.7K installs

nature-data

yuan1z0825/nature-skills

Draft or audit manuscript Data/Code Availability statements, dataset access routes, repository plans, and FAIR metadata. Use for 数据可用性声明、数据共享、数据仓库选择 and dataset citations; not general data cleaning or statistical analysis.

Data & Databases15.4K installs

Popular code quality & workflow skills

View category →

grill-me

mattpocock/skills

A relentless interview to sharpen a plan or design.

Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.

handoff

mattpocock/skills

Compact the current conversation into a handoff document for another agent to pick up.

domain-modeling

mattpocock/skills

Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a GLOSSARY.md, or recording or editing an ADR.

codebase-design

mattpocock/skills

Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.

diagnosing-bugs

mattpocock/skills

Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.