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yuan1z0825/nature-skills3.1k installs

nature-response

Draft, audit, or revise Nature-style revision correspondence packages: point-by-point reviewer response letters, rebuttal letters, revision cover letters, LaTeX cover/response templates, and red-marked revised-manuscript excerpts. Use for reviewer comments, editor decision letters, pasted editorial emails, response drafts, cover letters, response to reviewers, rebuttal, 修回信, 返修邮件, 编辑邮件, 返修 cover letter, 审稿意见回复, 逐点回复, 大修回复, 小修回复, 回复审稿人, 修改稿回复, 写rebuttal, 回应审稿意见, 标红修改, or LaTeX 模板.

How do I install this agent skill?

npx skills add https://github.com/yuan1z0825/nature-skills --skill nature-response
view source ↗

Is this agent skill safe to install?

  • Gen Agent Trust Hubpass

    The 'nature-response' skill is an instructional tool designed to assist researchers in drafting professional responses to academic journal reviewers. It contains no executable code, requires no network access, and includes specific guardrails to prevent the AI from fabricating data, citations, or manuscript details. No security vulnerabilities were detected.

  • Socketpass

    No alerts

  • Snykpass

    Risk: LOW · No issues

What does this agent skill do?

Nature Reviewer Response — Router

This skill is split into two layers:

  • A static layer under static/ that holds versioned, reusable content fragments (the default stance and red lines, and the response workflow with output format).
  • A dynamic layer (this file plus manifest.yaml) that loads the core every time and reaches for the deeper response references or templates only when a step needs them.

Do not try to apply the response logic from memory or from this router. Always load fragments from disk as described below.

Routing protocol

Follow these four steps every time the skill is invoked.

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 modedraft / 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.

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.

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, and deadlines from the email; identify mode and decision type; extract editor instructions (IDs E.1) then reviewer comments (R1.1, R2.1) when present; classify each item; build a strategy summary; draft point-by-point responses and/or a revision cover letter; 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; start each new reviewer response on a new page in LaTeX/print-oriented outputs; flag missing author input; run QA; and return the package with a readiness state.

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, and references/qa-checklist.md before finalizing.

Why this split

  • The static layer is versioned and reviewable; the core stays small for a normal response.
  • The dynamic layer keeps each invocation cheap: the difficult-case, taxonomy, and QA depth load only when a step needs them.
  • The router itself is short on purpose. Update fragments and references, not this file, when adding scope.
  • This structure mirrors nature-writing, nature-polishing, nature-reader, nature-paper2ppt, nature-figure, and nature-citation.

Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.

<a href="https://skillzs.dev/skills/yuan1z0825/nature-skills/nature-response">View nature-response on skillZs</a>