nature-response

nature-response is a skill for Claude Code from YuanyuanMa03/academic-research-skills. It costs 91 tokens per session (1,342 once invoked), scanned A, a copy of nature-response, MIT.

A response-letter workflow for answering journal reviewers point by point during manuscript revision. A reviewer response letter explains how each reviewer concern was addressed, where the manuscript changed, or why the authors disagree.

In plain words
What is it for?
It helps draft, audit, and revise responses to reviewer comments and editor decision letters for Nature-family journal submissions.
Why use it?
It prevents comments from being missed and keeps each reply tied to evidence, a manuscript change, or an explicitly unresolved action. It also avoids inventing experiments, citations, locations, or changes.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter.

Part of the nature-response plugin — 1 skill shipped together

Good fit It helps draft, audit, and revise responses to reviewer comments and editor decision letters for Nature-family journal submissions.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/yuanyuanma03/academic-research-skills/nature-response
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add YuanyuanMa03/academic-research-skills --skill nature-response
Clone the repo
git clone --depth 1 https://github.com/YuanyuanMa03/academic-research-skills

Made for: Claude Code.

Or install nature-response, the plugin that ships this one along with the rest of its 1 skill.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for nature-response

README.md
[![agentmods](https://agentmods.dev/badge/skills/yuanyuanma03/academic-research-skills/nature-response/github.svg)](https://agentmods.dev/skills/yuanyuanma03/academic-research-skills/nature-response)
Your own site
<a href="https://agentmods.dev/skills/yuanyuanma03/academic-research-skills/nature-response"><img src="https://agentmods.dev/badge/skills/yuanyuanma03/academic-research-skills/nature-response/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for nature-response

Your own site · 80×15
<a href="https://agentmods.dev/skills/yuanyuanma03/academic-research-skills/nature-response"><img src="https://agentmods.dev/badge/skills/yuanyuanma03/academic-research-skills/nature-response.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 91 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,342 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 95% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00091 $0.01342
Opus 5.5 $0.00036 $0.00537
Sonnet 5.5 $0.00018 $0.00268
Haiku 4.5 $0.00009 $0.00134

Measured today against content hash 24fc2dd19e34, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

nature-response scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

95% identical to nature-response — 10 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

plugins/nature-response/skills/nature-response/SKILL.md · 129 lines

How it starts

The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Nature Reviewer Response Skill

Use this skill to convert editor decision letters, reviewer comments, author notes, or draft rebuttals into an auditable point-by-point response package for manuscript revisions.

The response letter is an editor-facing verification document. The goal is to show that every reviewer concern has been understood, addressed, and mapped to a concrete manuscript change, justified scientific response, or unresolved author action.

Default stance

  • Preserve each reviewer comment faithfully before responding.
  • Every reviewer concern must be answered, cross-referenced, or explicitly marked as unresolved.
  • Map every response to manuscript evidence, a revision location, a justified disagreement, or AUTHOR_INPUT_NEEDED.
  • Do not invent experiments, analyses, citations, line numbers, figure panels, supplementary materials, editor instructions, reviewer identities, or manuscript changes.
  • Prefer concise, evidence-linked replies over long defensive explanations.
  • When disagreeing, acknowledge the concern first, then give a scientific or scope-based reason.
  • When a reviewer misunderstood the manuscript, first consider whether the manuscript presentation caused the misunderstanding.
  • Treat rebuttal letters as potentially public review artifacts; write with professional tone and traceability.

Accepted inputs

The skill may receive:

  • editor decision letter
  • reviewer comments
  • previous response draft
  • manuscript change notes
  • tracked-change summary
  • line or page numbers
  • figure, table, and supplement list
  • author notes in Chinese or English
  • journal name and article type

If reviewer boundaries or comment segmentation are ambiguous, flag the ambiguity instead of inventing reviewer structure.

Workflow

  1. Identify task mode and input readiness: draft, audit, revise, triage-only, or appeal-like.
  2. Identify decision type: minor revision, major revision, revise-and-resubmit, transfer after review, or unclear.
  3. Extract editor instructions first and assign IDs such as E.1, then split reviewer comments with IDs such as R1.1, R1.2, and R2.1.
  4. Classify each item by category, severity, action label, missing input, readiness state, and risk.
  5. Create a response strategy summary before drafting prose.
  6. Draft responses using preserved reviewer comments unless the mode is triage-only or appeal-like.
  7. Map each claimed change to manuscript location, figure, table, supplement, citation, or explicit placeholder.
  8. Flag missing author input rather than fabricating details.
  9. Run QA for completeness, traceability, factuality, tone, and unresolved risk.
  10. Return the response package with package readiness: ready_to_submit, draft_with_placeholders, needs_author_input, or blocked.

Read the full file on GitHub · 129 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. today First seen · 129 lines · 91 tokens per session scan A 24fc2dd19e34

Subscribe to this mod's changes

nature-response is a skill published in the GitHub repository YuanyuanMa03/academic-research-skills (75 stars, last pushed today), licensed MIT. It adds 91 tokens to every session and 1,342 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 95% identical to nature-response, differing in 10 lines, and is treated as a copy.

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