nature-response

nature-response is a skill for Claude Code from Galaxy-Dawn/claude-scholar. It costs 91 tokens per session (1,329 once invoked), scanned A, original, MIT.

A workflow for writing point-by-point responses to Nature-family peer reviewers. It maps each reviewer concern to a manuscript change, explanation, or unresolved author task.

In plain words
What is it for?
Use it to draft, audit, and revise response letters based on reviewer comments, editor decisions, and documented manuscript changes.
Why use it?
It helps authors answer every comment accurately without inventing experiments, citations, line numbers, or revisions.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the claude-scholar plugin — 45 skills, 34 commands, 6 agents, 5 hooks shipped together

Good fit Use it to draft, audit, and revise response letters based on reviewer comments, editor decisions, and documented manuscript changes.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/galaxy-dawn/claude-scholar/nature-response
About the project

Claude Scholar is a semi-automated research assistant for academic research and software development, supporting literature review, coding, experiments, reporting, writing, and project knowledge management. Computer science and AI researchers use it across the research workflow with several coding-agent platforms; the catalogue contains its skills, commands, agents, hooks, plugin, and instruction.

Galaxy-Dawn/claude-scholar · 5,419 stars · on GitHub

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 Galaxy-Dawn/claude-scholar --skill nature-response
Clone the repo
git clone --depth 1 https://github.com/Galaxy-Dawn/claude-scholar

Made for: Claude Code.

Or install claude-scholar, the plugin that ships this one along with the rest of its 45 skills, 34 commands, 6 agents, 5 hooks.

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/galaxy-dawn/claude-scholar/nature-response/github.svg)](https://agentmods.dev/skills/galaxy-dawn/claude-scholar/nature-response)
Your own site
<a href="https://agentmods.dev/skills/galaxy-dawn/claude-scholar/nature-response"><img src="https://agentmods.dev/badge/skills/galaxy-dawn/claude-scholar/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/galaxy-dawn/claude-scholar/nature-response"><img src="https://agentmods.dev/badge/skills/galaxy-dawn/claude-scholar/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 1,329 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found 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 $0.01329
Opus 5 $0.00046 $0.00665
Sonnet 5 $0.00018 $0.00266
Haiku 4.5 $0.00009 $0.00133

Measured 7d ago against content hash 9521d5cd6d66, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, 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 7d ago.

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

Copies of this mod

1 near-identical copy found in the catalogue:

skills/nature-response/SKILL.md · 128 lines

How it starts

The opening of the file, as written. The whole thing — 128 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 · 128 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. 7d ago First seen · 128 lines · 91 tokens per session scan A 9521d5cd6d66

Subscribe to this mod's changes

nature-response is a skill published in the GitHub repository Galaxy-Dawn/claude-scholar (5,419 stars, last pushed 15d ago), licensed MIT. It adds 91 tokens to every session and 1,329 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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