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Skills/yuan1z0825/nature-skills/nature-response
nature-response logo

nature-response

yuan1z0825/nature-skills
2K installs
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Installation

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

Summary

>-

SKILL.md

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 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 ten-step 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 / 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 ten-step workflow in core/workflow.md: identify mode and decision type, extract editor instructions (IDs E.1) then reviewer comments (R1.1, R2.1), classify each item, build a strategy summary, draft point-by-point responses from the preserved comments, map every claimed change to a manuscript location or an explicit placeholder, 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/ are deep references, 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, 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.

Score

0–100
55/ 100

Grade

C

Popularity15/30

1,811 installs — growing adoption.

Completeness19/30

Documented: full SKILL.md body, one-line install. Missing: description, category/license metadata.

Trust15/25

Community skill with a public GitHub source repository you can review.

Freshness6/15

No update timestamp is tracked for this skill in our catalog.

Scored automatically from popularity, completeness, trust, and freshness — computed only from data in our catalog, never fabricated.

Proud of your score? Add this badge to your README.

Paste a snippet into your GitHub README. The badge updates automatically and links back to this page.

Nature Response skill score badge previewScore badge

Markdown

[![Nature Response skill](https://www.claudemarket.ai/skills/yuan1z0825/nature-skills/nature-response/badges/score.svg)](https://www.claudemarket.ai/skills/yuan1z0825/nature-skills/nature-response)

HTML

<a href="https://www.claudemarket.ai/skills/yuan1z0825/nature-skills/nature-response"><img src="https://www.claudemarket.ai/skills/yuan1z0825/nature-skills/nature-response/badges/score.svg" alt="Nature Response skill"/></a>

Nature Response FAQ

How do I install the Nature Response skill?

Run “npx skills add https://github.com/yuan1z0825/nature-skills --skill nature-response” in your terminal. The skill is added to your agent's skills directory and picked up automatically on the next run — no restart or extra configuration needed.

What does the Nature Response skill do?

>- The full SKILL.md on this page shows the exact instructions the skill gives your agent.

Is the Nature Response skill free?

Yes. Nature Response is a free, open-source skill published from yuan1z0825/nature-skills. As with any third-party skill, review the source repository before installing it into an agent with sensitive access.

Does Nature Response work with Claude Code and OpenClaw?

Yes. Skills use the portable SKILL.md format, so Nature Response works with Claude Code, OpenClaw, Codex, Hermes, and any other agent that reads SKILL.md skills.

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