---
id: gh-nature-writing
name: "nature-writing"
url: https://skills.yangsir.net/skill/gh-nature-writing
author: yuan1z0825
domain: science
tags: ["scientific-writing", "academic-research", "manuscript-drafting", "nature-style", "research-paper"]
install_count: 15400
rating: 4.50 (120 reviews)
github: https://github.com/yuan1z0825/nature-skills/tree/main/plugins/nature-skills/skills/nature-writing
---

# nature-writing

> 此技能专为撰写或重构 Nature 风格的科学手稿而设计，能根据作者提供的论点、结果、图表、笔记或中文草稿，生成或优化摘要、引言、方法、讨论、结论等章节。它专注于构建严谨的论证结构和章节草稿，帮助科研人员高效地将研究成果转化为符合期刊要求的学术论文。

**Stats**: 15,400 installs · 4.5/5 (120 reviews)

## Before / After 对比

### 科学手稿初稿完成效率

**Before**:

用户在手动撰写或重构 Nature 风格的科学手稿时，常面临耗时、结构不一致和难以准确把握期刊规范的痛点。从原始数据和笔记中构建逻辑严谨的论证链条，并确保各章节符合高标准，需要投入大量精力与时间。

**After**:

此技能能高效地根据输入生成或优化 Nature 风格的科学手稿章节，确保论证结构严谨且符合期刊要求。它显著减少了科研人员将研究成果转化为高质量、可发表论文所需的时间和精力，提升了写作效率和质量。

| Metric | Before | After | Change |
|---|---|---|---|
| 初稿完成时间 | 80小时 | 10小时 | -87% |

## Readme

# Nature-Style Scientific Writing — Router

This skill is split into two layers:

- A **static layer** under `static/` that holds versioned, reusable content fragments (core stance + workflow, paper-type playbooks, per-section drafting guidance, language-specific rules, per-journal style).
- A **dynamic layer** (this file plus `manifest.yaml`) that detects the request's axes and loads only the fragments needed for the current job.

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

## Routing protocol

Follow these five steps every time the skill is invoked.

### 1. Load the manifest and the core layer

Read [manifest.yaml](manifest.yaml). It declares the axes (`paper_type`, `section`, `language`, `journal`), the allowed values, and the file paths each value maps to.

Also read every file listed under `always_load`. These hold the default stance, writing workflow, and output format that apply to every drafting job.

### 2. Detect the axis values for this request

For each axis in the manifest, decide the value using the manifest's `detect:` hint and the user's input:

- `paper_type` — research / methods / hypothesis / algorithmic / review. Default: research.
- `section` — abstract / intro / related-work / method / experiments / discussion / conclusion / title. May be multiple. Ask the user if it is ambiguous and matters for the draft.
- `language` — en or zh-to-en. Detect from the user's notes themselves.
- `journal` — nature / nat-comms / generic. Default: generic. If the user names a Nature subjournal, treat it as `nature`.

State the detected axis values in one short line to the user before drafting, so they can correct you cheaply.

### 3. Load the matching fragments

For each axis value, Read the file mapped in the manifest. Skip the `section` axis only when the user has explicitly asked for a free-floating argument paragraph with no section context.

Do **not** read every fragment in `static/`. Load only what step 2 selected.

### 4. Draft using the loaded material

Apply the loaded fragments in this priority order:

1. Core stance + intake (`core/stance.md`) — surface missing claim / evidence / boundary before drafting.
2. Paper-type playbook — argument chain, drafting order.
3. Section-specific drafting rules and structure.
4. Journal-specific framing and constraints.
5. Language-specific sentence and paragraph rules (apply last).

Run the 8-step workflow in `core/workflow.md` end-to-end. Do not skip steps 1-3 (planning) just because the user asked for prose immediately — write the one-sentence argument first.

If essential evidence or boundary is missing, write a placeholder and list it under `Assumptions or missing inputs:` instead of inventing content.

### 5. Reach for references only when needed

The files under `references/` are deep references and the example library, not defaults. Open them on demand per the `references.on_demand` table in the manifest. Typical triggers:

- The user asks for a concrete example or template → `references/examples/index.md`.
- A section's draft has structural problems that the section fragment alone does not explain → the matching `references/<section>.md`.
- The user needs a broad-audience `Nature` abstract opening or asks about a `summary paragraph` → `references/nature-summary-paragraph.md`.
- The user asks "does this paragraph flow?" → `references/paragraph-flow.md`.
- The user asks for a self-review or rejection-risk audit → `references/paper-review.md`.

## Why this split

- The static layer is versioned and reviewable. Adding a new journal style, paper type, or section is one new file plus one manifest line.
- The dynamic layer keeps each invocation cheap: only the fragments relevant to this draft enter context, instead of the full multi-thousand-line reference set.
- The router itself is short on purpose. Update fragments, not this file, when adding scope.
- This structure mirrors `nature-polishing` so shared content can later be lifted into a `_shared/` layer used by both skills.


---

# `nature-writing` skill

A Nature-style manuscript writing skill for drafting or rebuilding sections from
author-provided claims, figures, results, notes, or Chinese drafts.

## What it does

`nature-writing` helps write:

- titles
- abstracts
- introductions
- results narratives
- discussions
- conclusions
- significance paragraphs
- manuscript outlines

It is for argument construction and section drafting. For sentence-level polish
of an existing draft, use `nature-polishing`.

## Built from

Close reading of curated Nature and Nature Communications research articles
across materials, energy systems, construction decarbonization and machine
learning, combined with the existing writing-strategy rules in this repository.

Section-level writing and reviewer-facing self-review guidance is also adapted
from Prof. Peng Sida's open research-writing notes:

- https://pengsida.notion.site/c1a22465a0fa4b15a12985223916048e
- https://github.com/pengsida/learning_research

## File structure

```text
nature-writing/
├── README.md
├── SKILL.md
└── references/
    ├── abstract.md
    ├── article-architecture.md
    ├── chinese-author-workflow.md
    ├── conclusion.md
    ├── experiments.md
    ├── introduction.md
    ├── method.md
    ├── nature-summary-paragraph.md
    ├── paper-review.md
    ├── paragraph-flow.md
    ├── related-work.md
    └── examples/
```

## Key rules

| Domain | Core rule |
|---|---|
| Evidence first | Do not invent data, mechanisms, statistics, sample sizes or novelty |
| Abstract | Context, gap, approach, key result, implication, boundary |
| Introduction | Field scale, bottleneck, prior attempts, unresolved gap, present study; for `Nature`, use a staged summary-paragraph funnel |
| Method | Explain module motivation, design, forward process, and technical advantage |
| Results | Build an evidence ladder, not a chronological lab diary |
| Experiments | Tie every major claim to comparison, ablation, metric, or stress-test evidence |
| Discussion | Explain meaning, prior-work relation, constraints and future use |
| Review | Run adversarial self-review before submission |
| Chinese notes | Translate intent and argument, not clause order |


---
*Source: https://skills.yangsir.net/skill/gh-nature-writing*
*Markdown mirror: https://skills.yangsir.net/api/skill/gh-nature-writing/markdown*