Agent skill

Nature Writing

by Galaxy-Dawn in Galaxy-Dawn/claude-scholar

Draft, restructure, or plan Nature-style manuscript sections from author-provided claims, results, figures, notes, or Chinese drafts.

MITAuto-check passedResearch & Science

Install Nature Writing

skills CLI
$ npx skills add Galaxy-Dawn/claude-scholar --skill nature-writing -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Galaxy-Dawn/claude-scholar nature-writing --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Galaxy-Dawn/claude-scholar.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/nature-writing .claude/skills/nature-writing && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
nature-writing
GitHub stars
5.7k
Used in
1 other repo
Token cost
~1.9k tokens
SKILL.md length
802 words
Files
43 (incl. references)
Skills in repo
34
Repo updated
First seen
Licence
MIT

At a glance

Draft, restructure, or plan Nature-style manuscript sections from author-provided claims, results, figures, notes, or Chinese drafts.

  • Works in 8 steps: Build a one-sentence argument: `In… → Choose the section architecture from… → Map each paragraph to one job: context,… → …
  • The user wants to write
  • SKILL.md covers Core stance, Mined writing memory, When to open extra files and Intake, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Nature Writing is an agent skill from Galaxy-Dawn/claude-scholar. Draft, restructure, or plan Nature-style manuscript sections from author-provided claims, results, figures, notes, or Chinese drafts. Use when the user wants to write or rebuild an abstract, introduction, results narrative, discussion, conclusion, title, or full manuscript argument rather than only polish finished prose.

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 47 other files, including reference files (for example `README.md`, `agents/openai.yaml` and `references/abstract.md`).

It sits in Research & Science. The repository describes itself as: Semi-automated research assistant for academic research and software development. Supports Claude Code, Codex CLI, Kimi Code CLI, and OpenCode across ideation, coding… The licence is MIT.

When your agent uses it

  • The user wants to write
  • Rebuild an abstract
  • Results narrative
  • Full manuscript argument rather than only polish finished prose

Example prompts

  • “/nature-writing”

Workflow steps

8 steps, taken from the first numbered list in SKILL.md.

  1. Build a one-sentence argument: `In [system/problem], we show [advance] using
  2. Choose the section architecture from references/article-architecture.md.
  3. Map each paragraph to one job: context, gap, approach, result, comparison,
  4. Draft from evidence outward. Keep claims near the data that support them.
  5. Calibrate verbs: show, demonstrate, suggest, indicate, enable,
  6. Remove unsupported novelty and universal claims.
  7. Run a paragraph-flow check: one paragraph, one message, with a clear first
  8. Return prose plus concise notes on assumptions and missing inputs.

What it can do on your machine

Read from SKILL.md and the folder at commit 9037873. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Nature Writing loads about 1.9k tokens when it runs, and up to ~26k if it reads all its reference files. Until then it costs about 84 tokens; SKILL.md has 802 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~84
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~26k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Galaxy-Dawn/claude-scholar at commit 9037873, republished under its MIT licence (© Galaxy-Dawn). 802 words, ~1,880 tokens.

Download SKILL.mdSave it as .claude/skills/nature-writing/SKILL.md (or your agent's skills folder). This skill also uses 42 other files; get the full folder from GitHub.
name
nature-writing
description
Draft, restructure, or plan Nature-style manuscript sections from author-provided claims, results, figures, notes, or Chinese drafts. Use when the user wants to write or rebuild an abstract, introduction, results narrative, discussion, conclusion, title, or full manuscript argument rather than only polish finished prose.
version
0.2.0
author
Community contribution based on curated Nature/Nature Communications writing patterns and open research-writing notes

Nature-Style Scientific Writing

Use this skill when the user needs help creating or rebuilding manuscript prose, not merely polishing existing sentences.

Core stance

  • Author evidence comes first. Do not invent results, mechanisms, references, methods, novelty, sample sizes, statistics or limitations.
  • Write the argument before writing the sentences.
  • Make the paper easy to judge: relevance, novelty, trust, reuse and meaning.
  • Use ambitious but bounded claims.
  • If essential evidence is missing, write a placeholder or ask for the missing input instead of filling the gap.

Mined writing memory

Before drafting or restructuring academic prose, check the active installed skills/ml-paper-writing/references/knowledge/paper-miner-writing-memory.md under the current client's skill home. Read only entries relevant to this paper's section, article type, and venue. Use mined patterns for structure and wording ideas, while grounding every claim in the author's evidence and the target journal's requirements. Do not copy source phrasing. If the memory is absent or has no relevant entries, continue with this skill's references.

When to open extra files

FileOpen when
references/article-architecture.mdYou need section-level structure, argument order, or published-article writing patterns
references/abstract.mdDrafting or revising an abstract, especially challenge-contribution and challenge-insight-contribution forms
references/introduction.mdDrafting or revising an Introduction, task framing, technical challenge, contribution framing, or teaser/pipeline logic
references/related-work.mdRebuilding Related Work as topic synthesis instead of a paper-by-paper list
references/method.mdWriting Method sections, pipeline modules, module motivation, technical advantages, or implementation details
references/experiments.mdPlanning or writing Experiments/Results around baselines, ablations, metrics, tables, figures, and claim support
references/conclusion.mdWriting a bounded conclusion with contribution, evidence, impact, limitation, and future direction
references/paragraph-flow.mdUser asks whether a paragraph flows, makes sense, or is clear; use reverse outlining and paragraph-message checks
references/paper-review.mdFinal manuscript self-review, rejection-risk audit, claim-evidence alignment, or reviewer-facing critique
references/chinese-author-workflow.mdThe user's notes are Chinese, mixed Chinese-English, or organized as lab notes rather than manuscript prose
references/examples/index.mdYou need concrete abstract, introduction, or method examples after choosing the relevant guide

Intake

Before drafting, identify:

  • manuscript section: title, abstract, introduction, results, discussion, conclusion, significance paragraph or full outline
  • paper type: mechanism, method, resource, device, model, clinical, materials, computational or interdisciplinary
  • core claim: what the paper actually demonstrates
  • evidence: figures, measurements, comparisons, datasets, statistics or examples
  • boundary: where the claim stops
  • target journal or word limit, if provided

If any of core claim, evidence or boundary is absent, expose the gap before drafting. You may still produce a scaffold with explicit placeholders.

Writing workflow

  1. Build a one-sentence argument: In [system/problem], we show [advance] using [approach], supported by [evidence], with [boundary].
  2. Choose the section architecture from references/article-architecture.md.
  3. Map each paragraph to one job: context, gap, approach, result, comparison, mechanism, implication or limitation.
  4. Draft from evidence outward. Keep claims near the data that support them.
  5. Calibrate verbs: show, demonstrate, suggest, indicate, enable, may, could.
  6. Remove unsupported novelty and universal claims.
  7. Run a paragraph-flow check: one paragraph, one message, with a clear first sentence and explicit sentence-to-sentence relation.
  8. Return prose plus concise notes on assumptions and missing inputs.
Show full SKILL.md (308 more words)Show less

Section defaults

Abstract

Default Nature pattern:

context/problem -> gap -> approach -> key result -> implication -> boundary

For technical AI, ML, CV or method-heavy manuscripts, open references/abstract.md and choose one of:

  • challenge -> contribution
  • challenge -> insight -> contribution
  • multiple contributions

Keep it compact. Include quantitative or comparative detail when the user provided it. End with what the work enables, not generic importance.

Introduction

Use:

field scale -> bottleneck -> prior attempts -> unresolved gap -> present study

For method-heavy papers, open references/introduction.md and reason backward from the technical challenge and contribution before drafting forward.

Do not summarize all results. The final paragraph should state what this paper does and how it addresses the gap.

Results narrative

Use an evidence ladder:

system/workflow -> validation -> main result -> baseline comparison -> mechanism/diagnostic analysis -> application or generalization

Each subsection should have a claim-first opening and then data support.

For ML/conference-style experiment sections, open references/experiments.md and make sure each major claim is backed by comparison, ablation, or stress-test evidence.

Use:

topic scope -> representative methods -> limitation tied to this paper -> distinction

Group prior work by technical topic and mechanism, not by publication year.

Discussion

Use:

central advance -> evidence meaning -> relation to prior work -> constraints -> future use

This is where interpretation and limitations belong. Do not repeat the Results section figure by figure.

Conclusion

Use:

contribution -> decisive evidence -> implication -> boundary

No new data. No unsupported promises.

Title

Prefer concrete titles that combine:

system/object + action/capability + application or consequence

Avoid slogan titles, grant-style aims and overbroad field claims.

Output format

Default output:

  1. Draft: with the requested prose.
  2. Section outline: with 3-7 compact bullets when the task involves a full section.
  3. Assumptions or missing inputs: with only material issues.
  4. Claim-evidence map: for major claims, using Claim: ... | Evidence: ... | Status: supported/needs evidence.
  5. Why this structure: with 2-4 short bullets.

For Chinese author notes, provide polished English first, then brief Chinese notes explaining major structural choices.

© Galaxy-Dawn, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 42 other files (references) in skills/nature-writing of Galaxy-Dawn/claude-scholar.

  • SKILL.md
  • README.md
  • agents/openai.yaml
  • references/abstract.md
  • references/article-architecture.md
  • references/chinese-author-workflow.md
  • references/conclusion.md
  • references/examples/abstract-examples.md
  • references/examples/abstract/template-a.md
  • references/examples/abstract/template-b.md
  • references/examples/abstract/template-c.md
  • references/examples/index.md
  • references/examples/introduction-examples.md
  • references/examples/introduction/novel-task-challenge-decomposition.md
  • references/examples/introduction/pipeline-not-recommended-abstract-only.md
  • references/examples/introduction/pipeline-version-1-one-contribution-multi-advantages.md
  • … and 27 more

Open the folder on GitHubat commit 9037873

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in Galaxy-Dawn/claude-scholar, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Nature Writing next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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GitHub Deep Researchbytedance/deer-flow84k4 repos~1.3kAutomated safety check: PassMIT
Nature Paper CardYuan1z0825/nature-skills47k2 repos~2.1kAutomated safety check: PassApache-2.0
Content Research Writerweapp-tailwindcss/weapp-tailwindcss1.9k25 repos~3.5kAutomated safety check: PassMIT
Last30daysmvanhorn/last30days-skill64k—~7.9kAutomated safety check: NotesMIT

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Questions about Nature Writing

What does Nature Writing do?

Draft, restructure, or plan Nature-style manuscript sections from author-provided claims, results, figures, notes, or Chinese drafts. Nature Writing is an agent skill from Galaxy-Dawn/claude-scholar. Draft, restructure, or plan Nature-style manuscript sections from author-provided claims, results, figures, notes, or Chinese drafts.

When should I use Nature Writing?

Nature Writing fits situations like: the user wants to write; rebuild an abstract; results narrative; full manuscript argument rather than only polish finished prose.

How do I install Nature Writing in Claude Code?

Run `npx skills add Galaxy-Dawn/claude-scholar --skill nature-writing -a claude-code`. Or copy the skill folder (skills/nature-writing in Galaxy-Dawn/claude-scholar) into .claude/skills/nature-writing in your project. Claude Code loads it when a task matches its description.

How do I install Nature Writing in Codex?

Run `npx skills add Galaxy-Dawn/claude-scholar --skill nature-writing -a codex`. Or copy the skill folder (skills/nature-writing in Galaxy-Dawn/claude-scholar) into .agents/skills/nature-writing in your project. Codex loads it when a task matches its description.

Can I use Nature Writing in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Galaxy-Dawn/claude-scholar --skill nature-writing -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/nature-writing, .gemini/skills/nature-writing, .github/skills/nature-writing and .opencode/skills/nature-writing in your project.

What does Nature Writing need to run?

SKILL.md names no scripts, command-line tools or credentials: Nature Writing is instructions for the agent only.

Does Nature Writing access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Nature Writing safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Nature Writing use?

Nature Writing is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Nature Writing use?

About 1.9k tokens (SKILL.md is roughly 7.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 24k tokens, read only when the agent opens those files.

What are the alternatives to Nature Writing?

Skills that share tags, products or a category with Nature Writing: Hypothesis Generation (spacering-net/codeg, 3.9k stars), GitHub Deep Research (bytedance/deer-flow, 84k stars), Nature Paper Card (Yuan1z0825/nature-skills, 47k stars) and Content Research Writer (weapp-tailwindcss/weapp-tailwindcss, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Nature Writing?

Galaxy-Dawn (a GitHub user) maintains it in Galaxy-Dawn/claude-scholar, which has 5,725 GitHub stars. The repository holds 34 skills in this directory. The repository was last updated on September 23, 2026.

Source: Galaxy-Dawn/claude-scholar on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.