nature-writing

Yuan1z0825/nature-skills · Agent Skill

Assiste nella stesura, strutturazione e pianificazione di manoscritti scientifici in stile Nature e materiali per la prima sottomissione.

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Panoramica

AutoreYuan1z0825Community
RepositoryYuan1z0825/nature-skills ↗
Cartella dello skillnature-writing
Stelle39.583
File inclusi2
LicenzaApache-2.0
Aggiornato5 settembre 2026
LinkSorgente dello skill ↗ · Repository ↗

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Installazione

Uno skill è una cartella con un file SKILL.md. Scegli il tuo agente ed esegui i comandi in un terminale (macOS, Linux o Git Bash su Windows) dalla radice del progetto.

Incolla il prompt in Claude, Codex o un altro assistente: controllerà lo skill e lo installerà.

Install the “nature-writing” skill from mozgi.io (https://mozgi.io/skills/nature-writing/) for me.

1. Download the archive: https://mozgi.io/skills/nature-writing/download
   If it fails, take the skill folder from the source: https://github.com/Yuan1z0825/nature-skills/tree/main/skills/nature-writing
2. Read SKILL.md and the other files. Check the skill is safe: no hidden commands, no sending data elsewhere, no scripts doing something other than described. If anything looks suspicious, stop and tell me.
3. Put the “nature-writing” folder into your agent's skills folder: .claude/skills/ for Claude Code, .agents/skills/ for Codex, .cursor/skills/ for Cursor, .gemini/skills/ for Gemini CLI. Inside the project if we are in one, otherwise in the home folder (~/.claude/skills/ etc.).
4. Make sure <skills folder>/nature-writing/SKILL.md exists.
5. Briefly tell me what this skill does and offer to try it on my task.

If you cannot do a step yourself, tell me what to click or type.

File dello skill

2 file Scarica ZIP

Leggi SKILL.md e i file correlati prima di installare. Clicca un file per l'anteprima.

Contenuto di SKILL.md

Testo originale dell'autore · sola lettura

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, initial-submission 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 ↗. It declares the axes (task, 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:

  • task — manuscript / submission-package. Use submission-package for first-submission materials, never for revision correspondence.
  • 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 / nature-family / nat-comms / nat-mach-intell / generic.

Default: generic. Use nature only for the flagship journal Nature,

nat-comms for Nature Communications, nat-mach-intell for Nature Machine

Intelligence (NMI), and nature-family for other Nature Portfolio titles or

an unspecified Nature-family request.

State the detected axis values in one short line to the user before drafting, so they can correct you cheaply. This is a progress update, not an approval gate; continue unless a necessary decision remains unresolved.

3. Load the matching fragments

For each axis value, Read the file mapped in the manifest. Skip the section axis when the task is submission-package or when the user explicitly asks 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. Task-specific submission rules when task=submission-package.

5. Journal-specific framing and constraints.

6. Language-specific sentence and paragraph rules (apply last).

For task=manuscript, run the workflow in core/workflow.md end-to-end. Do not skip planning just because the user asked for prose immediately.

When drafting or restructuring Results, or compressing a full manuscript's main

text, also load ../nature-shared/core/main-text-discipline.md before building

the paragraph map. Classify every result by function, allocate it across main

text, captions, Methods/source data, and SI, then draft the shortest sufficient

evidence chain. Do not equate a complete analysis record with a complete main

text.

When the target is flagship Nature, Nature Communications, Nature Machine

Intelligence, or another Nature Portfolio title, load the matching shared

Nature-style corpus guidance for the section being drafted:

  • Results or Discussion →

../nature-shared/core/nature-results-discussion.md

  • Introduction or whole-manuscript narrative →

../nature-shared/core/nature-introduction.md

  • Abstract → ../nature-shared/core/nature-abstract.md

Use these files for claim escalation, question-chain alignment,

discovery-centred compression, and synthesis. They were initially distilled

from published NMI papers and generalized as Nature-style defaults; do not

present them as official policy, and let the target journal's current rules

override them.

For any Discussion drafting, restructuring, or section audit, also load

../nature-shared/core/discussion-argument-language.md. Use it to select the

opening anchor, control the reverse-funnel expansion, distinguish literature

positioning from citation decoration, calibrate modal strength to evidence,

and turn limitations and future work into claim-specific reasoning. This is

general writing guidance rather than an official journal rule.

For task=submission-package, follow static/fragments/task/submission-package.md and references/submission-package.md instead. Build the deliverable matrix and readiness audit; do not force manuscript paragraph architecture onto administrative submission materials.

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.
  • The user asks what belongs in the main text, captions, or SI; wants a shorter

Results section; or is adding reviewer-driven explanation →

../nature-shared/core/main-text-discipline.md.

  • The user requests a complete first-submission package, templates, or a submission-readiness audit → references/submission-package.md.
  • The target is the flagship journal Nature and exact submission or formatting

requirements matter → ../nature-shared/journal-formats/nature.md.

  • The target is Nature Machine Intelligence and exact content-type, submission,

data/code or production requirements matter →

../nature-shared/journal-formats/nature-machine-intelligence.md.

  • Any Nature / Nature Portfolio target needs Results claim progression,

evidence-bound interpretation, robustness placement, or Discussion synthesis

→ ../nature-shared/core/nature-results-discussion.md.

  • Any target needs a Discussion function chain, evidence-calibrated modal

language, claim-specific limitations, non-redundant literature positioning,

or uncertainty-driven future work →

../nature-shared/core/discussion-argument-language.md.

  • Any Nature / Nature Portfolio target needs an Introduction funnel, exact gap,

literature logic, question-first novelty, study roadmap, or alignment with

Results → ../nature-shared/core/nature-introduction.md.

  • Any Nature / Nature Portfolio target needs abstract evidence-chain,

main/supporting-claim, numeric-result, or final-payoff decisions →

../nature-shared/core/nature-abstract.md.

  • The work involves regulated or specialist research compliance →

../nature-shared/core/research-compliance.md.

Submission boundary

  • nature-writing owns initial submission materials prepared before peer review.
  • nature-response owns revision cover letters, rebuttals, point-by-point responses, marked manuscripts, appeals, and other post-decision correspondence.
  • Route graphical abstracts and TOC graphics to nature-figure; route simulated pre-submission peer review to nature-reviewer.

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 nature-shared/ layer used by both skills.

Domande frequenti

Che cosa fa lo skill nature-writing?

Assiste nella stesura, strutturazione e pianificazione di manoscritti scientifici in stile Nature e materiali per la prima sottomissione.

Come si installa nature-writing?

Apri il blocco “Installazione” in questa pagina e scegli il tuo agente — Claude Code, Codex, Cursor o Gemini CLI — per i comandi pronti che copiano la cartella dello skill nel posto giusto. Oppure copia il prompt dalla scheda “Con l'assistente” e lascia che sia l'assistente a controllare e installare lo skill.

Con quali modelli AI funziona nature-writing?

Gli skill sono semplici istruzioni in Markdown (formato Agent Skills), quindi nature-writing funziona con qualsiasi agente che legge SKILL.md: Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode e altri. Il modello carica le istruzioni solo quando il compito corrisponde alla descrizione dello skill.

nature-writing è gratuito?

Lo skill è pubblicato apertamente da Yuan1z0825 con licenza Apache-2.0. Lo skill in sé non costa nulla: paghi solo il tuo fornitore AI per i token usati.

È sicuro installare gli skill?

Uno skill è un insieme di istruzioni che il tuo agente seguirà: leggi SKILL.md e i file correlati prima di installarlo. Gli script nella cartella dello skill vengono eseguiti solo se li esegue l'agente: controlla cosa fa e non concedere permessi superflui.

In cosa differisce uno skill da un server MCP o da un plugin?

Un server MCP o un plugin danno al modello nuovi strumenti: codice che viene eseguito e restituisce un risultato. Uno skill fornisce conoscenza e metodo: come affrontare il compito, quali passi seguire e com'è un buon risultato. Non servono server né chiavi API.

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