agentsclimarketplace

Nature polishing

Skill aiskillstore/marketplace/skills/yuan1z0825/nature-polishing

Security-audited skills for Claude, Codex & Claude Code. One-click install, quality verified.

Install
npx -y skills add aiskillstore/marketplace --skill nature-polishing

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One thing to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.

What its author says it does

Copied from the file, not written here

Polish, restructure, or translate academic prose into Nature-leaning English using writing-strategy principles, curated Nature/Nature Communications article patterns, and phrase-level support from Academic Phrasebank. Use whenever the user asks to polish a manuscript paragraph, abstract, introduction, results, discussion, conclusion, title, methods section, or Chinese academic draft for publication-quality English. Also covers LaTeX layout/typesetting (排版) fixes — loose or sparse pages, stranded section headings, figures that don't fill the page or split across pages, "Float too large", multi-panel figure arrangement, and Supplementary Information that looks empty — via references/latex-layout.md. Also trigger on general academic/scientific writing requests even without the word "Nature", including academic writing, scientific writing, SCI/paper writing, English manuscript polishing, language editing, proofreading, and Chinese phrasings such as 学术写作、科研写作、论文润色、写paper、SCI写作、英文论文润色、语言润色、润色、改写、学术英语、英文写作.

SKILL.md

5.1 KB, 873 tokens by cl100k_base, as published. Nobody here has run it

Nature-Style Academic Polishing — Router

This skill is split into two layers:

  • A static layer under static/ that holds versioned, reusable content fragments (core principles, paper-type playbooks, per-section 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 polishing 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 (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, failure-mode diagnosis, ethics, and output format that apply to every polish 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 / results / discussion / conclusion / title / methods. May be multiple. Ask the user if it is ambiguous and matters for the polish.
  • language — en or zh-to-en. Detect from the draft itself.
  • 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 proceeding, 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 if the user has supplied free-floating prose with no section context.

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

4. Polish using the loaded material

Apply the loaded fragments in this priority order, matching the paper type -> section job -> paragraph logic -> claim/evidence/boundary -> sentence polish rule from core/failure-modes.md:

  1. Paper-type playbook (architecture, writing order).
  2. Section-specific job and failure modes.
  3. Journal-specific framing and constraints.
  4. Language-specific sentence and paragraph rules (apply last).
  5. Core stance and ethics throughout.

If a paragraph's structural problem cannot be fixed without inventing content, flag it instead of papering over it.

5. 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 when the user explicitly asks for phrasebank-style alternatives or a stricter style audit.

Layout/typesetting (排版) requests are different. If the user asks to fix placement rather than wording — loose/sparse pages, stranded headings, figures that don't fill the page or split across pages, "Float too large", multi-panel arrangement, sparse Supplementary Information — skip the prose axes (paper_type, section, language, journal) and load references/latex-layout.md directly. That file is self-contained: it carries the diagnosis workflow (render → contact-sheet → read the log), the float-glue and [H]/\clearpage/placeins patterns, and the "regenerate wide figures taller at the source" rule. Always compile and visually inspect rendered pages before and after — never judge layout from the .tex alone.

Why this split

  • The static layer is versioned and reviewable. Adding a new journal style or paper type 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 1000-line monolith.
  • The router itself is short on purpose. Update fragments, not this file, when adding scope.

Gives 0 of the 12 instructions most docs writing skills give in 873 tokens

Counted across 1,637 of the 3,044 authors here whose files we hold, read 2026-08-07

  • announce the skill at startin 54 of 1637, across 26 files
  • convert legacy doc files before editingin 45 of 1637, across 7 files
  • Predict questions readers might askin 42 of 1637, across 4 files
  • Generate clarifying questions for initial contextin 42 of 1637, across 3 files
  • Create document scaffold with placeholder textin 42 of 1637, across 3 files
  • Brainstorm content options for each sectionin 42 of 1637, across 3 files
  • Test document with fresh context-less instancein 42 of 1637, across 3 files
  • include exact file paths in every taskin 42 of 1637, across 15 files
  • ask interview questions one at a timein 42 of 1637, across 27 files
  • Apply surgical edits during refinementin 41 of 1637, across 2 files
  • Offer structured workflow or freeformin 40 of 1637, across 1 file
  • Ask for document meta-contextin 40 of 1637, across 2 files

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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