Agent skill · writing content · aiskillstore
nature-polishing
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.
Why this skill is useful
Provides structured guidance on polishing academic prose specific to Nature journals, including LaTeX layout fixes that the AI wouldn't reliably generate on its own.
What it needs
About 3k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
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 (papertype, section, language, journal), the allowed values, and the file paths each value maps to. Also read every file listed under alwaysload. 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: papertype — 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. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/nature-polishing