Agent skill · writing content · yuan1z0825
nature-polishing
Polish, restructure, or translate academic prose into concise Nature-leaning English while preserving facts, evidence boundaries, terminology, and citation intent. Use for manuscript paragraphs, abstracts, introductions, Results, discussions, conclusions, titles, Methods, Chinese drafts, proofreading, language editing, and general academic or scientific writing. Also use to shorten bloated Results, allocate evidence across main text, captions, and Supplementary Information, prevent reviewer-driven revision accretion, reduce repeated statistics or claims, and apply paragraph-necessity checks. Covers LaTeX layout or typesetting fixes such as sparse pages, stranded headings, oversized or split figures, float errors, multi-panel arrangement, and sparse Supplementary Information via references/latex-layout.md. Trigger on 学术写作、科研写作、论文润色、SCI写作、英文论文润色、语言润色、润色、改写、学术英语、排版.
Why this skill is useful
Provides specific guidance on polishing academic prose for Nature journals, including LaTeX layout fixes and structured writing strategies that the AI wouldn't reliably generate on its own.
What it needs
About 4k tokens when loaded. Last updated 2026-08-07. 33,818 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 / nat-mach-intell / generic. Default: generic. Use nature only for flagship Nature, nat-comms for Nature Communications and nat-mach-intell for Nature Machine Intelligence (NMI). Do not route another Nature Portfolio title through flagship Nature rules. 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. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills yuan1z0825/nature-polishing