MCPInstall

nature-polishing

Polish, translate, or tighten existing academic prose while preserving facts, terminology, and evidence boundaries. Use for 论文润色、学术翻译、正文精简, or manuscript LaTeX layout fixes. Use nature-writing when the main task is drafting new sections or rebuilding the manuscript argument.

Installs
17.6K
Last 24h
+109
Trending rank
#1883
Security
Pass

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/yuan1z0825/nature-skills --skill nature-polishing
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads nature-polishing automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

Security audits

Independent scans of the skill's instructions and bundled files.

Gen Agent Trust Hub PassSAFE ·The skill is safe. It consists entirely of markdown documents, style guides, and configuration files designed to help polish academic text in the style of Nature journals. It contains no executable scripts, external software dependencies, or network operations.
Socket PassNo alerts
Snyk PassLOW ·Risk: LOW · No issues

SKILL.md

The instructions your agent reads when the skill is triggered.

Nature-Style Academic Polishing — Router

Routing protocol

For a new polishing task, follow the routing below. For follow-up edits, reuse established task choices and already loaded guidance; read additional fragments only when the requested scope changes.

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 / 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. 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 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.

For Results, full-main-text compression, main-versus-SI allocation, or prose added during revision, load ../nature-shared/core/main-text-discipline.md before sentence polishing. Classify each result, retain the shortest sufficient evidence chain, and require every addition to trigger a deletion or replacement check across the affected paragraph.

For flagship Nature, Nature Communications, Nature Machine Intelligence, or another Nature Portfolio title, load the matching shared Nature-style corpus guidance:

  • 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

Preserve claim escalation, the fast question funnel, Introduction–Results alignment, discovery-centred abstract compression, evidence-bound local interpretation, and cross-Results synthesis. These defaults were initially distilled from published NMI papers; treat them as corpus-derived guidance, not official policy, and obey the target journal's current rules when they differ.

For any Discussion polish or restructuring job, also load ../nature-shared/core/discussion-argument-language.md. Use its function labels to remove Results replay, repair the movement from specific findings to bounded implications, calibrate modal and reporting verbs to evidence strength, and make limitations and future work resolve named claim boundaries. Treat it as general writing guidance, not journal policy.

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.

When the target is Nature Machine Intelligence and exact limits, availability sections, conference-extension disclosure or production checks affect the revision, load ../nature-shared/journal-formats/nature-machine-intelligence.md.

For a whole-manuscript consistency audit or evidence of drift across passages, load ../nature-shared/core/consistency-sweep.md. Local follow-up edits require checking the affected terms, numbers, and claims, not restarting a full audit solely because this is another editing round. After corrections, recheck affected occurrences and dependent claims; broaden the sweep when new discrepancies warrant it.

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.

FAQ

What does the nature-polishing skill do?

Polish, translate, or tighten existing academic prose while preserving facts, terminology, and evidence boundaries. Use for 论文润色、学术翻译、正文精简, or manuscript LaTeX layout fixes. Use nature-writing when the main task is drafting new sections or rebuilding the manuscript argument.

How do I install nature-polishing?

Run npx skills add https://github.com/yuan1z0825/nature-skills --skill nature-polishing in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/nature-polishing/ (personal) or .claude/skills/nature-polishing/ (project).

Which AI agents can use nature-polishing?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is nature-polishing safe to install?

Security partners have reviewed it: Gen Agent Trust Hub passed; Socket passed; Snyk passed. As with any skill, read the SKILL.md and bundled scripts before installing.

Who maintains nature-polishing?

It is published by yuan1z0825 in yuan1z0825/nature-skills. It has 17,646 recorded installs.

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