Agent skill

Qinyan Nature Polishing

by LeonChaoX in LeonChaoX/qinyan-academic-skills

面向 Nature、Nature Communications 及高影响力期刊的学术语言重构与润色技能。用于中译英、英文精修、摘要压缩、段落逻辑修复、术语统一、语气校准、过度声称检查和去除模板化 AI 文风,同时严格保持数据、引用意图和科学含义不变。触发场景包括 Nature 润色、SCI 英文润色、academic editing、paper…

MITAuto-check passedWriting & Content

Install Qinyan Nature Polishing

skills CLI
$ npx skills add LeonChaoX/qinyan-academic-skills --skill qinyan-nature-polishing -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install LeonChaoX/qinyan-academic-skills qinyan-nature-polishing --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/LeonChaoX/qinyan-academic-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/'skills/沁言学术skills/qinyan-nature-polishing' .claude/skills/qinyan-nature-polishing && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
qinyan-nature-polishing
GitHub stars
944
Token cost
~441 tokens
SKILL.md length
72 words
Files
5 (incl. scripts, references)
Skills in repo
31
Repo updated
First seen
Licence
MIT

At a glance

面向 Nature、Nature Communications 及高影响力期刊的学术语言重构与润色技能。用于中译英、英文精修、摘要压缩、段落逻辑修复、术语统一、语气校准、过度声称检查和去除模板化 AI 文风,同时严格保持数据、引用意图和科学含义不变。触发场景包括 Nature 润色、SCI 英文润色、academic editing、paper…

  • Works in 8 steps: 登记不可变事实。 提取数值、比较方向、样本、方法名、图表与引用位置,建立… → 识别文本职责。 判断论文类型、章节、目标读者、目标期刊和字数限制。 → 诊断优先级。 按“论证断点 → 段落功能 → 句法与搭配 →… → …
  • Tasks that involve Copy editing and proofreading
  • SKILL.md covers 工作边界, 执行流程, 模式选择 and 默认输出, plus 2 more sections
  • Runs Python scripts from its folder; calls python

What it does

Qinyan Nature Polishing is an agent skill from LeonChaoX/qinyan-academic-skills. 面向 Nature、Nature Communications 及高影响力期刊的学术语言重构与润色技能。用于中译英、英文精修、摘要压缩、段落逻辑修复、术语统一、语气校准、过度声称检查和去除模板化 AI 文风,同时严格保持数据、引用意图和科学含义不变。触发场景包括 Nature 润色、SCI 英文润色、academic editing、paper polishing、proofreading、rewrite、中文论文英译、abstract polishing、语言降重和学术表达优化。

Its SKILL.md is about 440 tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including scripts and reference files (for example `agents/openai.yaml`, `references/editing-protocol.md` and `references/section-style.md`).

It sits in Writing & Content, covering Copy editing and proofreading. The repository describes itself as: A curated, multilingual library of 182 installable AI agent skills for end-to-end academic research—spanning literature discovery, scientific writing, grant development… The licence is MIT.

When your agent uses it

  • Tasks that involve Copy editing and proofreading

Example prompts

  • “/qinyan-nature-polishing”

Requirements

  • Python 3

Workflow steps

8 steps, taken from the first numbered list in SKILL.md.

  1. 登记不可变事实。 提取数值、比较方向、样本、方法名、图表与引用位置,建立 fidelity ledger。
  2. 识别文本职责。 判断论文类型、章节、目标读者、目标期刊和字数限制。
  3. 诊断优先级。 按“论证断点 → 段落功能 → 句法与搭配 → 格式”处理,不从同义词替换开始。
  4. 重建段落。 让主题句定义本段任务,让证据句承担事实,让解释句受证据约束,让尾句自然推进。
  5. 精修句子。 优先明确主语与动作,减少空洞名词化、堆叠修饰和冗余元话语。
  6. 校准语气。 根据观察、关联、预测、干预和机制证据选择动词与限定语。
  7. 核对忠实度。 逐项检查数值、正负方向、比较对象、时态、引用归属和否定范围。
  8. 运行风格审计。 执行 python scripts/style_audit.py ,人工判断每条命中,不机械替换。

What it can do on your machine

Read from SKILL.md and the folder at commit df5a498. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Qinyan Nature Polishing loads about 441 tokens when it runs, and up to ~1.6k if it reads all its reference files. Until then it costs about 67 tokens; SKILL.md has 72 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~67
When it runs · the whole SKILL.md, loaded when a task matches
~441
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from LeonChaoX/qinyan-academic-skills at commit df5a498, republished under its MIT licence (© LeonChaoX). 72 words, ~441 tokens.

Download SKILL.mdSave it as .claude/skills/qinyan-nature-polishing/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
qinyan-nature-polishing
description
面向 Nature、Nature Communications 及高影响力期刊的学术语言重构与润色技能。用于中译英、英文精修、摘要压缩、段落逻辑修复、术语统一、语气校准、过度声称检查和去除模板化 AI 文风,同时严格保持数据、引用意图和科学含义不变。触发场景包括 Nature 润色、SCI 英文润色、academic editing、paper polishing、proofreading、rewrite、中文论文英译、abstract polishing、语言降重和学术表达优化。

沁言 Nature 学术润色

把润色分成“科学含义保护、段落逻辑修复、句子精修、最终核验”四层。不得用流畅度掩盖证据缺口。

工作边界

  • 处理已有文本的翻译、重构、压缩与语言校准。
  • 将从材料起草新章节交给 qinyan-nature-writing。
  • 不新增实验、数据、统计、引用、机制或作者未表达的结论。
  • 不把相关性改写为因果,不把趋势改写为显著,不把局部结果改写为普适结论。

执行流程

  1. 登记不可变事实。 提取数值、比较方向、样本、方法名、图表与引用位置,建立 fidelity ledger。
  2. 识别文本职责。 判断论文类型、章节、目标读者、目标期刊和字数限制。
  3. 诊断优先级。 按“论证断点 → 段落功能 → 句法与搭配 → 格式”处理,不从同义词替换开始。
  4. 重建段落。 让主题句定义本段任务,让证据句承担事实,让解释句受证据约束,让尾句自然推进。
  5. 精修句子。 优先明确主语与动作,减少空洞名词化、堆叠修饰和冗余元话语。
  6. 校准语气。 根据观察、关联、预测、干预和机制证据选择动词与限定语。
  7. 核对忠实度。 逐项检查数值、正负方向、比较对象、时态、引用归属和否定范围。
  8. 运行风格审计。 执行 python scripts/style_audit.py <file>,人工判断每条命中,不机械替换。

需要完整编辑协议时读取 references/editing-protocol.md。需要按章节处理时读取 references/section-style.md。

模式选择

  • clean:只返回可粘贴版本。
  • annotated:返回润色稿、关键修改与科学风险。
  • parallel:返回原文与改写的逐段对照。
  • minimal:只修正错误和明显不自然表达,尽量保留作者声音。

默认使用 annotated;用户明确要求“只给结果”时使用 clean。

默认输出

text
润色设定
- 章节 / 目标读者 / 模式:
- 不可变事实:

润色稿
[revised text]

关键编辑说明
- [结构、语气、术语或压缩]

科学含义风险
- [原文存在歧义或证据不足之处]

AUTHOR_INPUT_NEEDED
- [必须由作者确认的事实]

质量门槛

  • 保持全部数值、单位、比较方向、样本身份与引用意图。
  • 保持术语和缩写在全文一致。
  • 每段存在清楚的中心任务与信息推进。
  • 避免套话、宣传式形容词、虚假精确性和机械的过渡词堆叠。
  • 只有真实统计检验支持时才使用 significant/significantly。
  • 不把作者谨慎表达擅自增强,也不为“更像 Nature”删除必要限制。
  • 对无法仅靠语言修复的问题明确标记,不伪装修复完成。

资料路由

任务读取
忠实度账本、四层编辑、语气校准、中译英references/editing-protocol.md
标题、摘要、引言、结果、方法、讨论、结论references/section-style.md

© LeonChaoX, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (scripts, references) in skills/沁言学术skills/qinyan-nature-polishing of LeonChaoX/qinyan-academic-skills.

  • SKILL.md
  • agents/openai.yaml
  • references/editing-protocol.md
  • references/section-style.md
  • scripts/style_audit.py

Open the folder on GitHubat commit df5a498

Compare with similar skills

Qinyan Nature Polishing next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Qinyan Nature Polishing compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Qinyan Nature Polishing this skillLeonChaoX/qinyan-academic-skills944—~441Automated safety check: PassMIT
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Story Multi-Perspective Reviewzenstory-ai/oh-story-claudecode7.4k3 repos~3kAutomated safety check: PassMIT
Chinese Text Humanizerop7418/Humanizer-zh19k—~2kAutomated safety check: PassMIT
Baoyu TranslateJimLiu/baoyu-skills27k1 repos~3.9kAutomated safety check: PassMIT
Natural Japanese Business Writingcoji/natural-japanese1.9k—~2.1kAutomated safety check: PassMIT

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Questions about Qinyan Nature Polishing

What does Qinyan Nature Polishing do?

面向 Nature、Nature Communications 及高影响力期刊的学术语言重构与润色技能。用于中译英、英文精修、摘要压缩、段落逻辑修复、术语统一、语气校准、过度声称检查和去除模板化 AI 文风,同时严格保持数据、引用意图和科学含义不变。触发场景包括 Nature 润色、SCI 英文润色、academic editing、paper…. Qinyan Nature Polishing is an agent skill from LeonChaoX/qinyan-academic-skills.

When should I use Qinyan Nature Polishing?

Qinyan Nature Polishing fits situations like: tasks that involve Copy editing and proofreading.

How do I install Qinyan Nature Polishing in Claude Code?

Run `npx skills add LeonChaoX/qinyan-academic-skills --skill qinyan-nature-polishing -a claude-code`. Or copy the skill folder (skills/沁言学术skills/qinyan-nature-polishing in LeonChaoX/qinyan-academic-skills) into .claude/skills/qinyan-nature-polishing in your project. Claude Code loads it when a task matches its description.

How do I install Qinyan Nature Polishing in Codex?

Run `npx skills add LeonChaoX/qinyan-academic-skills --skill qinyan-nature-polishing -a codex`. Or copy the skill folder (skills/沁言学术skills/qinyan-nature-polishing in LeonChaoX/qinyan-academic-skills) into .agents/skills/qinyan-nature-polishing in your project. Codex loads it when a task matches its description.

Can I use Qinyan Nature Polishing in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LeonChaoX/qinyan-academic-skills --skill qinyan-nature-polishing -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/qinyan-nature-polishing, .gemini/skills/qinyan-nature-polishing, .github/skills/qinyan-nature-polishing and .opencode/skills/qinyan-nature-polishing in your project.

What does Qinyan Nature Polishing need to run?

Going by SKILL.md and its folder, Qinyan Nature Polishing needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Qinyan Nature Polishing access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Qinyan Nature Polishing safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Qinyan Nature Polishing use?

Qinyan Nature Polishing is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Qinyan Nature Polishing use?

About 441 tokens (SKILL.md is roughly 1.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.2k tokens, read only when the agent opens those files.

What are the alternatives to Qinyan Nature Polishing?

Skills that share tags, products or a category with Qinyan Nature Polishing: User-Facing Text Cleanup (guillaumemeyer/watermarks-remover, 24k stars), Story Multi-Perspective Review (zenstory-ai/oh-story-claudecode, 7.4k stars), Chinese Text Humanizer (op7418/Humanizer-zh, 19k stars) and Baoyu Translate (JimLiu/baoyu-skills, 27k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Qinyan Nature Polishing?

LeonChaoX (a GitHub user) maintains it in LeonChaoX/qinyan-academic-skills, which has 944 GitHub stars. The repository holds 31 skills in this directory. The repository was last updated on July 20, 2026.

Source: LeonChaoX/qinyan-academic-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.