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Get Started Free →leonchaox/qinyan-nature-polishing
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。
Passed 18 of 22 test cases with the skill, and 12 of 22 without it.
and 3 more in the full report
6 fixed12 passed either way4 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 6 test cases the skill fixed. Same model, same prompt, with and without the skill.
Here is a Results excerpt: 'Sample S2 exhibited a 35% higher yield than S1 at 250 °C (Figure 3b, ref 12).' What step must be performed first when setting up the editing process?
| Checked | Without skill | With skill |
|---|---|---|
| extracts the numerical values, comparison directions, sample identifiers, figure tags, and references into a fidelity tracking record | Missed | Passed |
The instructions your model reads when the skill loads.
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。
qinyan-nature-writing。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。
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。
润色设定
- 章节 / 目标读者 / 模式：
- 不可变事实：
test cases passed, vs 12 / 22 without
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