yuan1z0825/nature-skills

nature-shared

Internal shared-reference support package for installed Nature Skills, including nature-writing, nature-polishing, nature-response, nature-reader, and nature-paper2ppt.

查看源码

使用方法

  1. 复制安装命令,在自己的智能体环境安装前先检查源码包。
  2. 从原始文档核对所需工具、凭据和支持的宿主。
  3. 说明输入材料与期望交付物,并对照来源检查输出。
npx skills add https://github.com/yuan1z0825/nature-skills --skill nature-shared

开始前需了解

  • 安装不包含模型订阅、API 额度或访问文件的权限。
  • 仓库星数和安装量反映活跃情况,不等于独立质量或安全测试。
仓库原始内容

按源仓库内容呈现,保留标题、案例、代码、表格、链接以及原文引用的演示图片。

Nature Shared References

Use this package only as a dependency of another installed Nature skill.

  • Load the exact referenced file; do not preload the whole package.
  • Treat core/ and journal-formats/ as shared definitions, not standalone workflows.
  • Use journal-formats/nature.md only for the flagship journal Nature and

core/research-compliance.md only when its specialist applicability gate is triggered.

  • Use journal-formats/nature-machine-intelligence.md for exact NMI article

types, limits, initial-submission files, data/code duties and production requirements; do not import flagship Nature or Nature Communications limits.

  • Use core/main-text-discipline.md for result placement, main-text compression,

revision accretion, caption/SI allocation, and claim-repetition checks.

  • Use core/nature-results-discussion.md for corpus-derived Nature-style

Results claim escalation, evidence-bound local interpretation, and Discussion synthesis; do not present it as official journal policy.

  • Use core/discussion-argument-language.md for journal-general Discussion

function sequencing, reverse-funnel control, evidence-calibrated modality, claim-specific limitations, and uncertainty-driven future work.

  • Use core/nature-introduction.md for corpus-derived Nature-style problem

funnels, exact knowledge gaps, literature tension, question-first novelty, and Introduction–Results alignment; do not present it as official journal policy.

  • Use core/nature-abstract.md for corpus-derived Nature-style

discovery-centred abstract compression, claim hierarchy, selective numeric support, and field-level payoff; do not present it as official journal policy.

  • Return to the requesting skill for task logic, output format, and final QA.
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