---
name: nature-shared
version: 1.0.0
category: 内容创作
trigger_words:
tags:
  - writing
platform: coze
source: DeepseekModel
source_url: https://deepseekmodel.com/skill?id=yuan1z0825-nature-skills-skills-nature-shared-skill-md
---

name nature-shared description Internal shared-reference support package for installed Nature Skills, including nature-writing, nature-polishing, nature-response, nature-reader, and nature-paper2ppt. Do not invoke it as a standalone user workflow. Load only the specific core or journal-format file requested by another Nature skill. 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.