Skills Plugins MCP Prompt Model 博客 我的中心

nature-shared

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.

DeepseekModel Curated skill Quality Excellent · 90 v1.0.0

Get

https://deepseekmodel.com/api/download.php?id=yuan1z0825-nature-skills-skills-nature-shared-skill-md&format=skill
Download .skill Standard format with system_prompt and model_config, ready for any agent framework
The actual content of the system_prompt field in the .skill file.
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.
Keywords that activate this skill. Click one to copy it.

This skill does not provide trigger words.

The downloaded .skill package contains the following fields.
Field Description
formatFormat tag (skill/v1)
skill_idUnique skill ID
nameSkill name
versionVersion
descriptionDescription
categoryCategories (array)
trigger_wordsTrigger words
tagsTags
sourceSource
source_urlSource URL (this page)
exported_atExported at (set per download)
system_promptSystem prompt body
model_configModel config: provider / model / temperature / max_tokens / top_p
examplesExamples
install_guideImport guide for Coze / Dify / Claude / custom frameworks
The same skill can be exported in different platform formats.
.skill Standard format with system_prompt and model_config, ready for any agent framework Download
.skillpro Enhanced format with scripts, tools, dependencies and hooks Download
.json Plain JSON export with system_prompt and model parameters only Download
Coze Markdown with frontmatter, for Coze platform import Download
Dify Dify DSL, import directly after creating an app Download

每日精选 Skill 推荐,免费送到你邮箱

输入邮箱,每天接收一个精选 AI Agent 技能推荐。完全免费,持续更新。

提交后我们会发送一封确认邮件,点击邮件里的链接才会开始收信。

完全免费,取消任意时间。我们不会发送垃圾邮件。