scientific-writing by davila7/claude-code-templates
npx skills add https://github.com/davila7/claude-code-templates --skill scientific-writing这是深度研究与写作工具的核心技能——将 AI 驱动的深度研究与格式规范的书面输出相结合。生成的每份文档都通过 research-lookup 技能获得全面的文献检索和经过验证的引用支持。
科学写作是一个以精确性和清晰度交流研究的过程。使用 IMRAD 结构、引用(APA/AMA/Vancouver)、图表以及报告指南(CONSORT/STROBE/PRISMA)来撰写稿件。将此技能应用于研究论文和期刊投稿。
核心原则:始终使用完整的段落和流畅的散文体进行写作。切勿在最终稿件中提交要点列表。 使用两阶段流程:首先使用 research-lookup 创建包含要点的章节大纲,然后将这些大纲转换为完整的段落。
此技能应在以下情况使用:
⚠️ 强制要求:每篇科学论文必须使用 scientific-schematics 技能包含至少 1-2 个 AI 生成的图表。
这不是可选的。没有视觉元素的科学论文是不完整的。在最终确定任何文档之前:
如何生成图表:
如何生成示意图:
python scripts/generate_schematic.py "your diagram description" -o figures/output.png
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何时添加示意图:
有关创建示意图的详细指导,请参阅 scientific-schematics 技能文档。
IMRAD 格式:指导论文采用大多数科学学科使用的标准引言、方法、结果和讨论结构。这包括:
有关 IMRAD 结构的详细指导,请参阅 references/imrad_structure.md。
替代结构:支持特定学科格式,包括:
摘要撰写:撰写简洁、独立的摘要(100-250 字),概括论文的目的、方法、结果和结论。支持结构化摘要(带标签部分)和非结构化单段落格式。
引言撰写:构建引人入胜的引言,要求:
方法记录:通过以下方式确保可重复性:
结果呈现:呈现发现时需:
讨论构建:通过以下方式综合发现:
跨学科正确应用引用格式。有关全面的格式指南,请参阅 references/citation_styles.md。
主要引用格式:
最佳实践:
创建有效的数据可视化以增强理解。有关详细的最佳实践,请参阅 references/figures_tables.md。
何时使用表格与图表:
设计原则:
常见图表类型:
遵循既定的报告标准以确保完整性和透明度。有关全面的指南详情,请参阅 references/reporting_guidelines.md。
关键指南:
每个指南都提供了清单,确保报告所有关键的方法学要素。
应用基本的科学写作原则。有关详细指导,请参阅 references/writing_principles.md。
清晰性:
简洁性:
准确性:
客观性:
关键:始终使用完整的段落写作,切勿在科学论文中提交要点列表。
科学论文必须用完整、流畅的散文体撰写。使用这种两阶段方法进行有效写作:
阶段 1:创建包含要点的章节大纲
开始新章节时:
示例大纲(引言部分):
- Background: AI in drug discovery gaining traction
* Cite recent reviews (Smith 2023, Jones 2024)
* Traditional methods are slow and expensive
- Gap: Limited application to rare diseases
* Only 2 prior studies (Lee 2022, Chen 2023)
* Small datasets remain a challenge
- Our approach: Transfer learning from common diseases
* Novel architecture combining X and Y
- Study objectives: Validate on 3 rare disease datasets
阶段 2:将要点转换为完整段落
大纲完成后,将每个要点扩展为适当的散文:
转换为散文的示例:
Artificial intelligence approaches have gained significant traction in drug discovery
pipelines over the past decade (Smith, 2023; Jones, 2024). While these computational
methods show promise for accelerating the identification of therapeutic candidates,
traditional experimental approaches remain slow and resource-intensive, often requiring
years of laboratory work and substantial financial investment. However, the application
of AI to rare diseases has been limited, with only two prior studies demonstrating
proof-of-concept results (Lee, 2022; Chen, 2023). The primary obstacle has been the
scarcity of training data for conditions affecting small patient populations.
To address this challenge, we developed a transfer learning approach that leverages
knowledge from well-characterized common diseases to predict therapeutic targets for
rare conditions. Our novel neural architecture combines convolutional layers for
molecular feature extraction with attention mechanisms for protein-ligand interaction
modeling. The objective of this study was to validate our approach across three
independent rare disease datasets, assessing both predictive accuracy and biological
interpretability of the results.
大纲与最终文本的关键区别:
| 大纲(规划阶段) | 最终稿件 |
|---|---|
| 要点和片段 | 完整的句子和段落 |
| 电报式笔记 | 带有上下文的完整解释 |
| 引用列表 | 引用整合到散文中 |
| 简化的观点 | 带有过渡的展开论点 |
| 仅供你自己查看 | 用于发表和同行评审 |
需要避免的常见错误:
何时列表是可接受的(有限情况):
列表仅在特定上下文中出现在科学论文中:
与研究查找的整合:
research-lookup 技能对于阶段 1(创建大纲)至关重要:
这个两阶段流程确保你:
使稿件适应期刊要求:
调整语言、术语和惯例以匹配特定的科学学科。每个领域都有既定的词汇、偏好的措辞和领域特定的惯例,这些能体现专业性并确保目标受众的清晰度。
识别领域特定的语言惯例:
生物医学与临床科学:
分子生物学与遗传学:
化学与药物科学:
生态学与环境科学:
物理学与工程学:
神经科学:
社会与行为科学:
通用原则:
匹配受众专业水平:
策略性地定义技术术语:
保持一致性:
避免领域混合错误:
验证术语用法:
主要拒稿原因:
写作质量问题:
阶段 1:规划
阶段 2:起草(对每个章节使用两阶段写作流程)
记住:要点仅用于规划——最终稿件必须是完整的段落。
阶段 3:修订
阶段 4:最终准备
此技能可与以下技能有效配合:
此技能包含涵盖科学写作特定方面的综合参考文件:
references/imrad_structure.md:IMRAD 格式和章节特定内容的详细指南references/citation_styles.md:完整的引用格式指南(APA、AMA、Vancouver、Chicago、IEEE)references/figures_tables.md:创建有效数据可视化的最佳实践references/reporting_guidelines.md:特定研究的报告标准和清单references/writing_principles.md:有效科学交流的核心原则在处理科学写作的特定方面时,根据需要加载这些参考文献。
每周安装量
507
代码库
GitHub 星标数
22.6K
首次出现
2026年1月21日
安全审计
安装于
opencode412
gemini-cli383
codex369
claude-code350
cursor327
github-copilot325
This is the core skill for the deep research and writing tool —combining AI-driven deep research with well-formatted written outputs. Every document produced is backed by comprehensive literature search and verified citations through the research-lookup skill.
Scientific writing is a process for communicating research with precision and clarity. Write manuscripts using IMRAD structure, citations (APA/AMA/Vancouver), figures/tables, and reporting guidelines (CONSORT/STROBE/PRISMA). Apply this skill for research papers and journal submissions.
Critical Principle: Always write in full paragraphs with flowing prose. Never submit bullet points in the final manuscript. Use a two-stage process: first create section outlines with key points using research-lookup, then convert those outlines into complete paragraphs.
This skill should be used when:
⚠️ MANDATORY: Every scientific paper MUST include at least 1-2 AI-generated figures using the scientific-schematics skill.
This is not optional. Scientific papers without visual elements are incomplete. Before finalizing any document:
How to generate figures:
How to generate schematics:
python scripts/generate_schematic.py "your diagram description" -o figures/output.png
The AI will automatically:
When to add schematics:
For detailed guidance on creating schematics, refer to the scientific-schematics skill documentation.
IMRAD Format : Guide papers through the standard Introduction, Methods, Results, And Discussion structure used across most scientific disciplines. This includes:
For detailed guidance on IMRAD structure, refer to references/imrad_structure.md.
Alternative Structures : Support discipline-specific formats including:
Abstract Composition : Craft concise, standalone summaries (100-250 words) that capture the paper's purpose, methods, results, and conclusions. Support both structured abstracts (with labeled sections) and unstructured single-paragraph formats.
Introduction Development : Build compelling introductions that:
Methods Documentation : Ensure reproducibility through:
Results Presentation : Present findings with:
Discussion Construction : Synthesize findings by:
Apply citation styles correctly across disciplines. For comprehensive style guides, refer to references/citation_styles.md.
Major Citation Styles:
Best Practices:
Create effective data visualizations that enhance comprehension. For detailed best practices, refer to references/figures_tables.md.
When to Use Tables vs. Figures:
Design Principles:
Common Figure Types:
Ensure completeness and transparency by following established reporting standards. For comprehensive guideline details, refer to references/reporting_guidelines.md.
Key Guidelines:
Each guideline provides checklists ensuring all critical methodological elements are reported.
Apply fundamental scientific writing principles. For detailed guidance, refer to references/writing_principles.md.
Clarity :
Conciseness :
Accuracy :
Objectivity :
CRITICAL: Always write in full paragraphs, never submit bullet points in scientific papers.
Scientific papers must be written in complete, flowing prose. Use this two-stage approach for effective writing:
Stage 1: Create Section Outlines with Key Points
When starting a new section:
Example outline (Introduction section):
- Background: AI in drug discovery gaining traction
* Cite recent reviews (Smith 2023, Jones 2024)
* Traditional methods are slow and expensive
- Gap: Limited application to rare diseases
* Only 2 prior studies (Lee 2022, Chen 2023)
* Small datasets remain a challenge
- Our approach: Transfer learning from common diseases
* Novel architecture combining X and Y
- Study objectives: Validate on 3 rare disease datasets
Stage 2: Convert Key Points to Full Paragraphs
Once the outline is complete, expand each bullet point into proper prose:
Example conversion to prose:
Artificial intelligence approaches have gained significant traction in drug discovery
pipelines over the past decade (Smith, 2023; Jones, 2024). While these computational
methods show promise for accelerating the identification of therapeutic candidates,
traditional experimental approaches remain slow and resource-intensive, often requiring
years of laboratory work and substantial financial investment. However, the application
of AI to rare diseases has been limited, with only two prior studies demonstrating
proof-of-concept results (Lee, 2022; Chen, 2023). The primary obstacle has been the
scarcity of training data for conditions affecting small patient populations.
To address this challenge, we developed a transfer learning approach that leverages
knowledge from well-characterized common diseases to predict therapeutic targets for
rare conditions. Our novel neural architecture combines convolutional layers for
molecular feature extraction with attention mechanisms for protein-ligand interaction
modeling. The objective of this study was to validate our approach across three
independent rare disease datasets, assessing both predictive accuracy and biological
interpretability of the results.
Key Differences Between Outlines and Final Text:
| Outline (Planning Stage) | Final Manuscript |
|---|---|
| Bullet points and fragments | Complete sentences and paragraphs |
| Telegraphic notes | Full explanations with context |
| List of citations | Citations integrated into prose |
| Abbreviated ideas | Developed arguments with transitions |
| For your eyes only | For publication and peer review |
Common Mistakes to Avoid:
When Lists ARE Acceptable (Limited Cases):
Lists may appear in scientific papers only in specific contexts:
Integration with Research Lookup:
The research-lookup skill is essential for Stage 1 (creating outlines):
This two-stage process ensures you:
Adapt manuscripts to journal requirements:
Adapt language, terminology, and conventions to match the specific scientific discipline. Each field has established vocabulary, preferred phrasings, and domain-specific conventions that signal expertise and ensure clarity for the target audience.
Identify Field-Specific Linguistic Conventions:
Biomedical and Clinical Sciences:
Molecular Biology and Genetics:
Chemistry and Pharmaceutical Sciences:
Ecology and Environmental Sciences:
Physics and Engineering:
Neuroscience:
Social and Behavioral Sciences:
General Principles:
Match Audience Expertise:
Define Technical Terms Strategically:
Maintain Consistency:
Avoid Field Mixing Errors:
Verify Terminology Usage:
Top Rejection Reasons:
Writing Quality Issues:
Stage 1: Planning
Stage 2: Drafting (Use two-stage writing process for each section)
Remember : Bullet points are for planning only—the final manuscript must be in complete paragraphs.
Stage 3: Revision
Stage 4: Final Preparation
This skill works effectively with:
This skill includes comprehensive reference files covering specific aspects of scientific writing:
references/imrad_structure.md: Detailed guide to IMRAD format and section-specific contentreferences/citation_styles.md: Complete citation style guides (APA, AMA, Vancouver, Chicago, IEEE)references/figures_tables.md: Best practices for creating effective data visualizationsreferences/reporting_guidelines.md: Study-specific reporting standards and checklistsreferences/writing_principles.md: Core principles of effective scientific communicationLoad these references as needed when working on specific aspects of scientific writing.
Weekly Installs
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Repository
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First Seen
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Installed on
opencode412
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github-copilot325
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