skills/43-wentorai-research-plugins/skills/writing/composition/scientific-writing-guide/SKILL.md
Curated tools and techniques for scientific writing beyond LaTeX
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research scientific-writing-guideInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Scientific writing is a specialized skill that demands clarity, precision, and adherence to disciplinary conventions. Whether you are drafting a journal article, conference paper, or grant proposal, the quality of your prose directly influences how reviewers and readers perceive your research.
This guide distills best practices from the awesome-scientific-writing community (920+ stars) and supplements them with actionable techniques for structuring papers, writing compelling titles and abstracts, choosing the right authoring tools, and polishing manuscripts to publication quality. The focus is on practical, tool-agnostic advice that works across STEM and social-science disciplines.
Modern scientific writing extends well beyond LaTeX. Markdown-based workflows (Pandoc, Quarto, Jupyter Book), collaborative platforms (Overleaf, HackMD), and reference managers (Zotero, Paperpile) have reshaped how researchers draft and publish. This skill helps you navigate these options and adopt a workflow that fits your team.
A well-structured paper guides the reader from problem to contribution with minimal friction. The standard IMRaD (Introduction, Methods, Results, and Discussion) skeleton remains the default for empirical work, but variations exist for theoretical, review, and systems papers.
| Section | Purpose | Typical Length | |---------|---------|---------------| | Title | Concise summary of contribution | 8-15 words | | Abstract | Self-contained overview | 150-300 words | | Introduction | Context, gap, contribution | 1-2 pages | | Related Work | Position within the field | 1-2 pages | | Methods | Reproducible description | 2-4 pages | | Results | Empirical findings | 2-3 pages | | Discussion | Interpretation and limitations | 1-2 pages | | Conclusion | Takeaways and future work | 0.5-1 page |
A strong title is specific, informative, and free of jargon abbreviations. Compare:
Rules of thumb:
Use the four-sentence abstract formula:
Example template:
[Domain] faces the challenge of [problem]. Existing approaches [limitation].
We propose [method], which [key innovation]. Experiments on [benchmarks]
show that [method] achieves [metric improvements], demonstrating [significance].
For researchers who prefer plain text and version control:
# Convert Markdown to PDF via LaTeX
pandoc paper.md \
--citeproc \
--bibliography refs.bib \
--csl ieee.csl \
--pdf-engine=xelatex \
-o paper.pdf
# Convert to DOCX for collaborators
pandoc paper.md \
--citeproc \
--bibliography refs.bib \
-o paper.docx
Quarto extends R Markdown to Python, Julia, and Observable JS:
# _quarto.yml
project:
type: manuscript
manuscript:
article: paper.qmd
format:
html: default
pdf:
template: elsevier.tex
| Tool | Best For | Collaboration | Version Control | |------|----------|---------------|-----------------| | Overleaf | LaTeX teams | Real-time | Git integration | | Quarto | Code + prose | Git | Native | | Google Docs | Non-technical coauthors | Real-time | Suggest mode | | Typst | Fast typesetting | Git | Native |
tools
Recommend AND run open-source AI tools, agents, Claude Code / Codex skills, and MCP servers for any stage of a literature review — searching, reading, extracting, synthesizing, screening, citation-checking, and paper writing. Use when the user asks "what tool should I use to..." OR "install/run/use <tool> to ..." for research/lit-review work: automating a survey or related-work section, PDF→Markdown extraction for LLMs (MinerU/marker/docling), PRISMA / systematic review (ASReview), citation-backed Q&A over PDFs (PaperQA2), wiring papers into Claude/Cursor via MCP (arxiv/paper-search/zotero servers), or chatting with a Zotero library. Ships a launcher (scripts/litrun.py) that installs each tool in an isolated venv and runs it. Curated catalog of 70+ vetted projects. 支持中英文(用于「文献综述工具选型」与「一键安装/运行」)。
development
Route empirical-research requests through the Auto-Empirical Research Skills catalog when this whole repository is installed as one skill in Codex, CodeBuddy, Claude Code, or another IDE. Use to choose and load the right vendored AERS skill for causal inference, econometrics, replication, data acquisition, manuscript writing, peer review and referee responses, citation checking, de-AIGC editing, or full empirical-paper workflows without reading the entire repository at once.
documentation
Use when the project collects primary data or runs a field, lab, or survey experiment, before the intervention begins — write the pre-analysis plan, size the sample from a power calculation, and register with the AEA RCT Registry. Apply after the design is chosen in aer-identification and before any outcome data are seen.
tools
Guide economists to authoritative data sources with explicit, confirmed data specifications before retrieval; interfaces with Playwright MCP to navigate portals and extract real data, not articles about data.