scientific-writing
Core skill for the deep research and writing tool. Write scientific manuscripts in full paragraphs (never bullet points). Use two-stage process: (1) create section outlines with key points using research-lookup, (2) convert to flowing prose. IMRAD structure, citations (APA/AMA/Vancouver), figures/tables, reporting guidelines (CONSORT/STROBE/PRISMA), for research papers and journal submissions.
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill scientific-writing --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
What it does
The skill directs the agent to write scientific manuscripts in full paragraphs (no bullet points), following an IMRAD structure and including citations, figures, tables, and reporting guidelines. It enforces a two-stage process: first create section outlines with key points using research-lookup, then convert those outlines into flowing prose. It requires incorporation of figures/tables and adherence to reporting guidelines (CONSORT/STROBE/PRISMA) and supports various citation styles (APA/AMA/Vancouver). It also mandates inclusion of at least 1-2 AI-generated figures created via a separate schematics skill.
How it works
- Stage 1: Use the research-lookup skill to gather literature and data, then create a structured outline with bullet points marking main arguments, key studies to cite, data points, and the intended logical flow. These outlines are scaffolding, not the final manuscript.
- Stage 2: Transform each outline into full prose with complete sentences and transitions, integrate citations within sentences, expand context, ensure logical flow within each paragraph, and vary sentence structure.
- Throughout, the manuscript must follow IMRAD (Introduction, Methods, Results, Discussion) and may adapt to other standard formats; ensure alignment with selected citation style and study-specific reporting guidelines.
- Visuals: Generate at least 1-2 AI-generated figures using the scientific-schematics skill before finalizing, describing desired diagrams in natural language, and using the provided command to produce and save figures under figures/.
When to use it
Use for writing or revising any section of a scientific manuscript, structuring or formatting according to IMRAD or other standard formats, formatting citations/references, creating or improving figures/tables, applying CONSORT/STROBE/PRISMA guidance, drafting abstracts for journals, preparing submissions, improving writing clarity, and addressing reviewer comments.
What it can touch
- Interacts with research-lookup for literature gathering.
- Produces structured outlines and final prose.
- Generates and saves publication-quality figures via the scientific-schematics workflow:
- Generate with:
python scripts/generate_schematic.py "your diagram description" -o figures/output.png
- Generate with:
- Integrates citations in various styles (APA, AMA, Vancouver, Chicago, IEEE).
Caveats
- Final manuscripts must be in full paragraphs; bullet points are not allowed.
- At least 1-2 AI-generated figures are mandatory.
- The skill emphasizes adherence to IMRAD and standard reporting guidelines; deviations may require manual adjustments to comply with journal要求.
# Scientific Writing ## Overview **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. ## When to Use This Skill This skill should be used when: - Writing or revising any section of a scientific manuscript (abstract, introduction, methods, results, discussion) - Structuring a research paper using IMRAD or other standard formats - Formatting citations and references in specific styles (APA, AMA, Vancouver, Chicago, IEEE) - C
- Overview
- When to Use This Skill
- Visual Enhancement with Scientific Schematics
- Core Capabilities
- 1. Manuscript Structure and Organization
- 2. Section-Specific Writing Guidance
- 3. Citation and Reference Management
- 4. Figures and Tables
- 5. Reporting Guidelines by Study Type
- 6. Writing Principles and Style
- 7. Writing Process: From Outline to Full Paragraphs
- 8. Journal-Specific Formatting
- 9. Field-Specific Language and Terminology
- 10. Common Pitfalls to Avoid
python scripts/generate_schematic.py "your diagram description" -o figures/output.png
What does the scientific-writing skill do?
Core skill for the deep research and writing tool. Write scientific manuscripts in full paragraphs (never bullet points). Use two-stage process: (1) create section outlines with key points using research-lookup, (2) convert to flowing prose. IMRAD structure, citations (APA/AMA/Vancouver), figures/tables, reporting guidelines (CONSORT/STROBE/PRISMA), for research papers and journal submissions.
How do I install it?
Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill scientific-writing --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From FreedomIntelligence/OpenClaw-Medical-Skills, a repository with 2,909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.