Agent skill
science-writing
Write publication-quality scientific manuscripts with structured reference management, automated DOI validation via CrossRef API, and evidence-based writing principles. Always write in full paragraphs (never bullet points). Use for research papers, reviews, and journal submissions.
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/data/science-writing
SKILL.md
Science Writing
Overview
Science writing is the craft of communicating research with precision, clarity, and impact. This skill provides comprehensive guidance for writing publication-quality scientific manuscripts using evidence-based principles from Nature, OSU Writing Center, and leading scientific communication experts.
Core Principle: Write in complete, flowing paragraphs. Never submit manuscripts with bullet points outside of Methods sections (inclusion/exclusion criteria only).
When to Use This Skill
Use this skill when:
- Writing or revising manuscript sections (Abstract, Introduction, Methods, Results, Discussion)
- Structuring research papers using IMRAD or venue-specific formats
- Managing references with DOI validation and CrossRef API metadata retrieval
- Formatting citations in any style (APA, AMA, Vancouver, Chicago, IEEE, ACS, NLM)
- Creating publication-quality figures and tables
- Applying reporting guidelines (CONSORT, STROBE, PRISMA, STARD, ARRIVE, CARE)
- Adapting manuscripts for different target venues (Nature/Science, medical journals, ML conferences)
- Ensuring reproducibility and scientific rigor
- Addressing reviewer comments
Key Features
1. Evidence-Based Writing Principles
Based on research from Nature Masterclasses, OSU Writing Guide, and scientific communication studies:
Clarity Over Complexity
- Use precise, unambiguous language
- Define technical terms at first use
- Maintain logical flow within and between paragraphs
- Active voice when it improves readability
Conciseness Respects Time
- Eliminate redundant phrases ("due to the fact that" → "because")
- Use strong verbs instead of noun+verb combinations ("analyze" not "perform an analysis")
- Remove unnecessary intensifiers and throat-clearing phrases
- Keep sentences 15-20 words average (field-dependent)
Accuracy Builds Credibility
- Report exact values with appropriate precision
- Use consistent terminology throughout
- Distinguish observations from interpretations
- Match precision to measurement capability
Objectivity Maintains Integrity
- Present results without bias
- Acknowledge conflicting evidence
- Avoid emotional or evaluative language
- Use appropriate hedging ("suggests" not "proves" for correlational data)
2. Structured Reference Management with CrossRef API
Automated DOI Validation and Metadata Retrieval
This skill includes scripts/crossref_validator.py for:
- Validating DOIs against CrossRef database
- Retrieving complete citation metadata (authors, title, journal, year, DOI)
- Checking title accuracy and completeness
- Formatting references in multiple citation styles
- Detecting missing or incorrect DOIs
Usage:
python scripts/crossref_validator.py --doi "10.1038/d41586-018-02404-4"
python scripts/crossref_validator.py --title "How to write a first-class paper"
python scripts/crossref_validator.py --validate-file references.bib
Always Include DOIs
- Required for all journal articles when available
- Use CrossRef API to verify and retrieve DOIs for papers missing them
- Format DOIs as URLs:
https://doi.org/10.xxxx/xxxxx - Check that DOI links resolve correctly
Reference Quality Standards
- Prefer peer-reviewed journal articles over preprints
- Cite primary sources (not secondary citations)
- Use recent sources (within 5-10 years for active fields, 2-3 years for ML)
- Maintain <20% self-citations
- Verify all citations against original sources
3. IMRAD Structure for Maximum Impact
Introduction (10-20% of manuscript)
- Establish broad context and importance
- Review relevant prior research
- Identify specific knowledge gap
- State clear research question or hypothesis
Methods (20-30% of manuscript)
- Provide sufficient detail for replication
- Describe study design, participants, procedures
- Specify statistical analysis with justification
- Include ethical approval statements
Results (25-35% of manuscript)
- Present findings objectively without interpretation
- Integrate with figures and tables
- Include statistical significance, effect sizes, and confidence intervals
- Report all tested hypotheses (not just significant results)
Discussion (25-40% of manuscript)
- Interpret findings in context of prior research
- Propose mechanisms or explanations
- Acknowledge limitations honestly and specifically
- Suggest future research directions
- State practical implications
For details on IMRAD structure: See references/imrad_structure.md
4. Venue-Specific Adaptation
Different venues have distinct expectations for style, structure, and emphasis:
| Venue Type | Word Count | Focus | Methods Detail | Writing Style |
|---|---|---|---|---|
| Nature/Science | 2,000-4,500 | Broad significance | Supplement | Engaging, accessible |
| Medical (NEJM/Lancet) | 2,700-3,500 | Clinical outcomes | Main text | Conservative, precise |
| Field journals | 3,000-6,000 | Technical depth | Main text | Formal, comprehensive |
| ML conferences | ~6,000 (8 pages) | Novel contribution | Concise main text | Direct, technical |
Key Adaptations by Venue:
Nature/Science:
- Lead with broad significance
- Accessible to non-specialists
- Story-driven organization
- Methods in supplement
- Strong visual presentation
Medical Journals:
- Clinical relevance prominent
- Strict IMRAD structure
- CONSORT/STROBE compliance
- Primary outcome first in Results
- Conservative interpretation
ML Conferences (NeurIPS/ICML/ICLR):
- Numbered contributions in Introduction
- Pseudocode and mathematical notation
- Extensive ablation studies
- Brief conclusion with limitations
- ArXiv preprints acceptable
For complete venue adaptation guidance: See references/writing_principles.md and references/imrad_structure.md
5. Two-Stage Writing Process
Stage 1: Create Structured Outlines
- Gather literature and data
- Create bullet-point outline with:
- Main arguments or findings
- Key studies to cite (with DOIs)
- Data points and statistics
- Logical flow and transitions
- These bullets are scaffolding—NOT the final manuscript
Stage 2: Convert to Flowing Prose
- Transform bullets into complete sentences
- Add transitions between ideas (however, moreover, subsequently)
- Integrate citations naturally within sentences
- Expand with context and explanation
- Ensure logical flow from sentence to sentence
- Vary sentence structure for engagement
Example Transformation:
Outline (Stage 1):
- 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
Final Prose (Stage 2):
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.
6. Citation Styles and Formatting
Support for all major citation styles with automated formatting:
Numbered Styles:
- AMA: Superscript numbers (medical research)
- Vancouver: Brackets [1] (biomedical sciences)
- IEEE: Brackets [1] (engineering, computer science)
- ACS: Superscript or numbered (chemistry)
Author-Date Styles:
- APA: (Smith, 2023) - psychology, social sciences
- Chicago: (Smith 2023) - humanities, some sciences
- Cell: (Smith et al., 2023) - life sciences
For complete citation formatting: See references/citation_styles.md
7. Scientific Nomenclature Standards
Microbial Nomenclature (International Committee on Systematics of Prokaryotes):
- Genus capitalized, species lowercase, both italicized: Escherichia coli
- After first use, abbreviate genus: E. coli
- "sp." for single unnamed species; "spp." for multiple
- Infrasubspecific terms in roman text: Staphylococcus aureus subsp. aureus
Genetic Nomenclature:
- Gene names: Three italicized letters (his, lac, gfp)
- Phenotypes: Non-italicized with superscripts (His+, Lac-, GFP+)
- Genotypes: Italicized mutations (hisA, lacZ, gfp)
- Alleles: With numbers (hisG251)
- Deletions: Δ symbol (ΔlacZ)
- Insertions: :: notation (lacZ::Tn10)
Viral Nomenclature (International Committee on Taxonomy of Viruses):
- English common names (not Latinized binomials)
- Example: "severe acute respiratory syndrome coronavirus 2" (SARS-CoV-2)
Chemical Nomenclature (IUPAC):
- Systematic names for novel compounds
- Common names for well-known substances
- SMILES or InChI for database submissions
For field-specific guidance: See sections 9 (Field-Specific Language) in full skill documentation
8. Reporting Guidelines by Study Type
Ensure completeness and transparency:
| Study Type | Guideline | Key Requirements |
|---|---|---|
| Randomized controlled trials | CONSORT | Flow diagram, randomization, blinding |
| Observational studies | STROBE | Study design, participants, variables, bias |
| Systematic reviews | PRISMA | Search strategy, selection, quality assessment |
| Diagnostic accuracy | STARD | Patient selection, index test, reference standard |
| Prediction models | TRIPOD | Development/validation, model specification |
| Animal research | ARRIVE | Species, housing, experimental procedures |
| Case reports | CARE | Patient information, timeline, outcomes |
For complete reporting guidelines: See references/reporting_guidelines.md
9. Figures and Tables
Design Principles:
- Self-explanatory with complete captions
- Consistent formatting and terminology
- Label all axes, columns, rows with units
- Include sample sizes (n) and statistical annotations
- One figure/table per 1000 words guideline
When to Use:
- Tables: Precise numerical data, multiple variables requiring exact values
- Figures: Trends, patterns, relationships, comparisons best understood visually
Common Figure Types:
- Bar graphs: Comparing discrete categories
- Line graphs: Showing trends over time
- Scatterplots: Displaying correlations
- Box plots: Showing distributions and outliers
- Heatmaps: Visualizing matrices and patterns
For detailed guidance: See references/figures_tables.md
10. Common Pitfalls to Avoid
Top Rejection Reasons:
- Inappropriate, incomplete, or insufficiently described statistics
- Over-interpretation of results or unsupported conclusions
- Poorly described methods affecting reproducibility
- Small, biased, or inappropriate samples
- Poor writing quality or difficult-to-follow text
- Inadequate literature review or context
- Unclear or poorly designed figures and tables
- Failure to follow reporting guidelines
Writing Quality Issues:
- Mixing tenses inappropriately
- Excessive jargon or undefined acronyms
- Paragraph breaks disrupting logical flow
- Missing transitions between sections
- Inconsistent notation or terminology
- Bullet points in Results/Discussion (use paragraphs)
Workflow for Manuscript Development
Planning Phase
- Identify target journal and review author guidelines
- Determine applicable reporting guideline
- Outline manuscript structure (IMRAD or venue-specific)
- Plan figures and tables as the data story backbone
Drafting Phase (Use two-stage process for each section)
- Create figures and tables first (core data story)
- For each section:
- First: Create bullet-point outline with literature/data
- Second: Convert bullets to flowing paragraphs with transitions
- Draft in this order:
- Methods (often easiest first)
- Results (describing figures/tables objectively)
- Discussion (interpreting findings)
- Introduction (setting up research question)
- Abstract (synthesizing complete story)
- Title (concise and descriptive)
Revision Phase
- Check logical flow and "red thread" throughout
- Verify terminology and notation consistency
- Ensure figures/tables are self-explanatory
- Confirm adherence to reporting guidelines
- Validate all citations with CrossRef API
- Check word counts for each section
- Proofread for grammar, spelling, and clarity
Final Preparation
- Format according to journal requirements
- Prepare supplementary materials
- Write cover letter highlighting significance
- Complete submission checklists
- Gather required statements (funding, COI, data availability, ethics)
Integration with CrossRef API for Reference Management
Validating and Enriching References
The CrossRef API integration provides:
DOI Validation:
# Validate a single DOI
python scripts/crossref_validator.py --doi "10.1038/nature12373"
# Validate multiple DOIs from a file
python scripts/crossref_validator.py --validate-file my_references.txt
Title Verification:
# Look up complete metadata by title
python scripts/crossref_validator.py --title "CRISPR-Cas9 genome editing"
# Verify title matches DOI
python scripts/crossref_validator.py --doi "10.1126/science.1231143" --check-title
Automated Reference Formatting:
# Generate formatted references in multiple styles
python scripts/crossref_validator.py --doi "10.1038/nature12373" --style vancouver
python scripts/crossref_validator.py --doi "10.1038/nature12373" --style apa
Batch Processing:
# Process bibliography and report missing/incorrect DOIs
python scripts/crossref_validator.py --audit-bibliography references.bib --output report.txt
Best Practices for Reference Management
- Always verify DOIs: Use CrossRef API to validate before submission
- Check title accuracy: Ensure titles are complete and correctly formatted
- Include all metadata: Authors, year, journal, volume, pages, DOI
- Use persistent DOI URLs: Format as
https://doi.org/10.xxxx/xxxxx - Verify link resolution: Test that DOIs resolve to correct articles
- Update preprints: Replace arXiv citations with published versions when available
- Maintain currency: Check for retractions or corrections via CrossRef
Verb Tense Guidelines
| Section | Tense | Usage |
|---|---|---|
| Abstract - Background | Present/past | Present for facts, past for prior studies |
| Abstract - Methods | Past | "We recruited...", "Participants completed..." |
| Abstract - Results | Past | "The intervention reduced..." |
| Abstract - Conclusions | Present | "These findings suggest..." |
| Introduction - Background | Present | "Exercise improves health..." |
| Introduction - Prior work | Past | "Smith et al. found..." |
| Methods | Past | "We measured...", "Samples were collected..." |
| Results | Past | "Mean age was 45 years..." |
| Discussion - Your findings | Past | "We found that..." |
| Discussion - Interpretation | Present | "This suggests...", "These data indicate..." |
For comprehensive tense guidance: See references/writing_principles.md
Resources and Supporting Files
This skill includes comprehensive reference files:
-
references/imrad_structure.md: Detailed IMRAD format and venue-specific variations -
references/citation_styles.md: Complete citation style guides (APA, AMA, Vancouver, Chicago, IEEE, ACS, NLM) -
references/figures_tables.md: Best practices for data visualization -
references/reporting_guidelines.md: Study-specific reporting standards with checklists -
references/writing_principles.md: Core principles of scientific communication with venue-specific adaptations -
scripts/crossref_validator.py: CrossRef API integration for DOI validation and metadata retrieval -
examples/: Example manuscripts showing proper structure and style
Load these references as needed when working on specific aspects of scientific writing.
Key Reminders
- Always write in complete paragraphs - bullet points are for planning only
- Validate all DOIs with CrossRef API - ensure completeness and accuracy
- Match writing style to target venue - adapt tone, length, and emphasis
- Follow two-stage writing process - outline first, then convert to prose
- Apply appropriate reporting guidelines - ensure transparency and completeness
- Use consistent terminology throughout - avoid synonym variation for key terms
- Distinguish observations from interpretations - be clear about what data show vs. what you infer
- Acknowledge limitations specifically - not generic statements like "larger sample needed"
Evidence Base:
This skill synthesizes guidance from:
- Nature Masterclasses: "How to write a first-class paper" (Gewin, 2018)
- Oregon State University Microbiology Writing Guide (scientific style standards)
- International Committee of Medical Journal Editors (ICMJE) recommendations
- EQUATOR Network reporting guidelines
- American Medical Association Manual of Style (11th ed.)
- Publication Manual of the American Psychological Association (7th ed.)
- Leading scientific communication research
CrossRef API Documentation:
- API endpoint: https://api.crossref.org/works/
- Rate limits: 50 requests/second for polite pool (with mailto in User-Agent)
- Full documentation: https://www.crossref.org/documentation/retrieve-metadata/rest-api/
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