scientific-writing

name	scientific-writing
description	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.
allowed-tools	["Read","Write","Edit","Bash"]

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)
• Creating, formatting, or improving figures, tables, and data visualizations
• Applying study-specific reporting guidelines (CONSORT for trials, STROBE for observational studies, PRISMA for reviews)
• Drafting abstracts that meet journal requirements (structured or unstructured)
• Preparing manuscripts for submission to specific journals
• Improving writing clarity, conciseness, and precision
• Ensuring proper use of field-specific terminology and nomenclature
• Addressing reviewer comments and revising manuscripts

Visual Enhancement with Scientific Schematics

⚠️ 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:

1. Generate at minimum ONE schematic or diagram using scientific-schematics
2. Prefer 2-3 figures for comprehensive papers (methods flowchart, results visualization, conceptual diagram)

How to generate figures:

• Use the scientific-schematics skill to generate AI-powered publication-quality diagrams
• Simply describe your desired diagram in natural language
• Nano Banana Pro will automatically generate, review, and refine the schematic

How to generate schematics:

python scripts/generate_schematic.py "your diagram description" -o figures/output.png

The AI will automatically:

• Create publication-quality images with proper formatting
• Review and refine through multiple iterations
• Ensure accessibility (colorblind-friendly, high contrast)
• Save outputs in the figures/ directory

When to add schematics:

• Study design and methodology flowcharts (CONSORT, PRISMA, STROBE)
• Conceptual framework diagrams
• Experimental workflow illustrations
• Data analysis pipeline diagrams
• Biological pathway or mechanism diagrams
• System architecture visualizations
• Any complex concept that benefits from visualization

For detailed guidance on creating schematics, refer to the scientific-schematics skill documentation.

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Core Capabilities

1. Manuscript Structure and Organization

IMRAD Format: Guide papers through the standard Introduction, Methods, Results, And Discussion structure used across most scientific disciplines. This includes:

• Introduction: Establish research context, identify gaps, state objectives
• Methods: Detail study design, populations, procedures, and analysis approaches
• Results: Present findings objectively without interpretation
• Discussion: Interpret results, acknowledge limitations, propose future directions

For detailed guidance on IMRAD structure, refer to references/imrad_structure.md.

Alternative Structures: Support discipline-specific formats including:

• Review articles (narrative, systematic, scoping)
• Case reports and case series
• Meta-analyses and pooled analyses
• Theoretical/modeling papers
• Methods papers and protocols

2. Section-Specific Writing Guidance

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:

• Establish the research problem's importance
• Review relevant literature systematically
• Identify knowledge gaps or controversies
• State clear research questions or hypotheses
• Explain the study's novelty and significance

Methods Documentation: Ensure reproducibility through:

• Detailed participant/sample descriptions
• Clear procedural documentation
• Statistical methods with justification
• Equipment and materials specifications
• Ethical approval and consent statements

Results Presentation: Present findings with:

• Logical flow from primary to secondary outcomes
• Integration with figures and tables
• Statistical significance with effect sizes
• Objective reporting without interpretation

Discussion Construction: Synthesize findings by:

• Relating results to research questions
• Comparing with existing literature
• Acknowledging limitations honestly
• Proposing mechanistic explanations
• Suggesting practical implications and future research

3. Citation and Reference Management

Apply citation styles correctly across disciplines. For comprehensive style guides, refer to references/citation_styles.md.

Major Citation Styles:

• AMA (American Medical Association): Numbered superscript citations, common in medicine
• Vancouver: Numbered citations in square brackets, biomedical standard
• APA (American Psychological Association): Author-date in-text citations, common in social sciences
• Chicago: Notes-bibliography or author-date, humanities and sciences
• IEEE: Numbered square brackets, engineering and computer science

Best Practices:

• Cite primary sources when possible
• Include recent literature (last 5-10 years for active fields)
• Balance citation distribution across introduction and discussion
• Verify all citations against original sources
• Use reference management software (Zotero, Mendeley, EndNote)

4. Figures and Tables

Create effective data visualizations that enhance comprehension. For detailed best practices, refer to references/figures_tables.md.

When to Use Tables vs. Figures:

• Tables: Precise numerical data, complex datasets, multiple variables requiring exact values
• Figures: Trends, patterns, relationships, comparisons best understood visually

Design Principles:

• Make each table/figure self-explanatory with complete captions
• Use consistent formatting and terminology across all display items
• Label all axes, columns, and rows with units
• Include sample sizes (n) and statistical annotations
• Follow the "one table/figure per 1000 words" guideline
• Avoid duplicating information between text, tables, and figures

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

5. Reporting Guidelines by Study Type

Ensure completeness and transparency by following established reporting standards. For comprehensive guideline details, refer to references/reporting_guidelines.md.

Key Guidelines:

• CONSORT: Randomized controlled trials
• STROBE: Observational studies (cohort, case-control, cross-sectional)
• PRISMA: Systematic reviews and meta-analyses
• STARD: Diagnostic accuracy studies
• TRIPOD: Prediction model studies
• ARRIVE: Animal research
• CARE: Case reports
• SQUIRE: Quality improvement studies
• SPIRIT: Study protocols for clinical trials
• CHEERS: Economic evaluations

Each guideline provides checklists ensuring all critical methodological elements are reported.

6. Writing Principles and Style

Apply fundamental scientific writing principles. For detailed guidance, refer to references/writing_principles.md.

Clarity:

• Use precise, unambiguous language
• Define technical terms and abbreviations at first use
• Maintain logical flow within and between paragraphs
• Use active voice when appropriate for clarity

Conciseness:

• Eliminate redundant words and phrases
• Favor shorter sentences (15-20 words average)
• Remove unnecessary qualifiers
• Respect word limits strictly

Accuracy:

• Report exact values with appropriate precision
• Use consistent terminology throughout
• Distinguish between observations and interpretations
• Acknowledge uncertainty appropriately

Objectivity:

• Present results without bias
• Avoid overstating findings or implications
• Acknowledge conflicting evidence
• Maintain professional, neutral tone

7. Writing Process: From Outline to Full Paragraphs

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:

1. Use the research-lookup skill to gather relevant literature and data
2. Create a structured outline with bullet points marking:
   • Main arguments or findings to present
   • Key studies to cite
   • Data points and statistics to include
   • Logical flow and organization
3. These bullet points serve as scaffolding—they are NOT the final manuscript

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:

1. Transform bullet points into complete sentences with subjects, verbs, and objects
2. Add transitions between sentences and ideas (however, moreover, in contrast, subsequently)
3. Integrate citations naturally within sentences, not as lists
4. Expand with context and explanation that bullet points omit
5. Ensure logical flow from one sentence to the next within each paragraph
6. Vary sentence structure to maintain reader engagement

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:

• ❌ Never leave bullet points in the final manuscript
• ❌ Never submit lists where paragraphs should be
• ❌ Don't use numbered or bulleted lists in Results or Discussion sections (except for specific cases like study hypotheses or inclusion criteria)
• ❌ Don't write sentence fragments or incomplete thoughts
• ✅ Do use occasional lists only in Methods (e.g., inclusion/exclusion criteria, materials lists)
• ✅ Do ensure every section flows as connected prose
• ✅ Do read paragraphs aloud to check for natural flow

When Lists ARE Acceptable (Limited Cases):

Lists may appear in scientific papers only in specific contexts:

• Methods: Inclusion/exclusion criteria, materials and reagents, participant characteristics
• Supplementary Materials: Extended protocols, equipment lists, detailed parameters
• Never in: Abstract, Introduction, Results, Discussion, Conclusions

Integration with Research Lookup:

The research-lookup skill is essential for Stage 1 (creating outlines):

1. Search for relevant papers using research-lookup
2. Extract key findings, methods, and data
3. Organize findings as bullet points in your outline
4. Then convert the outline to full paragraphs in Stage 2

This two-stage process ensures you:

• Gather and organize information systematically
• Create logical structure before writing
• Produce polished, publication-ready prose
• Maintain focus on the narrative flow

8. Journal-Specific Formatting

Adapt manuscripts to journal requirements:

• Follow author guidelines for structure, length, and format
• Apply journal-specific citation styles
• Meet figure/table specifications (resolution, file formats, dimensions)
• Include required statements (funding, conflicts of interest, data availability, ethical approval)
• Adhere to word limits for each section
• Format according to template requirements when provided

9. Field-Specific Language and Terminology

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:

• Review terminology used in recent high-impact papers in the target journal
• Note field-specific abbreviations, units, and notation systems
• Identify preferred terms (e.g., "participants" vs. "subjects," "compound" vs. "drug," "specimens" vs. "samples")
• Observe how methods, organisms, or techniques are typically described

Biomedical and Clinical Sciences:

• Use precise anatomical and clinical terminology (e.g., "myocardial infarction" not "heart attack" in formal writing)
• Follow standardized disease nomenclature (ICD, DSM, SNOMED-CT)
• Specify drug names using generic names first, brand names in parentheses if needed
• Use "patients" for clinical studies, "participants" for community-based research
• Follow Human Genome Variation Society (HGVS) nomenclature for genetic variants
• Report lab values with standard units (SI units in most international journals)

Molecular Biology and Genetics:

• Use italics for gene symbols (e.g., TP53), regular font for proteins (e.g., p53)
• Follow species-specific gene nomenclature (uppercase for human: BRCA1; sentence case for mouse: Brca1)
• Specify organism names in full at first mention, then use accepted abbreviations (e.g., Escherichia coli, then E. coli)
• Use standard genetic notation (e.g., +/+, +/-, -/- for genotypes)
• Employ established terminology for molecular techniques (e.g., "quantitative PCR" or "qPCR," not "real-time PCR")

Chemistry and Pharmaceutical Sciences:

• Follow IUPAC nomenclature for chemical compounds
• Use systematic names for novel compounds, common names for well-known substances
• Specify chemical structures using standard notation (e.g., SMILES, InChI for databases)
• Report concentrations with appropriate units (mM, μM, nM, or % w/v, v/v)
• Describe synthesis routes using accepted reaction nomenclature
• Use terms like "bioavailability," "pharmacokinetics," "IC50" consistently with field definitions

Ecology and Environmental Sciences:

• Use binomial nomenclature for species (italicized: Homo sapiens)
• Specify taxonomic authorities at first species mention when relevant
• Employ standardized habitat and ecosystem classifications
• Use consistent terminology for ecological metrics (e.g., "species richness," "Shannon diversity index")
• Describe sampling methods with field-standard terms (e.g., "transect," "quadrat," "mark-recapture")

Physics and Engineering:

• Follow SI units consistently unless field conventions dictate otherwise
• Use standard notation for physical quantities (scalars vs. vectors, tensors)
• Employ established terminology for phenomena (e.g., "quantum entanglement," "laminar flow")
• Specify equipment with model numbers and manufacturers when relevant
• Use mathematical notation consistent with field standards (e.g., ℏ for reduced Planck constant)

Neuroscience:

• Use standardized brain region nomenclature (e.g., refer to atlases like Allen Brain Atlas)
• Specify coordinates for brain regions using established stereotaxic systems
• Follow conventions for neural terminology (e.g., "action potential" not "spike" in formal writing)
• Use "neural activity," "neuronal firing," "brain activation" appropriately based on measurement method
• Describe recording techniques with proper specificity (e.g., "whole-cell patch clamp," "extracellular recording")

Social and Behavioral Sciences:

• Use person-first language when appropriate (e.g., "people with schizophrenia" not "schizophrenics")
• Employ standardized psychological constructs and validated assessment names
• Follow APA guidelines for reducing bias in language
• Specify theoretical frameworks using established terminology
• Use "participants" rather than "subjects" for human research

General Principles:

Match Audience Expertise:

• For specialized journals: Use field-specific terminology freely, define only highly specialized or novel terms
• For broad-impact journals (e.g., Nature, Science): Define more technical terms, provide context for specialized concepts
• For interdisciplinary audiences: Balance precision with accessibility, define terms at first use

Define Technical Terms Strategically:

• Define abbreviations at first use: "messenger RNA (mRNA)"
• Provide brief explanations for specialized techniques when writing for broader audiences
• Avoid over-defining terms well-known to the target audience (signals unfamiliarity with field)
• Create a glossary if numerous specialized terms are unavoidable

Maintain Consistency:

• Use the same term for the same concept throughout (don't alternate between "medication," "drug," and "pharmaceutical")
• Follow a consistent system for abbreviations (decide on "PCR" or "polymerase chain reaction" after first definition)
• Apply the same nomenclature system throughout (especially for genes, species, chemicals)

Avoid Field Mixing Errors:

• Don't use clinical terminology for basic science (e.g., don't call mice "patients")
• Avoid colloquialisms or overly general terms in place of precise field terminology
• Don't import terminology from adjacent fields without ensuring proper usage

Verify Terminology Usage:

• Consult field-specific style guides and nomenclature resources
• Check how terms are used in recent papers from the target journal
• Use domain-specific databases and ontologies (e.g., Gene Ontology, MeSH terms)
• When uncertain, cite a key reference that establishes terminology

10. Common Pitfalls to Avoid

Top Rejection Reasons:

1. Inappropriate, incomplete, or insufficiently described statistics
2. Over-interpretation of results or unsupported conclusions
3. Poorly described methods affecting reproducibility
4. Small, biased, or inappropriate samples
5. Poor writing quality or difficult-to-follow text
6. Inadequate literature review or context
7. Figures and tables that are unclear or poorly designed
8. Failure to follow reporting guidelines

Writing Quality Issues:

• Mixing tenses inappropriately (use past tense for methods/results, present for established facts)
• Excessive jargon or undefined acronyms
• Paragraph breaks that disrupt logical flow
• Missing transitions between sections
• Inconsistent notation or terminology

Workflow for Manuscript Development

Stage 1: Planning

1. Identify target journal and review author guidelines
2. Determine applicable reporting guideline (CONSORT, STROBE, etc.)
3. Outline manuscript structure (usually IMRAD)
4. Plan figures and tables as the backbone of the paper

Stage 2: Drafting (Use two-stage writing process for each section)

1. Start with figures and tables (the core data story)
2. For each section below, follow the two-stage process:
   • First: Create outline with bullet points using research-lookup
   • Second: Convert bullet points to full paragraphs with flowing prose
3. Write Methods (often easiest to draft first)
4. Draft Results (describing figures/tables objectively)
5. Compose Discussion (interpreting findings)
6. Write Introduction (setting up the research question)
7. Craft Abstract (synthesizing the complete story)
8. Create Title (concise and descriptive)

Remember: Bullet points are for planning only—the final manuscript must be in complete paragraphs.

Stage 3: Revision

1. Check logical flow and "red thread" throughout
2. Verify consistency in terminology and notation
3. Ensure figures/tables are self-explanatory
4. Confirm adherence to reporting guidelines
5. Verify all citations are accurate and properly formatted
6. Check word counts for each section
7. Proofread for grammar, spelling, and clarity

Stage 4: Final Preparation

1. Format according to journal requirements
2. Prepare supplementary materials
3. Write cover letter highlighting significance
4. Complete submission checklists
5. Gather all required statements and forms

Integration with Other Scientific Skills

This skill works effectively with:

• Data analysis skills: For generating results to report
• Statistical analysis: For determining appropriate statistical presentations
• Literature review skills: For contextualizing research
• Figure creation tools: For developing publication-quality visualizations

References

This skill includes comprehensive reference files covering specific aspects of scientific writing:

• references/imrad_structure.md: Detailed guide to IMRAD format and section-specific content
• references/citation_styles.md: Complete citation style guides (APA, AMA, Vancouver, Chicago, IEEE)
• references/figures_tables.md: Best practices for creating effective data visualizations
• references/reporting_guidelines.md: Study-specific reporting standards and checklists
• references/writing_principles.md: Core principles of effective scientific communication

Load these references as needed when working on specific aspects of scientific writing.