Hypothesis generation is a systematic process for developing testable explanations. Formulate evidence-based hypotheses from observations, design experiments, explore competing explanations, and develop predictions. Apply this agent for scientific inquiry across domains.

When to Use This Agent

This agent should be used when:

Developing hypotheses from observations or preliminary data
Designing experiments to test scientific questions
Exploring competing explanations for phenomena
Formulating testable predictions for research
Conducting literature-based hypothesis generation
Planning mechanistic studies across scientific domains

Visual Enhancement with Scientific Schematics

⚠️ MANDATORY: Every hypothesis generation report MUST include at least 1-2 AI-generated figures using the scientific-schematics agent.

This is not optional. Hypothesis reports without visual elements are incomplete. Before finalizing any document:

Generate at minimum ONE schematic or diagram (e.g., hypothesis framework showing competing explanations)
Prefer 2-3 figures for comprehensive reports (mechanistic pathway, experimental design flowchart, prediction decision tree)

How to generate figures:

Use the scientific-schematics agent 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:

Hypothesis framework diagrams showing competing explanations
Experimental design flowcharts
Mechanistic pathway diagrams
Prediction decision trees
Causal relationship diagrams
Theoretical model visualizations
Any complex concept that benefits from visualization

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

Workflow

Follow this systematic process to generate robust scientific hypotheses:

1. Understand the Phenomenon

Start by clarifying the observation, question, or phenomenon that requires explanation:

Identify the core observation or pattern that needs explanation
Define the scope and boundaries of the phenomenon
Note any constraints or specific contexts
Clarify what is already known vs. what is uncertain
Identify the relevant scientific domain(s)

2. Conduct Comprehensive Literature Search

Search existing scientific literature to ground hypotheses in current evidence. Use both PubMed (for biomedical topics) and general web search (for broader scientific domains):

For biomedical topics:

Use WebFetch with PubMed URLs to access relevant literature
Search for recent reviews, meta-analyses, and primary research
Look for similar phenomena, related mechanisms, or analogous systems

For all scientific domains:

Use WebSearch to find recent papers, preprints, and reviews
Search for established theories, mechanisms, or frameworks
Identify gaps in current understanding

Search strategy:

Begin with broad searches to understand the landscape
Narrow to specific mechanisms, pathways, or theories
Look for contradictory findings or unresolved debates
Consult references/literature_search_strategies.md for detailed search techniques

3. Synthesize Existing Evidence

Analyze and integrate findings from literature search:

Summarize current understanding of the phenomenon
Identify established mechanisms or theories that may apply
Note conflicting evidence or alternative viewpoints
Recognize gaps, limitations, or unanswered questions
Identify analogies from related systems or domains

4. Generate Competing Hypotheses

Develop 3-5 distinct hypotheses that could explain the phenomenon. Each hypothesis should:

Provide a mechanistic explanation (not just description)
Be distinguishable from other hypotheses
Draw on evidence from the literature synthesis
Consider different levels of explanation (molecular, cellular, systemic, population, etc.)

Strategies for generating hypotheses:

Apply known mechanisms from analogous systems
Consider multiple causative pathways
Explore different scales of explanation
Question assumptions in existing explanations
Combine mechanisms in novel ways

5. Evaluate Hypothesis Quality

Assess each hypothesis against established quality criteria from references/hypothesis_quality_criteria.md:

Testability: Can the hypothesis be empirically tested? Falsifiability: What observations would disprove it? Parsimony: Is it the simplest explanation that fits the evidence? Explanatory Power: How much of the phenomenon does it explain? Scope: What range of observations does it cover? Consistency: Does it align with established principles? Novelty: Does it offer new insights beyond existing explanations?

Explicitly note the strengths and weaknesses of each hypothesis.

6. Design Experimental Tests

For each viable hypothesis, propose specific experiments or studies to test it. Consult references/experimental_design_patterns.md for common approaches:

Experimental design elements:

What would be measured or observed?
What comparisons or controls are needed?
What methods or techniques would be used?
What sample sizes or statistical approaches are appropriate?
What are potential confounds and how to address them?

Consider multiple approaches:

Laboratory experiments (in vitro, in vivo, computational)
Observational studies (cross-sectional, longitudinal, case-control)
Clinical trials (if applicable)
Natural experiments or quasi-experimental designs

7. Formulate Testable Predictions

For each hypothesis, generate specific, quantitative predictions:

State what should be observed if the hypothesis is correct
Specify expected direction and magnitude of effects when possible
Identify conditions under which predictions should hold
Distinguish predictions between competing hypotheses
Note predictions that would falsify the hypothesis

8. Present Structured Output

Generate a professional LaTeX document using the template in assets/hypothesis_report_template.tex. The report should be well-formatted with colored boxes for visual organization and divided into a concise main text with comprehensive appendices.

Document Structure:

Main Text (Maximum 4 pages):

Executive Summary - Brief overview in summary box (0.5-1 page)
Competing Hypotheses - Each hypothesis in its own colored box with brief mechanistic explanation and key evidence (2-2.5 pages for 3-5 hypotheses)
- IMPORTANT: Use \newpage before each hypothesis box to prevent content overflow
- Each box should be ≤0.6 pages maximum
Testable Predictions - Key predictions in amber boxes (0.5-1 page)
Critical Comparisons - Priority comparison boxes (0.5-1 page)

Keep main text highly concise - only the most essential information. All details go to appendices.

Page Break Strategy:

Always use \newpage before hypothesis boxes to ensure they start on fresh pages
This prevents content from overflowing off page boundaries
LaTeX boxes (tcolorbox) do not automatically break across pages

Appendices (Comprehensive, Detailed):

Appendix A: Comprehensive literature review with extensive citations
Appendix B: Detailed experimental designs with full protocols
Appendix C: Quality assessment tables and detailed evaluations
Appendix D: Supplementary evidence and analogous systems

Colored Box Usage:

Use the custom box environments from hypothesis_generation.sty:

hypothesisbox1 through hypothesisbox5 - For each competing hypothesis (blue, green, purple, teal, orange)
predictionbox - For testable predictions (amber)
comparisonbox - For critical comparisons (steel gray)
evidencebox - For supporting evidence highlights (light blue)
summarybox - For executive summary (blue)

Each hypothesis box should contain (keep concise for 4-page limit):

Mechanistic Explanation: 1-2 brief paragraphs (6-10 sentences max) explaining HOW and WHY
Key Supporting Evidence: 2-3 bullet points with citations (most important evidence only)
Core Assumptions: 1-2 critical assumptions

All detailed explanations, additional evidence, and comprehensive discussions belong in the appendices.

Critical Overflow Prevention:

Insert \newpage before each hypothesis box to start it on a fresh page
Keep each complete hypothesis box to ≤0.6 pages (approximately 15-20 lines of content)
If content exceeds this, move additional details to Appendix A
Never let boxes overflow off page boundaries - this creates unreadable PDFs

Citation Requirements:

Aim for extensive citation to support all claims:

Main text: 10-15 key citations for most important evidence only (keep concise for 4-page limit)
Appendix A: 40-70+ comprehensive citations covering all relevant literature
Total target: 50+ references in bibliography

Main text citations should be selective - cite only the most critical papers. All comprehensive citation and detailed literature discussion belongs in the appendices. Use \citep{author2023} for parenthetical citations.

LaTeX Compilation:

The template requires XeLaTeX or LuaLaTeX for proper rendering:

xelatex hypothesis_report.tex
bibtex hypothesis_report
xelatex hypothesis_report.tex
xelatex hypothesis_report.tex

Required packages: The hypothesis_generation.sty style package must be in the same directory or LaTeX path. It requires: tcolorbox, xcolor, fontspec, fancyhdr, titlesec, enumitem, booktabs, natbib.

Page Overflow Prevention:

To prevent content from overflowing on pages, follow these critical guidelines:

Monitor Box Content Length: Each hypothesis box should fit comfortably on a single page. If content exceeds ~0.7 pages, it will likely overflow.

Use Strategic Page Breaks: Insert \newpage before boxes that contain substantial content:

\newpage
\begin{hypothesisbox1}[Hypothesis 1: Title]
% Long content here
\end{hypothesisbox1}

Keep Main Text Boxes Concise: For the 4-page main text limit:
- Each hypothesis box: Maximum 0.5-0.6 pages
- Mechanistic explanation: 1-2 brief paragraphs only (6-10 sentences max)
- Key evidence: 2-3 bullet points only
- Core assumptions: 1-2 items only
- If content is longer, move details to appendices
Break Long Content: If a hypothesis requires extensive explanation, split across main text and appendix:
- Main text box: Brief mechanistic overview + 2-3 key evidence points
- Appendix A: Detailed mechanism explanation, comprehensive evidence, extended discussion
Test Page Boundaries: Before each new box, consider if remaining page space is sufficient. If less than 0.6 pages remain, use \newpage to start the box on a fresh page.
Appendix Page Management: In appendices, use \newpage between major sections to avoid overflow in detailed content areas.

Quick Reference: See assets/FORMATTING_GUIDE.md for detailed examples of all box types, color schemes, and common formatting patterns.

Quality Standards

Ensure all generated hypotheses meet these standards:

Evidence-based: Grounded in existing literature with citations
Testable: Include specific, measurable predictions
Mechanistic: Explain how/why, not just what
Comprehensive: Consider alternative explanations
Rigorous: Include experimental designs to test predictions

Resources

references/

hypothesis_quality_criteria.md - Framework for evaluating hypothesis quality (testability, falsifiability, parsimony, explanatory power, scope, consistency)
experimental_design_patterns.md - Common experimental approaches across domains (RCTs, observational studies, lab experiments, computational models)
literature_search_strategies.md - Effective search techniques for PubMed and general scientific sources

assets/

hypothesis_generation.sty - LaTeX style package providing colored boxes, professional formatting, and custom environments for hypothesis reports
hypothesis_report_template.tex - Complete LaTeX template with main text structure and comprehensive appendix sections
FORMATTING_GUIDE.md - Quick reference guide with examples of all box types, color schemes, citation practices, and troubleshooting tips

Related Agents

When preparing hypothesis-driven research for publication, consult the venue-templates agent for writing style guidance:

venue_writing_styles.md - Master guide comparing styles across venues
Venue-specific guides for Nature/Science, Cell Press, medical journals, and ML/CS conferences
reviewer_expectations.md - What reviewers look for when evaluating research hypotheses