Stats
Actions
Tags
From literature-and-topic-selection
Formulates testable hypotheses from observations or data, proposes mechanisms and predictions, and designs experiments. Follows scientific method; mandates AI-generated schematics.
How this skill is triggered — by the user, by Claude, or both
Slash command
/literature-and-topic-selection:hypothesis-generationThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
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 skill for scientific inquiry across domains.
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 skill for scientific inquiry across domains.
This skill should be used when:
⚠️ MANDATORY: Every hypothesis generation report MUST include at least 1-2 AI-generated figures using the scientific-schematics skill.
This is not optional. Hypothesis reports without visual elements are incomplete. Before finalizing any document:
How to generate figures:
How to generate schematics:
python scripts/generate_schematic.py "your diagram description" -o figures/output.png
The AI will automatically:
When to add schematics:
For detailed guidance on creating schematics, refer to the scientific-schematics skill documentation.
Follow this systematic process to generate robust scientific hypotheses:
Start by clarifying the observation, question, or phenomenon that requires explanation:
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:
For all scientific domains:
Search strategy:
references/literature_search_strategies.md for detailed search techniquesAnalyze and integrate findings from literature search:
Develop 3-5 distinct hypotheses that could explain the phenomenon. Each hypothesis should:
Strategies for generating hypotheses:
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.
For each viable hypothesis, propose specific experiments or studies to test it. Consult references/experimental_design_patterns.md for common approaches:
Experimental design elements:
Consider multiple approaches:
For each hypothesis, generate specific, quantitative predictions:
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):
\newpage before each hypothesis box to prevent content overflowKeep main text highly concise - only the most essential information. All details go to appendices.
Page Break Strategy:
\newpage before hypothesis boxes to ensure they start on fresh pagesAppendices (Comprehensive, Detailed):
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):
All detailed explanations, additional evidence, and comprehensive discussions belong in the appendices.
Critical Overflow Prevention:
\newpage before each hypothesis box to start it on a fresh pageCitation Requirements:
Aim for extensive citation to support all claims:
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:
Break Long Content: If a hypothesis requires extensive explanation, split across main text and appendix:
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.
Ensure all generated hypotheses meet these standards:
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 sourceshypothesis_generation.sty - LaTeX style package providing colored boxes, professional formatting, and custom environments for hypothesis reportshypothesis_report_template.tex - Complete LaTeX template with main text structure and comprehensive appendix sectionsFORMATTING_GUIDE.md - Quick reference guide with examples of all box types, color schemes, citation practices, and troubleshooting tipsWhen preparing hypothesis-driven research for publication, consult the venue-templates skill for writing style guidance:
venue_writing_styles.md - Master guide comparing styles across venuesreviewer_expectations.md - What reviewers look for when evaluating research hypothesesnpx claudepluginhub youyinnn/skills-collection --plugin literature-and-topic-selectionFormulates structured, testable hypotheses from observations or data, proposes mechanisms, and designs experiments following the scientific method.
Formulates structured, testable hypotheses from experimental observations using a scientific-method framework — derives predictions, proposes mechanisms, and designs experiments to test them.
Turns observations into testable hypotheses with predictions, mechanisms, and experiments. Follows scientific method; use for ideation or LLM testing on datasets.