What is the Scientific Hypothesis Generation skill?

It is a specialized tool for Claude Code that helps researchers formulate evidence-based hypotheses, design experiments, and document scientific inquiry through a systematic, literature-grounded workflow.

What fields of science can this skill be used for?

While it features specific integration for biomedical research via PubMed, the framework is designed for scientific inquiry across all domains, including physics, chemistry, and environmental sciences.

Does this skill support visual diagrams?

Yes, it includes a mandatory requirement to generate AI-powered scientific schematics, such as mechanistic pathways, experimental design flowcharts, and prediction decision trees.

What kind of output does the skill produce?

It generates a professional LaTeX document featuring an executive summary, colored hypothesis boxes for comparison, and comprehensive appendices containing detailed literature reviews and protocols.

Scientific Hypothesis Generator

Name: Scientific Hypothesis Generator
Author: K-Dense-AI

byK-Dense-AI

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3,719

数据科学与机器学习

Formulates testable, evidence-based scientific hypotheses and experimental designs from observations and literature.

关于

This skill empowers researchers and scientists to systematically develop robust hypotheses using a structured workflow that includes literature synthesis, mechanistic exploration, and experimental planning. It guides users through the creation of multiple competing explanations for scientific phenomena, evaluates them against quality criteria like falsifiability and parsimony, and generates comprehensive LaTeX reports. A unique requirement of this skill is the mandatory inclusion of AI-generated scientific schematics, ensuring that every hypothesis is supported by publication-quality visual models and mechanistic diagrams.

主要功能

Systematic generation of 3-5 distinct, mechanistic hypotheses from initial observations.
Automated literature synthesis via PubMed and WebSearch for evidence-based grounding.
3,719 GitHub stars
Professional LaTeX report output with specialized formatting for executive summaries and detailed appendices.
Mandatory generation of AI-powered scientific schematics and experimental flowcharts.
Integrated quality assessment based on testability, parsimony, and explanatory power.

使用场景

Developing research protocols and experimental designs for novel scientific inquiries.
Exploring competing mechanistic explanations for observed biological or physical phenomena.
Synthesizing large volumes of scientific literature into testable predictions and structured reports.

关于

主要功能

Systematic generation of 3-5 distinct, mechanistic hypotheses from initial observations.
Automated literature synthesis via PubMed and WebSearch for evidence-based grounding.
3,719 GitHub stars
Professional LaTeX report output with specialized formatting for executive summaries and detailed appendices.
Mandatory generation of AI-powered scientific schematics and experimental flowcharts.
Integrated quality assessment based on testability, parsimony, and explanatory power.

使用场景

Developing research protocols and experimental designs for novel scientific inquiries.
Exploring competing mechanistic explanations for observed biological or physical phenomena.
Synthesizing large volumes of scientific literature into testable predictions and structured reports.