Which scientific domains can this skill be used for?

This skill is designed for scientific inquiry across all domains, including biomedical, physical, and social sciences, using domain-agnostic frameworks and specific integrations like PubMed for biomedical topics.

How does the skill ensure the quality of hypotheses?

Each hypothesis is evaluated against a set of quality criteria including testability, falsifiability, parsimony, and explanatory power to ensure they are scientifically sound.

Does it include visual aids in the output?

Yes, the skill requires at least 1-2 AI-generated figures (schematics) for every report, such as mechanistic pathway diagrams or experimental flowcharts, to ensure visual clarity.

What is the final output format provided by this skill?

The skill generates a structured LaTeX document including an executive summary, colored hypothesis boxes for the main text, and comprehensive appendices for literature and protocols.

Scientific Hypothesis Generation

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

byK-Dense-AI

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2,188

Data Science & ML

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

About

This skill empowers researchers and scientists to systematically develop robust hypotheses across diverse domains. It guides the user through the entire scientific inquiry process—from initial observation and literature synthesis using PubMed and web search to the generation of competing mechanistic explanations. By enforcing rigorous quality assessment and mandatory visual schematics, it ensures that scientific inquiries are evidence-based, falsifiable, and ready for experimental validation, culminating in professional LaTeX reports suitable for academic review.

Key Features

Professional LaTeX report generation with specialized formatting and extensive citations.
Systematic generation of 3-5 competing mechanistic hypotheses per inquiry.
Mandatory AI-generated scientific schematics and experimental design flowcharts.
Integrated literature search using PubMed and general web tools for evidence synthesis.
2,188 GitHub stars
Quality assessment based on testability, falsifiability, and parsimony criteria.

Use Cases

Exploring alternative mechanistic explanations for anomalous laboratory data or observations.
Developing research proposals or grant applications with structured, evidence-backed hypotheses.
Designing comprehensive experimental frameworks and testable predictions for new scientific studies.

About

Key Features

Professional LaTeX report generation with specialized formatting and extensive citations.
Systematic generation of 3-5 competing mechanistic hypotheses per inquiry.
Mandatory AI-generated scientific schematics and experimental design flowcharts.
Integrated literature search using PubMed and general web tools for evidence synthesis.
2,188 GitHub stars
Quality assessment based on testability, falsifiability, and parsimony criteria.

Use Cases

Exploring alternative mechanistic explanations for anomalous laboratory data or observations.
Developing research proposals or grant applications with structured, evidence-backed hypotheses.
Designing comprehensive experimental frameworks and testable predictions for new scientific studies.