hypothesis-generation

Generate structured, testable scientific hypotheses with experimental designs from observations and literature.

2|Updated Oct 29, 2025

Search Tags:#structured-output #literature-review #hypothesis-generation #scientific-method #experimental-design #mechanistic-hypotheses

Ready to run

npx skills add https://github.com/shanelindsay/agentic-r --skill hypothesis-generation-shanelindsay

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: hypothesis-generation
Source: https://github.com/shanelindsay/agentic-r/tree/main/skills/scientific-thinking/hypothesis-generation
Command: npx skills add https://github.com/shanelindsay/agentic-r --skill hypothesis-generation-shanelindsay

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) and assets (resource) components.

What problem does it solve?

Helps researchers systematically transform observations and literature into testable hypotheses and actionable research plans, reducing guesswork and ensuring rigorous reasoning.

Core Features & Use Cases

Structured hypothesis generation: produce multiple mechanistic hypotheses with testable predictions.
Quality assessment & design templates: evaluate hypotheses against criteria and draft experimental tests using the provided templates.
Cross-domain applicability: usable across biology, psychology, ecology, and engineering for theory-driven inquiry.

Quick Start

Provide a phenomenon description and let the system generate 3-5 testable hypotheses with accompanying experimental designs.

Frequently Asked Questions about hypothesis-generation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I generate testable scientific hypotheses from literature and observations?▼

To generate testable scientific hypotheses, provide a phenomenon description and relevant literature. The system then outputs 3-5 structured mechanistic hypotheses with background context, testable predictions, and experimental designs.

What is the best way to structure mechanistic hypotheses for experimental design?▼

Structuring mechanistic hypotheses involves defining competing explanations, evaluating their quality against specific criteria, and drafting aligned experimental tests. This yields standardized predictions and actionable research plans ready for empirical validation.

Can I use structured hypothesis generation for cross-domain research like psychology and ecology?▼

Structured hypothesis generation supports cross-domain applicability across biology, psychology, ecology, and engineering. It applies scientific method principles to transform discipline-specific observations into theory-driven inquiry and testable predictions.

How do I create competing explanations with testable predictions for my research?▼

Creating competing explanations involves systematically transforming observations into multiple mechanistic hypotheses. The system outputs structured predictions, quality assessments, and experimental designs to rigorously evaluate each potential explanation.

Does hypothesis generation work without requiring external data processing dependencies?▼

Hypothesis generation works independently without external dependencies. It uses built-in standardized templates and references to evaluate hypotheses and draft experimental tests directly from your provided phenomenon description.