Individual skill
hypothesis-generation
Structured hypothesis formulation from observations. Use when you have experimental observations or data and need to formulate testable hypotheses with predictions, propose mechanisms, and design experiments to test them. Follows scientific method framework. For open-ended ideation use scientific-brainstorming; for automated LLM-driven hypothesis testing on datasets use hypogenic.
skills/hypothesis-generation/SKILL.md
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SKILL.mdcore · 14,671 bytesSKILL.mdcore · 14,671 bytesSKILL.mdcore · 14,671 bytesassets/FORMATTING_GUIDE.mddoc · 19,304 bytesassets/hypothesis_generation.styasset · 7,625 bytesassets/hypothesis_report_template.texasset · 20,148 bytesreferences/experimental_design_patterns.mddoc · 14,208 bytesreferences/hypothesis_quality_criteria.mddoc · 8,051 bytesreferences/literature_search_strategies.mddoc · 20,277 bytesscripts/__pycache__/demo.cpython-313.pycasset · 2,249 bytesscripts/demo.pyruns · 1,436 bytes
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# Scientific Hypothesis Generation
## Overview
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.
## When to Use This Skill
This skill 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