hypothesis-generation

原文涵盖的主题

• Scientific Hypothesis Generation
• Overview
• When to Use This Skill
• Visual Enhancement with Scientific Schematics
• Workflow
• 1. Understand the Phenomenon
• 2. Conduct Comprehensive Literature Search
• 3. Synthesize Existing Evidence

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: 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 Planning mechanistic studies across scientific domains ⚠️ 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: 1. Generate at minimum ONE schematic or diagram (e.g., hypothesis framework showing competing explanations) 2. Prefer 2-3 figures for comprehensive reports (mechanistic pathway, experimental design flowchart, prediction decision tree) How to generate figures: Use the scientific-schematics skill to generate AI-powered publication-quality

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