# Hypothesis Generation

Generate testable hypotheses.

- Repository: https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills (4869 stars)
- Category: Design
- License: see repository
- Last updated: 2026-10-30
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill hypothesis-generation -g -a claude-code -y`
Codex: `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill hypothesis-generation -g -a codex -y`
Cursor: `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill hypothesis-generation -g -a cursor -y`
Gemini CLI: `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill hypothesis-generation -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add brycewang-stanford/Auto-Empirical-Research-Skills`

## Description

Generate testable hypotheses. Formulate from observations, design experiments, explore competing explanations, develop predictions, propose mechanisms, for scientific inquiry across domains.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

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  ║  本文件为开源 Skill 原始文档，收录仅供学习与研究参考        ║
  ║  CoPaper.AI 收集整理 | https://copaper.ai                  ║
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  来源仓库: https://github.com/K-Dense-AI/claude-scientific-writer
  项目名称: claude-scientific-writer
  开源协议: MIT License
  收录日期: 2026-04-02

  声明: 本文件版权归原作者所有。此处收录旨在为社会科学实证研究者
  提供 AI Agent Skills 的集中参考。如有侵权，请联系删除。
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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
- Planning mechanistic studies across scientific domains

## Visual Enhancement with Scientific Schematics

**⚠️ 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 diagrams
- Simply describe your desired diagram in natural language
- Nano Banana Pro will automatically generate, review, and refine the schematic

The rest: https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/blob/HEAD/skills/04-K-Dense-AI-claude-scientific-writer/hypothesis-generation/SKILL.md