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DataRust

Hypothesis Generation

by xintaofei

Hypothesis Generation is a Data skill for Claude Code, published by xintaofei in codeg.

2.8K stars345 forkson xintaofei/codegAdded 2026/08/17+3% in starsRepository updated 2026/08/17
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Install in seconds
Install Hypothesis Generation
Copy Hypothesis Generation into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.
terminal
npx degit https://github.com/xintaofei/codeg/tree/main/src-tauri/science/skills/hypothesis-generation ~/.claude/skills/hypothesis-generation

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/xintaofei/codeg.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file
src-tauri/science/skills/hypothesis-generation/SKILL.md in xintaofei/codeg
Installs to
~/.claude/skills/hypothesis-generation
Collection
One of 25 skills cataloged from this repository
Category
Data — 668 skills

What Hypothesis Generation does

Hypothesis Generation formulates testable hypotheses from observations and data, proposes mechanisms, and designs experiments to test them. Use it for scientific inquiry, literature synthesis, and experimental planning across domains.

Hypothesis Generation is cataloged under Data on DirSkills. Hypothesis Generation comes from a repository tagged acp, agent, claude-code, cline and code-generation.

Documentation

README

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

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Hypothesis Generation

  • What else does xintaofei publish alongside Hypothesis Generation?

    Hypothesis Generation is one of 25 skills that DirSkills catalogs from xintaofei/codeg, the repository it ships in. Its siblings there include Brainstorming, Citation Management and Code Review Reception. Each one is a separate skill with its own page in this directory, installs the same way Hypothesis Generation does, and is maintained by xintaofei in that same repository. The rest of the collection is listed on the xintaofei/codeg page.

  • How does Hypothesis Generation compare to other Data skills?

    Hypothesis Generation ranks #298 by stars among the 668 Data skills in this catalog. The most-starred ones next to it are Benchmark Methodology, Jupyter Notebook and Solana. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Hypothesis Generation against them. Open each page to compare what they document and how they install.

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