Agent skill · Design & Presentation

hypothesis-generation

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

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill hypothesis-generation-ovachiever-droid-tings-10ca31f2 --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 6 KB
Bundled scripts: none
Path: skills/analysis/hypothesis-generation-ovachiever-droid-tings-10ca31f2/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# 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 ## Workflow Follow this systematic process to generate robust scientific hypotheses: ### 1. Understand the Phenomenon Start by clarifying the observation, question, or phenomenon that requires explanation: - Identify the core observation or pattern that needs explanation - Define the scope and boundaries of the phenomenon - Note any constraints or specific contexts - Clarify what is already known vs. what is uncertain - Identify the relevant scientific domain(s) ### 2. Conduct Comprehensive Litera

What's inside
Steps it walks through
  1. Overview
  2. When to Use This Skill
  3. Workflow
  4. 1. Understand the Phenomenon
  5. 2. Conduct Comprehensive Literature Search
  6. 3. Synthesize Existing Evidence
  7. 4. Generate Competing Hypotheses
  8. 5. Evaluate Hypothesis Quality
  9. 6. Design Experimental Tests
  10. 7. Formulate Testable Predictions
  11. 8. Present Structured Output
  12. Quality Standards
  13. Resources
  14. references/
Ships with 1 file
  • metadata.json
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About this skill
What does the hypothesis-generation skill do?

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

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill hypothesis-generation-ovachiever-droid-tings-10ca31f2 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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