hypothesis-generation
Generate testable hypotheses. Formulate from observations, design experiments, explore competing explanations, develop predictions, propose mechanisms, for scientific inquiry across domains.
npx skills add majiayu000/claude-skill-registry --skill hypothesis-generation-k-dense-ai-claude-scientific-wr-2 --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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 flo
- 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
- 4. Generate Competing Hypotheses
- 5. Evaluate Hypothesis Quality
- 6. Design Experimental Tests
- 7. Formulate Testable Predictions
- 8. Present Structured Output
- Quality Standards
- Resources
python scripts/generate_schematic.py "your diagram description" -o figures/output.png xelatex hypothesis_report.tex bibtex hypothesis_report
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-k-dense-ai-claude-scientific-wr-2 --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.