When you've got experimental data or observations and need to develop testable scientific hypotheses, this gives you a structured workflow. It walks you through literature search (PubMed and web), generating 3-5 competing mechanistic explanations, evaluating them against quality criteria like falsifiability and parsimony, then designing experiments to test each one. The output is a LaTeX report with hypothesis boxes, predictions, and mandatory AI-generated schematics using the scientific-schematics skill. It's opinionated about structure and leans heavy on visual documentation, which makes sense for research work. Best for actual scientific inquiry where you need rigorous hypothesis formulation, not casual brainstorming.
npx skills add https://github.com/k-dense-ai/scientific-agent-skills --skill hypothesis-generation