alterlab-hypothesis-gen

You can generate testable hypotheses from observations by producing 3-5 competing hypotheses, each with brief mechanism explanations, 2-3 key evidence points, and 1-2 core assumptions, ensuring rigorous reasoning and reproducible academic reporting.

Systematic hypothesis generation structures a literature review by synthesizing observations into competing hypotheses, providing evidence citations and appendices to clarify how raw data informs testable predictions and formal experimental design.

Yes, hypothesis generation outputs a LaTeX report template with comprehensive appendices and a YAML metadata payload, directly supporting formal experimental design and reproducible academic planning documentation.

Hypothesis generation applies across laboratory science, data analysis, literature synthesis, and formal experimental design, systematically transforming diverse observations into testable predictions regardless of the specific research domain.

Hypothesis generation produces 3-5 competing hypotheses from a given observation, each requiring brief mechanism explanations, 2-3 key evidence points, and 1-2 core assumptions to ensure comprehensive academic planning.

Generating testable hypotheses requires a SKILL.md frontmatter with name and description, alongside optional scripts, references, and assets, outputting a YAML metadata payload to structure the experimental design process.