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hypothesis-generation

Generate competing mechanistic hypotheses with evidence and falsifiable predictions for LaTeX reports.

94|11|Updated Mar 26, 2026
Search Tags:#visualization#LaTeX#hypothesis#literature-review#scientific-method#experimental-design#research-reporting
One-click install
npx skills add https://github.com/swaruplab/operon --skill hypothesis-generation-swaruplab
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: hypothesis-generation
Source: https://github.com/swaruplab/operon/tree/main/src-tauri/protocols/hypothesis-generation
Command: npx skills add https://github.com/swaruplab/operon --skill hypothesis-generation-swaruplab

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes assets (resource) components.

What problem does it solve?

Formulating robust, testable scientific hypotheses from observations, data, and literature is time-consuming and prone to bias; this Skill provides a structured framework to generate multiple mechanistic hypotheses, assess supporting evidence, and prepare appendices for rigorous reporting.

Core Features & Use Cases

  • Structured hypothesis generation for scientific inquiry, enabling the rapid creation of 3-5 distinct mechanistic hypotheses with concise explanations, 2-3 supporting evidence bullets, and 1-2 core assumptions.
  • Evidence synthesis and planning to organize literature, identify knowledge gaps, and outline experimental designs to distinguish hypotheses.
  • Appendix-ready reporting with a LaTeX-based template and guidance for comprehensive appendices, including literature review, detailed protocols, quality assessments, and supplementary data.

Quick Start

Describe the phenomenon and any known observations to receive a structured set of competing hypotheses and an appendices-ready report.

Frequently Asked Questions about hypothesis-generation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate testable scientific hypotheses from literature and observations?▼

Yes, you can create competing scientific hypotheses by providing your known observations; the Skill generates multiple distinct mechanistic explanations, each with concise evidence bullets and core assumptions to structure your research inquiry.

What's the best way to structure experimental designs for falsifiable predictions?▼

LaTeX reporting is integrated by packaging the generated hypotheses, evidence synthesis, and experimental plans into an appendices-heavy report template, including literature reviews, detailed protocols, and supplementary data sections.

Can I use this for literature review and evidence synthesis before hypothesis generation?▼

Yes, you can use this for literature review and evidence synthesis; it organizes existing literature, identifies knowledge gaps, and assesses supporting evidence to formulate distinct mechanistic hypotheses and prepare comprehensive appendices.

Do I need prior experimental data to formulate mechanistic hypotheses?▼

You do not need prior experimental data, but providing known observations and a clear scientific phenomenon allows the Skill to more accurately generate competing mechanistic hypotheses and propose discriminating experiments.

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