hypothesis-generation

Name: hypothesis-generation
Availability: InStock
Author: Daniel

Generate structured scientific hypotheses with evidence citations from literature.

1|2|Updated Jan 7, 2026

Search Tags:#hypothesis #critical-thinking #literature-review #evidence-synthesis #scientific-method #experimental-design #research-planning

Ready to run

npx skills add https://github.com/danieldekay/copilot-config-promptops --skill hypothesis-generation-danieldekay

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: hypothesis-generation
Source: https://github.com/danieldekay/copilot-config-promptops/tree/main/skills/hypothesis-generation
Command: npx skills add https://github.com/danieldekay/copilot-config-promptops --skill hypothesis-generation-danieldekay

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) and assets (resource) components.

What problem does it solve?

This Skill provides a structured, reproducible approach to turning raw observations into testable hypotheses, reducing ad-hoc reasoning and promoting evidence-based reasoning across disciplines.

Core Features & Use Cases

YAML-frontmatter driven templates for organizing mechanistic explanations, supporting evidence, and core assumptions, enabling consistent hypothesis documentation.
Guided literature synthesis and appendices support to capture background, conflicting findings, state-of-the-art methods, and knowledge gaps.
Cross-domain applicability for hypothesis development in biology, physics, social sciences, and data-driven research, with workflows for literature review, experimental design planning, and prediction formulation.

Quick Start

Draft three competing hypotheses for a chosen phenomenon with concise mechanisms and two supporting evidences each.

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 hypotheses from literature review observations?▼

You generate testable hypotheses by synthesizing literature into structured briefs containing mechanistic explanations, supporting evidence citations, and traceable appendices. This reduces ad-hoc reasoning and promotes reproducible, evidence-based research planning across scientific disciplines.

What is the best way to structure scientific hypotheses for experimental design?▼

Structure scientific hypotheses using YAML-frontmatter templates to organize mechanistic explanations, supporting evidence, and core assumptions. This enables consistent documentation for experimental design planning and predictive reasoning across biology, physics, and social sciences.

Can I use this hypothesis generation approach for social science research planning?▼

Yes, hypothesis generation supports social science research planning alongside biological and physical sciences. It provides cross-domain applicability for literature review, experimental design, and prediction formulation in data-driven research workflows.

How do I synthesize conflicting findings and knowledge gaps into competing hypotheses?▼

Synthesize conflicting findings and knowledge gaps into competing hypotheses using guided literature synthesis and appendices support. This captures background context and state-of-the-art methods to draft multiple hypotheses with concise mechanisms and supporting evidence.

Does evidence synthesis for hypothesis generation work without prior source citations?▼

Evidence synthesis for hypothesis generation outputs structured briefs with explicit evidence citations traceable to cited sources and supporting appendices. Prior literature inputs are synthesized to capture background, conflicting findings, and knowledge gaps.