How does the Scientific Brainstorming skill help with research?

It acts as a collaborative partner to generate hypotheses, identify research gaps, and challenge existing frameworks through structured brainstorming phases.

Can it help with interdisciplinary scientific work?

Yes, it specifically utilizes cross-domain analogies to connect concepts from diverse fields, such as applying biological systems to physics or social networks to ecology.

Is this skill suitable for both theoretical and experimental research?

Absolutely. It is designed to assist with everything from abstract theory development and hypothesis generation to practical experimental design and methodology refinement.

Does it support specific ideation frameworks?

The skill integrates proven methodologies including SCAMPER, TRIZ principles, and Six Thinking Hats to provide a rigorous structure for creative problem-solving.

Scientific Brainstorming

Name: Scientific Brainstorming
Author: x-cmd

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Data Science & ML

Facilitates collaborative research ideation through hypothesis generation, interdisciplinary exploration, and systematic challenge of scientific assumptions.

About

This skill transforms Claude into an intellectual research partner designed to break through creative blocks and expand scientific horizons. It employs a structured, five-phase workflow—ranging from divergent exploration to critical evaluation—using advanced techniques like cross-domain analogies and assumption reversal. Whether you are identifying research gaps, developing novel methodologies, or seeking to bridge diverse fields, this skill provides the structured yet flexible environment needed to synthesize complex insights into actionable experimental directions.

Key Features

Integration of structured methodologies like SCAMPER and TRIZ
Multi-phase brainstorming workflow covering context, exploration, and synthesis
Collaborative conversational style that functions as an equal thought partner
8 GitHub stars
Cross-disciplinary analogy generation to spark innovative solutions
Systematic assumption reversal and scale-shifting techniques

Use Cases

Identifying interdisciplinary connections and analogies across scientific fields
Generating novel research hypotheses or experimental directions
Developing and refining new methodological approaches for complex problems

About

Key Features

Integration of structured methodologies like SCAMPER and TRIZ
Multi-phase brainstorming workflow covering context, exploration, and synthesis
Collaborative conversational style that functions as an equal thought partner
8 GitHub stars
Cross-disciplinary analogy generation to spark innovative solutions
Systematic assumption reversal and scale-shifting techniques

Use Cases

Identifying interdisciplinary connections and analogies across scientific fields
Generating novel research hypotheses or experimental directions
Developing and refining new methodological approaches for complex problems