cirq
Cirq is Google Quantum AI's open-source framework for designing, simulating, and running quantum circuits on quantum computers and simulator…
Maintainer K-Dense Inc. · Last updated April 1, 2026
Hypothesis generation is a systematic process for developing testable explanations. Formulate evidence-based hypotheses from observations, design experiments, explore competing explanations, and develop predictions. Apply this skill for scientific inquiry across domains.
Original source
https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/hypothesis-generation
Skill Snapshot
Source Doc
⚠️ MANDATORY: Every hypothesis generation report MUST include at least 1-2 AI-generated figures using the scientific-schematics skill.
This is not optional. Hypothesis reports without visual elements are incomplete. Before finalizing any document:
How to generate figures:
How to generate schematics:
The AI will automatically:
When to add schematics:
For detailed guidance on creating schematics, refer to the scientific-schematics skill documentation.
Follow this systematic process to generate robust scientific hypotheses:
Start by clarifying the observation, question, or phenomenon that requires explanation:
Related skills
Cirq is Google Quantum AI's open-source framework for designing, simulating, and running quantum circuits on quantum computers and simulator…
Gtars is a high-performance Rust toolkit for manipulating, analy.
MarkItDown is a Python tool developed by Microsoft for converting various file formats to Markdown. It's particularly useful for converting…
PennyLane is a quantum computing library that enables training quantum computers like neural networks. It provides automatic differentiation…