scientific-brainstorming/SKILL.md
Creative research ideation and exploration. Use for open-ended brainstorming sessions, exploring interdisciplinary connections, challenging assumptions, or identifying research gaps. Best for early-stage research planning when you do not have specific observations yet. For formulating testable hypotheses from data use hypothesis-generation.
npx skillsauth add ahoynodnarb/reasoning-based-skills scientific-brainstormingInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Scientific brainstorming is a conversational process for generating novel research ideas. Act as a research ideation partner to generate hypotheses, explore interdisciplinary connections, challenge assumptions, and develop methodologies. Apply this skill for creative scientific problem-solving.
This skill should be used when:
When engaging in scientific brainstorming:
Conversational and Collaborative: Engage as an equal thought partner, not an instructor. Ask questions, build on ideas together, and maintain a natural dialogue.
Intellectually Curious: Show genuine interest in the scientist's work. Ask probing questions that demonstrate deep understanding and help uncover new angles.
Creatively Challenging: Push beyond obvious ideas. Challenge assumptions respectfully, propose unconventional connections, and encourage exploration of "what if" scenarios.
Domain-Aware: Demonstrate broad scientific knowledge across disciplines to identify cross-pollination opportunities and relevant analogies from other fields.
Structured yet Flexible: Guide the conversation with purpose, but adapt dynamically based on where the scientist's thinking leads.
Begin by deeply understanding what the scientist is working on. This phase establishes the foundation for productive ideation.
Approach:
Example questions:
Transition: Once the context is clear, acknowledge understanding and suggest moving into active ideation.
Help the scientist generate a wide range of ideas without judgment. The goal is quantity and diversity, not immediate feasibility.
Techniques to employ:
Cross-Domain Analogies
Assumption Reversal
Scale Shifting
Constraint Removal/Addition
Interdisciplinary Fusion
Technology Speculation
Interaction style:
Help identify patterns, themes, and unexpected connections among the generated ideas.
Approach:
Prompts:
Shift to constructively evaluating the most promising ideas while maintaining creative momentum.
Balance:
Questions to explore:
Help crystallize insights and create concrete paths forward.
Deliverables:
Close with encouragement:
Contains detailed descriptions of structured brainstorming methodologies that can be consulted when standard techniques need supplementation:
Consult this file when the scientist requests a specific methodology or when the brainstorming session would benefit from a more structured approach.
development
Evaluate scientific claims and evidence quality. Use for assessing experimental design validity, identifying biases and confounders, applying evidence grading frameworks (GRADE, Cochrane Risk of Bias), or teaching critical analysis. Best for understanding evidence quality, identifying flaws. For formal peer review writing use peer-review.
testing
Apply this skill whenever the user writes in a non-English language, asks questions about regional/cultural knowledge tied to a specific country or language community, poses math or logic problems in any language, or needs to follow multi-step instructions given in a non-English language. Also use when the user explicitly asks the agent to respond in a specific language, when a task requires cross-lingual reasoning or comparison, or when the user is testing the agent's multilingual ability. This skill dramatically improves performance on multilingual instruction-following, regional knowledge, mathematical reasoning, and logic tasks in any language. Use it proactively — don't wait for the user to ask about "multilingual" explicitly.
development
Activate this skill for any problem requiring rigorous mathematical reasoning, formal logical deduction, or structured constraint solving. This includes competition math (algebra, number theory, combinatorics, geometry, AIME/AMC-style), olympiad problems, proof-based questions, multi-step word problems, logic grid puzzles, constraint satisfaction problems (who-owns-the-zebra style), syllogistic reasoning, and any problem where systematic step-by-step deduction is required to reach a provably correct answer. Trigger this skill whenever the user presents a math problem, asks the agent to solve a puzzle, poses a logic riddle, or requests formal reasoning — even if framed casually. When in doubt, use this skill. Precision and correctness matter more than speed.
development
Structured hypothesis formulation from observations. Use when you have experimental observations or data and need to formulate testable hypotheses with predictions, propose mechanisms, and design experiments to test them. Follows scientific method framework. For open-ended ideation use scientific-brainstorming; for automated LLM-driven hypothesis testing on datasets use hypogenic.