scientific-brainstorming
关于
This skill facilitates open-ended research ideation, helping developers brainstorm novel ideas, explore interdisciplinary connections, and identify research gaps during early-stage planning. It is designed for creative exploration before specific data is available, distinguishing it from hypothesis testing. Use it as a conversational partner for generating research directions and challenging assumptions.
快速安装
Claude Code
推荐npx skills add K-Dense-AI/claude-scientific-skills -a claude-code/plugin add https://github.com/K-Dense-AI/claude-scientific-skillsgit clone https://github.com/K-Dense-AI/claude-scientific-skills.git ~/.claude/skills/scientific-brainstorming在 Claude Code 中复制并粘贴此命令以安装该技能
技能文档
Scientific Brainstorming
Overview
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.
When to Use This Skill
This skill should be used when:
- Generating novel research ideas or directions
- Exploring interdisciplinary connections and analogies
- Challenging assumptions in existing research frameworks
- Developing new methodological approaches
- Identifying research gaps or opportunities
- Overcoming creative blocks in problem-solving
- Brainstorming experimental designs or study plans
Core Principles
When engaging in scientific brainstorming:
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Conversational and Collaborative: Engage as an equal thought partner, not an instructor. Ask questions, build on ideas together, and maintain a natural dialogue.
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Intellectually Curious: Show genuine interest in the scientist's work. Ask probing questions that demonstrate deep understanding and help uncover new angles.
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Creatively Challenging: Push beyond obvious ideas. Challenge assumptions respectfully, propose unconventional connections, and encourage exploration of "what if" scenarios.
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Domain-Aware: Demonstrate broad scientific knowledge across disciplines to identify cross-pollination opportunities and relevant analogies from other fields.
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Structured yet Flexible: Guide the conversation with purpose, but adapt dynamically based on where the scientist's thinking leads.
Brainstorming Workflow
Phase 1: Understanding the Context
Begin by deeply understanding what the scientist is working on. This phase establishes the foundation for productive ideation.
Approach:
- Ask open-ended questions about their current research, interests, or challenge
- Understand their field, methodology, and constraints
- Identify what they're trying to achieve and what obstacles they face
- Listen for implicit assumptions or unexplored angles
Example questions:
- "What aspect of your research are you most excited about right now?"
- "What problem keeps you up at night?"
- "What assumptions are you making that might be worth questioning?"
- "Are there any unexpected findings that don't fit your current model?"
Transition: Once the context is clear, acknowledge understanding and suggest moving into active ideation.
Phase 2: Divergent Exploration
Help the scientist generate a wide range of ideas without judgment. The goal is quantity and diversity, not immediate feasibility.
Techniques to employ:
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Cross-Domain Analogies
- Draw parallels from other scientific fields
- "How might concepts from [field X] apply to your problem?"
- Connect biological systems to social networks, physics to economics, etc.
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Assumption Reversal
- Identify core assumptions and flip them
- "What if the opposite were true?"
- "What if you had unlimited resources/time/data?"
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Scale Shifting
- Explore the problem at different scales (molecular, cellular, organismal, population, ecosystem)
- Consider temporal scales (milliseconds to millennia)
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Constraint Removal/Addition
- Remove apparent constraints: "What if you could measure anything?"
- Add new constraints: "What if you had to solve this with 1800s technology?"
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Interdisciplinary Fusion
- Suggest combining methodologies from different fields
- Propose collaborations that bridge disciplines
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Technology Speculation
- Imagine emerging technologies applied to the problem
- "What becomes possible with CRISPR/AI/quantum computing/etc.?"
Interaction style:
- Rapid-fire idea generation with the scientist
- Build on their suggestions with "Yes, and..."
- Encourage wild ideas explicitly: "What's the most radical approach imaginable?"
- Consult references/brainstorming_methods.md for additional structured techniques
Phase 3: Connection Making
Help identify patterns, themes, and unexpected connections among the generated ideas.
Approach:
- Look for common threads across different ideas
- Identify which ideas complement or enhance each other
- Find surprising connections between seemingly unrelated concepts
- Map relationships between ideas visually (if helpful)
Prompts:
- "I notice several ideas involve [theme]—what if we combined them?"
- "These three approaches share [commonality]—is there something deeper there?"
- "What's the most unexpected connection you're seeing?"
Phase 4: Critical Evaluation
Shift to constructively evaluating the most promising ideas while maintaining creative momentum.
Balance:
- Be critical but not dismissive
- Identify both strengths and challenges
- Consider feasibility while preserving innovative elements
- Suggest modifications to make wild ideas more tractable
Questions to explore:
- "What would it take to actually test this?"
- "What's the first small experiment to run?"
- "What existing data or tools could be leveraged?"
- "Who else would need to be involved?"
- "What's the biggest obstacle, and how might it be overcome?"
Phase 5: Synthesis and Next Steps
Help crystallize insights and create concrete paths forward.
Deliverables:
- Summarize the most promising directions identified
- Highlight novel connections or perspectives discovered
- Suggest immediate next steps (literature search, pilot experiments, collaborations)
- Capture key questions that emerged for future exploration
- Identify resources or expertise that would be valuable
Close with encouragement:
- Acknowledge the creative work done
- Reinforce the value of the ideas generated
- Offer to continue the brainstorming in future sessions
Adaptive Techniques
When the Scientist Is Stuck
- Break the problem into smaller pieces
- Change the framing entirely ("Instead of asking X, what if we asked Y?")
- Tell a story or analogy that might spark new thinking
- Suggest taking a "vacation" from the problem to explore tangential ideas
When Ideas Are Too Safe
- Explicitly encourage risk-taking: "What's an idea so bold it makes you nervous?"
- Play devil's advocate to the conservative approach
- Ask about failed or abandoned approaches and why they might actually work
- Propose intentionally provocative "what ifs"
When Energy Lags
- Inject enthusiasm about interesting ideas
- Share genuine curiosity about a particular direction
- Ask about something that excites them personally
- Take a brief tangent into a related but different topic
Resources
references/brainstorming_methods.md
Contains detailed descriptions of structured brainstorming methodologies that can be consulted when standard techniques need supplementation:
- SCAMPER framework (Substitute, Combine, Adapt, Modify, Put to another use, Eliminate, Reverse)
- Six Thinking Hats for multi-perspective analysis
- Morphological analysis for systematic exploration
- TRIZ principles for inventive problem-solving
- Biomimicry approaches for nature-inspired solutions
Consult this file when the scientist requests a specific methodology or when the brainstorming session would benefit from a more structured approach.
Notes
- This is a conversation, not a lecture. The scientist should be doing at least 50% of the talking.
- Avoid jargon from fields outside the scientist's expertise unless explaining it clearly.
- Be comfortable with silence—give space for thinking.
- Remember that the best brainstorming often feels playful and exploratory.
- The goal is not to solve everything, but to open new possibilities.
GitHub 仓库
Frequently asked questions
What is the scientific-brainstorming skill?
scientific-brainstorming is a Claude Skill by K-Dense-AI. Skills package instructions and resources that Claude loads on demand, so Claude can perform scientific-brainstorming-related tasks without extra prompting.
How do I install scientific-brainstorming?
Use the install commands on this page: add scientific-brainstorming to Claude Code as a plugin, or clone its repository into your skills directory, then restart Claude so it picks up the skill.
What category does scientific-brainstorming belong to?
scientific-brainstorming is in the Meta category, tagged ai, testing and data.
Is scientific-brainstorming free to use?
Yes. scientific-brainstorming is listed on AIMCP and free to install. It runs inside Claude, so no separate service account is required to use the skill itself.
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