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skills/scientific-brainstorming/SKILL.md

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+---
+name: scientific-brainstorming
+description: "Research ideation partner. Generate hypotheses, explore interdisciplinary connections, challenge assumptions, develop methodologies, identify research gaps, for creative scientific problem-solving."
+---
+
+# 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:
+
+1. **Conversational and Collaborative**: Engage as an equal thought partner, not an instructor. Ask questions, build on ideas together, and maintain a natural dialogue.
+
+2. **Intellectually Curious**: Show genuine interest in the scientist's work. Ask probing questions that demonstrate deep understanding and help uncover new angles.
+
+3. **Creatively Challenging**: Push beyond obvious ideas. Challenge assumptions respectfully, propose unconventional connections, and encourage exploration of "what if" scenarios.
+
+4. **Domain-Aware**: Demonstrate broad scientific knowledge across disciplines to identify cross-pollination opportunities and relevant analogies from other fields.
+
+5. **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:**
+
+1. **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.
+
+2. **Assumption Reversal**
+   - Identify core assumptions and flip them
+   - "What if the opposite were true?"
+   - "What if you had unlimited resources/time/data?"
+
+3. **Scale Shifting**
+   - Explore the problem at different scales (molecular, cellular, organismal, population, ecosystem)
+   - Consider temporal scales (milliseconds to millennia)
+
+4. **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?"
+
+5. **Interdisciplinary Fusion**
+   - Suggest combining methodologies from different fields
+   - Propose collaborations that bridge disciplines
+
+6. **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.

skills/scientific-brainstorming/references/brainstorming_methods.md

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+# Advanced Brainstorming Methodologies
+
+This reference document provides detailed descriptions of structured brainstorming frameworks that can be applied to scientific ideation. Consult these when standard techniques need supplementation or when the scientist requests a specific methodology.
+
+## SCAMPER Framework
+
+SCAMPER is an acronym for seven different ways to approach a problem or idea. Particularly useful for improving existing methods or adapting known techniques.
+
+### Substitute
+- What elements can be replaced? (materials, methods, models, assumptions)
+- What other processes could achieve similar results?
+- What if you used a different organism/system/dataset?
+
+**Scientific applications:**
+- Substitute chemical catalysts with biological enzymes
+- Replace traditional microscopy with super-resolution techniques
+- Use computational models instead of animal models
+
+### Combine
+- What ideas, methods, or technologies can be merged?
+- What collaborations would create synergy?
+- Can you combine data sources or techniques?
+
+**Scientific applications:**
+- Merge genomics with metabolomics for multi-omics analysis
+- Combine machine learning with traditional statistical methods
+- Integrate field observations with laboratory experiments
+
+### Adapt
+- What can be borrowed from other fields?
+- How have others solved similar problems?
+- What analogous systems exist in nature or other disciplines?
+
+**Scientific applications:**
+- Adapt evolutionary algorithms to drug design
+- Use concepts from network theory to understand protein interactions
+- Apply ecological principles to microbiome research
+
+### Modify (Magnify/Minify)
+- What can be amplified, exaggerated, or made more prominent?
+- What can be reduced, simplified, or made more subtle?
+- Change scale, frequency, or magnitude?
+
+**Scientific applications:**
+- Scale up from single cells to populations
+- Miniaturize assays for high-throughput screening
+- Increase temporal resolution of measurements
+- Simplify complex models to essential components
+
+### Put to Another Use
+- What new applications could this serve?
+- Can this be used in a different context?
+- What unexpected applications might exist?
+
+**Scientific applications:**
+- Repurpose existing drugs for new diseases
+- Use industrial waste products as research materials
+- Apply failed experiments' insights to different questions
+
+### Eliminate
+- What can be removed or simplified?
+- What's unnecessary?
+- What if you did less but better?
+
+**Scientific applications:**
+- Remove confounding variables
+- Eliminate expensive reagents or equipment requirements
+- Simplify experimental protocols
+- Remove assumptions to see what's truly necessary
+
+### Reverse/Rearrange
+- What if you worked backwards?
+- Can you invert the process?
+- What if you changed the sequence?
+
+**Scientific applications:**
+- Work backwards from desired outcomes to methods
+- Reverse causality questions (what if the effect causes the cause?)
+- Rearrange experimental order
+- Invert the control and experimental groups conceptually
+
+## Six Thinking Hats
+
+A method for exploring ideas from six distinct perspectives, ensuring comprehensive analysis. Have the scientist metaphorically "wear" different hats to shift thinking modes.
+
+### White Hat (Facts and Information)
+- What data do we have?
+- What information is missing?
+- What facts are known?
+- What measurements exist?
+
+**Usage:** Start here to establish baseline knowledge
+
+### Red Hat (Emotions and Intuition)
+- What's your gut feeling?
+- What excites or worries you?
+- What seems promising intuitively?
+- What emotional responses arise?
+
+**Usage:** Allow intuitive responses without justification
+
+### Black Hat (Critical Judgment)
+- What could go wrong?
+- What are the weaknesses?
+- Why might this fail?
+- What are the risks?
+
+**Usage:** Identify potential problems constructively
+
+### Yellow Hat (Optimistic View)
+- What's the best-case scenario?
+- What are the benefits?
+- Why might this work brilliantly?
+- What value could this create?
+
+**Usage:** Explore positive possibilities fully
+
+### Green Hat (Creativity)
+- What alternatives exist?
+- What wild ideas come to mind?
+- What if anything were possible?
+- What creative solutions emerge?
+
+**Usage:** Generate novel ideas without constraint
+
+### Blue Hat (Process Control)
+- What's the big picture?
+- What have we learned?
+- What should we do next?
+- How do we organize these ideas?
+
+**Usage:** Step back to synthesize and plan
+
+## Morphological Analysis
+
+Systematic exploration of all possible combinations of different dimensions of a problem. Particularly powerful for complex research questions with multiple variables.
+
+### Method:
+1. **Identify key dimensions** of the research question (organism, technique, variable, scale, etc.)
+2. **List options** for each dimension
+3. **Create combinations** systematically
+4. **Evaluate** promising combinations
+
+### Example: Drug Delivery Research
+
+| Dimension | Options |
+|-----------|---------|
+| Carrier | Liposomes, Nanoparticles, Viruses, Exosomes |
+| Target | Brain, Tumor, Liver, Specific cell type |
+| Trigger | pH, Temperature, Light, Enzyme |
+| Cargo | Small molecule, Protein, RNA, DNA |
+
+This creates 4×4×4×4 = 256 possible combinations to explore.
+
+### Scientific applications:
+- Design comprehensive experimental matrices
+- Identify unexplored parameter spaces
+- Systematically consider all methodological options
+- Find unique combinations others haven't tried
+
+## TRIZ (Theory of Inventive Problem Solving)
+
+Originally developed for engineering, TRIZ principles apply remarkably well to scientific challenges. Based on patterns identified across millions of patents.
+
+### Key Concepts:
+
+#### Contradictions
+Identify competing requirements and find principles that resolve them.
+
+**Example contradictions in science:**
+- Need high sensitivity vs. need high specificity
+- Want more data vs. limited resources
+- Need fast results vs. need accuracy
+
+#### Principles for Resolution:
+1. **Segmentation** - Divide into parts, increase modularity
+2. **Taking out** - Remove interfering components
+3. **Local quality** - Optimize each part for its specific function
+4. **Asymmetry** - Break symmetry for advantage
+5. **Merging** - Combine similar operations
+6. **Universality** - Make objects perform multiple functions
+7. **Nesting** - Place objects inside each other
+8. **Counterweight** - Use opposing forces
+9. **Prior action** - Perform changes in advance
+10. **Cushion in advance** - Prepare emergency measures
+
+### Ideal Final Result
+Imagine the perfect solution where the problem solves itself or disappears.
+
+**Questions:**
+- What if the system optimized itself?
+- What if the measurement didn't require intervention?
+- What if the sample prepared itself?
+
+### Use of Resources
+Identify unused resources in the system (waste products, byproducts, available data, existing equipment).
+
+## Biomimicry Approach
+
+Look to nature's 3.8 billion years of R&D for solutions. Particularly powerful in biology, chemistry, materials science, and engineering.
+
+### The Process:
+
+#### 1. Define the Function
+Focus on what you need to accomplish, not how.
+- "I need to transport molecules across a membrane"
+- "I need to sense trace chemicals"
+- "I need to self-assemble structures"
+
+#### 2. Biologize the Question
+Reframe in biological terms:
+- "How does nature move substances across barriers?"
+- "How do organisms detect minute concentrations?"
+- "How do biological systems build themselves?"
+
+#### 3. Discover Natural Models
+Search for organisms that excel at this function:
+- Which species are champions at this?
+- What ecosystems manage this process?
+- What molecular mechanisms exist?
+
+#### 4. Abstract the Strategy
+Identify the underlying principle, not just the literal mechanism:
+- What's the core strategy?
+- What patterns repeat?
+- What universal principles apply?
+
+#### 5. Apply to Your Challenge
+Adapt the natural strategy to your scientific context:
+- How can this principle be implemented?
+- What would be the scientific equivalent?
+- What modifications are needed?
+
+### Scientific Examples:
+- **Gecko feet → Adhesives**: Van der Waals forces in nanoscale structures
+- **Lotus leaf → Self-cleaning surfaces**: Superhydrophobic micro-textures
+- **Firefly bioluminescence → Imaging**: Luciferase reporters
+- **Shark skin → Antibacterial surfaces**: Microscale patterns inhibit bacteria
+- **Octopus camouflage → Adaptive materials**: Responsive color-changing systems
+
+### Nature's Strategies:
+- **Self-assembly**: Components organize without external direction
+- **Adaptation**: Systems adjust to environmental changes
+- **Resilience**: Systems recover from disturbance
+- **Efficiency**: Maximum output for minimum input
+- **Multifunctionality**: One structure serves many purposes
+- **Redundancy**: Backup systems ensure reliability
+
+## Additional Techniques
+
+### Provocation Technique
+Use deliberately absurd or impossible statements to break mental patterns.
+
+**Format**: "Po (Provocation Operation) + [impossible statement]"
+
+**Examples:**
+- Po: The experiment runs itself
+- Po: Results arrive before the experiment
+- Po: The sample tells you what to test
+- Po: Funding is unlimited
+- Po: Time runs backwards
+
+**Then ask:** "What's interesting about this?" and "How could we move toward this?"
+
+### Random Input
+Introduce a completely random word, concept, or image and force connections to the problem.
+
+**Method:**
+1. Select a random noun (use a random word generator or dictionary)
+2. Explore its properties and associations
+3. Force connections to the research question
+4. See what unexpected ideas emerge
+
+**Example:**
+Random word: "Bridge"
+- What bridges are needed in my research? (Between fields? Scales? Concepts?)
+- How can I bridge gaps? (Data gaps? Knowledge gaps?)
+- What acts as a bridge in biological systems?
+
+### Reverse Assumptions
+List fundamental assumptions, then deliberately reverse each one.
+
+**Example in molecular biology:**
+- Assumption: "Proteins fold after translation"
+- Reverse: "What if proteins folded during translation?" → co-translational folding research
+- Assumption: "DNA is the template"
+- Reverse: "What if RNA is the template?" → reverse transcription, RNA world hypothesis
+
+### Future Backwards
+Imagine it's 10 years in the future and the problem has been solved brilliantly. Work backwards to figure out how it happened.
+
+**Questions:**
+- What breakthrough enabled this?
+- What had to happen first?
+- What obstacles were overcome?
+- What unexpected development made it possible?
+
+## Selecting a Method
+
+Choose based on the situation:
+
+- **SCAMPER**: When improving existing methods or adapting known approaches
+- **Six Hats**: When the scientist needs to break out of one thinking mode
+- **Morphological Analysis**: For systematic exploration of complex parameter spaces
+- **TRIZ**: When facing apparent contradictions or impossible requirements
+- **Biomimicry**: When the function exists in nature or biological inspiration is relevant
+- **Provocation**: When completely stuck or thinking is too conventional
+- **Random Input**: When the conversation feels stale or circular
+- **Reverse Assumptions**: When fundamental rethinking is needed
+- **Future Backwards**: When envisioning breakthrough outcomes
+
+## Combining Methods
+
+These methods work powerfully in combination:
+- Use **Six Hats** to approach **SCAMPER** questions from different perspectives
+- Apply **Biomimicry** to find natural solutions, then use **TRIZ** to abstract principles
+- Use **Morphological Analysis** to map the space, then **Random Input** to explore unexpected corners
+- Start with **Reverse Assumptions** to break frames, then **SCAMPER** to build new approaches
+
+## Notes on Application
+
+- Don't announce the method unless the scientist asks—just use it naturally in conversation
+- Methods are tools, not rigid procedures—adapt as needed
+- Sometimes the best approach is no explicit method—just curious questioning
+- Watch for when a method is generating energy vs. when it feels forced
+- Be ready to switch methods if one isn't working