Back to AI Tools & Agents

Scientific Brainstorming

researchideationscientific-methodproblem-solvingbrainstorming
4.7 (72)28.1k📄 MIT🕒 2026-06-16Source ↗

Install this skill

npx skills add davila7/claude-code-templates

Works across Claude Code, Cursor, Codex, Copilot & Antigravity

What this skill does

  • Generates and stress-tests scientific hypotheses
  • Maps cross-domain analogies to solve domain-specific problems
  • Systematically deconstructs core research assumptions
  • Scales research problems across temporal and physical dimensions
  • Evaluates the feasibility of experimental designs

When to use it

  • You are stuck on a specific research problem and need new angles
  • You want to combine two distinct scientific fields to find a novel solution
  • You need to sanity-check your experimental assumptions
  • You are planning a study and need to identify potential methodology gaps

When not to use it

  • You need a final, peer-reviewed conclusion or verified experimental data
  • The task requires actual physical lab work or empirical observation
  • You are performing administrative tasks unrelated to research ideation

How to invoke it

Example prompts that trigger this skill:

  • Help me brainstorm alternative hypotheses for my current research on [topic].
  • I'm hitting a wall with [methodology]; let's apply assumption reversal to find a new path.
  • Can you help me identify potential research gaps in the context of [field]?
  • What analogies from [field A] might help explain the phenomenon I'm seeing in [field B]?
  • Let's challenge the core assumptions of my current study design.

Example workflow

  1. Provide the agent with a brief overview of your current research context and specific goals.
  2. Engage in a divergent exploration phase to generate a high volume of radical, constraint-free ideas.
  3. Apply techniques like scale-shifting or interdisciplinary mapping to refine specific concepts.
  4. Identify common themes or patterns that emerged across the initial brainstorming threads.
  5. Transition to the critical evaluation phase to assess feasibility and prioritize the strongest research directions.

Pitfalls & limitations

  • !The agent may occasionally hallucinate scientific jargon if the research domain is extremely niche.
  • !It can produce too many ideas if the scope is not narrowed early in the session.
  • !The output requires human expertise to validate feasibility against real-world constraints.

FAQ

Is this skill meant to replace my own subject matter expertise?
No, it acts as a collaborator to help you surface new perspectives. You must evaluate all ideas based on your own domain knowledge.
Can it suggest specific lab equipment or materials?
It can suggest methodologies or categories of tools, but it cannot guarantee the availability or appropriateness of physical equipment for your specific environment.
How does it handle highly specialized, unpublished data?
The agent operates on the information you provide in the chat. The more context you provide about your proprietary findings, the more tailored its suggestions will be.

How it compares

Generic prompts often result in surface-level feedback; this skill forces a systematic, multi-phase methodology that mimics professional research brainstorming sessions.

Source & trust

28k stars📄 MIT🕒 Updated 2026-06-16🛡 no risky patterns found

From the source: “# 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 cr…”

View the full SKILL.md source

# 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.

Quoted from davila7/claude-code-templates for reference — see the original for the authoritative, latest version.

📄 Full skill instructions — original source: davila7/claude-code-templates
Scientific Brainstorming transforms an AI agent into a rigorous research collaborator. This skill facilitates deep-thinking sessions focused on hypothesis generation, cross-disciplinary synthesis, and systematic challenge of established research assumptions. It moves beyond standard ideation by employing structured techniques such as assumption reversal, scale shifting, and analogical reasoning across different scientific domains. Whether a researcher is navigating a creative block or attempting to bridge gaps in a complex study plan, this skill provides a logical framework for exploring unconventional paths while maintaining high intellectual standards. By acting as a critical thought partner, the agent encourages users to test the boundaries of their methodologies and identify overlooked connections. It serves professional scientists, academic researchers, and technical innovators who require a systematic, conversational partner to refine their experimental designs and broaden their investigative scope.

How to Use This Skill Unit

Option A: Project-Specific (Recommended)

  1. Click "Download" above
  2. In your project, create the directory: .agent/skills/scientific-brainstorming/
  3. Save the file as SKILL.md
  4. The agent will automatically discover the skill based on its description.

Option B: Global Installation (All Agents)

Save the file to these locations to make it available across all projects:

  • Claude Code: ~/.claude/skills/davila7/claude-code-templates/scientific-brainstorming/SKILL.md
  • Cursor: ~/.cursor/skills/davila7/claude-code-templates/scientific-brainstorming/SKILL.md
  • Antigravity: ~/.gemini/antigravity/skills/davila7/claude-code-templates/scientific-brainstorming/SKILL.md

🚀 Install with CLI:
npx skills add davila7/claude-code-templates

Read the Master Guide: Mastering Agent Skills

Recommended Rules

View more rules

Recommended Workflows

View more workflows

Recommended MCP Servers

View more MCP servers

Take It Further

Maximize your productivity with these powerful resources

📋

Define Your Standards

Set up coding standards to ensure this workflow produces consistent, high-quality results.

Browse Rules Library
📖

Master Workflows

Learn how to create custom workflows, use Turbo Mode, and build your automation library.

Complete Guide

How to use this Skill in Claude Code & Cursor

For Claude Code (CLI)

To use this skill in Claude Code, copy the rule content into your project's custom instructions or follow our Add-Skill CLI guide. This ensures Claude follows your standards during every code generation.

For Cursor & Windsurf

For Cursor or Windsurf, individual skills are best used in the "Rules for AI" section. This specific unit helps the agent avoid ai tools & agents issues, leading to cleaner, more efficient code.

Why the skill format matters: the standardized Agent Skills format lets your AI agent load detailed instructions only when they are relevant, keeping your prompt clean while improving results.

Source & attribution

This skill is categorized under AI Tools & Agents and is published by davila7, maintained in davila7/claude-code-templates.

← Browse All Agent Skills
Sponsored AI assistant. Recommendations may be paid.