Research ideation partner for generating hypotheses, exploring interdisciplinary connections, and developing novel methodologies.
Works with
Engages as a collaborative thought partner through five-phase workflow: understanding context, divergent exploration, connection making, critical evaluation, and synthesis
Employs cross-domain analogies, assumption reversal, scale shifting, constraint manipulation, and technology speculation to generate diverse ideas
Includes adaptive techniques for unstic
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionscientific-brainstormingExecute the skills CLI command in your project's root directory to begin installation:
Fetches scientific-brainstorming from davila7/claude-code-templates and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate scientific-brainstorming. Access via /scientific-brainstorming in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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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.
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
davila7/claude-code-templates
davila7/claude-code-templates
davila7/claude-code-templates
davila7/claude-code-templates
davila7/claude-code-templates
davila7/claude-code-templates
scientific-brainstorming reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend scientific-brainstorming for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in scientific-brainstorming — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
scientific-brainstorming reduced setup friction for our internal harness; good balance of opinion and flexibility.
We added scientific-brainstorming from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
scientific-brainstorming fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Registry listing for scientific-brainstorming matched our evaluation — installs cleanly and behaves as described in the markdown.
scientific-brainstorming has been reliable in day-to-day use. Documentation quality is above average for community skills.
scientific-brainstorming is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in scientific-brainstorming — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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