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Agents51k · #1969

scientific-brainstorming

Helps your agent generate and discuss scientific ideas in a structured way. It evaluates ideas based on evidence. It's useful for researchers in the early stages of projects to explore new directions.

What it does

Helps brainstorm new scientific research ideas, organizing and evaluating them transparently. It's useful for starting research or prioritizing directions.

When to use it

  • ✓When you have a scientific question and want to explore possible answers.
  • ✓When deciding which research idea is most promising to investigate.
  • ✓To challenge and improve existing ideas based on evidence.

Example of what to ask your AI

“What are potential approaches to understanding the impact of climate change on bird migration, considering current evidence?”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/K-Dense-AI/scientific-agent-skills/blob/main/skills/scientific-brainstorming/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/K-Dense-AI/scientific-agent-skills/blob/main/skills/scientific-brainstorming/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

The AI helps generate ideas independently, then organizes and evaluates them based on defined criteria. It ensures all opinions are considered and decisions are transparent.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add K-Dense-AI/scientific-agent-skills --skill scientific-brainstorming

Or download just the file:

curl -L https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/main/skills/scientific-brainstorming/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

Scientific Brainstorming

Purpose and boundaries

Use this skill to create, organize, challenge, and transparently prioritize candidate research directions. Treat every output as a proposal, not a finding. Creativity methods can alter participation and idea yield, but no method universally improves originality, usefulness, or scientific validity. The evidence base and its limits are summarized in references/sources.md.

Keep these activities separate:

  • Ideation creates questions, mechanisms, alternatives, or study concepts.
  • Evidence assessment checks what reliable literature and data support.
  • Hypothesis validation requires observations, predictions, suitable designs, analyses, and independent scrutiny; brainstorming cannot validate a hypothesis.
  • Ethics, biosafety, dual-use, regulatory, and institutional review require the relevant authorized reviewers. A brainstorm is never approval.
  • Clinical advice requires qualified clinicians and patient-specific context. Do not turn research ideas into diagnosis or treatment guidance.

For an observation-led testable hypothesis, hand off to hypothesis-generation. For study architecture, use experimental-design; for sample size, statistical-power; for existing evidence, literature-review; and for analysis, statistical-analysis.

Operating rules

  1. Label claims as idea, assumption, prediction, located evidence, or decision. Never blur these categories.
  2. Generate independently before exposing participants to other people's or AI-generated ideas. Face-to-face turn-taking can block production, and examples can anchor later output.
  3. Preserve minority views, negative evidence, uncertainty, and abstentions. Consensus is not truth and vote counts are not effect sizes.
  4. Record provenance without exposing confidential, personal, controlled, or unpublished information.
  5. Define evaluation criteria and directions before scoring. Keep raw ratings, reasons, ranges, and disagreement visible.
  6. Search the literature after an initial independent round when practical, then deliberately reopen ideation. This reduces early anchoring without mistaking an incomplete search for a research gap.
  7. Do not automatically select a “winner.” Scores are traceable decision aids; qualitative judgment, uncertainty, feasibility, and ethics gates remain controlling.

Reproducible workflow

1. Scope the session

Write one focal question and record:

  • purpose, audience, decision owner, and time horizon;
  • in-scope and out-of-scope topics;
  • constraints that are real, assumed, negotiable, or unknown;
  • current knowledge, unresolved observations, and prohibited outputs;
  • whether human participants, animals, clinical care, sensitive data, pathogens, controlled technologies, or environmental release could be implicated.

If the request seeks patient-specific care, evasion of oversight, harmful optimization, or operationally enabling dual-use details, stop ideation and route to the appropriate professional or institutional process.

2. Diversify perspectives deliberately

Invite relevant methodological, domain, implementation, statistical, safety, ethics, stakeholder, and lived-experience perspectives. Diversity is not a guarantee of creativity: explain whose perspective is represented, missing, or structurally disadvantaged. Use accessible participation modes and pseudonymous participant IDs where appropriate.

The facilitator should disclose conflicts, avoid offering a preferred answer first, prevent senior members from dominating, and ask leaders to contribute after the independent round.

3. Generate independently

Give everyone the same neutral prompt, constraints, and fixed time window. Participants write ideas privately and in parallel before discussion. For each idea, capture:

  • a stable ID and one-sentence statement;
  • contributor ID(s) and stage (independent, discussion, or post-check);
  • origin (human, AI-assisted, literature-inspired, mixed, or other);
  • assumptions, predicted observations, uncertainties, and possible disconfirming evidence;
  • source identifiers for literature-inspired ideas and tool/purpose disclosure for AI assistance.

Do not show example solutions before this round unless examples are necessary; if they are, record them as potential anchors.

4. Share without immediate evaluation

…

FAQ

What does 'evidence-aware' mean?

It means the generated ideas consider what is already known (scientific evidence) and also acknowledge the limits of that knowledge.

Can I use this to validate a scientific hypothesis?

No. This tool is for generating and organizing ideas. Actual hypothesis validation requires specific experiments and analyses, which are handled by other tools or experts.

Will the AI choose the best idea for me?

The AI helps organize and evaluate ideas based on criteria you define, but the final decision on which path to take is still yours, considering all factors.

Details

Original description by the author

Facilitates evidence-aware scientific ideation with independent generation, structured discussion, explicit assumptions, transparent evaluation, adversarial review, and decision logs. Use for early-stage research brainstorming or prioritizing candidate directions; hand off empirical validation, study design, ethics or regulatory review, and clinical questions to appropriate experts or skills.

repo: K-Dense-AI/scientific-agent-skills

Popularity

GitHub stars
51k
Ranking position
#1969
License
MIT
Updated
10/15/2026

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