scientific-brainstorming
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.
npx skills add K-Dense-AI/scientific-agent-skills --skill scientific-brainstorming --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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-de
- Purpose and boundaries
- Operating rules
- Reproducible workflow
- 1. Scope the session
- 2. Diversify perspectives deliberately
- 3. Generate independently
- 4. Share without immediate evaluation
- 5. Cluster structurally
- 6. Define transparent criteria
- 7. Run adversarial review
- 8. Check literature and evidence
- 9. Apply feasibility, rigor, and ethics gates
- 10. Decide and log
- Bias and failure controls
python scripts/session_scaffold.py --help python scripts/validate_register.py --help python scripts/evaluate_matrix.py --help python scripts/session_scaffold.py \ python scripts/validate_register.py session.json --output validation.json python scripts/evaluate_matrix.py scores.csv \
What does the scientific-brainstorming skill do?
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.
How do I install it?
Run `npx skills add K-Dense-AI/scientific-agent-skills --skill scientific-brainstorming --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From K-Dense-AI/scientific-agent-skills, a repository with 32,619 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.