alterlab-scientific-brainstorm

$npx mdskill add AlterLab-IEU/AlterLab-Academic-Skills/alterlab-scientific-brainstorm

Generates novel research ideas through creative brainstorming and interdisciplinary exploration.

  • Solves open-ended ideation for early-stage research planning without specific observations.
  • Optionally uses WebFetch or WebSearch to find cross-disciplinary analogies or gaps.
  • Decides based on conversational prompts, user input, and optionally fetched web content.
  • Delivers conversational guidance and structured idea suggestions to the user.

SKILL.md

.github/skills/alterlab-scientific-brainstormView on GitHub ↗
---
name: alterlab-scientific-brainstorm
description: Creative research ideation and exploration for open-ended brainstorming, surfacing interdisciplinary connections, challenging assumptions, and identifying research gaps. Use when starting early-stage research planning with no specific observations yet — for open-ended brainstorming sessions, exploring cross-disciplinary connections, or finding gaps. For formulating testable hypotheses from observations or data use hypothesis-gen; for grading evidence or spotting design flaws use scientific-thinking. Part of the AlterLab Academic Skills suite.
license: MIT
allowed-tools: Read WebFetch WebSearch
compatibility: No API key required. Guidance-focused, conversational skill; optionally uses WebFetch/WebSearch to pull cross-disciplinary analogies or check whether a research gap is already covered.
metadata:
    skill-author: AlterLab
    version: "1.0.0"
---

# 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.

More from AlterLab-IEU/AlterLab-Academic-Skills

SkillDescription
alterlab-abm-mesaBuilds agent-based models of social systems with Mesa 3 — the current AgentSet API (model.agents.shuffle_do('step'), auto-assigned unique_id, mandatory super().__init__(seed=...)), cell spaces (mesa.discrete_space OrthogonalMooreGrid / classic mesa.space grids), the DataCollector, batch_run parameter sweeps, and SolaraViz — for emergence, segregation, diffusion, opinion dynamics, and cooperation models. It uses the Mesa 3.x API (the old mesa.time schedulers like RandomActivation are removed) and treats the model as a generative theory to be validated, not just run. Use when the request mentions an agent-based model, Mesa, simulating interacting agents, or emergent macro behavior from micro rules. For discrete-event (queueing/process) simulation prefer alterlab-simpy; for reinforcement learning prefer alterlab-stable-baselines3. Part of the AlterLab Academic Skills suite.
alterlab-academic-careerPrepares academic career documents and professional-development materials for faculty and researchers. Use when drafting academic CVs, research statements, teaching philosophies, diversity statements, faculty-position cover letters, tenure dossiers, promotion narratives, academic portfolios, or mentorship statements, and when planning conference-networking strategy, building academic web presence, setting up ORCID profiles, or understanding impact metrics. Part of the AlterLab Academic Skills suite.
alterlab-accreditation-aolScaffolds program-level Assurance-of-Learning (AoL) documentation for AACSB (2020 Standard 5) and ABET (Criterion 3 Student Outcomes, Criterion 4 Continuous Improvement) accreditation — program learning outcomes / competency goals, curriculum-to-outcome mapping matrices, direct- and indirect-assessment plans, rubric design, and closing-the-loop continuous-improvement narratives — and validates the structure of an outcome-mapping matrix with scripts/aol_matrix.py. Use when the user needs AACSB or ABET assurance-of-learning material, a program-learning-outcomes set, a curriculum/outcome map or coverage matrix, a direct/indirect assessment plan, a closing-the-loop report, or accreditation self-study text. For single-course design or course rubrics prefer alterlab-teaching-design; for post-award grant reports prefer alterlab-grant-reporting. Part of the AlterLab Academic Skills suite.
alterlab-adaptyvSubmits and tracks protein-testing experiments on the Adaptyv Bio Foundry cloud lab (wet-lab validation), and optimizes protein sequences before submission with computational tools (NetSolP, SoluProt, SolubleMPNN, ESM). Use when designing proteins that need wet-lab validation - binding/affinity screening, expression testing, thermostability, or fluorescence assays - or when submitting experiments to the Foundry API, browsing the target catalog, tracking experiment status, retrieving results, or pre-screening sequences for solubility/expression. Triggers on "Adaptyv", "Foundry API", "cloud lab", "biolayer interferometry / BLI", "wet-lab validation". Part of the AlterLab Academic Skills suite.
alterlab-aeonRuns time series machine learning with the aeon library — classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search via scikit-learn compatible APIs. Use when working with temporal data, sequential patterns, or time-indexed observations (univariate or multivariate) that need specialized algorithms beyond standard ML approaches. Part of the AlterLab Academic Skills suite.
alterlab-akademik-tesvikComputes the annual Turkish academic-incentive (akademik teşvik) score for Devlet (state) university öğretim elemanı (academic staff) from a classified activity list, applying the verified Akademik Teşvik Ödeneği Yönetmeliği (2018/11834) Faaliyet Hesaplama Tablosu headline puanları (Proje 20, Araştırma 15, Yayın 30, Patent 30, Atıf 30, Tebliğ 20, Ödül 20) with the k (author-count), p (Q1 1/Q2 0.8/Q3 0.5/Q4 0.25), and r (project-role) coefficients via türü puanı = Σ(faaliyet oranları) × headline (MADDE 8/2), then enforcing the per-type headline ceilings, the 100 cap (MADDE 8/3), and the net-30 payment gate (MADDE 10/3) in a deterministic scripts/tesvik_score.py. Use when the user wants to calculate akademik teşvik puanı, check the en az 30 (net-30) threshold, apply TABLO 4 ceilings, or estimate teşvik eligibility; keeps its coefficients separate from doçentlik scoring. For doçentlik point eligibility prefer alterlab-docentlik-eligibility. Part of the AlterLab Academic Skills suite.
alterlab-alpha-vantageAccesses real-time and historical stock market data, forex rates, cryptocurrency prices, commodities, economic indicators, and 50+ technical indicators via the Alpha Vantage API (requires a free API key from alphavantage.co). Use when fetching stock prices (OHLCV), company fundamentals (income statement, balance sheet, cash flow), earnings, options data, market news/sentiment, insider transactions, GDP, CPI, treasury yields, gold/silver/oil prices, Bitcoin/crypto prices, forex exchange rates, or calculating technical indicators (SMA, EMA, MACD, RSI, Bollinger Bands). Part of the AlterLab Academic Skills suite.
alterlab-alphafoldPredict protein 3D structures with AlphaFold2 via ColabFold — MMseqs2-accelerated MSAs, monomer and AlphaFold2-Multimer complex folding, and confidence-based validation (pLDDT, pTM/ipTM, PAE). Use when folding a protein sequence or complex from FASTA, generating a predicted structure with confidence metrics, ranking models, or checking self-consistency of a design. For co-folding a protein WITH a small-molecule ligand or predicting binding affinity prefer alterlab-boltz; for antibody–antigen or one-FASTA multi-entity complexes prefer alterlab-chai; to LOOK UP an already-computed structure prefer alterlab-alphafold-db; for ESM embeddings or inverse folding prefer alterlab-esm. Part of the AlterLab Academic Skills suite.
alterlab-alphafold-dbAccess the AlphaFold DB of 200M+ AI-PREDICTED protein structures — retrieve models by UniProt accession, download PDB/mmCIF files, and analyze prediction confidence metrics (pLDDT, PAE). Use when a UniProt ID needs a computationally predicted 3D structure or when no experimental structure exists, for homology modeling, protein engineering, or structure-based drug discovery; for EXPERIMENTALLY determined structures (X-ray, cryo-EM, NMR) prefer alterlab-pdb, and for protein sequences, annotations, or accession ID mapping prefer alterlab-uniprot instead. Part of the AlterLab Academic Skills suite.
alterlab-anndataBuild, slice, concatenate, read, and write AnnData annotated data matrices (obs, var, X, layers, obsm, uns) — the scverse data STRUCTURE, not an analysis pipeline. Use when creating or wrangling .h5ad/zarr files, managing cell and gene annotations, concatenating batches, or handling layers/obsm/backed-mode; for the QC, normalization, clustering, UMAP, and differential-expression analysis pipeline prefer alterlab-scanpy instead, and for RNA velocity from spliced/unspliced layers prefer alterlab-scvelo instead. Part of the AlterLab Academic Skills suite.