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Brainstorming research ideas

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Guides researchers through structured ideation frameworks to discover high-impact research directions.

OpenRaiserOpenRaiser
1.5k
26 mai 2026
MIT License
// contenu du skill

name: brainstorming-research-ideas

description: Guides researchers through structured ideation frameworks to discover high-impact research directions. Use when exploring new problem spaces, pivoting between projects, or seeking novel angles on existing work.

version: 1.0.0

author: Orchestra Research

license: MIT

tags: [Research Ideation, Brainstorming, Problem Discovery, Creative Thinking, Research Strategy]

dependencies: []


Research Idea Brainstorming

Structured frameworks for discovering the next research idea. This skill provides ten complementary ideation lenses that help researchers move from vague curiosity to concrete, defensible research proposals. Each framework targets a different cognitive mode—use them individually or combine them for comprehensive exploration.

When to Use This Skill

  • Starting a new research direction and need structured exploration
  • Feeling stuck on a current project and want fresh angles
  • Evaluating whether a half-formed idea has real potential
  • Preparing for a brainstorming session with collaborators
  • Transitioning between research areas and seeking high-leverage entry points
  • Reviewing a field and looking for underexplored gaps

Do NOT use this skill when:

  • You already have a well-defined research question and need execution guidance
  • You need help with experimental design or methodology (use domain-specific skills)
  • You want a literature review (use scientific-skills:literature-review)

Core Ideation Frameworks

1. Problem-First vs. Solution-First Thinking

Research ideas originate from two distinct modes. Knowing which mode you are in prevents a common failure: building solutions that lack real problems, or chasing problems without feasible approaches.

Problem-First (pain point → method):

  • Start with a concrete failure, bottleneck, or unmet need
  • Naturally yields impactful work because the motivation is intrinsic
  • Risk: may converge on incremental fixes rather than paradigm shifts

Solution-First (new capability → application):

  • Start with a new tool, insight, or technique seeking application
  • Often drives breakthroughs by unlocking previously impossible approaches
  • Risk: "hammer looking for a nail"—solution may lack genuine demand

Workflow:

  1. Write down your idea in one sentence
  2. Classify it: Is this problem-first or solution-first?
  3. If problem-first → verify the problem matters (who suffers? how much?)
  4. If solution-first → identify at least two genuine problems it addresses
  5. For either mode, articulate the gap: what cannot be done today that this enables?

Self-Check:

  • [ ] Can I name a specific person or community who needs this?
  • [ ] Is the problem I am solving actually unsolved (not just under-marketed)?
  • [ ] If solution-first, does the solution create new capability or just replicate existing ones?

2. The Abstraction Ladder

Every research problem sits at a particular level of abstraction. Deliberately moving up or down the ladder reveals ideas invisible at your current level.

DirectionActionOutcome
Move Up (generalize)Turn a specific result into a broader principleFramework papers, theoretical contributions
Move Down (instantiate)Test a general paradigm under concrete constraintsEmpirical papers, surprising failure analyses
Move Sideways (analogize)Apply same abstraction level to adjacent domainCross-pollination, transfer papers

Workflow:

  1. State your current research focus in one sentence
  2. Move UP: What is the general principle behind this? What class of problems does this belong to?
  3. Move DOWN: What is the most specific, constrained instance of this? What happens at the extreme?
  4. Move SIDEWAYS: Where else does this pattern appear in a different field?
  5. For each new level, ask: Is this a publishable contribution on its own?

Example:

  • Current: "Improving retrieval accuracy for RAG systems"
  • Up: "What makes context selection effective for any augmented generation system?"
  • Down: "How does retrieval accuracy degrade when documents are adversarially perturbed?"
  • Sideways: "Database query optimization uses similar relevance ranking—what can we borrow?"

3. Tension and Contradiction Hunting

Breakthroughs often come from resolving tensions between widely accepted but seemingly conflicting goals. These contradictions are not bugs—they are the research opportunity.

Common Research Tensions:

Tension PairResearch Opportunity
Performance ↔ EfficiencyCan we match SOTA with 10x less compute?
Privacy ↔ UtilityCan federated/encrypted methods close the accuracy gap?
Generality ↔ SpecializationWhen does fine-tuning beat prompting, and why?
Safety ↔ CapabilityCan alignment improve rather than tax capability?
Interpretability ↔ PerformanceDo mechanistic insights enable better archit
// source originale publique
OpenRaiser/NanoResearch
/skills/vendor-ai-research/brainstorming-research-ideas/SKILL.md
Licence : MIT License
Projet indépendant, non affilié à Anthropic. Ce skill reste la propriété de son auteur original.
// installer ce skill
Collez cette commande dans votre terminal à la racine de votre projet :
mkdir -p .claude/commands && curl -o ".claude/commands/SKILL.md" "https://raw.githubusercontent.com/OpenRaiser/NanoResearch/main/skills/vendor-ai-research/brainstorming-research-ideas/SKILL.md"
Ensuite dans Claude Code, tapez /SKILL pour l'activer.
open_in_newVoir la source originale
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// informations
CréateurOpenRaiser
Étoiles 1.5k
LicenceMIT License
Mis à jour26 mai 2026
Format.md
AccèsGratuit
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