Skill 详情
brainstorming-research-ideas
Strong brainstorming workflow, but limited to research ideation.
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SKILL.md
这段内容是审核时保存的快照。外部来源才是完整且最新的版本。
--- 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. | Direction | Action | Outcome | |-----------|--------|---------| | **Move Up** (generalize) | Turn a specific result into a broader principle | Framework papers, theoretical contributions | | **Move Down** (instantiate) | Test a general paradigm under concrete constraints | Empirical papers, surprising failure analyses | | **Move Sideways** (analogize) | Apply same abstraction level to adjacent domain | Cross-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"在 GitHub 阅读完整来源 (打开外部页面)