Helps transform a vague research interest into a concrete, tractable research question. Use when asked to refine a research idea, develop a research question, scope a research project, or figure out what to work on. Walks through systematic refinement with feasibility analysis.
Transforms vague research interests into concrete, tractable questions through systematic refinement and feasibility analysis.
/plugin marketplace add GhostScientist/skills/plugin install ghostscientist-documentation-skills@GhostScientist/skillsThis skill inherits all available tools. When active, it can use any tool Claude has access to.
Transform "I'm interested in X" into "I will investigate whether Y under conditions Z, measuring W."
Most research ideas fail not because they're bad, but because they're:
This skill fixes that.
Start by understanding what's actually pulling at you:
Questions to ask:
Output: A paragraph capturing the raw interest, unfiltered.
Before scoping, understand the landscape:
What's Known:
What's Unknown:
What's Controversial:
Output: A structured map with citations/references for each area.
A good research question lives in a gap that is:
| Property | Too Little | Just Right | Too Much |
|---|---|---|---|
| Novelty | Redoing existing work | New angle or combination | No foundation to build on |
| Difficulty | Trivial to answer | Challenging but doable | Requires breakthroughs |
| Impact | No one cares | Community would update beliefs | Nobel prize (unrealistic) |
| Scope | One experiment | Thesis chapter / paper | Multiple PhDs |
Gap-finding questions:
Output: 3-5 candidate gaps, each as one sentence.
For each candidate gap, sharpen into a question:
The Formula:
[Action verb] + [specific phenomenon] + [under conditions] + [measurable outcome]
Examples of refinement:
❌ Vague: "How can we make transformers more efficient?" ✅ Concrete: "Does structured sparsity in attention patterns preserve performance on long-context tasks while reducing compute by >50%?"
❌ Vague: "Can robots learn from humans better?" ✅ Concrete: "Does incorporating gaze direction in demonstrations improve sample efficiency for manipulation tasks compared to kinesthetic teaching alone?"
❌ Vague: "What makes language models hallucinate?" ✅ Concrete: "Do retrieval-augmented models hallucinate less on factual questions when retrieval confidence is used to modulate generation temperature?"
For each refined question, assess:
Resources Required:
Risk Assessment:
Dependencies:
A good research question passes all of these:
The Advisor Test:
"If I pitched this in 2 minutes, would a busy professor say 'yes, go do that' rather than 'hmm, let's talk more'?"
The Paper Test:
"Can I envision the title, abstract, and figure 1 of the resulting paper?"
The Null Result Test:
"If my hypothesis is wrong, would that still be interesting to report?"
The Motivation Test:
"Am I actually excited to work on this for 6+ months?"
The Explanation Test:
"Can I explain why this matters to a smart non-expert in 60 seconds?"
Deliver a Research Question Brief:
# Research Question Brief
## The Interest (Raw)
[Original unfiltered interest]
## Territory Map
### What's Known
- [Point 1] ([citation])
- [Point 2] ([citation])
### What's Unknown
- [Open question 1]
- [Open question 2]
### What's Controversial
- [Debate 1]
## Candidate Gaps
1. [Gap 1]
2. [Gap 2]
3. [Gap 3]
## Refined Questions
### Question 1: [Title]
**Statement:** [Precise question]
**Hypothesis:** [What you expect to find]
**Feasibility:** [Brief assessment]
**If it works:** [Impact]
**If it doesn't:** [What we still learn]
### Question 2: [Title]
[Same structure]
## Recommendation
[Which question to pursue and why]
## Immediate Next Steps
1. [Concrete action 1]
2. [Concrete action 2]
3. [Concrete action 3]
The Kitchen Sink: Trying to answer too many questions at once → Fix: Ruthlessly cut until there's ONE core question
The Solution in Search of a Problem: Starting with a method, not a question → Fix: Ask "Who has this problem? Why hasn't it been solved?"
The Incremental Trap: Small delta on existing work → Fix: Ask "Would this change how people think?"
The Impossible Dream: Beautiful question, can't be answered → Fix: Ask "What's the minimal version that's still interesting?"
The Boring Sure Thing: Will definitely work, nobody cares → Fix: Add ambition until there's meaningful risk
This skill should be used when the user asks about libraries, frameworks, API references, or needs code examples. Activates for setup questions, code generation involving libraries, or mentions of specific frameworks like React, Vue, Next.js, Prisma, Supabase, etc.