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.
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