research-question
Skill17 starsChanged 3 months agoMITView on GitHub
Interrogates a paper idea with six forcing questions — contribution, audience, identification, falsifiability, feasibility, scoop risk — and issues a green/yellow/red verdict. Use when the user pitches a new paper, asks whether a project is worth pursuing, or wants a research question pressure-tested before committing.
6 other projects use a version of this.
Adopted by
Most recently taken up by
- kinhluan/skillstheir own version, first seen Nov 8, 2026
- 1second1/personal-research-skillstheir own version, first seen Oct 7, 2026
- cellrishi-code/claude-skills-atlastheir own version, first seen Oct 4, 2026
- deanmikan/ai-native-company-startertheir own version, first seen Sep 4, 2026
- crfldrxyz/AuthorOps-Skillstheir own version, first seen Sep 1, 2026
- KhaledSaeed18/dotclaudetheir own version, first seen Jul 4, 2026
Other versions6 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 6
- cellrishi-code/claude-skills-atlas★ 6same name
- kinhluan/skills★ 6same name
- KhaledSaeed18/dotclaude★ 5same name
- 1second1/personal-research-skills★ 1same name
- crfldrxyz/AuthorOps-Skills★ 0same name
- deanmikan/ai-native-company-starter★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository38 other files it gives its agents.
- abstract-shotgunSkill
- analyzeSkill
- archiveSkill
- carefulSkill
- coauthor-reviewSkill
- codebookSkill
- cover-letterSkill
- data-acquireSkill
- data-cleanSkill
- design-researchSkill
- draft-sectionSkill
- freezeSkill
- guardSkill
- hypothesis-designSkill
- idea-shotgunSkill
- identification-reviewSkill
- journal-fitSkill
- learnSkill
- lit-mapSkill
- llm-checklistSkill
- mstack-initSkill
- mstack-upgradeSkill
- paper-statusSkill
- pdf-ingestSkill
- power-analysisSkill
- preregisterSkill
- r-and-rSkill
- referee-mockSkill
- results-auditSkill
- retroSkill
- robustnessSkill
- scope-challengeSkill
- submission-packSkill
- survey-buildSkill
- theory-buildSkill
- title-shotgunSkill
- unfreezeSkill
- vizSkill
The file
We split this skill into the rules it gives an agent
3 rules. 0 are common, 3 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 6 edited versions we read keep these.
3
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 33
Do not soften the verdict.
- Distinctive: line 43
Answering for the user: If they cannot answer, that is the signal.
- Distinctive: line 44
Skipping questions: All six, in order.
“Common” is measured: kept by at least 6 in 10 of the 6 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
/mstack:research-question
Stage: ideate · Voice: advisor
An interrogation, not a brainstorm: these are the questions that, asked at month six, become reasons to abandon a project. Do not encourage before the answers are in.
Procedure
Ask the six questions and wait for answers. In a live session ask one at a time, offering the option to answer all six in one message; in an asynchronous context (web/mobile, or a user who is clearly batching) present all six together rather than forcing six round-trips.
- Contribution in one sentence. "If this paper succeeds, what one sentence does it add to the literature?" Reject "contributes to our understanding of X"; push for a specific, falsifiable claim.
- Audience and venue. "Who reads this, and which journal or community is it pitched to?" "It could go anywhere" is a red flag: papers that fit everywhere fit nowhere.
- Identification. "What quantity are you estimating, for whom, and how do you separate it from the obvious confounders?" If observational and the answer is "controls," press for a placebo, instrument, discontinuity, or quasi-experiment; if the answer names a design, ask which assumption it needs and whether the data can test it. "I'll figure it out" means defer the project until the design is concrete.
- Falsifiability. "What pattern in the data would make you abandon the hypothesis?" No answer means the hypothesis will be unfalsifiable on the page too.
- Feasibility. "What is the longest pole (data access, computation, fieldwork, IRB), how long, and what is plan B?" Ask for a concrete timeline.
- Scoop risk. "Has anyone done this in the last 3 years? Is anyone visibly working on it?" Evidence, not "I haven't seen it": SSRN, NBER, and CEPR working papers; OSF and EGAP registrations; APSA, MPSA, EPSA, IPES, and PolMeth programs; NSF award abstracts; the recent volumes of the target journals.
Verdict, written with the answers and date to .mstack/research-question.md:
- Green — all six substantive. Proceed to
/mstack:lit-map. - Yellow — identification or scoop risk weak. Address the weak link explicitly, then proceed.
- Red — two or more answers vague or unsubstantiated. Defer until the gaps close, or run
/mstack:idea-shotgunfor a different angle on the same data.
Do not soften the verdict; if the answers do not justify the project, say so.
Outputs
.mstack/research-question.md— questions, answers, verdict, date.- Summary block: verdict + next step.
Anti-patterns
- Encouragement before interrogation.
- Answering for the user. If they cannot answer, that is the signal.
- Skipping questions. All six, in order.
Next
Green → /mstack:lit-map. Yellow → fix the weak link, re-run. Red → /mstack:idea-shotgun, or /mstack:scope-challenge if the project may simply be too big.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

