kw-question

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Sharpen a vague idea, a literature gap, or a stalled project into a GOOD research question — consequential, specific, falsifiable, feasible — BEFORE committing to a technical route. Produces a structured Question Card, then optionally hands off to /kw-explore to form the technical route. Triggers: "is this a good research question", "help me sharpen my question", "我这个想法值得做吗", "把想法变成研究问题", "问题挖掘 / 具象化", "帮我磨一下研究问题".

chenpg2 By chenpg2 schedule Updated 6/7/2026

name: kw-question description: Sharpen a vague idea, a literature gap, or a stalled project into a GOOD research question — consequential, specific, falsifiable, feasible — BEFORE committing to a technical route. Produces a structured Question Card, then optionally hands off to /kw-explore to form the technical route. Triggers: "is this a good research question", "help me sharpen my question", "我这个想法值得做吗", "把想法变成研究问题", "问题挖掘 / 具象化", "帮我磨一下研究问题".

/kw-question — from a vague idea to a good research question

This is the upstream step. /kw-explore assumes you already have a question worth pursuing and builds the technical route to attack it. /kw-question decides whether the question is worth asking at all, and sharpens it until it is. Run this first when the user has an idea, a gap, or a stalled project — not yet a real question.

Method distilled from public research-craft sources — Alon & Fischbach (problem choice as a trainable skill), Platt's strong inference (rival hypotheses + discriminating tests), Alvesson & Sandberg (challenge hidden assumptions, not just gap-spot), the Heilmeier Catechism (explicit goals/risks/success-failure criteria), Hamming & Nielsen (keep a list of important, attackable problems) — and the synthesis in the good-question project (https://github.com/Rimagination/good-question). Re-expressed here; credit to them.

Outputs go in the user's project (a Question Card markdown). Nothing is written to the knowledge base — a question is not yet a principle.

The bar: a question is "good" only if it has all seven

  1. Stakes — answering it changes theory, method, practice, policy, or the next research step.
  2. Specificity — evidence can directly touch it; it is not a topic.
  3. Rivalry — at least 2-3 competing explanations exist.
  4. Falsifiability — some achievable result could weaken, revise, or kill the claim.
  5. Pilot feasibility — a credible proof-of-concept can start within ~2 weeks (or the user's stated constraint).
  6. Negative learning — even a failed/negative result teaches something (a boundary, a mechanism, a method).
  7. Grounding — claims trace to public sources, or are explicitly labeled as inference (do not invent field consensus).

Workflow

  1. Diagnose the starting point. Classify what the user actually has: a broad interest, a literature gap, a half-formed idea, a draft proposal, or a stalled project. The starting category determines what's missing.
  2. Ground a short domain brief (only if the question is knowledge-dependent and you're unsure). Keep facts (with sources) separate from inference. If the library is linked, kw search the topic to see what mechanisms already exist — but do NOT invent consensus you can't ground.
  3. Diverge — generate candidate questions with structured lenses, e.g.:
    • challenge a hidden assumption the field takes for granted (Alvesson & Sandberg);
    • flip the default / reverse the causal arrow;
    • name the discriminating observation two rival explanations would disagree on (Platt);
    • shrink scope until evidence can touch it; widen until it matters. Produce several variants, not one.
  4. Converge — filter by the seven-point bar. Drop candidates that are only novel, have no audience, cannot fail, or teach nothing when negative.
  5. Rewrite weak forms into real questions. A topic, a method, a benchmark, or "there's a gap in X" is NOT a question. Convert each into a testable proposition.
  6. Editor desk-reject pass. For each survivor, state the single strongest reviewer objection and either fix it or discard the candidate. Be the harsh reviewer, not the cheerleader.
  7. Emit a Question Card for each surviving question.

Question Card → write to <project>/problems/<slug>/QUESTION.md

- Working title:
- The question (1-2 sentences):
- Why it matters (stakes):
- Core assumption challenged:
- Competing hypotheses (2-3):
- Discriminating observation / experiment:
- Falsification conditions (what result kills or revises it):
- Two-week pilot (the cheapest credible proof-of-concept):
- Strongest reviewer objection (+ your answer):
- Best next action:
- Grounding: [sources cited | labeled inference]

If several survive, present them ranked and let the user pick the one to pursue.

Handoff — the user's choice

After the card(s), ask explicitly:

"问题已经磨好了。要用 /kw-explore 把它做成技术路线吗?(映射原则库 → 找缺口 → 补读论文 → 组装带出处的方案。)还是先停在这张卡片?"

  • Yes → invoke /kw-explore. It takes QUESTION.md as its Phase 0 input: skip re-framing the worth of the question (already done here) and go straight to decomposing its structure for library matching.
  • No → stop. The Question Card stands on its own (e.g. for a proposal abstract or a lab discussion).

Never push a question into the technical route the user hasn't chosen to pursue.

Install via CLI
npx skills add https://github.com/chenpg2/kw-engine --skill kw-question
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