question-forge

Take a surface question and forge the question actually worth asking — diagnose what's broken in the asked question (smuggled answers, wrong level, false binary, self-protection), transform it, and re

SKILL.md

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Question Forge

Use this skill to reformulate a question rather than answer it. The premise, borrowed from fiction: a great novel doesn't answer "is revenge justified?" — it constructs the version of that question that becomes concrete, costly, and unavoidable. The illumination is in the formulation. Accordingly, this skill's contract inverts the usual one: the output is a question, not an answer.

Purpose

Most questions arrive broken in predictable ways. Answering a broken question efficiently just delivers the asker to the wrong destination faster. This skill diagnoses the break, applies transformations, tests candidates against the standards a dramatist would use, and hands back the forged question — explicitly refusing to answer it.

Procedure

1. Dispatch check (mandatory, first)

If the question is genuinely operational — factual, technical, well-posed ("why is the build failing?", "what's the capital gains rate?") — say the question is fine and answer it normally. Being preciously Socratic about factual questions is this skill's primary failure mode.

2. Diagnose the asked question

Common breaks:

  • Smuggled answer — the question presupposes its conclusion ("isn't it time we...")
  • Wrong level — asks tactics when the problem is values, or values when the problem is tactics
  • False binary — two options presented where the space is wider
  • Displaced subject — asks about the world when it's really about the asker ("should I quit?" is rarely about the job)
  • Wish in question syntax — a complaint or longing wearing a question mark
  • Shield question — a safe question standing guard in front of a harder one nearby

3. Generate reformulations along transformation axes

  • Subject shift — world → self: "should I quit?" → "what am I hoping quitting will fix?"
  • Level shift — up or down the ladder of abstraction
  • Time shift — this decision → the shape of a life; prospective → retrospective ("what will I wish I had asked?")
  • Inversion — "why can't I X?" → "what is not-X-ing accomplishing for me?"
  • Value excavation — "what would have to be true for this to matter?"
  • Dramatization — embody it in a concrete scene with stakes: not "is loyalty owed to institutions?" but "the whistleblower's sister works on the same floor"

4. Test candidates against the dramatist's criteria

A forged question should:

  • Sustain a novel — resist one-line resolution
  • Have live opposition — opposing answers both carry real weight; if one side is obviously right it's a quiz, not a question
  • Implicate the asker — not stay safely third-person
  • Cost something — answering it honestly requires giving something up
  • Stay generative — keep producing thought after you stop looking at it

5. Deliver — and hold the line

Present the forged question. Do not answer it.

Output format

## The question you asked
...

## What it's doing
<the diagnosis: what the question smuggles, protects, or displaces>

## The forged question
**...**

## What changed
<which transformation(s), and why this version has more torque>

## Living with it
<one short paragraph: what it would look like to carry this question for a while, rather than resolve it>

Guardrails

  • One pass. Forge once; do not reformulate the reformulation. No infinite regress.
  • Livable, not a koan. The forged question must be one a person can actually carry and act under — not mystical wordplay.
  • The original deserves respect. Diagnose without condescension; the asked question is the raw material, not an error.
  • Never answer the forged question. If the user wants it answered, they can ask — or pipe it into another skill.

Composition

Works as a preprocessor for the rest of this package: forge the question, then feed the result to dp-solve, decision-matrix, assumption-audit, or parable.

Canonical questions

  • "Should I quit my job?"
  • "Is AI going to take our jobs?"
  • "Was I right to end the relationship?"
  • "What should our company's mission be?"
  • "Why is engagement dropping?" (often forges into: "what did we build this for?")

Poor fits: operational questions (the dispatch check handles these), and questions the user has already carefully formulated — sometimes the question arrives correct.