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Generate a why-chain exactly n levels deep for any topic, question, observation, problem, or idea. Invoke like `n-whys n=8 q=<my question>`. The general form of five-whys — use this when you want an explicit depth.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | n-whys |
| description | Generate a why-chain exactly n levels deep for any topic, question, observation, problem, or idea. Invoke like `n-whys n=8 q=<my question>`. The general form of five-whys — use this when you want an explicit depth. |
| compatibility | Created for Zo Computer |
| metadata | {"author":"rob.zo.computer"} |
Use this skill when the user invokes n-whys or asks for a why-chain of a specified depth.
Relationship to five-whys: five-whys is a preset of this skill — depth ~5, root-cause orientation, flexible stopping. Use n-whys when the user wants a deliberate, exact depth or an unusually deep chain.
Expected form:
n-whys n=<integer> q=<question or topic>
Examples:
n-whys n=8 q=Why do people procrastinate on work they care about?
n-whys n=4 q=Why is this product hard to explain?
n-whys n=10 q=AI agents feel brittle
n: required integer depth for the chain.q: required question, topic, statement, problem, or observation to analyze.If n or q is missing, ask for the missing argument. If n is very large, proceed unless the user asks for something impractically long; keep each layer concise.
N Whys generalizes the Five Whys. It repeatedly asks "why?" exactly n times to expose deeper causes, assumptions, mechanisms, incentives, constraints, or principles beneath a surface question.
The chain can take several forms depending on the topic:
n and q from the invocation.q as the surface question or topic.n numbered why-layers.## Topic
<q>
## Why chain
1. **Why ...?**
- ...
2. **Why ...?**
- ...
...
N. **Why ...?**
- ...
## Deepest principle
...
## Implications
- ...
n why-layers unless the user changes the request.Compile natural language, a loose composition or pipeline sketch, or an existing program.md into a readable Haskell-esque Sem program that composes this repository's semantic skills. Use when a user asks to express, design, revise, expand, or simplify a semantic program without running it.
Compile and execute natural-language requests, loose semantic pipelines, or existing program.md files as squishy Sem programs. Use when a user invokes $sem-run, asks to run a composition of semantic-algos skills, or wants every semantic function application isolated in a fresh subagent with standalone Markdown artifacts and a linked final result.
Transform a topic, claim, question, or situation into an original joke by leading the audience into one plausible frame and using a concise punchline to reveal a second compatible frame. Use when the user asks for a joke, one-liner, punchline, comedic reframing, roast, or short humorous treatment of an idea.
Transform a question, tension, memory, or belief into an original poem or song lyric whose meaning emerges through voice, imagery, sound, and recurrence rather than explanation. Use when the user asks for a poem, song lyrics, a lyrical treatment of an idea, or a literary form that embodies an emotional contradiction without resolving it.
Solve a problem by systematically importing solutions from other domains: abstract the problem's deep structure, find 3–5 domains that share that structure, study how each solved it, and translate the mechanisms back — with an explicit disanalogy check. Use for 'how do other fields handle this?' and stuck problems that feel like they must have been solved somewhere before.
Structure a choice between concrete options: elicit the real criteria and their weights, score each option honestly, run a sensitivity check on the weights, and separate what the numbers say from what the gut says. Use when choosing between 2–6 named alternatives (jobs, tools, vendors, apartments, strategies).