MaybeMonad Interview Unknowns
Use this skill to ask only the questions that matter. The goal is not to gather all possible preferences; it is to resolve ambiguities that could change the work.
Workflow
- Inspect first when the answer may exist in the repo, docs, screenshots, prior decisions, or runtime behavior.
- List the decisions that are still ambiguous.
- Rank questions by impact:
- Architecture or data shape.
- User-facing behavior.
- Scope boundary.
- Validation and acceptance.
- Taste or copy preference.
- Ask one question at a time when the answer blocks the next step.
- Ask up to 3 grouped questions when the answers are helpful but not blocking.
- After each answer, update the working assumptions and state whether enough is known to proceed.
Question Quality
Good questions:
- Change the implementation path depending on the answer.
- Offer concrete choices when choices are known.
- Explain why the answer matters.
- Avoid asking the user to restate information already available in files.
Poor questions:
- Ask for generic preference without consequence.
- Offload repo inspection to the user.
- Ask many low-impact questions before the high-impact one.
- Hide a recommendation when one option is clearly safer.
Output Shape
When starting an interview, return:
- What I can infer already.
- The next highest-impact question.
- Why the answer changes the work.
- What I will assume if we need to proceed without an answer.
Stop Rule
Stop interviewing when the remaining ambiguity is cheaper to resolve by a prototype, reference read, implementation note, or normal validation.