ask

name	ask
description	Generate high-leverage questions and clarify missing context. Use for question-generation requests like "what should I ask", "right questions", "what are we missing", "clarify this", and ambiguous requests blocked by unknowns.
license	MIT
tags	["question-generation","clarification","questions"]
metadata	{"author":"Oleg Shulyakov","version":"1.1.0","source":"github.com/olegshulyakov/agent.md","catalog":"utility","category":"collaboration"}

ask

Generate the smallest useful set of questions that would change the next action.

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Workflow

1. Restate the blocked decision or task in one sentence when helpful.
2. Separate known facts from assumptions and missing context.
3. Select the fewest questions that would materially change the next action.
4. Order questions by leverage, dependency, or urgency.
5. Add default assumptions only when they let work proceed despite unanswered questions.

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Output

• Lead with the core gap: name the uncertainty that makes the questions necessary.
• Group only when needed: group questions into categories such as goal, scope, risk, data, owner, acceptance criteria only if they improve scannability.
• Use short lists when useful: prefer three to seven prioritized questions for normal work across all categories.
• Mark blockers: distinguish must-answer questions from nice-to-have questions.
• Include assumptions sparingly: list assumptions only when they affect the question set or proposed next step.

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Boundaries

Scenario: Resolving unknowns Given there are missing facts, constraints, stakeholders, acceptance criteria, data, ownership, risks, or decision criteria Then explicitly surface these gaps as questions

Scenario: Output crosses into action or planning Given the generated output is mainly a recommendation, plan, explanation, or classification Then flag that ask is no longer the right mode And adjust the output to remain question-first And avoid making decisions or producing implementation plans

Scenario: Full questionnaire was not requested Given the user has not explicitly requested a full discovery list Then ask only the few questions likely to affect the next move And do not generate a long, exhaustive questionnaire

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Error Paths

Scenario: Domain is entirely unclear Given there is no clear domain or context for the task Then ask exactly one question about the intended context And do not generate a detailed set of questions until answered

Scenario: Too many unknowns exist to prioritize Given the problem has too many unknowns to ask a concise list Then provide a first-pass discovery set And name what constraints would help refine it

Scenario: User asks for action alongside questions Given the user requests both questions and an action Then answer the question-generation part first And state what action can proceed after the answers are provided

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Verification

Scenario: Output passes quality check Given the question set is generated Then no decorative questions remain (questions whose answer would not change scope, approach, risk, or acceptance) And assumptions are not presented as facts And boundaries are respected (no implicit planning or decision making)