About this skill

Problem

When users have vague goals, complex decisions, or missing constraints, direct answers can miss the actual intent. An AI-guided questioning skill helps turn a single prompt into an ordered sequence of questions, so the model can confirm boundaries before proposing a solution.

How It Works

This skill is positioned for AI-agent scenarios. Its focus is not business execution, but structuring questioning behavior:
- identify the current information gaps, such as goal, constraints, priorities, and failure criteria
- ask a small number of concrete, answerable questions instead of generic prompts
- follow up based on user responses and build context
- when enough information exists, prompt the model to give a conclusion or next step

Boundaries

The provided material only identifies it as a large-model skill. It does not document APIs, benchmarks, or domain plugins. Use it for dialogue strategy and requirement clarification, not as a substitute for domain knowledge, external tool calls, or workflow orchestration.

Screenshots

Use Cases

When a PM receives a vague request, confirm goals, constraints, and acceptance criteria before solutioning.
When handling vague support tickets, confirm account, time, and failure behavior to reduce misdiagnosis.
Before escalating a technical ticket, follow up on version, repro steps, and impact scope.
When reviewing survey interviews, turn scattered answers into comparable question lists.

Best For

Support leads who need to turn vague user complaints into actionable ticket facts
Engineers who need to fill in cross-team constraints before design reviews
Product or ops staff who need to turn scattered interview answers into structured questions
Documentation engineers who need to confirm real user workflows before writing guides