interview

Clarify ambiguous task scope with batched AskUserQuestion prompts.

28|3|Updated Mar 27, 2026
One-click install
npx skills add https://github.com/mifunedev/openharness --skill interview-mifunedev
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: interview
Source: https://github.com/mifunedev/openharness/tree/main/.claude/skills/interview
Command: npx skills add https://github.com/mifunedev/openharness --skill interview-mifunedev

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Adaptive pre-work clarifier. Picks 2–4 task-specific questions via AskUserQuestion, echoes a brief scope summary, then proceeds. Refuses for trivial tasks.

Core Features & Use Cases

  • Batched, task-specific questioning via AskUserQuestion to resolve ambiguity before work.
  • Generates a concise 2–3 sentence scope brief reflecting user answers.
  • Honors a memory protocol to log outcomes and iterations for auditing.

Quick Start

Invoke the interview skill with a task description to start clarifying scope.

Frequently Asked Questions about interview

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I clarify task scope and resolve ambiguity before starting product management work?

Clarifying task scope requires identifying underspecified goals or constraints and resolving them through targeted questions. This skill batches 2–4 task-specific questions via AskUserQuestion to eliminate ambiguity before proceeding with non-trivial work.

When should I ask clarifying questions to define project requirements before execution?

You should ask clarifying questions to define project requirements when the prompt's goal, inputs, or constraints are unclear, underspecified, or require explicit pre-work alignment. Trivial tasks are automatically refused to avoid unnecessary questioning.

What is the best way to align on task scope without overwhelming the user with questions?

Aligning on task scope is best achieved by batching 2–4 task-specific questions together rather than asking them sequentially. This method efficiently resolves ambiguity and generates a concise 2–3 sentence scope brief reflecting the chosen direction.

How do I log scope decisions and task analysis outcomes for auditing?

Logging scope decisions utilizes a built-in memory protocol that records the decision flow, outcomes, and iterations during task analysis. This ensures safe, scoped execution and provides an audit trail for future reference.

Does this guided interview approach work for trivial tasks and simple requests?

This guided interview approach does not work for trivial tasks, as the skill explicitly refuses to process them. It is designed solely for non-trivial scenarios where pre-work alignment is necessary to ensure safe and scoped execution.

How can I summarize the agreed scope before an AI agent starts working on a task?

Summarizing the agreed scope happens automatically after you answer the clarifying questions. The skill echoes a brief 2–3 sentence scope brief reflecting your answers, ensuring alignment before it proceeds to the next task.