interview

Generate an interview.md file through adaptive product story interviews.

2|1|Updated Nov 7, 2025
One-click install
npx skills add https://github.com/is-ivanov/rpm-ddd --skill interview-is-ivanov
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: interview
Source: https://github.com/is-ivanov/rpm-ddd/tree/main/.opencode/skills/interview
Command: npx skills add https://github.com/is-ivanov/rpm-ddd --skill interview-is-ivanov

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps teams capture the missing context behind a product story before specification work begins. It replaces vague requirements with a structured interview that uncovers scope, constraints, APIs, decisions, and existing system context needed to produce a useful interview.md file.

Core Features & Use Cases

  • Structured discovery workflow: Reads existing product specs, archived drafts, interviews, code, adapters, and tests before asking questions.
  • Adaptive interviewing: Guides the user through short rounds of relevant questions, skipping unnecessary topics and avoiding duplicate information.
  • Story-ready output: Produces an interview.md file that can feed downstream story, mockup, API specification, and test specification workflows.
  • Use Case: When a product manager or engineer has a story number or rough feature name but not enough detail to write a solid specification, this Skill interviews stakeholders and turns their answers into a grounded context document.

Quick Start

Ask the AI to run the interview skill for a specific story number or story name and answer its follow-up questions to generate interview.md.

Frequently Asked Questions about interview

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

FAQPage Schema
How do I gather requirements for a product story before writing a specification?

Requirements gathering for product stories involves conducting an interactive interview that reads existing specs, code, and tests to ask adaptive questions and compile a structured interview.md file capturing scope, constraints, and context.

How does an interactive interview workflow clarify API planning and scope definition?

An interactive interview workflow clarifies API planning and scope definition by analyzing backend modules and acceptance tests first, then asking targeted questions to extract technical and business constraints into a structured output document.

What is the best way to turn vague feature ideas into actionable product specifications?

Turning vague feature ideas into actionable product specifications is best achieved through an adaptive interview that skips duplicate information and structures stakeholder answers into a story-ready context document.

Do I need existing codebase context and acceptance tests to run a story discovery interview?

Existing codebase context and acceptance tests are not strictly required to run a story discovery interview, but reading archived drafts, backend modules, and tests beforehand allows the workflow to skip unnecessary topics and avoid duplicate information.

Can I use an interview.md file to feed downstream mockup and test specification workflows?

Yes, an interview.md file can feed downstream mockup, API specification, and test specification workflows because the output captures the technical and business constraints needed to produce useful story specifications.