deep-interview

Name: deep-interview
Availability: InStock
Author: eszxcvfd

Identifies ambiguity in requests through guided Socratic clarification loops with quantitative scoring.

Updated Mar 10, 2026

Search Tags:#planning #specification #requirements #ambiguity #execution #socratic

Ready to run

npx skills add https://github.com/eszxcvfd/ANIZAKI --skill deep-interview-eszxcvfd

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: deep-interview
Source: https://github.com/eszxcvfd/ANIZAKI/tree/main/.agents/skills/deep-interview
Command: npx skills add https://github.com/eszxcvfd/ANIZAKI --skill deep-interview-eszxcvfd

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Deep Interview reduces requirement ambiguity by guiding users through a structured Socratic questioning and scoring process before planning or execution.

Core Features & Use Cases

Socratic clarification loop that asks targeted questions to elicit explicit specs.
Quantitative ambiguity scoring across dimensions (goal, constraints, criteria; context for brownfield).
Phase-based workflow: preflight context, iterative interviews, crystallization of artifacts, and execution-bridge handoff.
Scales from quick to deep inquiries to fit project risk and time constraints.

Quick Start

Start a deep-interview to turn vague ideas into explicit, testable specifications before planning or implementation.

Frequently Asked Questions about deep-interview

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

FAQPage Schema

How do I reduce ambiguity in vague software requirements before planning?▼

A Socratic clarification loop reduces ambiguity in vague requirements by guiding targeted questions to elicit explicit, testable specifications. It quantitatively scores ambiguity across goal, constraints, and criteria dimensions until a target clarity threshold is reached.

What is the best way to turn vague ideas into explicit specifications for execution?▼

The best way to turn vague ideas into explicit specifications is a phased workflow conducting iterative interviews and crystallizing artifacts. This execution-bridge hands off quantified specifications directly to downstream planning or automation tools.

Can I use Socratic questioning for both brownfield and greenfield project specifications?▼

Yes, Socratic questioning applies to broad or underspecified requests across both brownfield and greenfield projects. It gathers preflight context for brownfield environments and conducts phased interviews to extract explicit specifications regardless of project age.

How does quantitative ambiguity scoring work in requirement clarification?▼

Quantitative ambiguity scoring works by measuring vagueness across dimensions like goal, constraints, and criteria. The Socratic loop conducts iterative interview rounds, tracking these scores until a specified target clarity threshold is reached.

Does requirement clarification scale for quick inquiries versus deep project planning?▼

Yes, requirement clarification scales from quick to deep inquiries to fit project risk and time constraints. The Socratic interview loop adjusts its depth, conducting iterative rounds of targeted questions to match the necessary scale for execution handoff.

Why do I need a structured pipeline for software requirement interviews?▼

You need a structured pipeline for software requirement interviews to enforce consistency in extracting explicit specs from vague requests. It mandates preflight context, phased interviews, artifact crystallization, and execution-bridge handoff, preventing underspecified requirements from reaching planning.