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nw-jtbd-analysis

Extract job statements, abstraction layers, ODI outcomes, and opportunity scoring from feature requests.

Updated Apr 15, 2026
Search Tags:#jobs-to-be-done#jtbd#feature-requests#job-statements#abstraction-layers#odi-outcomes
One-click install
npx skills add https://github.com/StudentCristian/nWave-github --skill nw-jtbd-analysis
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: nw-jtbd-analysis
Source: https://github.com/StudentCristian/nWave-github/tree/main/.github/skills/nw-jtbd-analysis
Command: npx skills add https://github.com/StudentCristian/nWave-github --skill nw-jtbd-analysis

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

JTBD methodology to reveal the real jobs customers are trying to achieve behind feature requests, extracting job statements, abstraction layers, ODI outcomes, and opportunity scoring.

Core Features & Use Cases

  • Extract job statements from user requests to identify underlying needs
  • Map abstraction layers (tactical, operational, strategic, physical) to reach the real job
  • Produce ODI outcome statements and opportunity candidates to guide prioritization

Quick Start

Provide a feature request and have the tool extract the JTBD analysis, including the job statements and ODI outcomes.

Frequently Asked Questions about nw-jtbd-analysis

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

FAQPage Schema
How do I extract underlying jobs from customer feature requests?▼

Jobs-to-be-done analysis reveals underlying jobs by extracting job statements and mapping abstraction layers from feature requests. This translates inbound requests into ODI outcomes and scored opportunities for prioritization.

What are ODI outcome statements and when do I need them?▼

ODI outcome statements define customer needs as measurable desired outcomes. They are needed when translating raw feature requests into structured opportunities to guide product prioritization and opportunity scoring.

How do I map abstraction layers to reach the real customer job?▼

Mapping abstraction layers involves categorizing requests across tactical, operational, strategic, and physical levels to reach the real customer job. This reveals the true motivation behind inbound feature requests and clarifies underlying needs.

Can I use jobs-to-be-done analysis to prioritize inbound product opportunities?▼

Yes, jobs-to-be-done analysis structures inbound feature requests into job statements and ODI outcomes to prioritize opportunities. It provides opportunity scoring guidance to help product teams evaluate and rank real customer jobs.

What is the best way to structure feature requests for JTBD analysis?▼

The best way to structure feature requests for JTBD analysis is providing the raw request to extract job statements, map abstraction layers, and generate ODI outcomes. This structured output reveals underlying jobs and guides opportunity scoring.

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