nw-discuss

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Conducts Jobs-to-be-Done analysis, UX journey design, and requirements gathering through interactive discovery. Use when starting feature analysis, defining user stories, or creating acceptance criteria.

AI & Automation 526 stars 55 forks Updated 1 weeks ago MIT

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Skill Content

# NW-DISCUSS: Jobs-to-be-Done Analysis, UX Journey Design, and Requirements Gathering **Wave**: DISCUSS (wave 2 of 6) | **Agent**: Luna (nw-product-owner) | **Command**: `/nw-discuss` ## Overview Execute DISCUSS wave through Luna's integrated workflow: JTBD analysis|UX journey discovery|emotional arc design|shared artifact tracking|requirements gathering|user story creation|acceptance criteria definition. Luna uncovers jobs users accomplish, maps to journeys and requirements, handles complete lifecycle from user motivations through DoR-validated stories ready for DESIGN. Establishes ATDD foundation. For greenfield projects (no src/ code, no docs/feature/ history), Luna proposes Walking Skeleton as Feature 0. ## Interactive Decision Points ### Decision 1: Feature Type **Question**: What type of feature is this? **Options**: 1. User-facing -- UI/UX functionality visible to end users 2. Backend -- APIs, services, data processing 3. Infrastructure -- DevOps, CI/CD, tooling 4. Cross-cutting -- Spans multiple layers (auth, logging, etc.) 5. Other -- user provides custom input ### Decision 2: Walking Skeleton **Question**: Should we start with a walking skeleton? **Options**: 1. Yes -- recommended for greenfield projects 2. Depends -- brownfield; Luna evaluates existing structure first 3. No -- feature is isolated enough to skip ### Decision 3: UX Research Depth **Question**: Priority for UX research depth? **Options**: 1. Lightweight -- quick journey map, focus on happy pat...

Details

Author
nWave-ai
Repository
nWave-ai/nWave
Created
3 months ago
Last Updated
1 weeks ago
Language
Python
License
MIT

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