/nw-jtbd-analysis
JTBD methodology for extracting real jobs behind feature requests — job statements, abstraction layers, first-principles extraction, ODI outcome statements, and opportunity scoring
Claude Code
$ npx -y skills add nWave-ai/nWave --skill nw-jtbd-analysis --agent claude-code
Codex
$ npx skills add nWave-ai/nWave --skill nw-jtbd-analysis -a codex -y
Cursor
$ npx skills add nWave-ai/nWave --skill nw-jtbd-analysis -a cursor -y
Gemini CLI
$ npx skills add nWave-ai/nWave --skill nw-jtbd-analysis -a gemini-cli -y
GitHub Copilot
$ npx skills add nWave-ai/nWave --skill nw-jtbd-analysis -a github-copilot -y
OpenCode
$ npx skills add nWave-ai/nWave --skill nw-jtbd-analysis -a opencode -y
Windsurf
$ npx skills add nWave-ai/nWave --skill nw-jtbd-analysis -a windsurf -y
SKILL.md
nw-jtbd-analysis.SKILL.mdname: nw-jtbd-analysis
description: JTBD methodology for extracting real jobs behind feature requests — job statements, abstraction layers, first-principles extraction, ODI outcome statements, and opportunity scoring
user-invocable: false
disable-model-invocation: true
JTBD Analysis
Core Principle
A job is the progress a person is trying to make in a particular circumstance. Jobs are stable over time — technology changes, jobs don't. People hire products to make progress; they fire them when they fail.
**The trap**: Feature requests describe a proposed solution, not the underlying job. Always extract the job first.
---
Job Statement Format
When [situation/trigger], I want to [motivation/action], so I can [expected outcome]
**Examples (good)**:
- "When I'm hosting a virtual networking event, I want to facilitate natural conversations between strangers, so I can create valuable connections that wouldn't happen otherwise."
- "When I join an event as a participant, I want to quickly find relevant people to talk to, so I can maximize the value of my limited time."
---
Job Types — Explore Where Evidenced
Use supplied evidence for each job type. Label proposals and open questions explicitly; emotional and social claims require the human's own account, never inferred feelings or confirmed choices.
| Type | Question | Example | |------|----------|---------| | Functional | What task is the user trying to accomplish? | Find someone with complementary expertise | | Emotional | How does the user want to feel? | Feel confident approaching strangers | | Social | How does the user want to be perceived? | Appear professional and well-connected |
---
Abstraction Layers — Navigate to the Real Job
Jobs usually live at strategic or physical level, not tactical.
| Layer | Question | Example | |-------|----------|---------| | Tactical | How do we improve this interaction? | Better drag-and-drop for notes | | Operational | Why does this workflow exist? | Why do we need a facilitator? | | Strategic | What decision is being pursued? | How do we reduce direction uncertainty? | | Physical | What's the irreducible function? | Input → Synthesis → Convergence |
**Navigation rules**:
- Use "why?" to move up layers
- Use "how?" to move down layers
- Stop when further "why?" produces a life-goal answer
---
First-Principles Extraction — 3-Step Inversion
When a feature request is presented as a job, apply this:
1. **Identify the Activity** — What visible action is the user performing?
- e.g., "User brainstorms on a whiteboard"
2. **Reject the Activity as the Job** — Does anyone wake up wanting to do this activity?
- "Nobody wakes up wanting to brainstorm" → the job is deeper
3. **Strip to Irreducible Function** — What remains if all tools and methods are removed?
- e.g., "Reduce uncertainty via input-synthesis-convergence"
**Disruption check**: Is there a higher-level job that would make this entire job unnecessary?
---
ODI Outcome Statements — Measurable Success Criteria
Format: `[Direction] + [Metric] + [Object] + [Context]`
**Direction**: Always "Minimize" (95% of time). "Maximize" only when more is genuinely better.
**Metrics priority**: 1. `the time it takes to` — speed/efficiency (preferred) 2. `the likelihood of` — avoiding occurrences 3. `the likelihood that` — avoiding results 4. `the number of` — quantity reduction 5. `the effort required to` — ease
**Good vs bad examples**:
| Bad | Problem | Good | |-----|---------|------| | "I want easy video calls" | Ambiguous + solution | "Minimize the time it takes to start a conversation with a specific person" | | "Manage my network effectively" | Vague verb + ambiguous | "Minimize the time it takes to identify who can help with a specific need" | | "Use breakout rooms to talk privately" | Solution embedded | "Minimize the likelihood of conversations being overheard by unintended parties" | | "Don't miss important people" | Negative framing | "Minimize the likelihood of failing to connect with relevant attendees" |
**Forbidden words**: easy, reliable, good, better, effective, efficient, manage, handle, deal with. **Forbidden patterns**: solution references ("using AI", "via the app"), compound statements with "and"/"or", demographics.
---
Opportunity Scoring
Formula: `Score = Importance + Max(0, Importance - Satisfaction)`
Where Importance and Satisfaction are surveyed 1-10.
| Score | Interpretation | |-------|---------------| | 15-20 | Extremely under-served — highest opportunity | | >12 and <15 | Under-served — high opportunity | | 10-12 inclusive | Appropriately served — maintain | | <10 | Over-served — do not invest |
These are the canonical bands in `nw-jtbd-opportunity-scoring`; DISCOVER's >8 eligibility threshold is a different decision, not a served-status classification.
**Output format per opportunity**:
| Outcome | Importance | Satisfaction | Score | Status |
|---------|------------|--------------|-------|--------|
| Minimize time to find relevant attendees | 9.2 | 4.1 | 14.3 | Under-served |
---
DIVERGE Output for JTBD Phase
Produce `docs/feature/{feature-id}/diverge/job-analysis.md` with:
1. **Raw request** — verbatim feature/problem statement received 2. **Job extraction** — 5 Why chain from tactical to physical/strategic level 3. **Job statements** — functional (required) + emotional + social (if identifiable) 4. **Disruption check** — Is there a higher-level job this entire job is serving? 5. **Outcome statements** — 3-6 measurable ODI-format statements 6. **Opportunity candidates** — Which outcomes appear most under-served?
**Gate**: Job must be at strategic or physical abstraction level. Tactical-level jobs are not acceptable input for brainstorming — elevate first.
Read more
name: nw-jtbd-analysis description: JTBD methodology for extracting real jobs behind feature requests — job statements, abstraction layers, first-principles extraction, ODI outcome statements, and opportunity scoring user-invocable: false disable-model-invocation: true
JTBD Analysis
Core Principle
A job is the progress a person is trying to make in a particular circumstance. Jobs are stable over time — technology changes, jobs don't. People hire products to make progress; they fire them when they fail.
**The trap**: Feature requests describe a proposed solution, not the underlying job. Always extract the job first.
---
Job Statement Format
When [situation/trigger], I want to [motivation/action], so I can [expected outcome]
**Examples (good)**:
- "When I'm hosting a virtual networking event, I want to facilitate natural conversations between strangers, so I can create valuable connections that wouldn't happen otherwise."
- "When I join an event as a participant, I want to quickly find relevant people to talk to, so I can maximize the value of my limited time."
---
Job Types — Explore Where Evidenced
Use supplied evidence for each job type. Label proposals and open questions explicitly; emotional and social claims require the human's own account, never inferred feelings or confirmed choices.
| Type | Question | Example | |------|----------|---------| | Functional | What task is the user trying to accomplish? | Find someone with complementary expertise | | Emotional | How does the user want to feel? | Feel confident approaching strangers | | Social | How does the user want to be perceived? | Appear professional and well-connected |
---
Abstraction Layers — Navigate to the Real Job
Jobs usually live at strategic or physical level, not tactical.
| Layer | Question | Example | |-------|----------|---------| | Tactical | How do we improve this interaction? | Better drag-and-drop for notes | | Operational | Why does this workflow exist? | Why do we need a facilitator? | | Strategic | What decision is being pursued? | How do we reduce direction uncertainty? | | Physical | What's the irreducible function? | Input → Synthesis → Convergence |
**Navigation rules**:
- Use "why?" to move up layers
- Use "how?" to move down layers
- Stop when further "why?" produces a life-goal answer
---
First-Principles Extraction — 3-Step Inversion
When a feature request is presented as a job, apply this:
1. **Identify the Activity** — What visible action is the user performing?
- e.g., "User brainstorms on a whiteboard"
2. **Reject the Activity as the Job** — Does anyone wake up wanting to do this activity?
- "Nobody wakes up wanting to brainstorm" → the job is deeper
3. **Strip to Irreducible Function** — What remains if all tools and methods are removed?
- e.g., "Reduce uncertainty via input-synthesis-convergence"
**Disruption check**: Is there a higher-level job that would make this entire job unnecessary?
---
ODI Outcome Statements — Measurable Success Criteria
Format: `[Direction] + [Metric] + [Object] + [Context]`
**Direction**: Always "Minimize" (95% of time). "Maximize" only when more is genuinely better.
**Metrics priority**: 1. `the time it takes to` — speed/efficiency (preferred) 2. `the likelihood of` — avoiding occurrences 3. `the likelihood that` — avoiding results 4. `the number of` — quantity reduction 5. `the effort required to` — ease
**Good vs bad examples**:
| Bad | Problem | Good | |-----|---------|------| | "I want easy video calls" | Ambiguous + solution | "Minimize the time it takes to start a conversation with a specific person" | | "Manage my network effectively" | Vague verb + ambiguous | "Minimize the time it takes to identify who can help with a specific need" | | "Use breakout rooms to talk privately" | Solution embedded | "Minimize the likelihood of conversations being overheard by unintended parties" | | "Don't miss important people" | Negative framing | "Minimize the likelihood of failing to connect with relevant attendees" |
**Forbidden words**: easy, reliable, good, better, effective, efficient, manage, handle, deal with. **Forbidden patterns**: solution references ("using AI", "via the app"), compound statements with "and"/"or", demographics.
---
Opportunity Scoring
Formula: `Score = Importance + Max(0, Importance - Satisfaction)`
Where Importance and Satisfaction are surveyed 1-10.
| Score | Interpretation | |-------|---------------| | 15-20 | Extremely under-served — highest opportunity | | >12 and <15 | Under-served — high opportunity | | 10-12 inclusive | Appropriately served — maintain | | <10 | Over-served — do not invest |
These are the canonical bands in `nw-jtbd-opportunity-scoring`; DISCOVER's >8 eligibility threshold is a different decision, not a served-status classification.
**Output format per opportunity**:
| Outcome | Importance | Satisfaction | Score | Status | |---------|------------|--------------|-------|--------| | Minimize time to find relevant attendees | 9.2 | 4.1 | 14.3 | Under-served |
---
DIVERGE Output for JTBD Phase
Produce `docs/feature/{feature-id}/diverge/job-analysis.md` with:
1. **Raw request** — verbatim feature/problem statement received 2. **Job extraction** — 5 Why chain from tactical to physical/strategic level 3. **Job statements** — functional (required) + emotional + social (if identifiable) 4. **Disruption check** — Is there a higher-level job this entire job is serving? 5. **Outcome statements** — 3-6 measurable ODI-format statements 6. **Opportunity candidates** — Which outcomes appear most under-served?
**Gate**: Job must be at strategic or physical abstraction level. Tactical-level jobs are not acceptable input for brainstorming — elevate first.
AI agents that guide you from idea to working code, with human judgment at every gate. nWave runs inside Claude Code. It breaks feature delivery into seven waves (discover, diverge, discuss, design, devops, distill, deliver).
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brainstorming
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Questions about nw-jtbd-analysis.
- Which coding agents can use nw-jtbd-analysis?
- nw-jtbd-analysis installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.

