/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
$ npx -y skills add nWave-ai/nWave --skill nw-jtbd-analysis --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/nw-jtbd-analysis
Context preview
The summary Claude sees to decide when to auto-load this skill.
JTBD methodology for extracting real jobs behind feature requests — job statements, abstraction layers, first-principles extraction, ODI outcome statements, and opportunity scoring
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 — Extract All Three
| 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 | |-------|---------------| | > 12 | Under-served — high opportunity | | 10-12 | Appropriately served — maintain | | < 10 | Over-served — do not invest |
**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 — Extract All Three
| 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 | |-------|---------------| | > 12 | Under-served — high opportunity | | 10-12 | Appropriately served — maintain | | < 10 | Over-served — do not invest |
**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).
Repo: nWave-ai/nWave
Other skills on nwave.
- /nw-ab-critique-dimensions
Review dimensions for validating agent quality - template compliance, safety, testing, and priority validation
Open skill - /nw-abr-critique-dimensions
Review dimensions for validating agent quality - template compliance, safety, testing, and priority validation
Open skill - /nw-ad-critique-dimensions
Review dimensions for acceptance test quality - happy path bias, GWT compliance, business language purity, coverage completeness, walking skeleton user-centricity, priority validation, observable behavior assertions, traceability coverage, and walking skeleton boundary proof
Open skill - /nw-agent-creation-workflow
Detailed 5-phase workflow for creating agents - from requirements analysis through validation and iterative refinement
Open skill - /nw-agent-testing
5-layer testing approach for agent validation including adversarial testing, security validation, and prompt injection resistance
Open skill - /nw-architectural-styles-tradeoffs
Architectural style selection decision matrices, trade-off analysis, structural enforcement rules, and combination patterns. Load when choosing or evaluating architecture styles.
Open skill

