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JTBD methodology for extracting real jobs behind feature requests — job statements, abstraction layers, first-principles extraction, ODI outcome statements, and opportunity scoring

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$ npx -y skills add nWave-ai/nWave --skill nw-jtbd-analysis --agent claude-code

SKILL.md

nw-jtbd-analysis.SKILL.md
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.

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