/nw-diverge
Generates 3-5 divergent design directions through JTBD analysis, competitive research, structured brainstorming, and taste evaluation before convergence. Use when the team has a validated problem but hasn't chosen a solution approach.
$ npx -y skills add nWave-ai/nWave --skill nw-diverge --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-diverge
Context preview
The summary Claude sees to decide when to auto-load this skill.
Generates 3-5 divergent design directions through JTBD analysis, competitive research, structured brainstorming, and taste evaluation before convergence. Use when the team has a validated problem but hasn't chosen a solution approach.
SKILL.md
nw-diverge.SKILL.mdname: nw-diverge
description: "Generates 3-5 divergent design directions through JTBD analysis, competitive research, structured brainstorming, and taste evaluation before convergence. Use when the team has a validated problem but hasn't chosen a solution approach."
user-invocable: true
argument-hint: '[feature-id] - Optional: --work-type=[new-product|brownfield|pivot]'
NW-DIVERGE: Structured Divergent Thinking Before Convergence
**Wave**: DIVERGE (between DISCOVER and DISCUSS, optional) | **Agent**: Flux (nw-diverger) | **Command**: `/nw-diverge`
Overview
Execute DIVERGE wave through Flux's 4-phase workflow: JTBD analysis|competitive research|structured brainstorming|taste-filtered evaluation. Transforms a validated problem into 3-5 concrete, taste-scored design directions so DISCUSS can converge on one with confidence.
DIVERGE is optional. Brownfield features with a clear direction may skip it (see skip checklist in design spec). New products and pivot decisions benefit most from structured divergence.
Interactive Decision Points
Decision 1: Work Type
**Question**: What type of work is this? **Options**: 1. New product -- no prior solution exists, full divergence needed 2. Brownfield feature -- existing product, exploring approach alternatives 3. Pivot / redesign -- existing feature being reconsidered from scratch 4. Other -- user provides custom context
Decision 2: Research Depth
**Question**: How deep should competitive research go? **Options**: 1. Lightweight -- 3 competitors, known market 2. Comprehensive -- 5+ competitors including non-obvious alternatives 3. Deep-dive -- cross-category research, adjacent markets, academic references
Prior Wave Consultation
Before beginning DIVERGE work, read SSOT and prior wave artifacts:
1. **SSOT** (if `docs/product/` exists):
- `docs/product/jobs.yaml` -- validated jobs and opportunity scores
- `docs/product/vision.md` -- product vision and strategic context
2. **Project context**: `docs/project-brief.md` | `docs/stakeholders.yaml` (if available) 3. **DISCOVER artifacts**: Read `docs/feature/{feature-id}/discover/` (if present)
- `wave-decisions.md` -- validated assumptions and key decisions
- `problem-validation.md` -- customer evidence grounding the problem
**Migration gate**: If `docs/product/` does not exist but `docs/feature/` has existing features, STOP. Guide the user to `docs/guides/migrating-to-ssot-model/README.md` and complete the migration first. If greenfield, DIVERGE will bootstrap `docs/product/jobs.yaml` with the validated job.
**READING ENFORCEMENT**: You MUST read every file listed in Prior Wave Consultation above using the Read tool before proceeding. After reading, output a confirmation checklist. Do NOT skip files that exist -- skipping causes options disconnected from evidence.
Agent Invocation
@nw-diverger
Execute \*diverge for {feature-id}.
**Context Files:** see Prior Wave Consultation above + project context files.
**Configuration:**
- work_type: {Decision 1}
- research_depth: {Decision 2}
- output_directory: docs/feature/{feature-id}/
**SKILL_LOADING**: Before starting work, load your skill files using the Read tool from `~/.claude/skills/nw-{skill-name}/SKILL.md`. Skills encode your methodology -- without them you operate with generic knowledge only.
At the start of execution, create these tasks using TaskCreate and follow them in order:
1. **JTBD Analysis** — Load `jtbd-analysis` skill. Extract and elevate the job from the raw request or DISCOVER evidence. Produce job statements (functional + emotional + social) and ODI outcome statements. Gate: job at strategic or physical level (not tactical), minimum 3 ODI outcome statements produced. 2. **Competitive Research** — Invoke `nw-researcher` sub-agent for evidence-grounded competitive research. Map how existing products serve the validated job. Identify non-obvious alternatives. Gate: 3+ real competitors named, at least one non-obvious alternative, evidence quality confirmed. 3. **Brainstorming** — Load `brainstorming` skill. Frame HMW question, apply SCAMPER lenses, generate structurally diverse options. Gate: 6 options generated with diversity confirmed (mechanism, assumption, and cost structure differ across options). 4. **Taste Evaluation** — Load `taste-evaluation` skill. Apply DVF filter, score surviving options on 4 taste criteria with locked weights, produce weighted ranking and recommendation with dissenting case. Gate: all surviving options scored on all 4 criteria, recommendation traceable to scoring matrix, dissenting case documented. 5. **Peer Review** — Invoke `nw-diverger-reviewer` (Prism) to validate all 5 dimensions. Revise if needed (max 2 iterations). Gate: reviewer approval confirmed, handoff accepted by nw-product-owner.
Success Criteria
- [ ] Job extracted at strategic or physical level (not tactical, not a feature description)
- [ ] Minimum 3 ODI outcome statements produced
- [ ] 3+ real competitors researched, at least one non-obvious alternative
- [ ] 6 structurally diverse options generated (different mechanism, assumption, cost)
- [ ] All surviving options scored on all 4 taste criteria with locked weights
- [ ] Recommendation traceable to scoring matrix (no "feels right" overrides)
- [ ] Dissenting case documented for second-place option
- [ ] Peer review approved by nw-diverger-reviewer
- [ ] Handoff accepted by nw-product-owner (DISCUSS wave)
Next Wave
**Handoff To**: nw-product-owner (DISCUSS wave) **Deliverables**: `recommendation.md` with explicit decision statement + supporting DIVERGE artifacts
Wave Decisions Summary
Before completing DIVERGE, produce (or append to) `docs/feature/{feature-id}/wave-decisions.md`:
# DIVERGE Decisions -- {feature-id}
## Key Decisions
- [D1] {decision}: {rationale} (see: {source-file})
## Job Summary
- Validated job: {job statement at strategic/physical level}
- ODI outcomes: {count} outcome statements
## OptioRead more
name: nw-diverge description: "Generates 3-5 divergent design directions through JTBD analysis, competitive research, structured brainstorming, and taste evaluation before convergence. Use when the team has a validated problem but hasn't chosen a solution approach." user-invocable: true argument-hint: '[feature-id] - Optional: --work-type=[new-product|brownfield|pivot]'
NW-DIVERGE: Structured Divergent Thinking Before Convergence
**Wave**: DIVERGE (between DISCOVER and DISCUSS, optional) | **Agent**: Flux (nw-diverger) | **Command**: `/nw-diverge`
Overview
Execute DIVERGE wave through Flux's 4-phase workflow: JTBD analysis|competitive research|structured brainstorming|taste-filtered evaluation. Transforms a validated problem into 3-5 concrete, taste-scored design directions so DISCUSS can converge on one with confidence.
DIVERGE is optional. Brownfield features with a clear direction may skip it (see skip checklist in design spec). New products and pivot decisions benefit most from structured divergence.
Interactive Decision Points
Decision 1: Work Type
**Question**: What type of work is this? **Options**: 1. New product -- no prior solution exists, full divergence needed 2. Brownfield feature -- existing product, exploring approach alternatives 3. Pivot / redesign -- existing feature being reconsidered from scratch 4. Other -- user provides custom context
Decision 2: Research Depth
**Question**: How deep should competitive research go? **Options**: 1. Lightweight -- 3 competitors, known market 2. Comprehensive -- 5+ competitors including non-obvious alternatives 3. Deep-dive -- cross-category research, adjacent markets, academic references
Prior Wave Consultation
Before beginning DIVERGE work, read SSOT and prior wave artifacts:
1. **SSOT** (if `docs/product/` exists):
- `docs/product/jobs.yaml` -- validated jobs and opportunity scores
- `docs/product/vision.md` -- product vision and strategic context
2. **Project context**: `docs/project-brief.md` | `docs/stakeholders.yaml` (if available) 3. **DISCOVER artifacts**: Read `docs/feature/{feature-id}/discover/` (if present)
- `wave-decisions.md` -- validated assumptions and key decisions
- `problem-validation.md` -- customer evidence grounding the problem
**Migration gate**: If `docs/product/` does not exist but `docs/feature/` has existing features, STOP. Guide the user to `docs/guides/migrating-to-ssot-model/README.md` and complete the migration first. If greenfield, DIVERGE will bootstrap `docs/product/jobs.yaml` with the validated job.
**READING ENFORCEMENT**: You MUST read every file listed in Prior Wave Consultation above using the Read tool before proceeding. After reading, output a confirmation checklist. Do NOT skip files that exist -- skipping causes options disconnected from evidence.
Agent Invocation
@nw-diverger
Execute \*diverge for {feature-id}.
**Context Files:** see Prior Wave Consultation above + project context files.
**Configuration:**
- work_type: {Decision 1}
- research_depth: {Decision 2}
- output_directory: docs/feature/{feature-id}/
**SKILL_LOADING**: Before starting work, load your skill files using the Read tool from `~/.claude/skills/nw-{skill-name}/SKILL.md`. Skills encode your methodology -- without them you operate with generic knowledge only.
At the start of execution, create these tasks using TaskCreate and follow them in order:
1. **JTBD Analysis** — Load `jtbd-analysis` skill. Extract and elevate the job from the raw request or DISCOVER evidence. Produce job statements (functional + emotional + social) and ODI outcome statements. Gate: job at strategic or physical level (not tactical), minimum 3 ODI outcome statements produced. 2. **Competitive Research** — Invoke `nw-researcher` sub-agent for evidence-grounded competitive research. Map how existing products serve the validated job. Identify non-obvious alternatives. Gate: 3+ real competitors named, at least one non-obvious alternative, evidence quality confirmed. 3. **Brainstorming** — Load `brainstorming` skill. Frame HMW question, apply SCAMPER lenses, generate structurally diverse options. Gate: 6 options generated with diversity confirmed (mechanism, assumption, and cost structure differ across options). 4. **Taste Evaluation** — Load `taste-evaluation` skill. Apply DVF filter, score surviving options on 4 taste criteria with locked weights, produce weighted ranking and recommendation with dissenting case. Gate: all surviving options scored on all 4 criteria, recommendation traceable to scoring matrix, dissenting case documented. 5. **Peer Review** — Invoke `nw-diverger-reviewer` (Prism) to validate all 5 dimensions. Revise if needed (max 2 iterations). Gate: reviewer approval confirmed, handoff accepted by nw-product-owner.
Success Criteria
- [ ] Job extracted at strategic or physical level (not tactical, not a feature description)
- [ ] Minimum 3 ODI outcome statements produced
- [ ] 3+ real competitors researched, at least one non-obvious alternative
- [ ] 6 structurally diverse options generated (different mechanism, assumption, cost)
- [ ] All surviving options scored on all 4 taste criteria with locked weights
- [ ] Recommendation traceable to scoring matrix (no "feels right" overrides)
- [ ] Dissenting case documented for second-place option
- [ ] Peer review approved by nw-diverger-reviewer
- [ ] Handoff accepted by nw-product-owner (DISCUSS wave)
Next Wave
**Handoff To**: nw-product-owner (DISCUSS wave) **Deliverables**: `recommendation.md` with explicit decision statement + supporting DIVERGE artifacts
Wave Decisions Summary
Before completing DIVERGE, produce (or append to) `docs/feature/{feature-id}/wave-decisions.md`:
# DIVERGE Decisions -- {feature-id}
## Key Decisions
- [D1] {decision}: {rationale} (see: {source-file})
## Job Summary
- Validated job: {job statement at strategic/physical level}
- ODI outcomes: {count} outcome statements
## OptioAI 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
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