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Nw jtbd workflow selection

Skill nWave-ai/nWave/plugins/nw/skills/nw-jtbd-workflow-selection

AI agents that guide you from idea to working code, with you in control at every step.

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npx -y skills add nWave-ai/nWave --skill nw-jtbd-workflow-selection

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JTBD workflow classification and routing - ODI two-phase framework, five job types with workflow sequences, baseline type selection, workflow anti-patterns, and common recipes

SKILL.md

6.8 KB, ~1.4k tokens by cl100k_base, as published. Nobody here has run it

JTBD Workflow Selection

Classify incoming work by job type and recommend the appropriate nWave workflow entry point. Use during Phase 1 (GATHER) to triage before crafting stories.

ODI Two-Phase Framework

Determine which phase applies before proceeding.

Phase 1: Discovery -- when you do not know what to build

[research] --> discuss --> design --> distill
    |            |           |          |
GATHER        WHAT are    HOW should  WHAT does
evidence      the needs?  it work?    "done" look like?

Phase 2: Execution Loop -- when you know what needs to change

[research] --> baseline --> roadmap --> split --> execute --> review
    |            |            |           |          |          |
GATHER        MEASURE      PLAN it     BREAK it   DO each    CHECK
evidence      first        completely  into atoms  task       quality
                                          |
                              <-----------+ (loop per task)

Key insight: research is a cross-wave capability invocable at any point for evidence-based decisions.

When to Skip Discovery

Skip discovery and enter execution loop directly when ALL hold:

  • User already understands the problem domain
  • Problem is identified and scoped
  • No stakeholder alignment needed
  • User can articulate what "done" looks like

If any fail, start with discovery (DISCUSS wave).

Five Job Types

Job 1: Build Something New (Greenfield)

"I need to create something that doesn't exist yet"

[research] -> discuss -> design -> [diagram] -> distill -> baseline -> roadmap -> split -> execute -> review
StepPurpose
research(Optional) Gather domain knowledge before requirements
discussGather requirements -- you don't know what's needed yet
designArchitecture decisions, technology selection
diagram(Optional) Visualize architecture for stakeholders
distillDefine acceptance tests -- what does "done" look like?
baselineMeasure starting point for tracking improvement
roadmapComprehensive plan while context is fresh
splitBreak into atomic, self-contained tasks
executeDo each task with clean context
reviewQuality gate before proceeding

Job 2: Improve Existing System (Brownfield)

"I know what needs to change in our system"

[research] -> baseline -> roadmap -> split -> execute -> review (repeat)

Skip discovery: system understood and problem identified. Baseline is blocking gate -- measure current state before planning. Prevents "optimizing the wrong thing."

Job 3: Complex Refactoring

"Code works but structure needs improvement"

Simple refactoring:

[root-why] -> mikado -> refactor (incremental)

Complex refactoring with tracking:

[research] -> baseline -> roadmap (methodology: mikado) -> split -> execute -> review

Mikado Method explores dependencies before committing. Reversible at every step.

Job 4: Investigate and Fix Issue

"Something is broken and I need to find why"

[research] -> root-why -> develop -> deliver

Minimal sequence -- focused intervention only.

Job 5: Research and Understand

"I need to gather information before deciding"

research -> [decision point: which job to pursue next]

No execution -- pure information gathering feeding into other jobs.

Quick Reference Matrix

JobYou Know What?Sequence
GreenfieldNo[research] -> discuss -> design -> [diagram] -> distill -> baseline -> roadmap -> split -> execute -> review
BrownfieldYes[research] -> baseline -> roadmap -> split -> execute -> review
RefactoringPartially[research] -> baseline -> mikado/roadmap -> split -> execute -> review
Bug FixYes (symptom)[research] -> root-why -> develop -> deliver
ResearchNoresearch -> (output informs next job)

Items in [brackets] are optional. Cross-wave commands (usable anytime): research, diagram, root-why, git.

Baseline Type Selection

When workflow includes a baseline step, advise on which type to create.

Performance Optimization

Use when improving speed, reducing resource usage, or optimizing throughput. Required: timing measurements with breakdown | bottleneck ranking | target metrics with evidence | quick wins identified.

Process Improvement

Use when fixing workflow issues, preventing incidents, or improving reliability. Required: incident references or failure modes | simplest alternatives considered (with why insufficient).

Feature Development

Use when building new capabilities (greenfield or brownfield). Required: current state analysis | requirements source and validation.

Workflow Anti-Patterns

Operate at project/feature level, distinct from story-level anti-patterns in leanux-methodology skill.

Anti-PatternProblemSolution
Skip researchDecisions without evidenceResearch when unfamiliar with domain
Skip baselineOptimize the wrong thingAlways baseline before roadmap
Monolithic tasksContext degradationUse split for atomic tasks
Skip reviewQuality issues propagateReview before each execute
Architecture before measurementOver-engineeringBaseline identifies quick wins first
Forward references in tasksTasks not self-containedEach task must have all context embedded

Common Workflow Recipes

SituationEntry PointKey Characteristic
New feature on existing codebasebaseline (skip discovery)Existing system, new capability
Performance optimizationbaseline (type: performance)Measurement-first
Legacy system modernizationresearch + root-why + baselineDeep understanding first
Quick bug fixroot-why + develop + deliverMinimal sequence
Pure research taskresearchOutput informs next job selection
Data-heavy projectresearch + baselineSpecialist agent involvement

Job Categories Summary

CategoryCore Job
UnderstandingKnow what to build and why
PlanningBreak work into safe, trackable chunks
ExecutingDo work without context degradation
ValidatingCatch issues early with quality gates
CommunicatingShare understanding via diagrams and docs
InvestigatingFind truth before acting

For deep opportunity analysis with ODI scoring, defer to product-discoverer agent. Product-owner applies simpler prioritization (MoSCoW, Value/Effort) for story-level ordering -- see leanux-methodology skill.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 0 of the 12 instructions most automation workflows skills give in ~1.4k tokens

Counted across 745 of the 1,008 authors here whose files we hold, read 2026-08-07

  • Write conventional commit messagesin 36 of 745, across 35 files
  • Delete branches after mergein 30 of 745, across 21 files
  • Make atomic commitsin 25 of 745, across 15 files
  • Write minimal code to pass testsin 22 of 745, across 10 files
  • Re-snapshot after navigation or DOM changesin 21 of 745, across 13 files
  • Use try-catch for error handlingin 20 of 745, across 8 files
  • Run tests before committingin 20 of 745, across 12 files
  • Write tests before implementationin 20 of 745, across 8 files
  • Configure branch protection rulesin 19 of 745, across 5 files
  • Explain the why in commit messagesin 19 of 745, across 9 files
  • Refactor code while tests remain greenin 19 of 745, across 6 files
  • Interact with elements using refsin 19 of 745, across 11 files

Said here and by no other author read

  • classify incoming work by job type
  • determine the applicable phase before proceeding
  • skip discovery only if all criteria are met
  • recommend the appropriate workflow entry point
  • advise on which baseline type to create
  • create a baseline before planning

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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