JTBD workflow classification and routing - ODI two-phase framework, five job types with workflow sequences, baseline type selection, workflow anti-patterns, and common recipes
npx skills add https://github.com/nWave-ai/nWave --skill nw-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.
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.
Skip discovery and enter execution loop directly when ALL hold:
If any fail, start with discovery (DISCUSS wave).
> "I need to create something that doesn't exist yet"
[research] -> discuss -> design -> [diagram] -> distill -> baseline -> roadmap -> split -> execute -> review
| Step | Purpose |
|------|---------|
| research | (Optional) Gather domain knowledge before requirements |
| discuss | Gather requirements -- you don't know what's needed yet |
| design | Architecture decisions, technology selection |
| diagram | (Optional) Visualize architecture for stakeholders |
| distill | Define acceptance tests -- what does "done" look like? |
| baseline | Measure starting point for tracking improvement |
| roadmap | Comprehensive plan while context is fresh |
| split | Break into atomic, self-contained tasks |
| execute | Do each task with clean context |
| review | Quality gate before proceeding |
> "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."
> "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.
> "Something is broken and I need to find why"
[research] -> root-why -> develop -> deliver
Minimal sequence -- focused intervention only.
> "I need to gather information before deciding"
research -> [decision point: which job to pursue next]
No execution -- pure information gathering feeding into other jobs.
| Job | You Know What? | Sequence |
|-----|---------------|----------|
| Greenfield | No | [research] -> discuss -> design -> [diagram] -> distill -> baseline -> roadmap -> split -> execute -> review |
| Brownfield | Yes | [research] -> baseline -> roadmap -> split -> execute -> review |
| Refactoring | Partially | [research] -> baseline -> mikado/roadmap -> split -> execute -> review |
| Bug Fix | Yes (symptom) | [research] -> root-why -> develop -> deliver |
| Research | No | research -> (output informs next job) |
Items in [brackets] are optional. Cross-wave commands (usable anytime): research, diagram, root-why, git.
When workflow includes a baseline step, advise on which type to create.
Use when improving speed, reducing resource usage, or optimizing throughput.
Required: timing measurements with breakdown | bottleneck ranking | target metrics with evidence | quick wins identified.
Use when fixing workflow issues, preventing incidents, or improving reliability.
Required: incident references or failure modes | simplest alternatives considered (with why insufficient).
Use when building new capabilities (greenfield or brownfield).
Required: current state analysis | requirements source and validation.
Operate at project/feature level, distinct from story-level anti-patterns in leanux-methodology skill.
| Anti-Pattern | Problem | Solution |
|--------------|---------|----------|
| Skip research | Decisions without evidence | Research when unfamiliar with domain |
| Skip baseline | Optimize the wrong thing | Always baseline before roadmap |
| Monolithic tasks | Context degradation | Use split for atomic tasks |
| Skip review | Quality issues propagate | Review before each execute |
| Architecture before measurement | Over-engineering | Baseline identifies quick wins first |
| Forward references in tasks | Tasks not self-contained | Each task must have all context embedded |
| Situation | Entry Point | Key Characteristic |
|-----------|------------|-------------------|
| New feature on existing codebase | baseline (skip discovery) | Existing system, new capability |
| Performance optimization | baseline (type: performance) | Measurement-first |
| Legacy system modernization | research + root-why + baseline | Deep understanding first |
| Quick bug fix | root-why + develop + deliver | Minimal sequence |
| Pure research task | research | Output informs next job selection |
| Data-heavy project | research + baseline | Specialist agent involvement |
| Category | Core Job |
|----------|----------|
| Understanding | Know what to build and why |
| Planning | Break work into safe, trackable chunks |
| Executing | Do work without context degradation |
| Validating | Catch issues early with quality gates |
| Communicating | Share understanding via diagrams and docs |
| Investigating | Find 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.
Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.
Intelligently organizes your files and folders across your computer by understanding context, finding duplicates, suggesting better structures, and automating cleanup tasks. Reduces cognitive load and keeps your digital workspace tidy without manual effort.
Generates creative domain name ideas for your project and checks availability across multiple TLDs (.com, .io, .dev, .ai, etc.). Saves hours of brainstorming and manual checking.
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
Implements Manus-style file-based planning for complex tasks. Creates task_plan.md, findings.md, and progress.md. Use when starting complex multi-step tasks, research projects, or any task requiring >5 tool calls.
Creative research ideation and exploration. Use for open-ended brainstorming sessions, exploring interdisciplinary connections, challenging assumptions, or identifying research gaps. Best for early-stage research planning when you do not have specific observations yet. For formulating testable hypotheses from data use hypothesis-generation.
Comprehensive GitHub project management with swarm-coordinated issue tracking, project board automation, and sprint planning
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".
Take nwave-ai/nw-jtbd-workflow-selection from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.