plugins/nw/skills/nw-persona-jtbd-analysis/SKILL.md
Structured persona creation and JTBD analysis methodology - persona templates, ODI job step tables, pain point mapping, success metric quantification, and multi-persona segmentation
npx skillsauth add nwave-ai/nwave nw-persona-jtbd-analysisInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Use during Phase 1 (GATHER) when the user lacks clear personas or the "Who" section needs rigorous definition. Provides structured alternative to ad-hoc persona descriptions.
For each user type, build a complete persona:
## Persona: {Name}
**Who**: {Role description -- one sentence capturing relationship to product}
**Demographics**:
- {Characteristic 1: e.g., technical proficiency level}
- {Characteristic 2: e.g., frequency of interaction}
- {Characteristic 3: e.g., environment/context of use}
- {Characteristic 4: e.g., primary motivation}
**Jobs-to-be-Done**: (see Job Step Table below)
**Pain Points**:
- {Pain 1} -- maps to Job Step: {step name}
- {Pain 2} -- maps to Job Step: {step name}
**Success Metrics**:
- {Quantified outcome 1: e.g., "Task completed in < 2 minutes"}
- {Quantified outcome 2: e.g., "Zero manual configuration steps"}
Each persona has job steps describing what they accomplish. Steps follow ODI format.
| Job Step | Goal | Desired Outcome | |----------|------|-----------------| | {Verb} | {What the user wants to achieve} | Minimize {metric} of {undesirable state} |
| Job Step | Goal | Desired Outcome | |----------|------|-----------------| | Discover | Find the right tool for the task | Minimize time to evaluate fit | | Install | Get the tool running locally | Minimize steps to working state | | Configure | Adapt to local environment | Minimize likelihood of misconfiguration | | Verify | Confirm correct installation | Minimize uncertainty about readiness | | Start | Begin productive work | Minimize time from install to first output |
Every pain point maps to a specific job step. Pain points without a corresponding step indicate either a missing step or irrelevant pain point.
Pain Point: "I don't know if the tool supports my OS"
-> Job Step: Discover
-> Desired Outcome: Minimize uncertainty about compatibility
Pain Point: "Installation fails silently with no error message"
-> Job Step: Install
-> Desired Outcome: Minimize time to diagnose installation failures
Prioritize: pain points on high-frequency job steps deserve attention first.
Every success metric needs a number or threshold. Qualitative metrics ("easy to use") are not actionable.
| Qualitative | Quantified | |-------------|-----------| | "Easy to install" | "Install completed in < 2 minutes with zero manual steps" | | "Fast startup" | "First productive output within 30 seconds of launch" | | "Reliable" | "Zero silent failures; all errors produce actionable messages" | | "Intuitive" | "New user completes core task without reading documentation" |
Different users have fundamentally different jobs even when using the same product. Segment by relationship to the product.
Common axes: Frequency (first-time vs returning vs power user) | Role (end user vs admin vs developer) | Context (individual vs team vs CI/CD) | Motivation (exploration vs production vs evaluation)
| Persona | Primary Job | Key Difference | |---------|-------------|----------------| | Explorer | Evaluate the tool quickly | Needs fast time-to-value, minimal commitment | | Returner | Resume work after absence | Needs state preservation, quick re-orientation | | Deployer | Install for a team | Needs configuration management, multi-user setup | | Automator | Integrate into CI/CD pipeline | Needs scriptability, headless operation, exit codes |
Each persona gets their own Job Step table because workflows differ. Do not merge personas -- JTBD analysis value comes from surfacing differences.
After completing persona analysis, feed results into LeanUX user story template:
Cross-reference: use bdd-requirements skill for Example Mapping once personas established. Use jtbd-workflow-selection skill to determine workflow for resulting stories.
testing
Acceptance test creation methodology for the DISTILL wave. Domain knowledge for the acceptance designer agent: port-to-port principle, prior wave reading, wave-decision reconciliation, graceful degradation, and document back-propagation.
development
Cross-agent collaboration protocols, workflow handoff patterns, and commit message formats for TDD/Mikado/refactoring workflows
development
Creates a phased roadmap.json for a feature goal with acceptance criteria and TDD steps. Use when planning implementation steps before execution.
testing
Acceptance test creation methodology for the DISTILL wave. Domain knowledge for the acceptance designer agent: port-to-port principle, prior wave reading, wave-decision reconciliation, graceful degradation, and document back-propagation.