Approach and advantage
Separate workflows connect observed user needs to design decisions and test plans.
Structure personas, journey maps, usability studies, and research synthesis.
Structure personas, journey maps, usability studies, and research synthesis. Separate workflows connect observed user needs to design decisions and test plans.
Separate workflows connect observed user needs to design decisions and test plans.
Synthesize research-backed customer personas; Map a purchase or onboarding journey; Plan a usability study with observable task success.
Redacted interviews, behavior data, target journeys, research questions, and design constraints.
Use a Skill-capable agent with file access. Python 3 is required for the bundled Python helpers; inspect their sample schemas before supplying data.
The bundled persona CLI runs built-in sample data and exposes no user-file input argument. Real-data automation needs code adaptation; sample personas are not customer research.
The repository installer copies this complete Skill into your Codex skills directory. Git and the installer’s shell/Python requirements must be available.
git clone https://github.com/alirezarezvani/claude-skills.git
cd claude-skills
git checkout 6d2f02ea077eead1bee5411a31bcc6db5a11a70c
./scripts/codex-install.sh --skill ux-researcher-designerThis is the unchanged source SKILL.md for the reviewed version. Install the complete package to retain referenced scripts, assets, and instructions. Starter prompts below are EcomAgentTools examples.
Source and package files reviewed on October 25, 2026: GitHub 6d2f02ea077e. This is a static review, not an installation or business-outcome test.
View the reviewed source · MIT
MIT License Copyright (c) 2025 Alireza Rezvani Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
---
name: "ux-researcher-designer"
description: UX research and design toolkit for Senior UX Designer/Researcher including data-driven persona generation, journey mapping, usability testing frameworks, and research synthesis. Use when conducting user research, creating personas, mapping user journeys, planning usability tests, or validating designs.
---
# UX Researcher & Designer
Generate user personas from research data, create journey maps, plan usability tests, and synthesize research findings into actionable design recommendations.
---
## Table of Contents
- [Trigger Terms](#trigger-terms)
- [Workflows](#workflows)
- [Workflow 1: Generate User Persona](#workflow-1-generate-user-persona)
- [Workflow 2: Create Journey Map](#workflow-2-create-journey-map)
- [Workflow 3: Plan Usability Test](#workflow-3-plan-usability-test)
- [Workflow 4: Synthesize Research](#workflow-4-synthesize-research)
- [Tool Reference](#tool-reference)
- [Quick Reference Tables](#quick-reference-tables)
- [Knowledge Base](#knowledge-base)
---
## Trigger Terms
Use this skill when you need to:
- "create user persona"
- "generate persona from data"
- "build customer journey map"
- "map user journey"
- "plan usability test"
- "design usability study"
- "analyze user research"
- "synthesize interview findings"
- "identify user pain points"
- "define user archetypes"
- "calculate research sample size"
- "create empathy map"
- "identify user needs"
---
## Workflows
### Workflow 1: Generate User Persona
**Situation:** You have user data (analytics, surveys, interviews) and need to create a research-backed persona.
**Steps:**
1. **Prepare user data**
Required format (JSON):
```json
[
{
"user_id": "user_1",
"age": 32,
"usage_frequency": "daily",
"features_used": ["dashboard", "reports", "export"],
"primary_device": "desktop",
"usage_context": "work",
"tech_proficiency": 7,
"pain_points": ["slow loading", "confusing UI"]
}
]
```
2. **Run persona generator**
```bash
# Human-readable output
python scripts/persona_generator.py
# JSON output for integration
python scripts/persona_generator.py json
```
3. **Review generated components**
| Component | What to Check |
|-----------|---------------|
| Archetype | Does it match the data patterns? |
| Demographics | Are they derived from actual data? |
| Goals | Are they specific and actionable? |
| Frustrations | Do they include frequency counts? |
| Design implications | Can designers act on these? |
4. **Validate persona**
- Show to 3-5 real users: "Does this sound like you?"
- Cross-check with support tickets
- Verify against analytics data
5. **Reference:** See `references/persona-methodology.md` for validity criteria
---
### Workflow 2: Create Journey Map
**Situation:** You need to visualize the end-to-end user experience for a specific goal.
**Steps:**
1. **Define scope**
| Element | Description |
|---------|-------------|
| Persona | Which user type |
| Goal | What they're trying to achieve |
| Start | Trigger that begins journey |
| End | Success criteria |
| Timeframe | Hours/days/weeks |
2. **Gather journey data**
Sources:
- User interviews (ask "walk me through...")
- Session recordings
- Analytics (funnel, drop-offs)
- Support tickets
3. **Map the stages**
Typical B2B SaaS stages:
```
Awareness → Evaluation → Onboarding → Adoption → Advocacy
```
4. **Fill in layers for each stage**
```
Stage: [Name]
├── Actions: What does user do?
├── Touchpoints: Where do they interact?
├── Emotions: How do they feel? (1-5)
├── Pain Points: What frustrates them?
└── Opportunities: Where can we improve?
```
5. **Identify opportunities**
Priority Score = Frequency × Severity × Solvability
6. **Reference:** See `references/journey-mapping-guide.md` for templates
---
### Workflow 3: Plan Usability Test
**Situation:** You need to validate a design with real users.
**Steps:**
1. **Define research questions**
Transform vague goals into testable questions:
| Vague | Testable |
|-------|----------|
| "Is it easy to use?" | "Can users complete checkout in <3 min?" |
| "Do users like it?" | "Will users choose Design A or B?" |
| "Does it make sense?" | "Can users find settings without hints?" |
2. **Select method**
| Method | Participants | Duration | Best For |
|--------|--------------|----------|----------|
| Moderated remote | 5-8 | 45-60 min | Deep insights |
| Unmoderated remote | 10-20 | 15-20 min | Quick validation |
| Guerrilla | 3-5 | 5-10 min | Rapid feedback |
3. **Design tasks**
Good task format:
```
SCENARIO: "Imagine you're planning a trip to Paris..."
GOAL: "Book a hotel for 3 nights in your budget."
SUCCESS: "You see the confirmation page."
```
Task progression: Warm-up → Core → Secondary → Edge case → Free exploration
4. **Define success metrics**
| Metric | Target |
|--------|--------|
| Completion rate | >80% |
| Time on task | <2× expected |
| Error rate | <15% |
| Satisfaction | >4/5 |
5. **Prepare moderator guide**
- Think-aloud instructions
- Non-leading prompts
- Post-task questions
6. **Reference:** See `references/usability-testing-frameworks.md` for full guide
---
### Workflow 4: Synthesize Research
**Situation:** You have raw research data (interviews, surveys, observations) and need actionable insights.
**Steps:**
1. **Code the data**
Tag each data point:
- `[GOAL]` - What they want to achieve
- `[PAIN]` - What frustrates them
- `[BEHAVIOR]` - What they actually do
- `[CONTEXT]` - When/where they use product
- `[QUOTE]` - Direct user words
2. **Cluster similar patterns**
```
User A: Uses daily, advanced features, shortcuts
User B: Uses daily, complex workflows, automation
User C: Uses weekly, basic needs, occasional
Cluster 1: A, B (Power Users)
Cluster 2: C (Casual User)
```
3. **Calculate segment sizes**
| Cluster | Users | % | Viability |
|---------|-------|---|-----------|
| Power Users | 18 | 36% | Primary persona |
| Business Users | 15 | 30% | Primary persona |
| Casual Users | 12 | 24% | Secondary persona |
4. **Extract key findings**
For each theme:
- Finding statement
- Supporting evidence (quotes, data)
- Frequency (X/Y participants)
- Business impact
- Recommendation
5. **Prioritize opportunities**
| Factor | Score 1-5 |
|--------|-----------|
| Frequency | How often does this occur? |
| Severity | How much does it hurt? |
| Breadth | How many users affected? |
| Solvability | Can we fix this? |
6. **Reference:** See `references/persona-methodology.md` for analysis framework
---
## Tool Reference
### persona_generator.py
Generates data-driven personas from user research data.
| Argument | Values | Default | Description |
|----------|--------|---------|-------------|
| format | (none), json | (none) | Output format |
**Sample Output:**
```
============================================================
PERSONA: Alex the Power User
============================================================
📝 A daily user who primarily uses the product for work purposes
Archetype: Power User
Quote: "I need tools that can keep up with my workflow"
👤 Demographics:
• Age Range: 25-34
• Location Type: Urban
• Tech Proficiency: Advanced
🎯 Goals & Needs:
• Complete tasks efficiently
• Automate workflows
• Access advanced features
😤 Frustrations:
• Slow loading times (14/20 users)
• No keyboard shortcuts
• Limited API access
💡 Design Implications:
→ Optimize for speed and efficiency
→ Provide keyboard shortcuts and power features
→ Expose API and automation capabilities
📈 Data: Based on 45 users
Confidence: High
```
**Archetypes Generated:**
| Archetype | Signals | Design Focus |
|-----------|---------|--------------|
| power_user | Daily use, 10+ features | Efficiency, customization |
| casual_user | Weekly use, 3-5 features | Simplicity, guidance |
| business_user | Work context, team use | Collaboration, reporting |
| mobile_first | Mobile primary | Touch, offline, speed |
**Output Components:**
| Component | Description |
|-----------|-------------|
| demographics | Age range, location, occupation, tech level |
| psychographics | Motivations, values, attitudes, lifestyle |
| behaviors | Usage patterns, feature preferences |
| needs_and_goals | Primary, secondary, functional, emotional |
| frustrations | Pain points with evidence |
| scenarios | Contextual usage stories |
| design_implications | Actionable recommendations |
| data_points | Sample size, confidence level |
---
## Quick Reference Tables
### Research Method Selection
| Question Type | Best Method | Sample Size |
|---------------|-------------|-------------|
| "What do users do?" | Analytics, observation | 100+ events |
| "Why do they do it?" | Interviews | 8-15 users |
| "How well can they do it?" | Usability test | 5-8 users |
| "What do they prefer?" | Survey, A/B test | 50+ users |
| "What do they feel?" | Diary study, interviews | 10-15 users |
### Persona Confidence Levels
| Sample Size | Confidence | Use Case |
|-------------|------------|----------|
| 5-10 users | Low | Exploratory |
| 11-30 users | Medium | Directional |
| 31+ users | High | Production |
### Usability Issue Severity
| Severity | Definition | Action |
|----------|------------|--------|
| 4 - Critical | Prevents task completion | Fix immediately |
| 3 - Major | Significant difficulty | Fix before release |
| 2 - Minor | Causes hesitation | Fix when possible |
| 1 - Cosmetic | Noticed but not problematic | Low priority |
### Interview Question Types
| Type | Example | Use For |
|------|---------|---------|
| Context | "Walk me through your typical day" | Understanding environment |
| Behavior | "Show me how you do X" | Observing actual actions |
| Goals | "What are you trying to achieve?" | Uncovering motivations |
| Pain | "What's the hardest part?" | Identifying frustrations |
| Reflection | "What would you change?" | Generating ideas |
---
## Knowledge Base
Detailed reference guides in `references/`:
| File | Content |
|------|---------|
| `persona-methodology.md` | Validity criteria, data collection, analysis framework |
| `journey-mapping-guide.md` | Mapping process, templates, opportunity identification |
| `example-personas.md` | 3 complete persona examples with data |
| `usability-testing-frameworks.md` | Test planning, task design, analysis |
---
## Validation Checklist
### Persona Quality
- [ ] Based on 20+ users (minimum)
- [ ] At least 2 data sources (quant + qual)
- [ ] Specific, actionable goals
- [ ] Frustrations include frequency counts
- [ ] Design implications are specific
- [ ] Confidence level stated
### Journey Map Quality
- [ ] Scope clearly defined (persona, goal, timeframe)
- [ ] Based on real user data, not assumptions
- [ ] All layers filled (actions, touchpoints, emotions)
- [ ] Pain points identified per stage
- [ ] Opportunities prioritized
### Usability Test Quality
- [ ] Research questions are testable
- [ ] Tasks are realistic scenarios, not instructions
- [ ] 5+ participants per design
- [ ] Success metrics defined
- [ ] Findings include severity ratings
### Research Synthesis Quality
- [ ] Data coded consistently
- [ ] Patterns based on 3+ data points
- [ ] Findings include evidence
- [ ] Recommendations are actionable
- [ ] Priorities justified
## Related Skills
- **UI Design System** (`product-team/ui-design-system/`) — Research findings inform design system decisions
- **Product Manager Toolkit** (`product-team/product-manager-toolkit/`) — Customer interview analysis complements persona research
Starter prompts for the main use cases—copy and use them directly.
Synthesize research-backed customer personas Use for: Synthesize research-backed customer personas. Prepare: Redacted interviews, behavior data, target journeys, research questions, and design constraints.
Use the installed ux-researcher-designer Skill. Task: Synthesize research-backed customer personas. Inputs: [INPUT]. Constraints: [CONSTRAINTS]. Check missing information first. Produce a reviewable result with evidence, assumptions, and next steps. The bundled persona CLI runs built-in sample data and exposes no user-file input argument. Real-data automation needs code adaptation; sample personas are not customer research.[INPUT][CONSTRAINTS]Map a purchase or onboarding journey Use for: Map a purchase or onboarding journey. Prepare: Redacted interviews, behavior data, target journeys, research questions, and design constraints.
Use the installed ux-researcher-designer Skill. Task: Map a purchase or onboarding journey. Inputs: [INPUT]. Constraints: [CONSTRAINTS]. Check missing information first. Produce a reviewable result with evidence, assumptions, and next steps. The bundled persona CLI runs built-in sample data and exposes no user-file input argument. Real-data automation needs code adaptation; sample personas are not customer research.[INPUT][CONSTRAINTS]Plan a usability study with observable task success Use for: Plan a usability study with observable task success. Prepare: Redacted interviews, behavior data, target journeys, research questions, and design constraints.
Use the installed ux-researcher-designer Skill. Task: Plan a usability study with observable task success. Inputs: [INPUT]. Constraints: [CONSTRAINTS]. Check missing information first. Produce a reviewable result with evidence, assumptions, and next steps. The bundled persona CLI runs built-in sample data and exposes no user-file input argument. Real-data automation needs code adaptation; sample personas are not customer research.[INPUT][CONSTRAINTS]The bundled persona CLI runs built-in sample data and exposes no user-file input argument. Real-data automation needs code adaptation; sample personas are not customer research.
Source and package files reviewed on October 25, 2026: GitHub 6d2f02ea077e. This is a static review, not an installation or business-outcome test.
Use authorized inputs and keep secrets out of prompts. Review customer-facing claims, calculations, code changes, and any proposed external action before applying them.
Structure personas, journey maps, usability studies, and research synthesis. Separate workflows connect observed user needs to design decisions and test plans.
Choose the method for your agent and install the complete package, not just the displayed SKILL.md. Redacted interviews, behavior data, target journeys, research questions, and design constraints. Start a new agent session and explicitly ask to use ux-researcher-designer. Try one use case below with a small sample and review the output.
Synthesize research-backed customer personas; Map a purchase or onboarding journey; Plan a usability study with observable task success
The bundled persona CLI runs built-in sample data and exposes no user-file input argument. Real-data automation needs code adaptation; sample personas are not customer research.
Source and package files reviewed on October 25, 2026: GitHub 6d2f02ea077e. This is a static review, not an installation or business-outcome test.
Source and package files reviewed on October 25, 2026: GitHub 6d2f02ea077e. This is a static review, not an installation or business-outcome test.
Source and package files reviewed on October 25, 2026: GitHub 6d2f02ea077e. This is a static review, not an installation or business-outcome test.
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