ux-researcher-designer
Imported from https://github.com/Primadetaautomation/claude-dev-toolkit.
Packaged view
This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Install command
npx @skill-hub/cli install primadetaautomation-claude-dev-toolkit-ux-researcher-designer
Repository
Skill path: skills/ux-researcher-designer
Imported from https://github.com/Primadetaautomation/claude-dev-toolkit.
Open repositoryBest for
Primary workflow: Design Product.
Technical facets: Full Stack, Designer.
Target audience: everyone.
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: Primadetaautomation.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install ux-researcher-designer into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/Primadetaautomation/claude-dev-toolkit before adding ux-researcher-designer to shared team environments
- Use ux-researcher-designer for development workflows
Works across
Favorites: 0.
Sub-skills: 0.
Aggregator: No.
Original source / Raw SKILL.md
---
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 for user research, persona creation, journey mapping, and design validation.
triggers: [persona, UX, user research, journey map, usability, user testing, UX design, customer journey, user insights, design validation]
version: 1.0.0
agents: [ux-design-expert, frontend-specialist, product-manager]
context_levels:
minimal: Core UX research principles and persona basics
detailed: Complete persona generation and journey mapping patterns
full: Working scripts, templates, and comprehensive examples
---
# UX Researcher & Designer
Comprehensive toolkit for user-centered research and experience design with data-driven approaches.
## Overview
This skill provides professional UX research and design capabilities including persona generation from real user data, customer journey mapping, usability testing frameworks, and research synthesis methods.
## When to Use This Skill
- Creating data-driven user personas
- Analyzing user behavior patterns and insights
- Mapping customer journeys and touchpoints
- Conducting usability research and validation
- Synthesizing research data into actionable insights
- Generating design implications from user data
## Core Capabilities
### 1. Data-Driven Persona Generation
Create research-backed personas from quantitative and qualitative user data:
- Analyze user behavior patterns from analytics
- Identify persona archetypes automatically
- Extract psychographics (motivations, values, attitudes)
- Generate realistic usage scenarios
- Provide confidence scoring based on sample size
- Derive design implications from persona data
### 2. Persona Archetypes
Built-in archetype templates for common user types:
- **Power User**: Tech-savvy, frequent user, efficiency-focused
- **Casual User**: Occasional user, values simplicity and ease-of-use
- **Business User**: ROI-focused, team collaboration oriented
- **Mobile First**: Primarily mobile usage, on-the-go access
### 3. Customer Journey Mapping
Map complete user journeys with:
- Touchpoint identification
- Pain point analysis
- Opportunity discovery
- Emotion mapping across journey stages
### 4. Usability Testing Frameworks
Structured approaches for:
- Test plan creation
- Success metrics definition
- User task scenarios
- Observation frameworks
### 5. Research Synthesis
Transform raw research into insights:
- Pattern identification across users
- Theme extraction from interviews
- Quantitative and qualitative data integration
- Actionable design recommendations
## Available Tools
### Python Script: persona_generator.py
**Location:** `scripts/persona_generator.py`
**Purpose:** Generate comprehensive, data-driven user personas from user data and optional interview insights.
**Usage:**
```bash
# JSON output
python scripts/persona_generator.py json
# Human-readable output
python scripts/persona_generator.py
```
**Features:**
- Analyzes usage frequency, feature usage, device patterns
- Identifies persona archetype based on behavior patterns
- Aggregates demographics (age, location, tech proficiency)
- Extracts psychographics (motivations, values, lifestyle)
- Generates usage scenarios with context and pain points
- Calculates confidence level based on sample size
- Provides design implications for each persona
**Input Data Structure:**
```python
user_data = [
{
'user_id': 'user_1',
'age': 28,
'usage_frequency': 'daily', # daily, weekly, monthly
'features_used': ['dashboard', 'reports', 'settings'],
'primary_device': 'desktop', # desktop, mobile, tablet
'usage_context': 'work', # work, personal
'tech_proficiency': 7, # 1-10 scale
'pain_points': ['slow loading', 'confusing UI']
}
# ... more users
]
```
**Output Includes:**
- Persona name and archetype
- Demographics and psychographics
- Goals, needs, and frustrations
- Behavior patterns and feature preferences
- Usage scenarios with pain points
- Design implications
- Data confidence metrics
### TypeScript Script: persona-generator.ts
**Location:** `scripts/persona-generator.ts`
**Purpose:** Same functionality as Python version, integrated with Node.js/TypeScript ecosystem.
**Usage:**
```bash
# JSON output
ts-node scripts/persona-generator.ts --format=json
# Pretty output
ts-node scripts/persona-generator.ts
```
**TypeScript Advantages:**
- Type-safe data structures
- Better IDE integration
- Easy integration with existing Node.js projects
- Modern async/await patterns
## Design Implications Framework
Each generated persona includes specific design implications based on their characteristics:
**For High-Frequency Users:**
- Optimize for speed and efficiency
- Provide keyboard shortcuts and power features
- Minimize friction in common workflows
**For Casual Users:**
- Focus on discoverability and clear guidance
- Simplify onboarding experience
- Reduce cognitive load
**For Mobile Users:**
- Mobile-first responsive design
- Touch-optimized interactions
- Offline capability considerations
**For Business Users:**
- Professional visual design
- Enterprise features (SSO, audit logs, team management)
- Integration with business tools
## Best Practices
### Data Collection
1. **Minimum Sample Size**: 20+ users for Medium confidence, 50+ for High confidence
2. **Mix Methods**: Combine quantitative analytics with qualitative interviews
3. **Regular Updates**: Refresh personas quarterly or after major product changes
4. **Validation**: Test personas against real user behavior continuously
### Persona Usage
1. **Share Widely**: Make personas accessible to entire product team
2. **Reference Often**: Use in feature discussions and design reviews
3. **Update Regularly**: Keep personas current as user base evolves
4. **Measure Impact**: Track how persona-driven decisions affect metrics
### Research Synthesis
1. **Document Everything**: Keep detailed notes from all research activities
2. **Look for Patterns**: Identify recurring themes across multiple users
3. **Prioritize Insights**: Focus on actionable findings with high impact
4. **Validate Assumptions**: Test hypotheses with additional research
## Context Levels
### Level 1 - Minimal (Always Loaded)
- Core UX research principles
- Persona archetype definitions
- Basic usage patterns
### Level 2 - Detailed (Load on Request)
- Complete persona generation methodology
- Journey mapping frameworks
- Usability testing templates
- Research synthesis techniques
### Level 3 - Full (Scripts and Examples)
- Working Python and TypeScript scripts
- Sample data structures
- Complete persona examples
- Integration code samples
## Integration with Other Skills
Works well with:
- **ui-design-system**: Use personas to inform design token decisions
- **frontend-specialist**: Apply persona insights to component design
- **testing-fundamentals**: Create test scenarios based on persona behaviors
- **accessibility-specialist**: Ensure designs work for all persona types
## References
**UX Research Methods:**
- Nielsen Norman Group UX Research Guidelines
- IDEO Human-Centered Design Toolkit
- Google Design Sprint Methodology
**Persona Creation:**
- Alan Cooper's "The Inmates Are Running the Asylum"
- Data-Driven Personas (Jansen et al.)
- Jobs To Be Done Framework
**Journey Mapping:**
- Adaptive Path's Guide to Experience Mapping
- Service Design Toolkit
## Version History
**v1.0.0** - Initial release
- Data-driven persona generation
- Python and TypeScript implementations
- 4 persona archetype templates
- Design implications framework
- Confidence scoring system
---
**Maintained by:** Primadata Enhanced Toolkit
**Source:** Based on claude-skills repository by Alireza Rezvani
**Last Updated:** November 2025