| name | ux-researcher-designer |
| title | UX Researcher Designer Skill Package |
| 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. |
| domain | product |
| subdomain | ux-design |
| difficulty | intermediate |
| time-saved | TODO: Quantify time savings |
| frequency | TODO: Estimate usage frequency |
| use-cases | Primary workflow for Ux Researcher Designer, Analysis and recommendations for ux researcher designer tasks, Best practices implementation for ux researcher designer, Integration with related skills and workflows |
| related-agents | |
| related-skills | |
| related-commands | |
| orchestrated-by | |
| dependencies | [object Object] |
| compatibility | [object Object] |
| tech-stack | Python 3.8+, CLI, JSON processing, User data analysis, JSON export |
| examples | [object Object] |
| stats | [object Object] |
| version | v1.0.0 |
| author | Claude Skills Team |
| contributors | |
| created | Sun Oct 19 2025 00:00:00 GMT+0000 (Coordinated Universal Time) |
| updated | Sat Nov 08 2025 00:00:00 GMT+0000 (Coordinated Universal Time) |
| license | MIT |
| tags | data, design, designer, product, researcher, testing |
| featured | false |
| verified | true |
UX Researcher & Designer
Overview
This skill provides [TODO: Add 2-3 sentence overview].
Core Value: [TODO: Add value proposition with metrics]
Target Audience: [TODO: Define target users]
Use Cases: [TODO: List 3-5 primary use cases]
Core Capabilities
- [Capability 1] - [Description]
- [Capability 2] - [Description]
- [Capability 3] - [Description]
- [Capability 4] - [Description]
Key Workflows
Workflow 1: [Workflow Name]
Time: [Duration estimate]
Steps:
- [Step 1]
- [Step 2]
- [Step 3]
Expected Output: [What success looks like]
Workflow 2: [Workflow Name]
Time: [Duration estimate]
Steps:
- [Step 1]
- [Step 2]
- [Step 3]
Expected Output: [What success looks like]
Comprehensive toolkit for user-centered research and experience design. This skill provides Python tools for persona generation, research frameworks for validation, and battle-tested templates for interviews and journey mapping.
What This Skill Provides:
- Data-driven persona generator from user research
- User research methodologies (interviews, usability testing)
- Journey mapping and Jobs-to-be-Done frameworks
- Design validation methods (prototypes, A/B tests)
- Accessibility compliance frameworks (WCAG 2.1)
Best For:
- Conducting user research and synthesis
- Creating research-backed personas
- Journey mapping and empathy building
- Usability testing and validation
- Ensuring accessible design
Quick Start
Generate Personas
# Interactive mode
python scripts/persona_generator.py
# From user data
python scripts/persona_generator.py --data user_research.json
# Filter by segment
python scripts/persona_generator.py --data user_data.json --segment "premium"
Persona Components
Demographics: Age, role, company, technical proficiency Goals: Primary objectives and motivations Pain Points: Frustrations and challenges Behaviors: Usage patterns and preferences JTBD: Jobs-to-be-done framework
See frameworks.md for complete persona development framework.
Core Workflows
1. User Research Process
Steps:
- Define research questions
- Recruit participants (5-8 per cohort)
- Conduct interviews (30-45 min each)
- Synthesize findings
- Generate personas:
python scripts/persona_generator.py --data research.json - Validate with stakeholders
Research Methods:
- Qualitative: Interviews, usability testing, field studies
- Quantitative: Surveys, analytics, A/B tests
- Mixed: Combine both for comprehensive insights
Interview Structure:
- Introduction (5 min)
- Background (5 min)
- Problem exploration (20 min)
- Solution validation (10 min)
- Wrap-up (5 min)
Detailed Methods: See frameworks.md for qualitative and quantitative research frameworks.
Templates: See templates.md for interview scripts and usability test plans.
2. Persona Creation Process
Steps:
- Collect user data (interviews, surveys, analytics)
- Format as JSON input
- Generate personas:
python scripts/persona_generator.py --data user_research.json - Segment by user type (enterprise, SMB, individual)
- Validate with real users
- Update quarterly with new data
Persona Components:
- Demographics and psychographics
- Goals and motivations
- Pain points and frustrations
- Behavior patterns
- Jobs-to-be-done
- Representative quotes
Confidence Scoring:
- High: Based on 15+ interviews
- Medium: Based on 8-14 interviews
- Low: Based on <8 interviews
Detailed Framework: See frameworks.md for persona development and Jobs-to-be-Done framework.
Templates: See templates.md for persona template and journey map format.
3. Design Validation Process
Methods:
- Prototype Testing: Low/mid/high-fidelity testing
- Usability Testing: Task-based scenarios with 5-8 users
- A/B Testing: Quantitative validation of design decisions
- Design Critiques: Structured feedback sessions
Usability Test Structure:
- Plan (research questions, success metrics)
- Recruit (5-8 participants per round)
- Execute (45-50 min sessions)
- Analyze (severity rating, prioritization)
- Iterate (implement fixes, retest)
Severity Rating:
- Critical: Prevents task completion
- High: Causes significant frustration
- Medium: Minor inconvenience
- Low: Cosmetic issue
Detailed Frameworks: See frameworks.md for usability testing and validation methods.
Templates: See templates.md for usability test plan template.
Python Tools
persona_generator.py
Data-driven persona generation from user research.
Key Features:
- Demographic and psychographic profiling
- Goals and pain points extraction
- Behavior pattern identification
- Jobs-to-be-done analysis
- Confidence scoring based on sample size
- Multiple output formats (text, JSON, CSV)
Usage:
# Interactive persona creation
python3 scripts/persona_generator.py
# From user research JSON
python3 scripts/persona_generator.py --data user_research.json
# Filter by segment
python3 scripts/persona_generator.py --data user_data.json --segment "enterprise"
# JSON output
python3 scripts/persona_generator.py --data user_research.json --output json
# Save to file
python3 scripts/persona_generator.py --data user_research.json -o json -f personas.json
# Verbose mode
python3 scripts/persona_generator.py --data user_research.json -v
Generated Persona Includes:
- Name and archetype
- Demographics (age, role, company, industry)
- Goals (primary objectives)
- Pain points (frustrations)
- Behaviors (usage patterns)
- Jobs-to-be-done (JTBD framework)
- Representative quote
- Confidence level (based on sample size)
Input Format:
- JSON file with user research data
- Demographics, behaviors, goals, pain points, quotes
- Multiple users per segment
Complete Documentation: See tools.md for full usage guide, input formats, and integration patterns.
Reference Documentation
Frameworks (frameworks.md)
Comprehensive research and design frameworks:
- User Research Methods: Qualitative and quantitative approaches
- Persona Development: JTBD, persona components, validation criteria
- Journey Mapping: Customer journey stages, map components, insights
- Usability Testing: Test planning, execution, severity rating
- Accessibility Framework: WCAG 2.1 principles, compliance checklist
- Design Validation: Prototype testing, A/B testing, design critiques
Templates (templates.md)
Ready-to-use templates:
- User Interview Script: Complete interview guide with questions
- Persona Template: Comprehensive persona format
- Journey Map Template: Multi-stage journey mapping format
- Usability Test Plan: Complete test plan with scenarios
Tools (tools.md)
Python tool documentation:
- persona_generator.py: Complete usage guide
- Command-Line Options: All flags and parameters
- Input Format: User research JSON structure
- Generated Output: Persona format examples
- Integration Patterns: Figma, documentation, research synthesis
- Best Practices: DO/DON'T guidelines
Integration Points
This toolkit integrates with:
- Design Tools: Figma, Sketch, Miro (personas and journey maps)
- Research Tools: Dovetail, UserVoice, Maze, Optimal Workshop
- Analytics: Amplitude, Mixpanel, Hotjar, FullStory
- Testing: UserTesting.com, Lookback, UserZoom
- Documentation: Confluence, Notion, Airtable
See tools.md for detailed integration workflows.
Quick Commands
# Interactive persona creation
python scripts/persona_generator.py
# From user research data
python scripts/persona_generator.py --data user_research.json
# By segment
python scripts/persona_generator.py --data user_data.json --segment "enterprise"
python scripts/persona_generator.py --data user_data.json --segment "smb"
# Export formats
python scripts/persona_generator.py --data research.json -o json -f personas.json
python scripts/persona_generator.py --data research.json -o csv -f personas.csv
# Verbose output
python scripts/persona_generator.py --data research.json -v