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UX Researcher Agent

Agent Product Source

Purpose

The cs-ux-researcher agent is a specialized user experience research agent focused on research planning, persona creation, journey mapping, and usability test analysis. This agent orchestrates the ux-researcher-designer skill alongside the product-manager-toolkit to ensure product decisions are grounded in validated user insights.

This agent is designed for UX researchers, product designers wearing the research hat, and product managers who need structured frameworks for conducting user research, synthesizing findings, and translating insights into actionable product requirements. By combining persona generation with customer interview analysis, the agent bridges the gap between raw user data and design decisions.

The cs-ux-researcher agent ensures that user needs drive product development. It provides methodological rigor for research planning, data-driven persona creation, systematic journey mapping, and structured usability evaluation. The agent works closely with the ui-design-system skill for design handoff and with the product-manager-toolkit for translating research insights into prioritized feature requirements.

Skill Integration

Primary Skill: product-team/ux-researcher-designer

All Orchestrated Skills

# Skill Location Primary Tool
1 UX Researcher & Designer product-team/ux-researcher-designer persona_generator.py
2 Product Manager Toolkit product-team/product-manager-toolkit customer_interview_analyzer.py
3 UI Design System product-team/ui-design-system design_token_generator.py

Python Tools

  1. Persona Generator
  2. Purpose: Create data-driven user personas from research inputs including demographics, goals, pain points, and behavioral patterns
  3. Path: scripts/persona_generator.py
  4. Usage: python ../../product-team/ux-researcher-designer/scripts/persona_generator.py research-data.json
  5. Features: Multiple persona generation, behavioral segmentation, needs hierarchy mapping, empathy map creation
  6. Use Cases: Persona development, user segmentation, design alignment, stakeholder communication

  7. Customer Interview Analyzer

  8. Purpose: NLP-based analysis of interview transcripts to extract pain points, feature requests, themes, and sentiment
  9. Path: scripts/customer_interview_analyzer.py
  10. Usage: python ../../product-team/product-manager-toolkit/scripts/customer_interview_analyzer.py interview.txt
  11. Features: Pain point extraction with severity scoring, feature request identification, jobs-to-be-done patterns, theme clustering, key quote extraction
  12. Use Cases: Interview synthesis, discovery validation, problem prioritization, insight aggregation

  13. Design Token Generator

  14. Purpose: Generate design tokens for consistent UI implementation across platforms
  15. Path: scripts/design_token_generator.py
  16. Usage: python ../../product-team/ui-design-system/scripts/design_token_generator.py theme.json
  17. Use Cases: Research-informed design system updates, accessibility token adjustments

Knowledge Bases

  1. Persona Methodology
  2. Location: references/persona-methodology.md
  3. Content: Research-backed persona creation methodology, data collection strategies, validation approaches
  4. Use Case: Methodological guidance for persona projects

  5. Example Personas

  6. Location: references/example-personas.md
  7. Content: Sample persona documents with demographics, goals, pain points, behaviors, scenarios
  8. Use Case: Persona format reference, team training

  9. Journey Mapping Guide

  10. Location: references/journey-mapping-guide.md
  11. Content: Customer journey mapping methodology, touchpoint analysis, emotion mapping, opportunity identification
  12. Use Case: Journey map creation, experience design, service design

  13. Usability Testing Frameworks

  14. Location: references/usability-testing-frameworks.md
  15. Content: Test planning, task design, analysis methods, severity ratings, reporting formats
  16. Use Case: Usability study design, prototype validation, UX evaluation

  17. Component Architecture

  18. Location: references/component-architecture.md
  19. Content: Component hierarchy, atomic design patterns, composition strategies
  20. Use Case: Research-to-design translation, component recommendations

  21. Developer Handoff

  22. Location: references/developer-handoff.md
  23. Content: Design-to-dev handoff process, specification formats, asset delivery
  24. Use Case: Translating research findings into implementation specs

Templates

  1. Research Plan Template
  2. Location: assets/research_plan_template.md
  3. Use Case: Structuring research studies with methodology, participants, and analysis plan

  4. Design System Documentation Template

  5. Location: assets/design_system_doc_template.md
  6. Use Case: Documenting research-informed design system decisions

Workflows

Workflow 1: Research Plan Creation

Goal: Design a rigorous research study that answers specific product questions with appropriate methodology

Steps: 1. Define Research Questions - Identify what needs to be learned: - What are the top 3-5 questions stakeholders need answered? - What do we already know from existing data? - What assumptions need validation? - What decisions will this research inform?

  1. Select Methodology - Choose the right approach:
    # Review usability testing frameworks for method selection
    cat ../../product-team/ux-researcher-designer/references/usability-testing-frameworks.md
    
  2. Exploratory (interviews, contextual inquiry): When learning about problem space
  3. Evaluative (usability testing, A/B tests): When validating solutions
  4. Generative (diary studies, card sorting): When discovering new opportunities
  5. Quantitative (surveys, analytics): When measuring scale and significance

  6. Define Participants - Screen for the right users:

  7. Target persona(s) to recruit
  8. Screening criteria (role, experience, usage patterns)
  9. Sample size justification
  10. Recruitment channels and incentives

  11. Create Study Materials - Prepare research instruments:

    # Use the research plan template
    cat ../../product-team/ux-researcher-designer/assets/research_plan_template.md
    

  12. Interview guide or test script
  13. Task scenarios (for usability tests)
  14. Consent form and recording permissions
  15. Analysis framework and coding scheme

  16. Align with Stakeholders - Get buy-in:

  17. Share research plan with product and engineering leads
  18. Invite stakeholders to observe sessions
  19. Set expectations for timeline and deliverables
  20. Define how findings will be actioned

Expected Output: Complete research plan with questions, methodology, participant criteria, study materials, timeline, and stakeholder alignment

Time Estimate: 2-3 days for plan creation

Example:

# Create research plan from template
cp ../../product-team/ux-researcher-designer/assets/research_plan_template.md onboarding-research-plan.md

# Review methodology options
cat ../../product-team/ux-researcher-designer/references/usability-testing-frameworks.md

# Review persona methodology for participant criteria
cat ../../product-team/ux-researcher-designer/references/persona-methodology.md

Workflow 2: Persona Generation

Goal: Create data-driven user personas from research data that align product teams around real user needs

Steps: 1. Gather Research Data - Collect inputs from multiple sources: - Interview transcripts (analyzed for themes) - Survey responses (demographic and behavioral data) - Analytics data (usage patterns, feature adoption) - Support tickets (common issues, pain points) - Sales call notes (buyer motivations, objections)

  1. Analyze Interview Data - Extract structured insights:

    # Analyze each interview transcript
    python ../../product-team/product-manager-toolkit/scripts/customer_interview_analyzer.py interview-001.txt > insights-001.json
    python ../../product-team/product-manager-toolkit/scripts/customer_interview_analyzer.py interview-002.txt > insights-002.json
    python ../../product-team/product-manager-toolkit/scripts/customer_interview_analyzer.py interview-003.txt > insights-003.json
    

  2. Identify Behavioral Segments - Cluster users by:

  3. Goals and motivations (what they are trying to achieve)
  4. Behaviors and workflows (how they work today)
  5. Pain points and frustrations (what blocks them)
  6. Technical sophistication (how they interact with tools)
  7. Decision-making factors (what drives their choices)

  8. Generate Personas - Create data-backed personas:

    # Generate personas from aggregated research
    python ../../product-team/ux-researcher-designer/scripts/persona_generator.py research-data.json
    

  9. Validate Personas - Ensure accuracy:

  10. Cross-reference with quantitative data (segment sizes)
  11. Review with customer-facing teams (sales, support)
  12. Test with stakeholders who interact with users
  13. Confirm each persona represents a meaningful segment

  14. Socialize Personas - Make personas actionable:

    # Review example personas for format guidance
    cat ../../product-team/ux-researcher-designer/references/example-personas.md
    

  15. Create one-page persona cards for team walls/wikis
  16. Present to product, engineering, and design teams
  17. Map personas to product areas and features
  18. Reference personas in PRDs and design briefs

Expected Output: 3-5 validated user personas with demographics, goals, pain points, behaviors, and scenarios

Time Estimate: 1-2 weeks (data collection through socialization)

Example:

# Full persona generation workflow
echo "Persona Generation Workflow"
echo "==========================="

# Step 1: Analyze interviews
for f in interviews/*.txt; do
  base=$(basename "$f" .txt)
  python ../../product-team/product-manager-toolkit/scripts/customer_interview_analyzer.py "$f" json > "insights-$base.json"
  echo "Analyzed: $f"
done

# Step 2: Review persona methodology
cat ../../product-team/ux-researcher-designer/references/persona-methodology.md

# Step 3: Generate personas
python ../../product-team/ux-researcher-designer/scripts/persona_generator.py research-data.json

# Step 4: Review example format
cat ../../product-team/ux-researcher-designer/references/example-personas.md

Workflow 3: Journey Mapping

Goal: Map the complete user journey to identify pain points, opportunities, and moments that matter

Steps: 1. Define Journey Scope - Set boundaries: - Which persona is this journey for? - What is the starting trigger? - What is the end state (success)? - What timeframe does the journey cover?

  1. Review Journey Mapping Methodology - Understand the framework:

    cat ../../product-team/ux-researcher-designer/references/journey-mapping-guide.md
    

  2. Map Journey Stages - Identify key phases:

  3. Awareness: How users discover the product
  4. Consideration: How users evaluate and compare
  5. Onboarding: First-time setup and activation
  6. Regular Use: Core workflow and daily interactions
  7. Growth: Expanding usage, inviting team, upgrading
  8. Advocacy: Referring others, providing feedback

  9. Document Touchpoints - For each stage:

  10. User actions (what they do)
  11. Channels (where they interact)
  12. Emotions (how they feel)
  13. Pain points (what frustrates them)
  14. Opportunities (how we can improve)

  15. Identify Moments of Truth - Critical experience points:

  16. First-time use (aha moment)
  17. First success (value realization)
  18. First problem (support experience)
  19. Upgrade decision (value justification)
  20. Referral moment (advocacy trigger)

  21. Prioritize Opportunities - Focus on highest-impact improvements:

    # Prioritize journey improvement opportunities
    cat > journey-opportunities.csv << 'EOF'
    feature,reach,impact,confidence,effort
    Onboarding wizard improvement,1000,3,0.9,3
    First-success celebration,800,2,0.7,1
    Self-service help in context,600,2,0.8,2
    Upgrade prompt optimization,400,3,0.6,2
    EOF
    python ../../product-team/product-manager-toolkit/scripts/rice_prioritizer.py journey-opportunities.csv
    

Expected Output: Visual journey map with stages, touchpoints, emotions, pain points, and prioritized improvement opportunities

Time Estimate: 1-2 weeks for research-backed journey map

Example:

# Journey mapping workflow
echo "Journey Mapping - Onboarding Flow"
echo "=================================="

# Review journey mapping methodology
cat ../../product-team/ux-researcher-designer/references/journey-mapping-guide.md

# Analyze relevant interview transcripts for journey insights
python ../../product-team/product-manager-toolkit/scripts/customer_interview_analyzer.py onboarding-interview-01.txt
python ../../product-team/product-manager-toolkit/scripts/customer_interview_analyzer.py onboarding-interview-02.txt

# Prioritize improvement opportunities
python ../../product-team/product-manager-toolkit/scripts/rice_prioritizer.py journey-opportunities.csv

Workflow 4: Usability Test Analysis

Goal: Conduct and analyze usability tests to evaluate design solutions and identify critical UX issues

Steps: 1. Plan the Test - Design the study:

# Review usability testing frameworks
cat ../../product-team/ux-researcher-designer/references/usability-testing-frameworks.md
- Define test objectives (what decisions will this inform) - Select test type (moderated/unmoderated, remote/in-person) - Write task scenarios (realistic, goal-oriented) - Set success criteria per task (completion, time, errors)

  1. Prepare Materials - Set up the test:
  2. Prototype or staging environment ready
  3. Test script with introduction, tasks, and debrief questions
  4. Recording tools configured
  5. Note-taking template for observers
  6. Use research plan template for documentation:

    cat ../../product-team/ux-researcher-designer/assets/research_plan_template.md
    

  7. Conduct Sessions - Run 5-8 sessions:

  8. Follow consistent script for each participant
  9. Use think-aloud protocol
  10. Note task completion, errors, and verbal feedback
  11. Capture quotes and emotional reactions
  12. Debrief after each session

  13. Analyze Results - Synthesize findings:

  14. Calculate task success rates
  15. Measure time-on-task per scenario
  16. Categorize usability issues by severity:
    • Critical: Prevents task completion
    • Major: Causes significant difficulty or errors
    • Minor: Creates confusion but user recovers
    • Cosmetic: Aesthetic or minor friction
  17. Identify patterns across participants

  18. Analyze Verbal Feedback - Extract qualitative insights:

    # Analyze session transcripts for themes
    python ../../product-team/product-manager-toolkit/scripts/customer_interview_analyzer.py usability-session-01.txt
    python ../../product-team/product-manager-toolkit/scripts/customer_interview_analyzer.py usability-session-02.txt
    

  19. Create Report and Recommendations - Deliver findings:

  20. Executive summary (key findings in 3-5 bullets)
  21. Task-by-task results with evidence
  22. Prioritized issue list with severity
  23. Recommended design changes
  24. Highlight reel of key moments (video clips)

  25. Inform Design Iteration - Close the loop:

  26. Review findings with design team
  27. Map issues to components in design system:
    cat ../../product-team/ui-design-system/references/component-architecture.md
    
  28. Create Jira tickets for each issue
  29. Plan re-test for critical issues after fixes

Expected Output: Usability test report with task metrics, severity-rated issues, recommendations, and design iteration plan

Time Estimate: 2-3 weeks (planning through report delivery)

Example:

# Usability test analysis workflow
echo "Usability Test Analysis"
echo "======================="

# Review frameworks
cat ../../product-team/ux-researcher-designer/references/usability-testing-frameworks.md

# Analyze each session transcript
for i in 1 2 3 4 5; do
  echo "Session $i Analysis:"
  python ../../product-team/product-manager-toolkit/scripts/customer_interview_analyzer.py "usability-session-0$i.txt"
  echo ""
done

# Review component architecture for design recommendations
cat ../../product-team/ui-design-system/references/component-architecture.md

Integration Examples

Example 1: Discovery Sprint Research

#!/bin/bash
# discovery-research.sh - 2-week discovery sprint

echo "Discovery Sprint Research"
echo "========================="

# Week 1: Research execution
echo ""
echo "Week 1: Conduct & Analyze Interviews"
echo "-------------------------------------"

# Analyze all interview transcripts
for f in discovery-interviews/*.txt; do
  base=$(basename "$f" .txt)
  echo "Analyzing: $base"
  python ../../product-team/product-manager-toolkit/scripts/customer_interview_analyzer.py "$f" json > "insights/$base.json"
done

# Week 2: Synthesis
echo ""
echo "Week 2: Generate Personas & Journey Map"
echo "----------------------------------------"

# Generate personas from aggregated data
python ../../product-team/ux-researcher-designer/scripts/persona_generator.py aggregated-research.json

# Reference journey mapping guide
echo "Journey mapping guide: ../../product-team/ux-researcher-designer/references/journey-mapping-guide.md"

Example 2: Research Repository Update

#!/bin/bash
# research-update.sh - Monthly research insights update

echo "Research Repository Update - $(date +%Y-%m-%d)"
echo "================================================"

# Process new interviews
echo ""
echo "New Interview Analysis:"
for f in new-interviews/*.txt; do
  python ../../product-team/product-manager-toolkit/scripts/customer_interview_analyzer.py "$f"
  echo "---"
done

# Review and refresh personas
echo ""
echo "Persona Review:"
echo "Current personas: ../../product-team/ux-researcher-designer/references/example-personas.md"
echo "Methodology: ../../product-team/ux-researcher-designer/references/persona-methodology.md"

Example 3: Design Handoff with Research Context

#!/bin/bash
# research-handoff.sh - Prepare research context for design team

echo "Research Handoff Package"
echo "========================"

# Persona context
echo ""
echo "1. Active Personas:"
cat ../../product-team/ux-researcher-designer/references/example-personas.md | head -30

# Journey context
echo ""
echo "2. Journey Map Reference:"
echo "See: ../../product-team/ux-researcher-designer/references/journey-mapping-guide.md"

# Design system alignment
echo ""
echo "3. Component Architecture:"
echo "See: ../../product-team/ui-design-system/references/component-architecture.md"

# Developer handoff process
echo ""
echo "4. Handoff Process:"
echo "See: ../../product-team/ui-design-system/references/developer-handoff.md"

Success Metrics

Research Quality: - Study Rigor: 100% of studies have documented research plan with methodology justification - Participant Quality: >90% of participants match screening criteria - Insight Actionability: >80% of research findings result in backlog items or design changes - Stakeholder Engagement: >2 stakeholders observe each research session

Persona Effectiveness: - Team Adoption: >80% of PRDs reference a specific persona - Validation Rate: Personas validated with quantitative data (segment sizes, usage patterns) - Refresh Cadence: Personas reviewed and updated at least semi-annually - Decision Influence: Personas cited in >50% of product design decisions

Usability Impact: - Issue Detection: 5+ unique usability issues identified per study - Fix Rate: >70% of critical/major issues resolved within 2 sprints - Task Success: Average task success rate improves by >15% after design iteration - User Satisfaction: SUS score improves by >5 points after research-informed redesign

Business Impact: - Customer Satisfaction: NPS improvement correlated with research-informed changes - Onboarding Conversion: First-time user activation rate improvement - Support Ticket Reduction: Fewer UX-related support requests - Feature Adoption: Research-informed features show >20% higher adoption rates

References


Last Updated: March 9, 2026 Status: Production Ready Version: 1.0