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ux-researcher-designer用户体验研究员设计师

Agent Skill

用于辅助界面设计、视觉规范、排版、配色、布局和交互体验优化。它适合让 Agent 根据产品场景整理页面结构、生成 UI 方案、检查视觉一致性或改进组件层级。使用时需要结合现有品牌、设计系统和用户任务,不应只堆装饰元素;涉及真实页面改动时,应通过截图或浏览器预览检查文本溢出、对齐和响应式表现。

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2026-05-01

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请帮我安装这个 Agent Skill:ux-researcher-designer(用户体验研究员设计师)
来源仓库:https://skills.volces.com
仓库路径:ux-researcher-designer
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简介

ux-researcher-designer 用于辅助用户体验研究与设计,适合在 Local Agent 中开展用户调研与界面优化。

  • 适用于用户访谈分析、痛点挖掘和交互方案迭代等场景。
  • 使用时需结合真实用户数据和业务上下文,避免脱离实际场景的设计建议。
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SKILL.md

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

- Workflow 1: Generate User Persona - Workflow 2: Create Journey Map - Workflow 3: Plan Usability Test - Workflow 4: Synthesize Research


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): [{"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 # 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

  1. 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

  1. Map the stages Typical B2B SaaS stages: Awareness → Evaluation → Onboarding → Adoption → Advocacy
  2. 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?
  3. Identify opportunities Priority Score = Frequency × Severity × Solvability
  4. 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

  1. 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

  1. 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)
  2. Calculate segment sizes Cluster Users % Viability Power Users 18 36% Primary persona Business Users 15 30% Primary persona Casual Users 12 24% Secondary persona
  3. Extract key findings For each theme:

- Finding statement - Supporting evidence (quotes, data) - Frequency (X/Y participants) - Business impact - Recommendation

  1. 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?
  2. Reference: See references/persona-methodology.md for analysis framework

Tool Reference

persona_generator.py

Generates data-driven personas from user research data.

ArgumentValuesDefaultDescription
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:

ArchetypeSignalsDesign Focus
power_userDaily use, 10+ featuresEfficiency, customization
casual_userWeekly use, 3-5 featuresSimplicity, guidance
business_userWork context, team useCollaboration, reporting
mobile_firstMobile primaryTouch, offline, speed

Output Components:

ComponentDescription
demographicsAge range, location, occupation, tech level
psychographicsMotivations, values, attitudes, lifestyle
behaviorsUsage patterns, feature preferences
needs_and_goalsPrimary, secondary, functional, emotional
frustrationsPain points with evidence
scenariosContextual usage stories
design_implicationsActionable recommendations
data_pointsSample size, confidence level

Quick Reference Tables

Research Method Selection

Question TypeBest MethodSample Size
"What do users do?"Analytics, observation100+ events
"Why do they do it?"Interviews8-15 users
"How well can they do it?"Usability test5-8 users
"What do they prefer?"Survey, A/B test50+ users
"What do they feel?"Diary study, interviews10-15 users

Persona Confidence Levels

Sample SizeConfidenceUse Case
5-10 usersLowExploratory
11-30 usersMediumDirectional
31+ usersHighProduction

Usability Issue Severity

SeverityDefinitionAction
4 - CriticalPrevents task completionFix immediately
3 - MajorSignificant difficultyFix before release
2 - MinorCauses hesitationFix when possible
1 - CosmeticNoticed but not problematicLow priority

Interview Question Types

TypeExampleUse 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/:

FileContent
persona-methodology.mdValidity criteria, data collection, analysis framework
journey-mapping-guide.mdMapping process, templates, opportunity identification
example-personas.md3 complete persona examples with data
usability-testing-frameworks.mdTest 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

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