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Use for user research, persona creation, journey mapping, and design validation.","Mabbit143\u002FClaude-SKills","Mabbit143","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F192994237?v=4","01M7D6X2W63K4T3N13CSVAKE3V","Mabbit Rountree","01M7D6X2WRPSZF8VMW9MW5ZP1X",0,"MIT","https:\u002F\u002Fgithub.com\u002FMabbit143\u002FClaude-SKills\u002Fblob\u002Fclaude\u002Fregistry-repo-7lRiv\u002Fproduct-team\u002Fskills\u002Fux-researcher-designer\u002FSKILL.md",[],[],"2026-11-15 14:19:17",false,"---\nname: \"ux-researcher-designer\"\ndescription: UX research and design toolkit for Senior UX Designer\u002FResearcher including data-driven persona generation, journey mapping, usability testing frameworks, and research synthesis. Use for user research, persona creation, journey mapping, and design validation.\n---\n\n# UX Researcher & Designer\n\nGenerate user personas from research data, create journey maps, plan usability tests, and synthesize research findings into actionable design recommendations.\n\n---\n\n## Table of Contents\n\n- [Trigger Terms](#trigger-terms)\n- [Workflows](#workflows)\n  - [Workflow 1: Generate User Persona](#workflow-1-generate-user-persona)\n  - [Workflow 2: Create Journey Map](#workflow-2-create-journey-map)\n  - [Workflow 3: Plan Usability Test](#workflow-3-plan-usability-test)\n  - [Workflow 4: Synthesize Research](#workflow-4-synthesize-research)\n- [Tool Reference](#tool-reference)\n- [Quick Reference Tables](#quick-reference-tables)\n- [Knowledge Base](#knowledge-base)\n\n---\n\n## Trigger Terms\n\nUse this skill when you need to:\n\n- \"create user persona\"\n- \"generate persona from data\"\n- \"build customer journey map\"\n- \"map user journey\"\n- \"plan usability test\"\n- \"design usability study\"\n- \"analyze user research\"\n- \"synthesize interview findings\"\n- \"identify user pain points\"\n- \"define user archetypes\"\n- \"calculate research sample size\"\n- \"create empathy map\"\n- \"identify user needs\"\n\n---\n\n## Workflows\n\n### Workflow 1: Generate User Persona\n\n**Situation:** You have user data (analytics, surveys, interviews) and need to create a research-backed persona.\n\n**Steps:**\n\n1. **Prepare user data**\n\n   Required format (JSON):\n   ```json\n   [\n     {\n       \"user_id\": \"user_1\",\n       \"age\": 32,\n       \"usage_frequency\": \"daily\",\n       \"features_used\": [\"dashboard\", \"reports\", \"export\"],\n       \"primary_device\": \"desktop\",\n       \"usage_context\": \"work\",\n       \"tech_proficiency\": 7,\n       \"pain_points\": [\"slow loading\", \"confusing UI\"]\n     }\n   ]\n   ```\n\n2. **Run persona generator**\n   ```bash\n   # Human-readable output\n   python scripts\u002Fpersona_generator.py\n\n   # JSON output for integration\n   python scripts\u002Fpersona_generator.py json\n   ```\n\n3. **Review generated components**\n\n   | Component | What to Check |\n   |-----------|---------------|\n   | Archetype | Does it match the data patterns? |\n   | Demographics | Are they derived from actual data? |\n   | Goals | Are they specific and actionable? |\n   | Frustrations | Do they include frequency counts? |\n   | Design implications | Can designers act on these? |\n\n4. **Validate persona**\n\n   - Show to 3-5 real users: \"Does this sound like you?\"\n   - Cross-check with support tickets\n   - Verify against analytics data\n\n5. **Reference:** See `references\u002Fpersona-methodology.md` for validity criteria\n\n---\n\n### Workflow 2: Create Journey Map\n\n**Situation:** You need to visualize the end-to-end user experience for a specific goal.\n\n**Steps:**\n\n1. **Define scope**\n\n   | Element | Description |\n   |---------|-------------|\n   | Persona | Which user type |\n   | Goal | What they're trying to achieve |\n   | Start | Trigger that begins journey |\n   | End | Success criteria |\n   | Timeframe | Hours\u002Fdays\u002Fweeks |\n\n2. **Gather journey data**\n\n   Sources:\n   - User interviews (ask \"walk me through...\")\n   - Session recordings\n   - Analytics (funnel, drop-offs)\n   - Support tickets\n\n3. **Map the stages**\n\n   Typical B2B SaaS stages:\n   ```\n   Awareness → Evaluation → Onboarding → Adoption → Advocacy\n   ```\n\n4. **Fill in layers for each stage**\n\n   ```\n   Stage: [Name]\n   ├── Actions: What does user do?\n   ├── Touchpoints: Where do they interact?\n   ├── Emotions: How do they feel? (1-5)\n   ├── Pain Points: What frustrates them?\n   └── Opportunities: Where can we improve?\n   ```\n\n5. **Identify opportunities**\n\n   Priority Score = Frequency × Severity × Solvability\n\n6. **Reference:** See `references\u002Fjourney-mapping-guide.md` for templates\n\n---\n\n### Workflow 3: Plan Usability Test\n\n**Situation:** You need to validate a design with real users.\n\n**Steps:**\n\n1. **Define research questions**\n\n   Transform vague goals into testable questions:\n\n   | Vague | Testable |\n   |-------|----------|\n   | \"Is it easy to use?\" | \"Can users complete checkout in \u003C3 min?\" |\n   | \"Do users like it?\" | \"Will users choose Design A or B?\" |\n   | \"Does it make sense?\" | \"Can users find settings without hints?\" |\n\n2. **Select method**\n\n   | Method | Participants | Duration | Best For |\n   |--------|--------------|----------|----------|\n   | Moderated remote | 5-8 | 45-60 min | Deep insights |\n   | Unmoderated remote | 10-20 | 15-20 min | Quick validation |\n   | Guerrilla | 3-5 | 5-10 min | Rapid feedback |\n\n3. **Design tasks**\n\n   Good task format:\n   ```\n   SCENARIO: \"Imagine you're planning a trip to Paris...\"\n   GOAL: \"Book a hotel for 3 nights in your budget.\"\n   SUCCESS: \"You see the confirmation page.\"\n   ```\n\n   Task progression: Warm-up → Core → Secondary → Edge case → Free exploration\n\n4. **Define success metrics**\n\n   | Metric | Target |\n   |--------|--------|\n   | Completion rate | >80% |\n   | Time on task | \u003C2× expected |\n   | Error rate | \u003C15% |\n   | Satisfaction | >4\u002F5 |\n\n5. **Prepare moderator guide**\n\n   - Think-aloud instructions\n   - Non-leading prompts\n   - Post-task questions\n\n6. **Reference:** See `references\u002Fusability-testing-frameworks.md` for full guide\n\n---\n\n### Workflow 4: Synthesize Research\n\n**Situation:** You have raw research data (interviews, surveys, observations) and need actionable insights.\n\n**Steps:**\n\n1. **Code the data**\n\n   Tag each data point:\n   - `[GOAL]` - What they want to achieve\n   - `[PAIN]` - What frustrates them\n   - `[BEHAVIOR]` - What they actually do\n   - `[CONTEXT]` - When\u002Fwhere they use product\n   - `[QUOTE]` - Direct user words\n\n2. **Cluster similar patterns**\n\n   ```\n   User A: Uses daily, advanced features, shortcuts\n   User B: Uses daily, complex workflows, automation\n   User C: Uses weekly, basic needs, occasional\n\n   Cluster 1: A, B (Power Users)\n   Cluster 2: C (Casual User)\n   ```\n\n3. **Calculate segment sizes**\n\n   | Cluster | Users | % | Viability |\n   |---------|-------|---|-----------|\n   | Power Users | 18 | 36% | Primary persona |\n   | Business Users | 15 | 30% | Primary persona |\n   | Casual Users | 12 | 24% | Secondary persona |\n\n4. **Extract key findings**\n\n   For each theme:\n   - Finding statement\n   - Supporting evidence (quotes, data)\n   - Frequency (X\u002FY participants)\n   - Business impact\n   - Recommendation\n\n5. **Prioritize opportunities**\n\n   | Factor | Score 1-5 |\n   |--------|-----------|\n   | Frequency | How often does this occur? |\n   | Severity | How much does it hurt? |\n   | Breadth | How many users affected? |\n   | Solvability | Can we fix this? |\n\n6. **Reference:** See `references\u002Fpersona-methodology.md` for analysis framework\n\n---\n\n## Tool Reference\n\n### persona_generator.py\n\nGenerates data-driven personas from user research data.\n\n| Argument | Values | Default | Description |\n|----------|--------|---------|-------------|\n| format | (none), json | (none) | Output format |\n\n**Sample Output:**\n\n```\n============================================================\nPERSONA: Alex the Power User\n============================================================\n\n📝 A daily user who primarily uses the product for work purposes\n\nArchetype: Power User\nQuote: \"I need tools that can keep up with my workflow\"\n\n👤 Demographics:\n  • Age Range: 25-34\n  • Location Type: Urban\n  • Tech Proficiency: Advanced\n\n🎯 Goals & Needs:\n  • Complete tasks efficiently\n  • Automate workflows\n  • Access advanced features\n\n😤 Frustrations:\n  • Slow loading times (14\u002F20 users)\n  • No keyboard shortcuts\n  • Limited API access\n\n💡 Design Implications:\n  → Optimize for speed and efficiency\n  → Provide keyboard shortcuts and power features\n  → Expose API and automation capabilities\n\n📈 Data: Based on 45 users\n    Confidence: High\n```\n\n**Archetypes Generated:**\n\n| Archetype | Signals | Design Focus |\n|-----------|---------|--------------|\n| power_user | Daily use, 10+ features | Efficiency, customization |\n| casual_user | Weekly use, 3-5 features | Simplicity, guidance |\n| business_user | Work context, team use | Collaboration, reporting |\n| mobile_first | Mobile primary | Touch, offline, speed |\n\n**Output Components:**\n\n| Component | Description |\n|-----------|-------------|\n| demographics | Age range, location, occupation, tech level |\n| psychographics | Motivations, values, attitudes, lifestyle |\n| behaviors | Usage patterns, feature preferences |\n| needs_and_goals | Primary, secondary, functional, emotional |\n| frustrations | Pain points with evidence |\n| scenarios | Contextual usage stories |\n| design_implications | Actionable recommendations |\n| data_points | Sample size, confidence level |\n\n---\n\n## Quick Reference Tables\n\n### Research Method Selection\n\n| Question Type | Best Method | Sample Size |\n|---------------|-------------|-------------|\n| \"What do users do?\" | Analytics, observation | 100+ events |\n| \"Why do they do it?\" | Interviews | 8-15 users |\n| \"How well can they do it?\" | Usability test | 5-8 users |\n| \"What do they prefer?\" | Survey, A\u002FB test | 50+ users |\n| \"What do they feel?\" | Diary study, interviews | 10-15 users |\n\n### Persona Confidence Levels\n\n| Sample Size | Confidence | Use Case |\n|-------------|------------|----------|\n| 5-10 users | Low | Exploratory |\n| 11-30 users | Medium | Directional |\n| 31+ users | High | Production |\n\n### Usability Issue Severity\n\n| Severity | Definition | Action |\n|----------|------------|--------|\n| 4 - Critical | Prevents task completion | Fix immediately |\n| 3 - Major | Significant difficulty | Fix before release |\n| 2 - Minor | Causes hesitation | Fix when possible |\n| 1 - Cosmetic | Noticed but not problematic | Low priority |\n\n### Interview Question Types\n\n| Type | Example | Use For |\n|------|---------|---------|\n| Context | \"Walk me through your typical day\" | Understanding environment |\n| Behavior | \"Show me how you do X\" | Observing actual actions |\n| Goals | \"What are you trying to achieve?\" | Uncovering motivations |\n| Pain | \"What's the hardest part?\" | Identifying frustrations |\n| Reflection | \"What would you change?\" | Generating ideas |\n\n---\n\n## Knowledge Base\n\nDetailed reference guides in `references\u002F`:\n\n| File | Content |\n|------|---------|\n| `persona-methodology.md` | Validity criteria, data collection, analysis framework |\n| `journey-mapping-guide.md` | Mapping process, templates, opportunity identification |\n| `example-personas.md` | 3 complete persona examples with data |\n| `usability-testing-frameworks.md` | Test planning, task design, analysis |\n\n---\n\n## Validation Checklist\n\n### Persona Quality\n- [ ] Based on 20+ users (minimum)\n- [ ] At least 2 data sources (quant + qual)\n- [ ] Specific, actionable goals\n- [ ] Frustrations include frequency counts\n- [ ] Design implications are specific\n- [ ] Confidence level stated\n\n### Journey Map Quality\n- [ ] Scope clearly defined (persona, goal, timeframe)\n- [ ] Based on real user data, not assumptions\n- [ ] All layers filled (actions, touchpoints, emotions)\n- [ ] Pain points identified per stage\n- [ ] Opportunities prioritized\n\n### Usability Test Quality\n- [ ] Research questions are testable\n- [ ] Tasks are realistic scenarios, not instructions\n- [ ] 5+ participants per design\n- [ ] Success metrics defined\n- [ ] Findings include severity ratings\n\n### Research Synthesis Quality\n- [ ] Data coded consistently\n- [ ] Patterns based on 3+ data points\n- [ ] Findings include evidence\n- [ ] Recommendations are actionable\n- [ ] Priorities justified\n\n## Related Skills\n\n- **UI Design System** (`product-team\u002Fui-design-system\u002F`) — Research findings inform design system decisions\n- **Product Manager Toolkit** (`product-team\u002Fproduct-manager-toolkit\u002F`) — Customer interview analysis complements persona research\n","# UX Researcher & Designer\n\nGenerate user personas from research data, create journey maps, plan usability tests, and synthesize research findings into actionable design recommendations.\n\n---\n\n## Table of Contents\n\n- [Trigger Terms](#trigger-terms)\n- [Workflows](#workflows)\n  - [Workflow 1: Generate User Persona](#workflow-1-generate-user-persona)\n  - [Workflow 2: Create Journey Map](#workflow-2-create-journey-map)\n  - [Workflow 3: Plan Usability Test](#workflow-3-plan-usability-test)\n  - [Workflow 4: Synthesize Research](#workflow-4-synthesize-research)\n- [Tool Reference](#tool-reference)\n- [Quick Reference Tables](#quick-reference-tables)\n- [Knowledge Base](#knowledge-base)\n\n---\n\n## Trigger Terms\n\nUse this skill when you need to:\n\n- \"create user persona\"\n- \"generate persona from data\"\n- \"build customer journey map\"\n- \"map user journey\"\n- \"plan usability test\"\n- \"design usability study\"\n- \"analyze user research\"\n- \"synthesize interview findings\"\n- \"identify user pain points\"\n- \"define user archetypes\"\n- \"calculate research sample size\"\n- \"create empathy map\"\n- \"identify user needs\"\n\n---\n\n## Workflows\n\n### Workflow 1: Generate User Persona\n\n**Situation:** You have user data (analytics, surveys, interviews) and need to create a research-backed persona.\n\n**Steps:**\n\n1. **Prepare user data**\n\n   Required format (JSON):\n   ```json\n   [\n     {\n       \"user_id\": \"user_1\",\n       \"age\": 32,\n       \"usage_frequency\": \"daily\",\n       \"features_used\": [\"dashboard\", \"reports\", \"export\"],\n       \"primary_device\": \"desktop\",\n       \"usage_context\": \"work\",\n       \"tech_proficiency\": 7,\n       \"pain_points\": [\"slow loading\", \"confusing UI\"]\n     }\n   ]\n   ```\n\n2. **Run persona generator**\n   ```bash\n   # Human-readable output\n   python scripts\u002Fpersona_generator.py\n\n   # JSON output for integration\n   python scripts\u002Fpersona_generator.py json\n   ```\n\n3. **Review generated components**\n\n   | Component | What to Check |\n   |-----------|---------------|\n   | Archetype | Does it match the data patterns? |\n   | Demographics | Are they derived from actual data? |\n   | Goals | Are they specific and actionable? |\n   | Frustrations | Do they include frequency counts? |\n   | Design implications | Can designers act on these? |\n\n4. **Validate persona**\n\n   - Show to 3-5 real users: \"Does this sound like you?\"\n   - Cross-check with support tickets\n   - Verify against analytics data\n\n5. **Reference:** See `references\u002Fpersona-methodology.md` for validity criteria\n\n---\n\n### Workflow 2: Create Journey Map\n\n**Situation:** You need to visualize the end-to-end user experience for a specific goal.\n\n**Steps:**\n\n1. **Define scope**\n\n   | Element | Description |\n   |---------|-------------|\n   | Persona | Which user type |\n   | Goal | What they're trying to achieve |\n   | Start | Trigger that begins journey |\n   | End | Success criteria |\n   | Timeframe | Hours\u002Fdays\u002Fweeks |\n\n2. **Gather journey data**\n\n   Sources:\n   - User interviews (ask \"walk me through...\")\n   - Session recordings\n   - Analytics (funnel, drop-offs)\n   - Support tickets\n\n3. **Map the stages**\n\n   Typical B2B SaaS stages:\n   ```\n   Awareness → Evaluation → Onboarding → Adoption → Advocacy\n   ```\n\n4. **Fill in layers for each stage**\n\n   ```\n   Stage: [Name]\n   ├── Actions: What does user do?\n   ├── Touchpoints: Where do they interact?\n   ├── Emotions: How do they feel? (1-5)\n   ├── Pain Points: What frustrates them?\n   └── Opportunities: Where can we improve?\n   ```\n\n5. **Identify opportunities**\n\n   Priority Score = Frequency × Severity × Solvability\n\n6. **Reference:** See `references\u002Fjourney-mapping-guide.md` for templates\n\n---\n\n### Workflow 3: Plan Usability Test\n\n**Situation:** You need to validate a design with real users.\n\n**Steps:**\n\n1. **Define research questions**\n\n   Transform vague goals into testable questions:\n\n   | Vague | Testable |\n   |-------|----------|\n   | \"Is it easy to use?\" | \"Can users complete checkout in \u003C3 min?\" |\n   | \"Do users like it?\" | \"Will users choose Design A or B?\" |\n   | \"Does it make sense?\" | \"Can users find settings without hints?\" |\n\n2. **Select method**\n\n   | Method | Participants | Duration | Best For |\n   |--------|--------------|----------|----------|\n   | Moderated remote | 5-8 | 45-60 min | Deep insights |\n   | Unmoderated remote | 10-20 | 15-20 min | Quick validation |\n   | Guerrilla | 3-5 | 5-10 min | Rapid feedback |\n\n3. **Design tasks**\n\n   Good task format:\n   ```\n   SCENARIO: \"Imagine you're planning a trip to Paris...\"\n   GOAL: \"Book a hotel for 3 nights in your budget.\"\n   SUCCESS: \"You see the confirmation page.\"\n   ```\n\n   Task progression: Warm-up → Core → Secondary → Edge case → Free exploration\n\n4. **Define success metrics**\n\n   | Metric | Target |\n   |--------|--------|\n   | Completion rate | >80% |\n   | Time on task | \u003C2× expected |\n   | Error rate | \u003C15% |\n   | Satisfaction | >4\u002F5 |\n\n5. **Prepare moderator guide**\n\n   - Think-aloud instructions\n   - Non-leading prompts\n   - Post-task questions\n\n6. **Reference:** See `references\u002Fusability-testing-frameworks.md` for full guide\n\n---\n\n### Workflow 4: Synthesize Research\n\n**Situation:** You have raw research data (interviews, surveys, observations) and need actionable insights.\n\n**Steps:**\n\n1. **Code the data**\n\n   Tag each data point:\n   - `[GOAL]` - What they want to achieve\n   - `[PAIN]` - What frustrates them\n   - `[BEHAVIOR]` - What they actually do\n   - `[CONTEXT]` - When\u002Fwhere they use product\n   - `[QUOTE]` - Direct user words\n\n2. **Cluster similar patterns**\n\n   ```\n   User A: Uses daily, advanced features, shortcuts\n   User B: Uses daily, complex workflows, automation\n   User C: Uses weekly, basic needs, occasional\n\n   Cluster 1: A, B (Power Users)\n   Cluster 2: C (Casual User)\n   ```\n\n3. **Calculate segment sizes**\n\n   | Cluster | Users | % | Viability |\n   |---------|-------|---|-----------|\n   | Power Users | 18 | 36% | Primary persona |\n   | Business Users | 15 | 30% | Primary persona |\n   | Casual Users | 12 | 24% | Secondary persona |\n\n4. **Extract key findings**\n\n   For each theme:\n   - Finding statement\n   - Supporting evidence (quotes, data)\n   - Frequency (X\u002FY participants)\n   - Business impact\n   - Recommendation\n\n5. **Prioritize opportunities**\n\n   | Factor | Score 1-5 |\n   |--------|-----------|\n   | Frequency | How often does this occur? |\n   | Severity | How much does it hurt? |\n   | Breadth | How many users affected? |\n   | Solvability | Can we fix this? |\n\n6. **Reference:** See `references\u002Fpersona-methodology.md` for analysis framework\n\n---\n\n## Tool Reference\n\n### persona_generator.py\n\nGenerates data-driven personas from user research data.\n\n| Argument | Values | Default | Description |\n|----------|--------|---------|-------------|\n| format | (none), json | (none) | Output format |\n\n**Sample Output:**\n\n```\n============================================================\nPERSONA: Alex the Power User\n============================================================\n\n📝 A daily user who primarily uses the product for work purposes\n\nArchetype: Power User\nQuote: \"I need tools that can keep up with my workflow\"\n\n👤 Demographics:\n  • Age Range: 25-34\n  • Location Type: Urban\n  • Tech Proficiency: Advanced\n\n🎯 Goals & Needs:\n  • Complete tasks efficiently\n  • Automate workflows\n  • Access advanced features\n\n😤 Frustrations:\n  • Slow loading times (14\u002F20 users)\n  • No keyboard shortcuts\n  • Limited API access\n\n💡 Design Implications:\n  → Optimize for speed and efficiency\n  → Provide keyboard shortcuts and power features\n  → Expose API and automation capabilities\n\n📈 Data: Based on 45 users\n    Confidence: High\n```\n\n**Archetypes Generated:**\n\n| Archetype | Signals | Design Focus |\n|-----------|---------|--------------|\n| power_user | Daily use, 10+ features | Efficiency, customization |\n| casual_user | Weekly use, 3-5 features | Simplicity, guidance |\n| business_user | Work context, team use | Collaboration, reporting |\n| mobile_first | Mobile primary | Touch, offline, speed |\n\n**Output Components:**\n\n| Component | Description |\n|-----------|-------------|\n| demographics | Age range, location, occupation, tech level |\n| psychographics | Motivations, values, attitudes, lifestyle |\n| behaviors | Usage patterns, feature preferences |\n| needs_and_goals | Primary, secondary, functional, emotional |\n| frustrations | Pain points with evidence |\n| scenarios | Contextual usage stories |\n| design_implications | Actionable recommendations |\n| data_points | Sample size, confidence level |\n\n---\n\n## Quick Reference Tables\n\n### Research Method Selection\n\n| Question Type | Best Method | Sample Size |\n|---------------|-------------|-------------|\n| \"What do users do?\" | Analytics, observation | 100+ events |\n| \"Why do they do it?\" | Interviews | 8-15 users |\n| \"How well can they do it?\" | Usability test | 5-8 users |\n| \"What do they prefer?\" | Survey, A\u002FB test | 50+ users |\n| \"What do they feel?\" | Diary study, interviews | 10-15 users |\n\n### Persona Confidence Levels\n\n| Sample Size | Confidence | Use Case |\n|-------------|------------|----------|\n| 5-10 users | Low | Exploratory |\n| 11-30 users | Medium | Directional |\n| 31+ users | High | Production |\n\n### Usability Issue Severity\n\n| Severity | Definition | Action |\n|----------|------------|--------|\n| 4 - Critical | Prevents task completion | Fix immediately |\n| 3 - Major | Significant difficulty | Fix before release |\n| 2 - Minor | Causes hesitation | Fix when possible |\n| 1 - Cosmetic | Noticed but not problematic | Low priority |\n\n### Interview Question Types\n\n| Type | Example | Use For |\n|------|---------|---------|\n| Context | \"Walk me through your typical day\" | Understanding environment |\n| Behavior | \"Show me how you do X\" | Observing actual actions |\n| Goals | \"What are you trying to achieve?\" | Uncovering motivations |\n| Pain | \"What's the hardest part?\" | Identifying frustrations |\n| Reflection | \"What would you change?\" | Generating ideas |\n\n---\n\n## Knowledge Base\n\nDetailed reference guides in `references\u002F`:\n\n| File | Content |\n|------|---------|\n| `persona-methodology.md` | Validity criteria, data collection, analysis framework |\n| `journey-mapping-guide.md` | Mapping process, templates, opportunity identification |\n| `example-personas.md` | 3 complete persona examples with data |\n| `usability-testing-frameworks.md` | Test planning, task design, analysis |\n\n---\n\n## Validation Checklist\n\n### Persona Quality\n- [ ] Based on 20+ users (minimum)\n- [ ] At least 2 data sources (quant + qual)\n- [ ] Specific, actionable goals\n- [ ] Frustrations include frequency counts\n- [ ] Design implications are specific\n- [ ] Confidence level stated\n\n### Journey Map Quality\n- [ ] Scope clearly defined (persona, goal, timeframe)\n- [ ] Based on real user data, not assumptions\n- [ ] All layers filled (actions, touchpoints, emotions)\n- [ ] Pain points identified per stage\n- [ ] Opportunities prioritized\n\n### Usability Test Quality\n- [ ] Research questions are testable\n- [ ] Tasks are realistic scenarios, not instructions\n- [ ] 5+ participants per design\n- [ ] Success metrics defined\n- [ ] Findings include severity ratings\n\n### Research Synthesis Quality\n- [ ] Data coded consistently\n- [ ] Patterns based on 3+ data points\n- [ ] Findings include evidence\n- [ ] Recommendations are actionable\n- [ ] Priorities justified\n\n## Related Skills\n\n- **UI Design System** (`product-team\u002Fui-design-system\u002F`) — Research findings inform design system decisions\n- **Product Manager Toolkit** (`product-team\u002Fproduct-manager-toolkit\u002F`) — Customer interview analysis complements persona research\n",{"name":5,"description":7},"claude\u002Fregistry-repo-7lRiv","44e1a5b2d387b250bcd0794f7eb5e1228223d1e2","product-team\u002Fskills\u002Fux-researcher-designer","https:\u002F\u002Fgithub.com\u002FMabbit143\u002FClaude-SKills","https:\u002F\u002Fgithub.com\u002FMabbit143","I’m edgy and fun, probably too serious, but I love an 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ux-researcher-designer","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FMabbit143\u002FClaude-SKills\u002Fblob\u002Fclaude\u002Fregistry-repo-7lRiv\u002Fproduct-team\u002Fskills\u002Fux-researcher-designer\u002FSKILL.md",true,[45,51,57,61,65,69],{"path":46,"resourceType":47,"resourceTypeDesc":48,"sizeBytes":49,"sourceHtmlUrl":50},"assets\u002Fresearch_plan_template.md","ASSET","资产文件",4802,"https:\u002F\u002Fgithub.com\u002FMabbit143\u002FClaude-SKills\u002Fblob\u002Fclaude\u002Fregistry-repo-7lRiv\u002Fproduct-team\u002Fskills\u002Fux-researcher-designer\u002Fassets\u002Fresearch_plan_template.md",{"path":52,"resourceType":53,"resourceTypeDesc":54,"sizeBytes":55,"sourceHtmlUrl":56},"references\u002Fexample-personas.md","REFERENCE","参考文档",11990,"https:\u002F\u002Fgithub.com\u002FMabbit143\u002FClaude-SKills\u002Fblob\u002Fclaude\u002Fregistry-repo-7lRiv\u002Fproduct-team\u002Fskills\u002Fux-researcher-designer\u002Freferences\u002Fexample-personas.md",{"path":58,"resourceType":53,"resourceTypeDesc":54,"sizeBytes":59,"sourceHtmlUrl":60},"references\u002Fjourney-mapping-guide.md",18102,"https:\u002F\u002Fgithub.com\u002FMabbit143\u002FClaude-SKills\u002Fblob\u002Fclaude\u002Fregistry-repo-7lRiv\u002Fproduct-team\u002Fskills\u002Fux-researcher-designer\u002Freferences\u002Fjourney-mapping-guide.md",{"path":62,"resourceType":53,"resourceTypeDesc":54,"sizeBytes":63,"sourceHtmlUrl":64},"references\u002Fpersona-methodology.md",11644,"https:\u002F\u002Fgithub.com\u002FMabbit143\u002FClaude-SKills\u002Fblob\u002Fclaude\u002Fregistry-repo-7lRiv\u002Fproduct-team\u002Fskills\u002Fux-researcher-designer\u002Freferences\u002Fpersona-methodology.md",{"path":66,"resourceType":53,"resourceTypeDesc":54,"sizeBytes":67,"sourceHtmlUrl":68},"references\u002Fusability-testing-frameworks.md",11932,"https:\u002F\u002Fgithub.com\u002FMabbit143\u002FClaude-SKills\u002Fblob\u002Fclaude\u002Fregistry-repo-7lRiv\u002Fproduct-team\u002Fskills\u002Fux-researcher-designer\u002Freferences\u002Fusability-testing-frameworks.md",{"path":70,"resourceType":71,"resourceTypeDesc":72,"sizeBytes":73,"sourceHtmlUrl":74},"scripts\u002Fpersona_generator.py","SCRIPT","脚本",23675,"https:\u002F\u002Fgithub.com\u002FMabbit143\u002FClaude-SKills\u002Fblob\u002Fclaude\u002Fregistry-repo-7lRiv\u002Fproduct-team\u002Fskills\u002Fux-researcher-designer\u002Fscripts\u002Fpersona_generator.py",[76,83,90,97,104,111],{"skillNo":77,"name":78,"nameZh":6,"description":79,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":80,"categories":81,"keywords":82,"publishedAt":19},"01M7D99ZA4F916M5CM3K2EQFE8","syllabus","Generates a curated supplementary reading list from any course syllabus using Consensus academic search. Grill-me intake (syllabus input format + course audience + year range) plus a grouping forcing-options checkpoint before any search runs — so the reading list matches the course's level and recency need. Parses the syllabus to extract topics and learning outcomes, searches Consensus for recent peer-reviewed papers per topic, and produces a professionally formatted .docx with clickable Consensus links, plain-language summaries calibrated to audience level, and Bloom-higher-order discussion questions tied to course learning goals. Triggers whenever a user uploads a syllabus, course outline, or curriculum document and wants supplementary readings. Also triggers on: 'syllabus reading list', 'find papers for my course', 'create a reading list from this syllabus', 'recent research for my class', 'supplementary readings', 'find journal articles for these topics', 'what recent papers cover this material', 'any new research on these course topics', 'update my syllabus with recent papers'. Even casual mentions when a syllabus is attached should trigger this skill.","https:\u002F\u002Fgithub.com\u002FMabbit143\u002FClaude-SKills\u002Fblob\u002Fclaude\u002Fregistry-repo-7lRiv\u002Fresearch\u002Fsyllabus\u002Fskills\u002Fsyllabus\u002FSKILL.md",[],[],{"skillNo":84,"name":85,"nameZh":6,"description":86,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":87,"categories":88,"keywords":89,"publishedAt":19},"01M7D99ND4B38EG1BYQX722F5D","research","Default entry point for any research request — a hybrid router that classifies the question deterministically and either delegates to a specialist research skill (pulse for trends\u002Fsentiment, grants for NIH funding, litreview for academic literature, syllabus for course reading, patent for prior-art + IP landscape, dossier for entity research) or runs its own plan-decompose-multi-source-search-synthesize-cite fallback workflow when no specialist matches. Always surfaces the routing decision so users can override. Triggers — \"research [topic]\", \"look into [topic]\", \"what do we know about [topic]\", \"investigate [topic]\", \"find me information on [topic]\", \"do some research on [topic]\", \"I need to understand [topic]\", or any research request that doesn't obviously match a more-specific specialist skill. Output is a markdown briefing (default) or .docx document (on request) with full citations and an audit log.","https:\u002F\u002Fgithub.com\u002FMabbit143\u002FClaude-SKills\u002Fblob\u002Fclaude\u002Fregistry-repo-7lRiv\u002Fresearch\u002Fresearch\u002Fskills\u002Fresearch\u002FSKILL.md",[],[],{"skillNo":91,"name":92,"nameZh":6,"description":93,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":94,"categories":95,"keywords":96,"publishedAt":19},"01M7D999VS936SV9TX940A98AQ","pulse","Multi-source recency research skill that takes the pulse of any topic across Reddit, Hacker News, the open web, and optionally X\u002FTwitter within a configurable recent window (default 30 days). Forcing intake clarifies topic specificity, angle (trend\u002Fsentiment\u002Fproblems\u002Fopportunities\u002Fcomparison), time window, and platform scope before searching. Returns a synthesized briefing with citations, engagement metrics, and cross-platform pattern analysis. Triggers: 'pulse on [topic]', 'what's happening with [topic]', 'what are people saying about [topic]', 'current conversation about [topic]', 'take the pulse of [topic]', 'trending: [topic]', 'find me info on [topic]', or any variation requesting multi-source recency intelligence on a topic. Also use for competitor research, trend discovery, tool comparisons, and audience sentiment analysis.","https:\u002F\u002Fgithub.com\u002FMabbit143\u002FClaude-SKills\u002Fblob\u002Fclaude\u002Fregistry-repo-7lRiv\u002Fresearch\u002Fpulse\u002Fskills\u002Fpulse\u002FSKILL.md",[],[],{"skillNo":98,"name":99,"nameZh":6,"description":100,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":101,"categories":102,"keywords":103,"publishedAt":19},"01M7D98XBECS6368GEJNG8C1Z1","patent","Patent prior-art and landscape intelligence skill — not generic patent help. Commits to one of five sub-use-cases via forcing intake (novelty search \u002F freedom-to-operate \u002F competitive landscape \u002F acquisition diligence \u002F litigation prior-art) before any search runs. Searches Google Patents, Espacenet, USPTO, and optionally Lens.org for citation-graph signals. Output is an editable Word document (.docx) with verdict, ranked closest art (claim-text extracted), CPC-class-aware landscape, family-resolved hits, geographic coverage, FTO flags where applicable, strategy recommendations, and full audit log. Triggers: 'prior art search for [invention]', 'patent search on [topic]', 'freedom to operate analysis', 'FTO for [product]', 'patent landscape for [field]', 'is [invention] novel', 'patents on [topic]', 'competitive patent analysis', 'prior art for litigation', 'patent diligence on [company]'. Produces search signal, not legal advice — always recommends consulting a patent attorney before filing or licensing decisions. Trademark, copyright, and trade-secret questions are out of scope.","https:\u002F\u002Fgithub.com\u002FMabbit143\u002FClaude-SKills\u002Fblob\u002Fclaude\u002Fregistry-repo-7lRiv\u002Fresearch\u002Fpatent\u002Fskills\u002Fpatent\u002FSKILL.md",[],[],{"skillNo":105,"name":106,"nameZh":6,"description":107,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":108,"categories":109,"keywords":110,"publishedAt":19},"01M7D98N2R7CA7RM00PNP4VV6C","notebooklm","Browser automation skill for controlling Google's NotebookLM. Handles reading and querying notebooks, adding sources (URLs, text, files, YouTube links, synthesized content), generating Studio outputs (Audio Overview, infographics, slide decks, study guides, briefing docs, mind maps, timelines, FAQs), and creating new notebooks. Triggers on any phrase involving NotebookLM — 'open NotebookLM', 'check my [name] notebook', 'pull info from NotebookLM', 'ask my notebook about X', 'add [source] to NotebookLM', 'create an infographic in NotebookLM', 'use NotebookLM Studio', 'generate a slide deck from my notebook', or any variation where the goal involves NotebookLM. Requires browser automation environment — fails gracefully when unavailable.","https:\u002F\u002Fgithub.com\u002FMabbit143\u002FClaude-SKills\u002Fblob\u002Fclaude\u002Fregistry-repo-7lRiv\u002Fresearch\u002Fnotebooklm\u002Fskills\u002Fnotebooklm\u002FSKILL.md",[],[],{"skillNo":112,"name":113,"nameZh":6,"description":114,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":115,"categories":116,"keywords":117,"publishedAt":19},"01M7D98B1SCTS4RAWZFCF9QJ5M","litreview","Academic literature orientation skill that searches papers via Consensus, builds a strategic search plan using PICO (default) or SPIDER \u002F Decomposition \u002F hybrid as fallbacks, and synthesizes findings into a professionally formatted Word document (.docx) research guide. Grill-me intake (research question specificity + framework hint + tentative depth) before the recon search; a second forcing checkpoint after Phase 2 confirms framework + sub-areas + depth before searches consume budget. Configurable depth (5\u002F10\u002F20 queries) controls coverage vs. speed. Output is a 'launching pad' — not a finished review, but an orientation guide that lets a researcher dive in confidently. Triggers: 'litreview on [topic]', 'literature review on [topic]', 'I'm starting a literature review on X', 'I'm writing a paper on X', 'help me research X', 'I'm doing research on X', 'can you help me research X'. Do NOT trigger for single one-off paper searches where the user just wants a quick list — that's a plain Consensus search.","https:\u002F\u002Fgithub.com\u002FMabbit143\u002FClaude-SKills\u002Fblob\u002Fclaude\u002Fregistry-repo-7lRiv\u002Fresearch\u002Flitreview\u002Fskills\u002Flitreview\u002FSKILL.md",[],[]]