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Ux Researcher Designer

UX research and design toolkit for Senior UX Designer/Researcher including data-driven persona generation, journey mapping, usability testing frameworks, and research synthesis. Use when conducting user research, creating personas, mapping user journeys, planning usability tests…

testing
By alirezarezvani
21k2.8kUpdated 3 days agoPythonMIT

Skill Content

# 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

- [Trigger Terms](#trigger-terms)
- [Workflows](#workflows)
  - [Workflow 1: Generate User Persona](#workflow-1-generate-user-persona)
  - [Workflow 2: Create Journey Map](#workflow-2-create-journey-map)
  - [Workflow 3: Plan Usability Test](#workflow-3-plan-usability-test)
  - [Workflow 4: Synthesize Research](#workflow-4-synthesize-research)
- [Tool Reference](#tool-reference)
- [Quick Reference Tables](#quick-reference-tables)
- [Knowledge Base](#knowledge-base)

---

## 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):
   ```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**
   ```bash
   # 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

5. **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

3. **Map the stages**

   Typical B2B SaaS stages:
   ```
   Awareness → Evaluation → Onboarding → Adoption → Advocacy
   ```

4. **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?
   ```

5. **Identify opportunities**

   Priority Score = Frequency × Severity × Solvability

6. **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

6. **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

2. **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)
   ```

3. **Calculate segment sizes**

   | Cluster | Users | % | Viability |
   |---------|-------|---|-----------|
   | Power Users | 18 | 36% | Primary persona |
   | Business Users | 15 | 30% | Primary persona |
   | Casual Users | 12 | 24% | Secondary persona |

4. **Extract key findings**

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

5. **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? |

6. **Reference:** See `references/persona-methodology.md` for analysis framework

---

## Tool Reference

### persona_generator.py

Generates data-driven personas from user research data.

| Argument | Values | Default | Description |
|----------|--------|---------|-------------|
| 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:**

| Archetype | Signals | Design Focus |
|-----------|---------|--------------|
| power_user | Daily use, 10+ features | Efficiency, customization |
| casual_user | Weekly use, 3-5 features | Simplicity, guidance |
| business_user | Work context, team use | Collaboration, reporting |
| mobile_first | Mobile primary | Touch, offline, speed |

**Output Components:**

| Component | Description |
|-----------|-------------|
| demographics | Age range, location, occupation, tech level |
| psychographics | Motivations, values, attitudes, lifestyle |
| behaviors | Usage patterns, feature preferences |
| needs_and_goals | Primary, secondary, functional, emotional |
| frustrations | Pain points with evidence |
| scenarios | Contextual usage stories |
| design_implications | Actionable recommendations |
| data_points | Sample size, confidence level |

---

## Quick Reference Tables

### Research Method Selection

| Question Type | Best Method | Sample Size |
|---------------|-------------|-------------|
| "What do users do?" | Analytics, observation | 100+ events |
| "Why do they do it?" | Interviews | 8-15 users |
| "How well can they do it?" | Usability test | 5-8 users |
| "What do they prefer?" | Survey, A/B test | 50+ users |
| "What do they feel?" | Diary study, interviews | 10-15 users |

### Persona Confidence Levels

| Sample Size | Confidence | Use Case |
|-------------|------------|----------|
| 5-10 users | Low | Exploratory |
| 11-30 users | Medium | Directional |
| 31+ users | High | Production |

### Usability Issue Severity

| Severity | Definition | Action |
|----------|------------|--------|
| 4 - Critical | Prevents task completion | Fix immediately |
| 3 - Major | Significant difficulty | Fix before release |
| 2 - Minor | Causes hesitation | Fix when possible |
| 1 - Cosmetic | Noticed but not problematic | Low priority |

### Interview Question Types

| Type | Example | Use 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/`:

| File | Content |
|------|---------|
| `persona-methodology.md` | Validity criteria, data collection, analysis framework |
| `journey-mapping-guide.md` | Mapping process, templates, opportunity identification |
| `example-personas.md` | 3 complete persona examples with data |
| `usability-testing-frameworks.md` | Test 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

## Related Skills

- **UI Design System** (`product-team/ui-design-system/`) — Research findings inform design system decisions
- **Product Manager Toolkit** (`product-team/product-manager-toolkit/`) — Customer interview analysis complements persona research

How to use

  1. Copy the skill content above
  2. Create a .claude/skills directory in your project
  3. Save as .claude/skills/claude-skills-ux-researcher-designer.md
  4. Use /claude-skills-ux-researcher-designer in Claude Code to invoke this skill

Claude Code Skills & Plugins — Agent Skills for Every Coding Tool

355 production-ready Claude Code skills, plugins, and agent skills for 13 AI coding tools.

The most comprehensive open-source library of Claude Code skills and agent plugins — also works with OpenAI Codex, Gemini CLI, Cursor, and 9 more coding agents. Reusable expertise packages covering engineering, DevOps, marketing (incl. AEO — Answer Engine Optimization for LLM citation), security (PreToolUse hooks), compliance, C-level advisory (incl. founder-mode CFO/CMO/CRO/CPO/COO/CHRO/CISO/GC/CDO/CAIO/CCO/VPE personas + 21 /cs:* slash commands), productivity (capture/email/reflect), an academic research stack (litreview/grants/dossier/patent/syllabus/pulse/notebooklm/deep-research + hybrid router), and enterprise Research Operations (clinical-research/research-finance/market-research/product-research, v2.9.0).

Works with: Claude Code · OpenAI Codex · Gemini CLI · OpenClaw · Hermes Agent1 · Mistral Vibe2 · Cursor · Aider · Windsurf · Kilo Code · OpenCode · Augment · Antigravity

License: MIT Skills Agents Personas Commands Stars SkillCheck Validated

5,200+ GitHub stars — the most comprehensive open-source Claude Code skills & agent plugins library.


What Are Claude Code Skills & Agent Plugins?

Claude Code skills (also called agent skills or coding agent plugins) are modular instruction packages that give AI coding agents domain expertise they don't have out of the box. Each skill includes:

  • SKILL.md — structured instructions, workflows, and decision frameworks
  • Python tools — 602 CLI scripts (all stdlib-only, zero pip installs)
  • Reference docs — 711 templates, checklists, and domain-specific knowledge files

One repo, thirteen platforms. Works natively as Claude Code plugins, Codex agent skills, Gemini CLI skills, Hermes Agent skills, Mistral Vibe skills, and converts to more tools via scripts/convert.sh. All 602 Python tools run anywhere Python runs.

Skills vs Agents vs Personas

SkillsAgentsPersonas
PurposeHow to execute a taskWhat task to doWho is thinking
ScopeSingle domainSingle domainCross-domain
VoiceNeutralProfessionalPersonality-driven
Example"Follow these steps for SEO""Run a security audit""Think like a startup CTO"

All three work together. See Orchestration for how to combine them.


Quick Install

Gemini CLI (New)

# Clone the repository
git clone https://github.com/alirezarezvani/claude-skills.git
cd claude-skills

# Run the setup script
./scripts/gemini-install.sh

# Start using skills
> activate_skill(name="senior-architect")

Claude Code (Recommended)

# Add the marketplace
/plugin marketplace add alirezarezvani/claude-skills

# Install by domain
/plugin install engineering-skills@claude-code-skills          # 24 core engineering
/plugin install engineering-advanced-skills@claude-code-skills  # 25 POWERFUL-tier
/plugin install product-skills@claude-code-skills               # 12 product skills
/plugin install marketing-skills@claude-code-skills             # 43 marketing skills
/plugin install ra-qm-skills@claude-code-skills                 # 12 regulatory/quality
/plugin install pm-skills@claude-code-skills                    # 6 project management
/plugin install c-level-skills@claude-code-skills               # 28 C-level advisory (full C-suite)
/plugin install business-growth-skills@claude-code-skills       # 4 business & growth
/plugin install finance-skills@claude-code-skills               # 2 finance (analyst + SaaS metrics)

# Or install individual skills
/plugin install skill-security-auditor@claude-code-skills       # Security scanner
/plugin install playwright-pro@claude-code-skills                  # Playwright testing toolkit
/plugin install self-improving-agent@claude-code-skills         # Auto-memory curation
/plugin install content-creator@claude-code-skills              # Single skill

OpenAI Codex

npx agent-skills-cli add alirezarezvani/claude-skills --agent codex
# Or: git clone + ./scripts/codex-install.sh

OpenClaw

bash <(curl -s https://raw.githubusercontent.com/alirezarezvani/claude-skills/main/scripts/openclaw-install.sh)

Manual Installation

git clone https://github.com/alirezarezvani/claude-skills.git
# Copy any skill folder to ~/.claude/skills/ (Claude Code) or ~/.codex/skills/ (Codex)

Multi-Tool Support (New)

Convert all 345 skills to 9 AI coding tools with a single script:

ToolFormatInstall
Cursor.mdc rules./scripts/install.sh --tool cursor --target .
AiderCONVENTIONS.md./scripts/install.sh --tool aider --target .
Kilo Code.kilocode/rules/./scripts/install.sh --tool kilocode --target .
Windsurf.windsurf/skills/./scripts/install.sh --tool windsurf --target .
OpenCode.opencode/skills/./scripts/install.sh --tool opencode --target .
Augment.augment/rules/./scripts/install.sh --tool augment --target .
Antigravity~/.gemini/antigravity/skills/./scripts/install.sh --tool antigravity
Hermes Agent~/.hermes/skills/python scripts/sync-hermes-skills.py --verbose
Mistral Vibe~/.vibe/skills/./scripts/vibe-install.sh

How it works:

# 1. Convert all skills to all tools (takes ~15 seconds)
./scripts/convert.sh --tool all

# 2. Install into your project (with confirmation)
./scripts/install.sh --tool cursor --target /path/to/project

# Or use --force to skip confirmation:
./scripts/install.sh --tool aider --target . --force

# 3. Verify
find .cursor/rules -name "*.mdc" | wc -l  # Should show 346

Each tool gets:

  • ✅ All 345 skills converted to native format
  • ✅ Per-tool README with install/verify/update steps
  • ✅ Support for scripts, references, templates where applicable
  • ✅ Zero manual conversion work

Run ./scripts/convert.sh --tool all to generate tool-specific outputs locally.


Skills Overview

355 skills across 18 domains:

DomainSkillsHighlightsDetails
🔧 Engineering — Core52Architecture, frontend, backend, fullstack, QA, DevOps, SecOps, AI/ML, data, Playwright Pro (test gen, flaky fix, migrations), self-improving agent (auto-memory curation), security suite, a11y audit, named-persona-adversarial-review (review via named engineering philosophies)engineering-team/
⚡ Engineering — POWERFUL81Agent designer, RAG architect, database designer, CI/CD builder, security auditor, MCP builder, AgentHub, Helm charts, Terraform, self-eval, llm-wiki, tc-tracker, autoresearch-agent, reliability portfolio (feature-flags-architect, kubernetes-operator, chaos-engineering, slo-architect), ship-gate, security-guidance PreToolUse hook, Matt Pocock skills (write-a-skill, caveman, grill-me, handoff, grill-with-docs), zero-hallucination-coder (Discuss→Map→Decompose→Execute→Verify), agent-harness (goal→plan→execute→verify→close loops over any domain)engineering/
🎯 Product17Product manager, agile PO, strategist, UX researcher, UI design, landing pages, SaaS scaffolder, analytics, experiment designer, discovery, roadmap communicator, code-to-prd, apple-hig-expertproduct-team/
📣 Marketing488 pods: Content, SEO + AEO (aeo — E-E-A-T audit, citation tracking across 5 LLMs) + local (local-seo-manager — GBP/NAP/Map-Pack), CRO, Channels, Growth, Intelligence, Sales + context foundation + orchestration routermarketing-skill/
🚀 Productivity7capture (brain-dump-to-action), email pair (inbox-setup + inbox-triage), reflect (journal), handoff (Matt Pocock-inspired), andreessen (market-first decision mode), roast (5-angle idea panel → GO/RESHAPE/KILL)productivity/
🎨 Marketing (top-level)1landing — single-file HTML landing-page generator (4 design styles, GSAP patterns, brand palette validator)marketing/
🔬 Research (academic)9research orchestrator (hybrid router + fallback) + 8 specialists: pulse, litreview, grants (NIH), dossier, patent, syllabus, notebooklm, deep-research (rigor-first meta-research)research/
🧪 Research Operations ✨v2.9.05Enterprise/cross-functional research: orchestrator + clinical-research (study design), research-finance (R&D program finance), market-research (sizing/survey/segmentation), product-research (user research) — each with onboarding + customization + opt-in autoresearch bridgeresearch-ops/
📋 Project Management9Senior PM, scrum master, Jira, Confluence, Atlassian admin, templates + bundled Atlassian Remote MCPproject-management/
🏥 Regulatory & QM19ISO 13505, MDR 2017/745, FDA, ISO 27001, GDPR, SOC 2, CAPA, risk management, agent-decision-receipts (PQ-signed action receipts)ra-qm-team/
🛡️ Compliance OS9Compliance operating system — controls, evidence, audit-readiness workflowscompliance-os/
💼 C-Level Advisory68Full C-suite (CEO/CTO/CFO/CMO/CRO/CPO/COO/CHRO/CISO/GC/CDO/CAIO/CCO/VPE) + founder-mode agents + orchestration + board meetings + culture & collaborationc-level-advisor/
📈 Business & Growth5Customer success, sales engineer, revenue ops, contracts & proposals, BizDev toolkitbusiness-growth/
🏭 Business Operations7Orchestrator + process-mapper, vendor-management, capacity-planner, internal-comms, knowledge-ops, procurement-optimizerbusiness-operations/
🤝 Commercial8Orchestrator + pricing-strategist, deal-desk, partnerships-architect, channel-economics, commercial-policy, rfp-responder, commercial-forecastercommercial/
💰 Finance4Financial analyst (DCF, budgeting, forecasting), SaaS metrics coach, business investment advisorfinance/
🔄 Loop Library1loop-library — discover, find, audit/repair, adapt, and design bounded AI-agent loops; reads the live catalog from signals.forwardfuture.ai at runtime (vendored verbatim from [Forward-Future/loop-library](https://github.com/Forward-Future/loop-libr

Footnotes

  1. Hermes Agent is BYO-sync tier: the repo ships a pre-generated .hermes/skills/claude-skills/ tree, but you run python scripts/sync-hermes-skills.py once locally to install into ~/.hermes/skills/. Uses the same agentskills.io SKILL.md standard — no format conversion.

  2. Mistral Vibe is also BYO-sync tier: the repo ships a pre-generated .vibe/skills/claude-skills/ tree, run ./scripts/vibe-install.sh once locally to install into ~/.vibe/skills/. Same agentskills.io SKILL.md standard — no format conversion. Docs: https://docs.mistral.ai/mistral-vibe/agents-skills.

View source on GitHub