* chore: update gitignore for audit reports and playwright cache * fix: add YAML frontmatter (name + description) to all SKILL.md files - Added frontmatter to 34 skills that were missing it entirely (0% Tessl score) - Fixed name field format to kebab-case across all 169 skills - Resolves #284 * chore: sync codex skills symlinks [automated] * fix: optimize 14 low-scoring skills via Tessl review (#290) Tessl optimization: 14 skills improved from ≤69% to 85%+. Closes #285, #286. * chore: sync codex skills symlinks [automated] * fix: optimize 18 skills via Tessl review + compliance fix (closes #287) (#291) Phase 1: 18 skills optimized via Tessl (avg 77% → 95%). Closes #287. * feat: add scripts and references to 4 prompt-only skills + Tessl optimization (#292) Phase 2: 3 new scripts + 2 reference files for prompt-only skills. Tessl 45-55% → 94-100%. * feat: add 6 agents + 5 slash commands for full coverage (v2.7.0) (#293) Phase 3: 6 new agents (all 9 categories covered) + 5 slash commands. * fix: Phase 5 verification fixes + docs update (#294) Phase 5 verification fixes * chore: sync codex skills symlinks [automated] * fix: marketplace audit — all 11 plugins validated by Claude Code (#295) Marketplace audit: all 11 plugins validated + installed + tested in Claude Code * fix: restore 7 removed plugins + revert playwright-pro name to pw Reverts two overly aggressive audit changes: - Restored content-creator, demand-gen, fullstack-engineer, aws-architect, product-manager, scrum-master, skill-security-auditor to marketplace - Reverted playwright-pro plugin.json name back to 'pw' (intentional short name) * refactor: split 21 over-500-line skills into SKILL.md + references (#296) * chore: sync codex skills symlinks [automated] * docs: update all documentation with accurate counts and regenerated skill pages - Update skill count to 170, Python tools to 213, references to 314 across all docs - Regenerate all 170 skill doc pages from latest SKILL.md sources - Update CLAUDE.md with v2.1.1 highlights, accurate architecture tree, and roadmap - Update README.md badges and overview table - Update marketplace.json metadata description and version - Update mkdocs.yml, index.md, getting-started.md with correct numbers * fix: add root-level SKILL.md and .codex/instructions.md to all domains (#301) Root cause: CLI tools (ai-agent-skills, agent-skills-cli) look for SKILL.md at the specified install path. 7 of 9 domain directories were missing this file, causing "Skill not found" errors for bundle installs like: npx ai-agent-skills install alirezarezvani/claude-skills/engineering-team Fix: - Add root-level SKILL.md with YAML frontmatter to 7 domains - Add .codex/instructions.md to 8 domains (for Codex CLI discovery) - Update INSTALLATION.md with accurate skill counts (53→170) - Add troubleshooting entry for "Skill not found" error All 9 domains now have: SKILL.md + .codex/instructions.md + plugin.json Closes #301 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat: add Gemini CLI + OpenClaw support, fix Codex missing 25 skills Gemini CLI: - Add GEMINI.md with activation instructions - Add scripts/gemini-install.sh setup script - Add scripts/sync-gemini-skills.py (194 skills indexed) - Add .gemini/skills/ with symlinks for all skills, agents, commands - Remove phantom medium-content-pro entries from sync script - Add top-level folder filter to prevent gitignored dirs from leaking Codex CLI: - Fix sync-codex-skills.py missing "engineering" domain (25 POWERFUL skills) - Regenerate .codex/skills-index.json: 124 → 149 skills - Add 25 new symlinks in .codex/skills/ OpenClaw: - Add OpenClaw installation section to INSTALLATION.md - Add ClawHub install + manual install + YAML frontmatter docs Documentation: - Update INSTALLATION.md with all 4 platforms + accurate counts - Update README.md: "three platforms" → "four platforms" + Gemini quick start - Update CLAUDE.md with Gemini CLI support in v2.1.1 highlights - Update SKILL-AUTHORING-STANDARD.md + SKILL_PIPELINE.md with Gemini steps - Add OpenClaw + Gemini to installation locations reference table Marketplace: all 18 plugins validated — sources exist, SKILL.md present Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat(product,pm): world-class product & PM skills audit — 6 scripts, 5 agents, 7 commands, 23 references/assets Phase 1 — Agent & Command Foundation: - Rewrite cs-project-manager agent (55→515 lines, 4 workflows, 6 skill integrations) - Expand cs-product-manager agent (408→684 lines, orchestrates all 8 product skills) - Add 7 slash commands: /rice, /okr, /persona, /user-story, /sprint-health, /project-health, /retro Phase 2 — Script Gap Closure (2,779 lines): - jira-expert: jql_query_builder.py (22 patterns), workflow_validator.py - confluence-expert: space_structure_generator.py, content_audit_analyzer.py - atlassian-admin: permission_audit_tool.py - atlassian-templates: template_scaffolder.py (Confluence XHTML generation) Phase 3 — Reference & Asset Enrichment: - 9 product references (competitive-teardown, landing-page-generator, saas-scaffolder) - 6 PM references (confluence-expert, atlassian-admin, atlassian-templates) - 7 product assets (templates for PRD, RICE, sprint, stories, OKR, research, design system) - 1 PM asset (permission_scheme_template.json) Phase 4 — New Agents: - cs-agile-product-owner, cs-product-strategist, cs-ux-researcher Phase 5 — Integration & Polish: - Related Skills cross-references in 8 SKILL.md files - Updated product-team/CLAUDE.md (5→8 skills, 6→9 tools, 4 agents, 5 commands) - Updated project-management/CLAUDE.md (0→12 scripts, 3 commands) - Regenerated docs site (177 pages), updated homepage and getting-started Quality audit: 31 files reviewed, 29 PASS, 2 fixed (copy-frameworks.md, governance-framework.md) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix: audit and repair all plugins, agents, and commands - Fix 12 command files: correct CLI arg syntax, script paths, and usage docs - Fix 3 agents with broken script/reference paths (cs-content-creator, cs-demand-gen-specialist, cs-financial-analyst) - Add complete YAML frontmatter to 5 agents (cs-growth-strategist, cs-engineering-lead, cs-senior-engineer, cs-financial-analyst, cs-quality-regulatory) - Fix cs-ceo-advisor related agent path - Update marketplace.json metadata counts (224 tools, 341 refs, 14 agents, 12 commands) Verified: all 19 scripts pass --help, all 14 agent paths resolve, mkdocs builds clean. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix: repair 25 Python scripts failing --help across all domains - Fix Python 3.10+ syntax (float | None → Optional[float]) in 2 scripts - Add argparse CLI handling to 9 marketing scripts using raw sys.argv - Fix 10 scripts crashing at module level (wrap in __main__, add argparse) - Make yaml/prefect/mcp imports conditional with stdlib fallbacks (4 scripts) - Fix f-string backslash syntax in project_bootstrapper.py - Fix -h flag conflict in pr_analyzer.py - Fix tech-debt.md description (score → prioritize) All 237 scripts now pass python3 --help verification. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix(product-team): close 3 verified gaps in product skills - Fix competitive-teardown/SKILL.md: replace broken references DATA_COLLECTION.md → references/data-collection-guide.md and TEMPLATES.md → references/analysis-templates.md (workflow was broken at steps 2 and 4) - Upgrade landing_page_scaffolder.py: add TSX + Tailwind output format (--format tsx) matching SKILL.md promise of Next.js/React components. 4 design styles (dark-saas, clean-minimal, bold-startup, enterprise). TSX is now default; HTML preserved via --format html - Rewrite README.md: fix stale counts (was 5 skills/15+ tools, now accurately shows 8 skills/9 tools), remove 7 ghost scripts that never existed (sprint_planner.py, velocity_tracker.py, etc.) - Fix tech-debt.md description (score → prioritize) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * release: v2.1.2 — landing page TSX output, brand voice integration, docs update - Landing page generator defaults to Next.js TSX + Tailwind CSS (4 design styles) - Brand voice analyzer integrated into landing page generation workflow - CHANGELOG, CLAUDE.md, README.md updated for v2.1.2 - All 13 plugin.json + marketplace.json bumped to 2.1.2 - Gemini/Codex skill indexes re-synced - Backward compatible: --format html preserved, no breaking changes Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> --------- Co-authored-by: alirezarezvani <5697919+alirezarezvani@users.noreply.github.com> Co-authored-by: Leo <leo@openclaw.ai> Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
12 KiB
title, description
| title | description |
|---|---|
| UX Researcher & Designer | UX Researcher & Designer - Claude Code skill from the Product domain. |
UX Researcher & Designer
Domain: Product | Skill: ux-researcher-designer | Source: product-team/ux-researcher-designer/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
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:
-
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"] } ] -
Run persona generator
# Human-readable output python scripts/persona_generator.py # JSON output for integration python scripts/persona_generator.py json -
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? -
Validate persona
- Show to 3-5 real users: "Does this sound like you?"
- Cross-check with support tickets
- Verify against analytics data
-
Reference: See
references/persona-methodology.mdfor validity criteria
Workflow 2: Create Journey Map
Situation: You need to visualize the end-to-end user experience for a specific goal.
Steps:
-
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 -
Gather journey data
Sources:
- User interviews (ask "walk me through...")
- Session recordings
- Analytics (funnel, drop-offs)
- Support tickets
-
Map the stages
Typical B2B SaaS stages:
Awareness → Evaluation → Onboarding → Adoption → Advocacy -
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? -
Identify opportunities
Priority Score = Frequency × Severity × Solvability
-
Reference: See
references/journey-mapping-guide.mdfor templates
Workflow 3: Plan Usability Test
Situation: You need to validate a design with real users.
Steps:
-
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?" -
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 -
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
-
Define success metrics
Metric Target Completion rate >80% Time on task <2× expected Error rate <15% Satisfaction >4/5 -
Prepare moderator guide
- Think-aloud instructions
- Non-leading prompts
- Post-task questions
-
Reference: See
references/usability-testing-frameworks.mdfor full guide
Workflow 4: Synthesize Research
Situation: You have raw research data (interviews, surveys, observations) and need actionable insights.
Steps:
-
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
-
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) -
Calculate segment sizes
Cluster Users % Viability Power Users 18 36% Primary persona Business Users 15 30% Primary persona Casual Users 12 24% Secondary persona -
Extract key findings
For each theme:
- Finding statement
- Supporting evidence (quotes, data)
- Frequency (X/Y participants)
- Business impact
- Recommendation
-
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? -
Reference: See
references/persona-methodology.mdfor 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