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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。

总安装

636

周安装

26

GitHub Stars

公开资料未说明

下载量

206
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

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://github.com/rickydwilson-dcs/claude-skills
仓库路径:skills/ux-researcher-designer
安装命令:
npx skills add rickydwilson-dcs/claude-skills --skill "ux-researcher-designer"
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

AgentSkills.tonpx skills
npx skills add rickydwilson-dcs/claude-skills --skill "ux-researcher-designer"

简介

ux-researcher-designer 协助界面设计、布局和用户体验优化工作。

  • 可用于生成 UI 方案、检查视觉一致性及改进组件结构。
  • 需依据现有品牌资产和用户任务定义合理交互流程。
  • 不建议仅增加视觉元素,而应聚焦功能性与可访问性提升。
  • 安装前应评估其对系统资源的占用及是否需要联网权限。

SKILL.md

name
ux-researcher-designer
title
UX Researcher Designer Skill Package
description
UX research and design toolkit for Senior UX Designer/Researcher including data-driven persona generation, journey mapping, usability testing frameworks, and research synthesis. Use for user research, persona creation, journey mapping, and design validation.
domain
product
subdomain
ux-design
difficulty
intermediate
time-saved
TODO: Quantify time savings
frequency
TODO: Estimate usage frequency
use-cases
related-agents
[]
related-skills
[]
related-commands
[]
orchestrated-by
[]
dependencies
scripts
[]
references
[]
assets
[]
compatibility
python-version
3.8+
platforms
[macos, linux, windows]
tech-stack
examples
title
Example Usage
input
TODO: Add example input for ux-researcher-designer
output
TODO: Add expected output
stats
downloads
0
stars
0
rating
0.0
reviews
0
version
v1.0.0
author
Claude Skills Team
contributors
[]
created
2025-10-19
updated
2025-11-08
license
MIT
tags
[data, design, designer, product, researcher, testing]
featured
false
verified
true

UX Researcher & Designer

Overview

This skill provides [TODO: Add 2-3 sentence overview].

Core Value: [TODO: Add value proposition with metrics]

Target Audience: [TODO: Define target users]

Use Cases: [TODO: List 3-5 primary use cases]

Core Capabilities

  • [Capability 1] - [Description]
  • [Capability 2] - [Description]
  • [Capability 3] - [Description]
  • [Capability 4] - [Description]

Key Workflows

Workflow 1: [Workflow Name]

Time: [Duration estimate]

Steps:

  1. [Step 1]
  2. [Step 2]
  3. [Step 3]

Expected Output: [What success looks like]

Workflow 2: [Workflow Name]

Time: [Duration estimate]

Steps:

  1. [Step 1]
  2. [Step 2]
  3. [Step 3]

Expected Output: [What success looks like]

Comprehensive toolkit for user-centered research and experience design. This skill provides Python tools for persona generation, research frameworks for validation, and battle-tested templates for interviews and journey mapping.

What This Skill Provides:

  • Data-driven persona generator from user research
  • User research methodologies (interviews, usability testing)
  • Journey mapping and Jobs-to-be-Done frameworks
  • Design validation methods (prototypes, A/B tests)
  • Accessibility compliance frameworks (WCAG 2.1)

Best For:

  • Conducting user research and synthesis
  • Creating research-backed personas
  • Journey mapping and empathy building
  • Usability testing and validation
  • Ensuring accessible design

Quick Start

Generate Personas

# Interactive mode
python scripts/persona_generator.py

# From user data
python scripts/persona_generator.py --data user_research.json

# Filter by segment
python scripts/persona_generator.py --data user_data.json --segment "premium"

Persona Components

Demographics: Age, role, company, technical proficiency Goals: Primary objectives and motivations Pain Points: Frustrations and challenges Behaviors: Usage patterns and preferences JTBD: Jobs-to-be-done framework

See frameworks.md for complete persona development framework.

Core Workflows

1. User Research Process

Steps:

  1. Define research questions
  2. Recruit participants (5-8 per cohort)
  3. Conduct interviews (30-45 min each)
  4. Synthesize findings
  5. Generate personas: python scripts/persona_generator.py --data research.json
  6. Validate with stakeholders

Research Methods:

  • Qualitative: Interviews, usability testing, field studies
  • Quantitative: Surveys, analytics, A/B tests
  • Mixed: Combine both for comprehensive insights

Interview Structure:

  • Introduction (5 min)
  • Background (5 min)
  • Problem exploration (20 min)
  • Solution validation (10 min)
  • Wrap-up (5 min)

Detailed Methods: See frameworks.md for qualitative and quantitative research frameworks.

Templates: See templates.md for interview scripts and usability test plans.

2. Persona Creation Process

Steps:

  1. Collect user data (interviews, surveys, analytics)
  2. Format as JSON input
  3. Generate personas: python scripts/persona_generator.py --data user_research.json
  4. Segment by user type (enterprise, SMB, individual)
  5. Validate with real users
  6. Update quarterly with new data

Persona Components:

  • Demographics and psychographics
  • Goals and motivations
  • Pain points and frustrations
  • Behavior patterns
  • Jobs-to-be-done
  • Representative quotes

Confidence Scoring:

  • High: Based on 15+ interviews
  • Medium: Based on 8-14 interviews
  • Low: Based on <8 interviews

Detailed Framework: See frameworks.md for persona development and Jobs-to-be-Done framework.

Templates: See templates.md for persona template and journey map format.

3. Design Validation Process

Methods:

  • Prototype Testing: Low/mid/high-fidelity testing
  • Usability Testing: Task-based scenarios with 5-8 users
  • A/B Testing: Quantitative validation of design decisions
  • Design Critiques: Structured feedback sessions

Usability Test Structure:

  1. Plan (research questions, success metrics)
  2. Recruit (5-8 participants per round)
  3. Execute (45-50 min sessions)
  4. Analyze (severity rating, prioritization)
  5. Iterate (implement fixes, retest)

Severity Rating:

  • Critical: Prevents task completion
  • High: Causes significant frustration
  • Medium: Minor inconvenience
  • Low: Cosmetic issue

Detailed Frameworks: See frameworks.md for usability testing and validation methods.

Templates: See templates.md for usability test plan template.

Python Tools

persona_generator.py

Data-driven persona generation from user research.

Key Features:

  • Demographic and psychographic profiling
  • Goals and pain points extraction
  • Behavior pattern identification
  • Jobs-to-be-done analysis
  • Confidence scoring based on sample size
  • Multiple output formats (text, JSON, CSV)

Usage:

# Interactive persona creation
python3 scripts/persona_generator.py

# From user research JSON
python3 scripts/persona_generator.py --data user_research.json

# Filter by segment
python3 scripts/persona_generator.py --data user_data.json --segment "enterprise"

# JSON output
python3 scripts/persona_generator.py --data user_research.json --output json

# Save to file
python3 scripts/persona_generator.py --data user_research.json -o json -f personas.json

# Verbose mode
python3 scripts/persona_generator.py --data user_research.json -v

Generated Persona Includes:

  • Name and archetype
  • Demographics (age, role, company, industry)
  • Goals (primary objectives)
  • Pain points (frustrations)
  • Behaviors (usage patterns)
  • Jobs-to-be-done (JTBD framework)
  • Representative quote
  • Confidence level (based on sample size)

Input Format:

  • JSON file with user research data
  • Demographics, behaviors, goals, pain points, quotes
  • Multiple users per segment

Complete Documentation: See tools.md for full usage guide, input formats, and integration patterns.

Reference Documentation

Frameworks (frameworks.md)

Comprehensive research and design frameworks:

  • User Research Methods: Qualitative and quantitative approaches
  • Persona Development: JTBD, persona components, validation criteria
  • Journey Mapping: Customer journey stages, map components, insights
  • Usability Testing: Test planning, execution, severity rating
  • Accessibility Framework: WCAG 2.1 principles, compliance checklist
  • Design Validation: Prototype testing, A/B testing, design critiques

Templates (templates.md)

Ready-to-use templates:

  • User Interview Script: Complete interview guide with questions
  • Persona Template: Comprehensive persona format
  • Journey Map Template: Multi-stage journey mapping format
  • Usability Test Plan: Complete test plan with scenarios

Tools (tools.md)

Python tool documentation:

  • persona_generator.py: Complete usage guide
  • Command-Line Options: All flags and parameters
  • Input Format: User research JSON structure
  • Generated Output: Persona format examples
  • Integration Patterns: Figma, documentation, research synthesis
  • Best Practices: DO/DON'T guidelines

Integration Points

This toolkit integrates with:

  • Design Tools: Figma, Sketch, Miro (personas and journey maps)
  • Research Tools: Dovetail, UserVoice, Maze, Optimal Workshop
  • Analytics: Amplitude, Mixpanel, Hotjar, FullStory
  • Testing: UserTesting.com, Lookback, UserZoom
  • Documentation: Confluence, Notion, Airtable

See tools.md for detailed integration workflows.

Quick Commands

# Interactive persona creation
python scripts/persona_generator.py

# From user research data
python scripts/persona_generator.py --data user_research.json

# By segment
python scripts/persona_generator.py --data user_data.json --segment "enterprise"
python scripts/persona_generator.py --data user_data.json --segment "smb"

# Export formats
python scripts/persona_generator.py --data research.json -o json -f personas.json
python scripts/persona_generator.py --data research.json -o csv -f personas.csv

# Verbose output
python scripts/persona_generator.py --data research.json -v

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02

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03

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能力 2

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能力 4

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安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

29.88%
按下载量换算62

OpenCode

22.14%
按下载量换算46

windsurf

19.13%
按下载量换算39

trae

12.77%
按下载量换算26

Cursor

7.93%
按下载量换算16

Codex

4.07%
按下载量换算8

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权限和风险

可写文件

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安装前确认

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