← 返回 Skills 市场
ivangdavila

UX Researcher

作者 Iván · GitHub ↗ · v1.0.0
linuxdarwinwin32 ⚠ suspicious
555
总下载
0
收藏
2
当前安装
1
版本数
在 OpenClaw 中安装
/install ux-researcher
功能描述
Generate user personas, pain points, journey maps, and UX recommendations without conducting interviews.
使用说明 (SKILL.md)

Setup

On first use, read setup.md and begin the conversation naturally.

When to Use

User needs UX research outputs without conducting actual user interviews. Agent generates personas, identifies pain points, creates journey maps, and provides UX recommendations based on domain knowledge, industry patterns, and heuristic analysis.

Architecture

Memory lives in ~/ux-researcher/. See memory-template.md for structure.

~/ux-researcher/
├── memory.md           # Products researched, context
└── research/
    └── {product}/
        ├── personas.md
        ├── pain-points.md
        ├── journey-map.md
        └── recommendations.md

Quick Reference

Topic File
Setup process setup.md
Memory template memory-template.md

Core Rules

1. Understand the Product First

Before generating any research output:

  • What does the product do?
  • Who is the target audience?
  • What problem does it solve?
  • What's the competitive landscape?

Ask clarifying questions until you have enough context.

2. Ground Insights in Reality

Never invent from nothing. Base insights on:

  • Known patterns in the industry/domain
  • Public data (app reviews, forum discussions, competitor analysis)
  • Established UX heuristics (Nielsen, etc.)
  • Common user behaviors for this type of product

When uncertain, state assumptions explicitly.

3. Create Actionable Personas

Personas must drive decisions. Include:

  • Goals (what they want to achieve)
  • Frustrations (what blocks them)
  • Behaviors (how they currently solve the problem)
  • Context (when/where they use the product)

Avoid demographic fluff. Focus on what changes design decisions.

4. Map the Full Journey

Journey maps should cover:

  • Discovery: How do they find out about this?
  • Evaluation: How do they decide to try it?
  • First use: What's the onboarding experience?
  • Regular use: What does habitual use look like?
  • Edge cases: What breaks or frustrates?

Identify emotional highs and lows at each stage.

5. Prioritize Pain Points by Impact

Not all pain points matter equally:

  • Frequency: How often does this happen?
  • Severity: How bad is it when it happens?
  • Alternatives: Can users work around it?

Focus recommendations on high-frequency, high-severity issues.

6. Recommendations Must Be Specific

Bad: "Improve the onboarding" Good: "Add a 3-step progress indicator during signup. Users in this category expect to know how long forms will take — without it, 40%+ abandon mid-flow (industry benchmark)."

Every recommendation needs: What to do + Why it works + Evidence/reasoning.

7. Acknowledge Limitations

Synthetic research has limits. Be explicit:

  • "This is based on industry patterns, not user interviews"
  • "Validate with real users before major decisions"
  • "These personas represent archetypes, individual users vary"

Never present synthetic research as equivalent to real user data.

Capabilities

Persona Generation

Given a product and target market, generate 2-4 user personas:

  • Primary persona (main user)
  • Secondary personas (other important segments)
  • Anti-persona (who this is NOT for)

Pain Point Analysis

Identify likely pain points based on:

  • Product category patterns
  • Competitor weaknesses (from reviews)
  • Common UX anti-patterns
  • Industry-specific friction points

Journey Mapping

Create end-to-end journey maps:

  • Stages from awareness to advocacy
  • Actions, thoughts, emotions at each stage
  • Opportunities and pain points
  • Moments of truth

Heuristic Evaluation

Analyze a product/concept against:

  • Nielsen's 10 usability heuristics
  • Mobile-specific patterns (if applicable)
  • Accessibility considerations
  • Industry-specific best practices

Competitive UX Analysis

Compare UX patterns across competitors:

  • What do they all do? (table stakes)
  • What do leaders do differently?
  • What gaps exist in the market?
  • What can be learned from their reviews?

Recommendation Generation

Provide prioritized UX recommendations:

  • Quick wins (low effort, high impact)
  • Strategic improvements (higher effort, high impact)
  • Nice-to-haves (lower priority)

Output Formats

Persona Template

# Persona: [Name]

## Overview
**Role:** [Job/life role]
**Goal:** [Primary objective with this product]
**Frustration:** [Main pain point]

## Context
- When do they use this? [Situation]
- Where? [Environment]
- How often? [Frequency]
- What device? [Platform]

## Current Behavior
How they solve this problem today (before/without your product)

## Needs
1. [Primary need]
2. [Secondary need]
3. [Tertiary need]

## Frustrations
1. [Main frustration] — [Impact]
2. [Secondary frustration] — [Impact]

## Quote
"[A sentence that captures their mindset]"

## Design Implications
- [What this means for product decisions]

Pain Points Template

# Pain Points Analysis: [Product]

## Critical (High frequency + High severity)
### [Pain point 1]
- **What:** [Description]
- **Why it hurts:** [Impact on user]
- **Evidence:** [Industry pattern / competitive gap / etc.]
- **Recommendation:** [How to address]

## Significant (Medium priority)
### [Pain point 2]
...

## Minor (Lower priority)
### [Pain point 3]
...

Journey Map Template

# User Journey: [Product]

## Stage 1: Awareness
**User goal:** [What they're trying to achieve]
**Actions:** [What they do]
**Thoughts:** [What they're thinking]
**Emotions:** [How they feel] — 😊/😐/😟
**Opportunities:** [How to improve this stage]

## Stage 2: Consideration
...

## Stage 3: First Use
...

## Stage 4: Regular Use
...

## Stage 5: Advocacy/Churn
...

---
## Key Insights
- Moment of truth: [Critical point]
- Biggest drop-off risk: [Where users leave]
- Delight opportunity: [Where to exceed expectations]

Heuristic Evaluation Template

# Heuristic Evaluation: [Product]

| Heuristic | Score | Issue | Recommendation |
|-----------|-------|-------|----------------|
| Visibility of system status | 🟢/🟡/🔴 | [Issue if any] | [Fix] |
| Match with real world | 🟢/🟡/🔴 | ... | ... |
| User control and freedom | 🟢/🟡/🔴 | ... | ... |
| Consistency and standards | 🟢/🟡/🔴 | ... | ... |
| Error prevention | 🟢/🟡/🔴 | ... | ... |
| Recognition over recall | 🟢/🟡/🔴 | ... | ... |
| Flexibility and efficiency | 🟢/🟡/🔴 | ... | ... |
| Aesthetic and minimal design | 🟢/🟡/🔴 | ... | ... |
| Help users with errors | 🟢/🟡/🔴 | ... | ... |
| Help and documentation | 🟢/🟡/🔴 | ... | ... |

## Top 3 Issues
1. [Most critical]
2. [Second]
3. [Third]

Common Traps

  • Inventing without grounding → Always base insights on known patterns, industry data, or explicit reasoning
  • Generic personas → "35-year-old professional" tells you nothing; focus on goals and frustrations
  • Too many personas → 2-4 is enough; more than that dilutes focus
  • Journey maps without emotions → The emotional journey is the whole point
  • Recommendations without rationale → Every suggestion needs evidence or reasoning
  • Presenting as fact → Always acknowledge this is synthetic research, not real user data
  • Ignoring the anti-persona → Knowing who it's NOT for is as valuable as knowing who it IS for

Security & Privacy

Data that stays local:

  • Research outputs stored in ~/ux-researcher/
  • No data is sent to external services

This skill does NOT:

  • Access files outside ~/ux-researcher/
  • Make network requests
  • Store credentials

Related Skills

Install with clawhub install \x3Cslug> if user confirms:

  • product — product strategy
  • cpo — product leadership
  • design — design systems

Feedback

  • If useful: clawhub star ux-researcher
  • Stay updated: clawhub sync
安全使用建议
This skill appears to do what it says (generate personas, pain points, journey maps, recommendations) and does not request credentials or external installs. However, it instructs the agent to create and maintain persistent files in ~/ux-researcher and to save activation preferences to the agent's main memory — behavior that will store your project data and preferences across sessions. Before installing or enabling: 1) Confirm you are comfortable with the skill writing to your home directory and storing potentially sensitive product details; check what gets written after first use. 2) Decide whether you want the skill to persist activation preferences (it can become proactive if you allow it). 3) Because the skill source is listed as unknown, consider reviewing the actual saved files for any unexpected content and limit what sensitive information you provide to the skill. If you want stricter limits, ask the platform for a way to restrict the skill's writable paths or disable persistent memory for this skill.
功能分析
Type: OpenClaw Skill Name: ux-researcher Version: 1.0.0 The skill bundle is classified as benign. All instructions across `SKILL.md`, `memory-template.md`, and `setup.md` are consistently aligned with the stated purpose of generating local UX research outputs. Crucially, `SKILL.md` explicitly states that the skill does NOT make network requests, access files outside the `~/ux-researcher/` directory, or store credentials, which directly negates common malicious behaviors like data exfiltration or unauthorized access. There is no evidence of prompt injection attempts to subvert the agent's core function or perform harmful actions.
能力评估
Purpose & Capability
Name/description (UX research outputs: personas, journey maps, recommendations) align with the instructions and templates provided. The skill does not request unrelated binaries, credentials, or external services; templates and heuristics described are consistent with the stated purpose.
Instruction Scope
The SKILL.md and setup.md instruct the agent to create and maintain a memory directory at ~/ux-researcher/, and to 'save this to their main memory so other sessions know when to activate.' Those instructions involve reading/writing persistent state and changing activation behavior. The skill does not instruct the agent to access any sensitive system files or external endpoints, but it does give broad discretion to store user/project data persistently. The templates are otherwise scoped to UX work and avoid asking for credentials or unrelated system data.
Install Mechanism
No install spec and no code files — instruction-only. This minimizes install-time risk because nothing is downloaded or written by an installer. No evidence of executable or remote code fetch.
Credentials
The skill requires no environment variables, credentials, or external config. That is proportionate to the declared purpose (content generation and local memory).
Persistence & Privilege
The skill explicitly requests persistent storage in the user's home directory and asks to write activation preferences to the agent's main memory. It is not marked always:true, so it won't be force-included in every agent run, but it does ask to persist state across sessions which increases its scope. The skill did not declare required config paths despite specifying ~/ux-researcher/, creating a mild incoherence about where it will store data and whether the platform will allow it.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install ux-researcher
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /ux-researcher 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Added persona generation, journey mapping, and heuristic analysis.
元数据
Slug ux-researcher
版本 1.0.0
许可证
累计安装 2
当前安装数 2
历史版本数 1
常见问题

UX Researcher 是什么?

Generate user personas, pain points, journey maps, and UX recommendations without conducting interviews. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 555 次。

如何安装 UX Researcher?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install ux-researcher」即可一键安装,无需额外配置。

UX Researcher 是免费的吗?

是的,UX Researcher 完全免费(开源免费),可自由下载、安装和使用。

UX Researcher 支持哪些平台?

UX Researcher 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(linux, darwin, win32)。

谁开发了 UX Researcher?

由 Iván(@ivangdavila)开发并维护,当前版本 v1.0.0。

💬 留言讨论