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cognitive-walkthrough by mastepanoski/claude-skills
npx skills add https://github.com/mastepanoski/claude-skills --skill cognitive-walkthrough此技能使 AI 代理能够使用认知走查方法执行特定任务的可用性评估,该技术模拟用户(尤其是新手)如何思考在界面中完成特定任务。
与广泛的启发式评估不同,认知走查提供对特定用户旅程的深入分析,识别用户在何处遇到困难、感到困惑或出错。
当您需要对可学习性和首次使用的易用性进行细致的、以任务为中心的洞察时,请使用此技能。
可与 "Nielsen Heuristics" 结合用于通用可用性,与 "Don Norman Principles" 结合用于直观设计评估,或与 "WCAG Accessibility" 结合用于包容性访问。
在以下情况下调用此技能:
执行此走查时,请收集:
认知走查在每个步骤评估四个关键问题:
Q1:用户是否会尝试实现正确的效果?
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Q2:用户是否会注意到正确的操作是可用的?
Q3:用户是否会将正确的操作与他们试图实现的效果联系起来?
Q4:如果执行了正确的操作,用户是否会看到正在取得进展?
请系统地遵循以下步骤:
将任务分解为原子操作(最小的有意义的步骤):
示例任务: "创建账户并将商品添加到愿望清单"
关键原则: 每个操作都应是单一的、可观察的用户行为。
对于每个操作,回答 4 个认知问题:
## 操作 [N]: [描述]
**用户在此步骤的目标:** [他们试图完成什么]
**当前状态:** [他们看到什么/他们在哪里]
### Q1:用户是否会尝试实现正确的效果?
- **分析**:[用户是否知道下一步该做什么?]
- **问题**:[如果有的话]
- **评级**:✅ 清晰 / ⚠️ 不清晰 / ❌ 令人困惑
### Q2:用户是否会注意到正确的操作是可用的?
- **分析**:[控件是否可见/可找到?]
- **问题**:[如果有的话]
- **评级**:✅ 可见 / ⚠️ 有些隐藏 / ❌ 隐藏
### Q3:用户是否会将操作与预期效果联系起来?
- **分析**:[控件是否暗示了它的功能?]
- **问题**:[如果有的话]
- **评级**:✅ 清晰 / ⚠️ 模糊 / ❌ 误导
### Q4:用户是否会看到正在取得进展?
- **分析**:[操作后是否有反馈?]
- **问题**:[如果有的话]
- **评级**:✅ 清晰的反馈 / ⚠️ 延迟/微弱 / ❌ 无反馈
### 发现的关键问题:
- [问题 1]
- [问题 2]
### 建议:
- [具体改进 1]
- [具体改进 2]
---
逐步检查所有操作后:
创建全面的走查报告(见下文格式)。
# 认知走查报告
**任务**:[任务描述]
**用户画像**:[用户类型和特征]
**界面**:[被评估的系统/应用]
**日期**:[日期]
**评估者**:[AI 代理]
---
## 执行摘要
### 任务成功预测
**估计成功率(首次尝试)**:[X]% 的目标用户
### 关键发现
1. [最关键的问题]
2. [第二关键的问题]
3. [第三关键的问题]
### 总体评估
[2-3 句关于可学习性的总结]
---
## 用户上下文
### 目标用户画像
- **经验水平**:[新手/中级/专家]
- **领域知识**:[描述]
- **技术熟练度**:[低/中/高]
- **设备/上下文**:[桌面/移动设备,环境]
- **动机**:[他们为什么这样做]
- **先前经验**:[他们已经知道什么]
### 任务定义
**目标**:[用户想要完成什么]
**成功标准**:[如何知道他们成功了]
**起始点**:[任务从哪里开始]
---
## 逐步走查
### 操作 1:[导航到主页]
**用户目标**:找到开始创建账户的位置
**当前状态**:用户刚刚到达主页
#### Q1:用户是否会尝试实现正确的效果?
- **分析**:用户通常会在页眉/导航中寻找 "Sign Up"、"Register" 或 "Create Account"
- **问题**:预计没有 - 标准心智模型
- **评级**:✅ 清晰
#### Q2:用户是否会注意到正确的操作是可用的?
- **分析**:"Sign Up" 按钮位于页眉右上角(标准位置)
- **问题**:文本较小(12px),对比度低(#999 在 #FFF 上 = 2.8:1)
- **评级**:⚠️ 有些隐藏
#### Q3:用户是否会将操作与预期效果联系起来?
- **分析**:"Sign Up" 是标准术语,清楚地表明账户创建
- **问题**:无
- **评级**:✅ 清晰
#### Q4:用户是否会看到正在取得进展?
- **分析**:不适用 - 尚未采取任何操作(仅查看)
- **问题**:不适用
- **评级**:不适用
#### 关键问题:
- **"Sign Up" 按钮对比度低** - WCAG 失败,难以看清
- 按钮较小(24px 高度)- 移动用户可能难以操作
#### 建议:
1. 将对比度增加到至少 4.5:1(WCAG AA)
2. 将按钮大小增加到 44px(触摸目标指南)
3. 考虑更突出的位置或视觉权重
---
[为所有操作继续...]
---
## 失败点分析
### 关键障碍(用户很可能失败)
**1. 操作 7:创建具有复杂性要求的密码**
- **问题**:密码要求直到提交失败后才显示
- **影响**:用户猜测规则,因重复错误而感到沮丧
- **受影响的用户**:70-80% 的新手
- **严重性**:关键
- **修复优先级**:P0(必须修复)
- **建议**:在用户输入前内联显示要求
**2. 操作 12:找到 "Add to Wishlist" 按钮**
- **问题**:仅图标按钮(心形图标)无标签,不明显
- **影响**:用户看不到或不明白它的功能
- **受影响的用户**:50-60% 的首次用户
- **严重性**:高
- **修复优先级**:P1(应该修复)
- **建议**:在图标旁边添加文本标签 "Add to Wishlist"
### 主要摩擦点
[继续...]
### 次要问题
[继续...]
---
## 按用户类型划分的成功概率
| 用户类型 | 估计成功率 | 完成时间 | 信心度 |
|-----------|------------------------|------------------|------------|
| **新手** | 45% | 8-12 分钟 | 挫折容忍度低 |
| **中级** | 75% | 4-6 分钟 | 中等信心 |
| **专家** | 95% | 2-3 分钟 | 效率高 |
**目标**:新手应具有 ≥80% 的成功率且时间 ≤5 分钟。
**差距**:当前设计对新手的成功率低了 35 个百分点。
---
## 认知负荷评估
### 记忆负担
- **需要记住的项目**:[列出用户必须回忆的内容]
- **评级**:低 / 中 / 高
- **问题**:[如果高,解释原因]
### 决策点
- **用户做出的选择**:[数量和复杂性]
- **评级**:低 / 中 / 高
- **问题**:[不必要的决策会增加认知负荷]
### 错误恢复
- **纠正错误的难易程度**:[分析]
- **评级**:容易 / 中等 / 困难
- **问题**:[撤销/返回/重置方面的问题]
---
## 优先级建议
### 阶段 1:关键修复(1-2 周)
**1. 内联显示密码要求(操作 7)**
- **原因**:消除 #1 失败点
- **影响**:新手成功率提高 +25%
- **工作量**:低(4 小时)
**2. 为愿望清单按钮添加文本标签(操作 12)**
- **原因**:使功能可被发现
- **影响**:任务完成率提高 +15%
- **工作量**:低(2 小时)
**3. 提高 "Sign Up" 按钮对比度(操作 1)**
- **原因**:可访问性 + 可发现性
- **影响**:+10% 的用户找到起始点
- **工作量**:低(1 小时)
**阶段 1 总影响**:新手成功率提高 +50%(45% → 67.5%)
---
### 阶段 2:主要改进(1-2 个月)
[继续中等优先级项目...]
---
### 阶段 3:优化(3+ 个月)
[继续锦上添花的改进...]
---
## 替代设计方案建议
基于走查发现,考虑以下替代方法:
### 替代方案 1:注册的渐进式披露
**当前**:所有字段一次显示
**建议**:逐步进行(电子邮件 → 密码 → 确认)
**优点**:减少认知负荷,每步反馈更清晰
**缺点**:更多点击,可能感觉较慢
**建议**:与目标用户进行 A/B 测试
### 替代方案 2:社交注册
**当前**:仅电子邮件/密码
**建议**:添加 "使用 Google/Apple 注册"
**优点**:更快,无需记住密码
**缺点**:隐私问题,依赖第三方
**建议**:作为电子邮件注册的选项提供
[继续其他替代方案...]
---
## 与最佳实践对比
| 实践 | 当前实现 | 建议 |
|----------|------------------------|----------------|
| 密码要求可见性 | 错误前隐藏 | 输入前内联显示 |
| 按钮大小(移动端) | 24px | 至少 44px |
| 颜色对比度 | 2.8:1(WCAG 失败) | 4.5:1(WCAG AA) |
| 错误消息 | 通用 | 具体且可操作 |
| 确认反馈 | 弱 | 清晰的成功消息 |
---
## 后续步骤
1. **确定修复优先级**:从阶段 1 的关键项目开始
2. **原型改进**:创建包含更改的可点击模型
3. **用户测试**:与 5-8 名目标用户验证发现
4. **迭代**:更改后运行另一次认知走查
5. **监控指标**:跟踪任务完成率、任务时间、错误率
---
## 方法论说明
- **方法**:认知走查(Wharton 等人,1994)
- **评估者**:模拟 UX 专家的 AI 代理
- **视角**:新手用户(首次使用,未经培训)
- **局限性**:
- 基于界面分析,而非实际用户行为
- 成功率是估计值,非测量数据
- 应通过真实用户测试进行验证
---
## 参考文献
- Wharton, C., Rieman, J., Lewis, C., & Polson, P. (1994). "The Cognitive Walkthrough Method"
- Nielsen, J. (1994). "Heuristic Evaluation"
- Spencer, R. (2000). "The Streamlined Cognitive Walkthrough Method"
---
**版本**:1.0
**日期**:[日期]
可发现性问题:
不清晰的示能性:
反馈失败:
心智模型不匹配:
认知负荷:
衡量走查效果:
走查前:
实施修复后:
在以下情况下使用认知走查:
结合使用:
1.0 - 初始版本
请记住:认知走查是一种预测性方法。虽然它在识别可学习性问题方面非常有效,但始终应通过可用性测试与真实用户一起验证发现。
每周安装次数
62
仓库
GitHub 星标数
14
首次出现
2026年2月5日
安全审计
安装于
codex60
gemini-cli59
opencode59
github-copilot58
claude-code57
kimi-cli56
This skill enables AI agents to perform a task-specific usability evaluation using the Cognitive Walkthrough method, a technique that simulates how users (especially novices) think through completing specific tasks in an interface.
Unlike broad heuristic evaluations, Cognitive Walkthrough provides deep analysis of particular user journeys, identifying where users get stuck, confused, or make errors.
Use this skill when you need granular, task-focused insights into learnability and ease of first use.
Combine with "Nielsen Heuristics" for general usability, "Don Norman Principles" for intuitive design, or "WCAG Accessibility" for inclusive access.
Invoke this skill when:
When executing this walkthrough, gather:
Cognitive Walkthrough evaluates four key questions at each step:
Q1: Will users try to achieve the right effect?
Q2: Will users notice that the correct action is available?
Q3: Will users associate the correct action with the effect they're trying to achieve?
Q4: If the correct action is performed, will users see that progress is being made?
Follow these steps systematically:
Identify the task:
Define the user:
Establish starting state:
Break the task into atomic actions (smallest meaningful steps):
Example Task: "Create account and add item to wishlist"
Key principle: Each action should be a single, observable user behavior.
For each action , answer the 4 cognitive questions:
## Action [N]: [Description]
**User's Goal at this step:** [What they're trying to accomplish]
**Current State:** [What they see/where they are]
### Q1: Will users try to achieve the right effect?
- **Analysis**: [Will users know what to do next?]
- **Issues**: [Problems if any]
- **Rating**: ✅ Clear / ⚠️ Unclear / ❌ Confusing
### Q2: Will users notice the correct action is available?
- **Analysis**: [Is the control visible/findable?]
- **Issues**: [Problems if any]
- **Rating**: ✅ Visible / ⚠️ Somewhat hidden / ❌ Hidden
### Q3: Will users associate action with intended effect?
- **Analysis**: [Does the control suggest what it does?]
- **Issues**: [Problems if any]
- **Rating**: ✅ Clear / ⚠️ Ambiguous / ❌ Misleading
### Q4: Will users see progress is being made?
- **Analysis**: [Is there feedback after the action?]
- **Issues**: [Problems if any]
- **Rating**: ✅ Clear feedback / ⚠️ Delayed/weak / ❌ No feedback
### Critical Issues Found:
- [Issue 1]
- [Issue 2]
### Recommendations:
- [Specific improvement 1]
- [Specific improvement 2]
---
After walking through all actions:
Identify failure points:
Categorize issues:
Calculate success likelihood:
Prioritize improvements:
Create comprehensive walkthrough report (see format below).
# Cognitive Walkthrough Report
**Task**: [Task description]
**User Persona**: [User type and characteristics]
**Interface**: [System/app being evaluated]
**Date**: [Date]
**Evaluator**: [AI Agent]
---
## Executive Summary
### Task Success Prediction
**Estimated Success Rate (First Attempt)**: [X]% of target users
### Critical Findings
1. [Most critical issue]
2. [Second critical issue]
3. [Third critical issue]
### Overall Assessment
[2-3 sentence summary of learnability]
---
## User Context
### Target User Profile
- **Experience Level**: [Novice/Intermediate/Expert]
- **Domain Knowledge**: [Description]
- **Technical Proficiency**: [Low/Medium/High]
- **Device/Context**: [Desktop/Mobile, environment]
- **Motivation**: [Why they're doing this]
- **Prior Experience**: [What they already know]
### Task Definition
**Goal**: [What user wants to accomplish]
**Success Criteria**: [How to know they succeeded]
**Starting Point**: [Where task begins]
---
## Step-by-Step Walkthrough
### Action 1: [Navigate to homepage]
**User's Goal**: Find where to start creating an account
**Current State**: User just arrived at homepage
#### Q1: Will users try to achieve the right effect?
- **Analysis**: Users typically look for "Sign Up", "Register", or "Create Account" in header/nav
- **Issues**: None expected - standard mental model
- **Rating**: ✅ Clear
#### Q2: Will users notice the correct action is available?
- **Analysis**: "Sign Up" button is in top-right corner of header (standard location)
- **Issues**: Small text (12px), low contrast (#999 on #FFF = 2.8:1)
- **Rating**: ⚠️ Somewhat hidden
#### Q3: Will users associate action with intended effect?
- **Analysis**: "Sign Up" is standard terminology, clearly indicates account creation
- **Issues**: None
- **Rating**: ✅ Clear
#### Q4: Will users see progress is being made?
- **Analysis**: N/A - no action taken yet (just viewing)
- **Issues**: N/A
- **Rating**: N/A
#### Critical Issues:
- **Low contrast on "Sign Up" button** - WCAG fail, hard to see
- Button is small (24px height) - mobile users may struggle
#### Recommendations:
1. Increase contrast to 4.5:1 minimum (WCAG AA)
2. Increase button size to 44px (touch target guideline)
3. Consider more prominent placement or visual weight
---
[Continue for all actions...]
---
## Failure Points Analysis
### Critical Blockers (Users likely to fail)
**1. Action 7: Create password with complexity requirements**
- **Problem**: Password requirements not shown until after submission fails
- **Impact**: Users guess rules, get frustrated by repeated errors
- **Affected Users**: 70-80% of novices
- **Severity**: Critical
- **Fix Priority**: P0 (Must fix)
- **Recommendation**: Show requirements inline before user types
**2. Action 12: Find "Add to Wishlist" button**
- **Problem**: Icon-only button (heart icon) with no label, not obvious
- **Impact**: Users don't see it or don't understand what it does
- **Affected Users**: 50-60% of first-time users
- **Severity**: High
- **Fix Priority**: P1 (Should fix)
- **Recommendation**: Add text label "Add to Wishlist" next to icon
### Major Friction Points
[Continue...]
### Minor Issues
[Continue...]
---
## Success Probability by User Type
| User Type | Estimated Success Rate | Time to Complete | Confidence |
|-----------|------------------------|------------------|------------|
| **Novice** | 45% | 8-12 minutes | Low frustration tolerance |
| **Intermediate** | 75% | 4-6 minutes | Moderate confidence |
| **Expert** | 95% | 2-3 minutes | High efficiency |
**Target**: Novices should have ≥80% success rate with ≤5 minutes time.
**Gap**: Current design falls short for novices by 35 percentage points.
---
## Cognitive Load Assessment
### Memory Burden
- **Items to remember**: [List what users must recall]
- **Rating**: Low / Medium / High
- **Issue**: [If high, explain why]
### Decision Points
- **Choices users make**: [Number and complexity]
- **Rating**: Low / Medium / High
- **Issue**: [Unnecessary decisions increase cognitive load]
### Error Recovery
- **How easy to fix mistakes**: [Analysis]
- **Rating**: Easy / Moderate / Difficult
- **Issue**: [Problems with undo/back/reset]
---
## Prioritized Recommendations
### Phase 1: Critical Fixes (1-2 weeks)
**1. Show password requirements inline (Action 7)**
- **Why**: Eliminates #1 failure point
- **Impact**: +25% success rate for novices
- **Effort**: Low (4 hours)
**2. Add text label to wishlist button (Action 12)**
- **Why**: Makes feature discoverable
- **Impact**: +15% task completion
- **Effort**: Low (2 hours)
**3. Increase "Sign Up" button contrast (Action 1)**
- **Why**: Accessibility + discoverability
- **Impact**: +10% users find starting point
- **Effort**: Low (1 hour)
**Total Phase 1 Impact**: +50% novice success rate (45% → 67.5%)
---
### Phase 2: Major Improvements (1-2 months)
[Continue with medium priority items...]
---
### Phase 3: Polish (3+ months)
[Continue with nice-to-have improvements...]
---
## Alternative Design Suggestions
Based on walkthrough findings, consider these alternative approaches:
### Alternative 1: Progressive Disclosure for Signup
**Current**: All fields shown at once
**Proposed**: Step-by-step (email → password → confirm)
**Pros**: Reduces cognitive load, clearer feedback per step
**Cons**: More clicks, may feel slower
**Recommendation**: A/B test with target users
### Alternative 2: Social Sign-Up
**Current**: Email/password only
**Proposed**: Add "Sign up with Google/Apple"
**Pros**: Faster, no password to remember
**Cons**: Privacy concerns, dependency on third-party
**Recommendation**: Offer as option alongside email signup
[Continue with other alternatives...]
---
## Comparison to Best Practices
| Practice | Current Implementation | Recommendation |
|----------|------------------------|----------------|
| Password requirements visibility | Hidden until error | Show inline before typing |
| Button sizing (mobile) | 24px | 44px minimum |
| Color contrast | 2.8:1 (WCAG fail) | 4.5:1 (WCAG AA) |
| Error messages | Generic | Specific and actionable |
| Confirmation feedback | Weak | Clear success messages |
---
## Next Steps
1. **Prioritize fixes**: Start with Phase 1 critical items
2. **Prototype improvements**: Create clickable mockups with changes
3. **User testing**: Validate findings with 5-8 target users
4. **Iterate**: Run another cognitive walkthrough after changes
5. **Monitor metrics**: Track task completion rates, time-on-task, error rates
---
## Methodology Notes
- **Method**: Cognitive Walkthrough (Wharton et al., 1994)
- **Evaluator**: AI agent simulating UX expert
- **Perspective**: Novice user (first-time, no training)
- **Limitations**:
- Based on interface analysis, not actual user behavior
- Success rates are estimates, not measured data
- Should be validated with real user testing
---
## References
- Wharton, C., Rieman, J., Lewis, C., & Polson, P. (1994). "The Cognitive Walkthrough Method"
- Nielsen, J. (1994). "Heuristic Evaluation"
- Spencer, R. (2000). "The Streamlined Cognitive Walkthrough Method"
---
**Version**: 1.0
**Date**: [Date]
Discoverability Problems:
Unclear Affordances:
Feedback Failures:
Mental Model Mismatches:
Cognitive Load:
Measure walkthrough effectiveness:
Before Walkthrough:
After Implementing Fixes:
Use cognitive walkthrough when:
Complement with:
1.0 - Initial release
Remember : Cognitive Walkthrough is a predictive method. While it's highly effective at identifying learnability issues, always validate findings with real users through usability testing.
Weekly Installs
62
Repository
GitHub Stars
14
First Seen
Feb 5, 2026
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Installed on
codex60
gemini-cli59
opencode59
github-copilot58
claude-code57
kimi-cli56
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