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cognitive-load认知负荷

Agent Skill

cognitive-load 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

594

周安装

25

GitHub Stars

235

下载量

208
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

unknown

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:cognitive-load(认知负荷)
来源仓库:https://github.com/flpbalada/my-opencode-config
仓库路径:skills/cognitive-load
安装命令:
npx skills add https://github.com/flpbalada/my-opencode-config --skill cognitive-load
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。

skills.shnpx skills
npx skills add https://github.com/flpbalada/my-opencode-config --skill cognitive-load

简介

cognitive-load 基于工作记忆限制理论提供信息架构与界面简化策略。

  • 适用于在 Codex、Claude、Cursor、Gemini CLI 中优化复杂表单与多步流程。
  • 区分内在、外在与关联认知负荷,提出针对性减负措施。
  • 提供信息分块、渐进披露与视觉引导设计建议。
  • 需配合用户测试验证实际认知负担变化。

SKILL.md

Cognitive Load - Designing for Human Memory

Cognitive Load Theory (CLT), developed by John Sweller, provides a framework for designing experiences that work with human working memory limitations. Understanding the three types of cognitive load helps create interfaces that feel effortless and intuitive.

When to Use This Skill

  • Designing complex forms or workflows
  • Creating onboarding experiences
  • Simplifying feature-rich interfaces
  • Improving task completion rates
  • Planning information architecture
  • Reviewing designs for usability

Working Memory Limitations

Human Processing Capacity:

┌─────────────────────────────────────────────────────┐
│              WORKING MEMORY                          │
│                                                      │
│    Capacity: 7 ± 2 items simultaneously             │
│    Duration: ~20 seconds without rehearsal          │
│    Processing: Serial, not parallel                 │
│                                                      │
│    When exceeded → Errors, frustration, abandonment │
└─────────────────────────────────────────────────────┘

Design goal: Stay WITHIN capacity limits.

Three Types of Cognitive Load

Total Cognitive Load = Intrinsic + Extraneous + Germane

┌─────────────────────────────────────────────────────────────────┐
│                    WORKING MEMORY CAPACITY                       │
├─────────────────┬─────────────────┬─────────────────────────────┤
│   INTRINSIC     │   EXTRANEOUS    │          GERMANE            │
│                 │                 │                             │
│   Task          │   Bad design    │   Learning &                │
│   complexity    │   noise         │   schema building           │
│                 │                 │                             │
│   Can't reduce  │   ELIMINATE     │   MAXIMIZE                  │
│   without       │   THIS          │   THIS                      │
│   changing task │                 │                             │
└─────────────────┴─────────────────┴─────────────────────────────┘

1. Intrinsic Load

What it is: The inherent difficulty of the task itself.

CharacteristicExample
Determined by task complexityFiling taxes vs. sending email
Varies by user expertiseExpert finds it easy, novice struggles
Cannot be eliminatedOnly managed through design

Design strategies:

  • Break complex tasks into smaller steps
  • Provide progressive disclosure
  • Build on existing mental models
  • Offer different paths for different expertise levels

2. Extraneous Load

What it is: Unnecessary mental effort from poor design.

Common Sources of Extraneous Load:

Visual:
├── Cluttered layouts
├── Poor typography
├── Inconsistent patterns
└── Distracting animations

Interaction:
├── Unclear navigation
├── Unexpected behaviors
├── Too many options
└── Hidden functionality

Content:
├── Jargon and complexity
├── Redundant information
├── Missing context
└── Poor information hierarchy

Design strategies:

  • Eliminate decorative elements without purpose
  • Use consistent design patterns
  • Apply strong visual hierarchy
  • Remove redundant information

3. Germane Load

What it is: Productive mental effort that builds understanding.

BenefitExample
Builds mental modelsUser learns system behavior
Enables efficiencyExperienced user works faster
Creates transferable knowledgeSkills apply to similar tasks

Design strategies:

  • Provide clear feedback on actions
  • Create learnable, consistent patterns
  • Design onboarding that builds foundations
  • Use progressive enhancement for power features

Load Analysis Framework

Step 1: Map the Task

Task Decomposition:

[Main Task]
├── Step 1: [Action] → Load type: [I/E/G]
│   └── Decisions required: [count]
├── Step 2: [Action] → Load type: [I/E/G]
│   └── Decisions required: [count]
├── Step 3: [Action] → Load type: [I/E/G]
│   └── Decisions required: [count]
└── Completion

Step 2: Identify Load Sources

For each step, categorize the cognitive demands:

StepIntrinsic LoadExtraneous LoadGermane Load
1[Task complexity][Design issues][Learning value]
2[Task complexity][Design issues][Learning value]
3[Task complexity][Design issues][Learning value]

Step 3: Design Interventions

Intervention Strategy:

High Intrinsic Load?
├── YES → Break into smaller steps
├── YES → Add progressive disclosure
├── YES → Provide scaffolding/help
└── YES → Offer simplified path

High Extraneous Load?
├── YES → Remove unnecessary elements
├── YES → Improve visual hierarchy
├── YES → Simplify navigation
└── YES → Fix inconsistent patterns

Low Germane Load?
├── YES → Add meaningful feedback
├── YES → Create learnable patterns
├── YES → Design for skill building
└── YES → Connect to existing knowledge

Output Template

After completing analysis, document as:

## Cognitive Load Analysis

**Feature/Flow:** [Name]

**Date:** [Date]

### Task Map

| Step | Description | Intrinsic    | Extraneous   | Germane      |
| ---- | ----------- | ------------ | ------------ | ------------ |
| 1    | [Step]      | High/Med/Low | High/Med/Low | High/Med/Low |
| 2    | [Step]      | High/Med/Low | High/Med/Low | High/Med/Low |

### Load Issues Identified

#### Intrinsic Load Problems

- [Issue]: [Location]
- [Issue]: [Location]

#### Extraneous Load Problems

- [Issue]: [Location]
- [Issue]: [Location]

### Recommendations

| Priority | Change            | Expected Impact       |
| -------- | ----------------- | --------------------- |
| High     | [Specific change] | [Reduces X load by Y] |
| Medium   | [Specific change] | [Reduces X load by Y] |

### Success Metrics

| Metric               | Current | Target |
| -------------------- | ------- | ------ |
| Task completion rate | X%      | Y%     |
| Time to complete     | X min   | Y min  |
| Error rate           | X%      | Y%     |
| User satisfaction    | X       | Y      |

Real-World Examples

Google Search

Load Optimization:

Intrinsic:  Minimal - just type what you want
Extraneous: Near zero - white space + search box
Germane:    Focus on learning query refinement

Result: 2-3x faster searches than competitors

Slack Progressive Disclosure

New User Experience:
├── Basic: Messaging interface only
├── Intermediate: Threading, channels
├── Advanced: Integrations, workflows
└── Enterprise: Admin controls

Each level builds on previous knowledge (germane load)
without overwhelming new users (extraneous load).

Apple iOS Consistency

System-wide Patterns:

Gestures:
├── Swipe from left = back (everywhere)
├── Pull down = refresh (everywhere)
├── Long press = more options (everywhere)
└── Pinch = zoom (everywhere)

Consistency eliminates extraneous load.
Users learn once, apply everywhere.

Design Strategies by Load Type

Reducing Intrinsic Load

StrategyImplementation
Task chunkingMax 3-5 items per screen
Mental model alignmentUse familiar metaphors
Smart defaultsPre-select common choices
Contextual helpShow info when needed

Eliminating Extraneous Load

StrategyImplementation
Visual hierarchySize, color, position guide attention
Consistent patternsSame action = same interaction
Content prioritizationMost important info first
Distraction removalNo unnecessary animations/elements

Optimizing Germane Load

StrategyImplementation
Clear feedbackShow results of every action
Pattern consistencyCreate learnable behaviors
Progressive enhancementReveal features as expertise grows
Knowledge transferDesign transferable skills

Measurement Approaches

Quantitative

  • Task completion time
  • Error rate and recovery time
  • Number of help requests
  • Tab/window switches during task
  • Abandonment points

Qualitative

  • Think-aloud testing (confusion points)
  • Cognitive walkthroughs (step-by-step effort)
  • Post-task interviews (perceived difficulty)
  • Eye tracking (scanning patterns)

Integration with Other Methods

MethodCombined Use
Cognitive FluencyFluency is one way to reduce extraneous load
Hick's LawFewer choices = lower load
Progressive DisclosureManage intrinsic load over time
Graph ThinkingMap load relationships across system
Five WhysWhy are users struggling/abandoning?

Quick Reference

COGNITIVE LOAD CHECKLIST

Intrinsic Load Management:
□ Tasks broken into 3-5 step chunks
□ Progressive disclosure for complexity
□ Different paths for different expertise
□ Builds on familiar concepts

Extraneous Load Elimination:
□ Clear visual hierarchy
□ Consistent interaction patterns
□ No unnecessary decorative elements
□ Logical information architecture

Germane Load Optimization:
□ Clear feedback on all actions
□ Patterns that transfer across features
□ Onboarding builds mental models
□ Advanced features reward learning

Testing:
□ Task completion measured
□ Error rates tracked
□ User confusion points identified
□ Learning curve improving over time

Resources

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平台分布

Codex

34.78%
按下载量换算72

Claude

28.43%
按下载量换算59

Cursor

19.6%
按下载量换算41

Gemini CLI

9.17%
按下载量换算19

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