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halo-effect-psychology光环效应心理学

Agent Skill

halo-effect-psychology 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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

612

周安装

26

GitHub Stars

239

下载量

214
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:halo-effect-psychology(光环效应心理学)
来源仓库:https://github.com/flpbalada/my-opencode-config
仓库路径:skills/halo-effect-psychology
安装命令:
npx skills add https://github.com/flpbalada/my-opencode-config --skill halo-effect-psychology
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 halo-effect-psychology

简介

应用心理学原理优化人机交互与用户体验设计。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

  • 适用于界面引导、文案说服力和认知负荷评估场景。
  • 提供行为模式分析与 A/B 测试思路,辅助决策制定。
  • 理论建议需结合实际数据验证,不可盲目套用结论。
  • halo-effect-psychology 属于开发类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Halo Effect Psychology - First Impressions Shape Everything

The Halo Effect is a cognitive bias where our overall impression of something influences how we perceive its specific attributes. First documented by psychologist Edward Thorndike in 1920, it explains why a positive experience in one area creates favorable assumptions about unrelated areas.

When to Use This Skill

  • Designing onboarding experiences and first impressions
  • Planning feature releases and product announcements
  • Crafting brand positioning and visual identity
  • Optimizing landing pages and conversion funnels
  • Understanding user perception patterns
  • Prioritizing polish vs. functionality tradeoffs

Core Concepts

The Psychology Behind the Halo

First Impression (Positive)
         |
         v
    Global Judgment
   "This seems good"
         |
    +----+----+----+
    |    |    |    |
    v    v    v    v
  Speed Quality Trust Design
   (+)   (+)   (+)   (+)

All attributes get lifted by the initial positive impression

Halo Effect Triggers

TriggerExampleImpact
Visual DesignPolished UI"Must be high quality"
SpeedFast load times"Professional team"
Social ProofNotable logos"Trustworthy product"
PricingPremium price"Superior features"
AssociationCelebrity endorsement"Desirable brand"

Reverse Halo (Horn Effect)

The opposite also applies - one negative experience taints everything:

  • Slow website = "The whole product is probably slow"
  • One bug = "The code quality must be poor"
  • Poor support = "They don't care about customers"

Analysis Framework

Step 1: Map First Impression Points

Identify where users form initial judgments:

  1. Pre-product: Marketing, reviews, word-of-mouth
  2. First contact: Landing page, app store listing
  3. Onboarding: Setup, first interaction
  4. First value: Initial "aha" moment

Step 2: Audit Halo Triggers

For each touchpoint, evaluate:

+------------------+--------+--------+------------------+
| Touchpoint       | Visual | Speed  | Polish Level     |
+------------------+--------+--------+------------------+
| Landing page     | [ /5 ] | [ /5 ] | [ /5 ]           |
| Sign-up flow     | [ /5 ] | [ /5 ] | [ /5 ]           |
| First dashboard  | [ /5 ] | [ /5 ] | [ /5 ]           |
| Key action       | [ /5 ] | [ /5 ] | [ /5 ]           |
+------------------+--------+--------+------------------+

Step 3: Strategic Polish Allocation

Prioritize polish where halo effects are strongest:

PriorityAreaRationale
CriticalFirst 30 secondsSets global perception
HighCore feature first useDefines product quality
MediumSecondary featuresBorrows from initial halo
LowerAdvanced featuresUsers already committed

Output Template

## Halo Effect Analysis

**Product/Feature:** [Name] **Analysis Date:** [Date]

### First Impression Audit

| Touchpoint | Current Score | Target | Priority |
| ---------- | ------------- | ------ | -------- |
| [Point 1]  | [1-5]         | [1-5]  | [H/M/L]  |
| [Point 2]  | [1-5]         | [1-5]  | [H/M/L]  |

### Halo Triggers Present

- [ ] Professional visual design
- [ ] Fast performance
- [ ] Social proof elements
- [ ] Premium positioning
- [ ] Quality copywriting

### Horn Effect Risks

| Risk     | Likelihood | Impact  | Mitigation |
| -------- | ---------- | ------- | ---------- |
| [Risk 1] | [H/M/L]    | [H/M/L] | [Action]   |

### Recommendations

1. **Quick wins:** [Immediate improvements]
2. **Strategic investments:** [Longer-term polish]
3. **Risk mitigation:** [Prevent negative halos]

Real-World Examples

Example 1: Apple's Unboxing Experience

Apple invests heavily in packaging despite it being discarded:

  • Trigger: Premium unboxing creates positive first impression
  • Halo transfer: "If they care this much about packaging, the product must be exceptional"
  • Result: Higher perceived quality before device is even turned on

Example 2: Stripe's Documentation

Stripe's exceptionally clear documentation creates perception of:

  • Clean, well-designed API
  • Professional engineering team
  • Reliable infrastructure
  • Easy integration

Reality: Documentation quality correlates with but doesn't guarantee these attributes.

Example 3: Slow SaaS Onboarding

A B2B tool with:

  • 4-second page loads
  • Clunky form validation
  • Visual glitches

Creates horn effect:

  • "If signup is this bad, the product must be worse"
  • "They probably don't have good engineers"
  • "My data might not be safe here"

Best Practices

Do

  • Invest disproportionately in first impressions
  • Fix performance issues before adding features
  • Use loading states and animations to mask delays
  • Maintain consistency - one polished area raises expectations
  • Test with fresh users who haven't developed familiarity

Avoid

  • Relying on "users will understand once they see the value"
  • Shipping MVP quality for core features
  • Letting one broken flow undermine perception
  • Assuming rational users will judge features independently
  • Inconsistent quality that breaks the halo

Integration with Other Methods

MethodCombined Use
Cognitive LoadReduce load at first impression points
Progressive DisclosureShow polished essentials first
Fogg Behavior ModelHigh motivation overcomes minor friction
Curiosity GapCreate intrigue before revealing full experience

Resources

适合场景

01

用户想查找某类 Agent Skill 时

02

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03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

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能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

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

Codex

36.17%
按下载量换算77

Claude

30.06%
按下载量换算64

Cursor

20.08%
按下载量换算43

Gemini CLI

10.41%
按下载量换算22

安全审计

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通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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