Token导航 LogoToken导航

Agent Skill · 开发

halo-effect-psychology(光环效应心理学)

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。

halo-effect-psychology 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 15,264。

总安装 612周安装 26GitHub Stars 239下载 214核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

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。

来源仓库内路径:skills/halo-effect-psychology

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/flpbalada/my-opencode-config --skill halo-effe…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

halo-effect-psychology 怎么安装?

在终端执行 npx skills add https://github.com/flpbalada/my-opencode-config --skill halo-effect-psychol…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

halo-effect-psychology 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

halo-effect-psychology 需要什么权限?

权限级别是需要联网。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。

halo-effect-psychology 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

halo-effect-psychology 用的人多吗?

公开数据是累计安装 612 次,近一周安装 26 次,下载 214 次,GitHub 239 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

halo-effect-psychology 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
halo-effect-psychology

光环效应心理学 · 本页

612239需要联网未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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

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

Gen Agent Trust Hub

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。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills