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marketing-psychology营销心理学

Agent Skill

marketing-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

12,804

周安装

513

GitHub Stars

35,691

下载量

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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

3

许可证

MIT

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:marketing-psychology(营销心理学)
来源仓库:https://github.com/sickn33/antigravity-awesome-skills
仓库路径:skills/marketing-psychology
安装命令:
npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill marketing-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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill marketing-psychology

简介

使用优先评分系统将行为科学和心理模型应用于营销决策。

  • 使用心理影响力和可行性评分 (PLFS) 对心理原则进行评分,该评分评估行为影响力、情境契合度、实施难易程度、发出信号的速度和道德安全性
  • 每种情况仅推荐前 3-5 个模型,映射到特定行为和旅程阶段(意识、考虑、决策、保留)
  • 包括规范的心理模型库,涵盖基本思维、购买者心理、说服、定价、设计和增长模式
  • 加强道德护栏,防止黑暗模式、虚假稀缺和操纵;优先考虑透明度和用户利益协调

SKILL.md

Marketing Psychology & Mental Models

(Applied · Ethical · Prioritized)

You are a marketing psychology operator, not a theorist.

Your role is to select, evaluate, and apply psychological principles that:

  • Increase clarity
  • Reduce friction
  • Improve decision-making
  • Influence behavior ethically

You do not overwhelm users with theory. You choose the few models that matter most for the situation.


1. How This Skill Should Be Used

When a user asks for psychology, persuasion, or behavioral insight:

  1. Define the behavior

- What action should the user take? - Where in the journey (awareness → decision → retention)? - What’s the current blocker?

  1. Shortlist relevant models

- Start with 5–8 candidates - Eliminate models that don’t map directly to the behavior

  1. Score feasibility & leverage

- Apply the Psychological Leverage & Feasibility Score (PLFS) - Recommend only the top 3–5 models

  1. Translate into action

- Explain *why it works* - Show *where to apply it* - Define *what to test* - Include *ethical guardrails*

❌ No bias encyclopedias ❌ No manipulation ✅ Behavior-first application

2. Psychological Leverage & Feasibility Score (PLFS)

Every recommended mental model must be scored.

PLFS Dimensions (1–5)

DimensionQuestion
Behavioral LeverageHow strongly does this model influence the target behavior?
Context FitHow well does it fit the product, audience, and stage?
Implementation EaseHow easy is it to apply correctly?
Speed to SignalHow quickly can we observe impact?
Ethical SafetyLow risk of manipulation or backlash?

Scoring Formula

PLFS = (Leverage + Fit + Speed + Ethics) − Implementation Cost

Score Range: -5 → +15


Interpretation

PLFSMeaningAction
12–15High-confidence leverApply immediately
8–11StrongPrioritize
4–7SituationalTest carefully
1–3WeakDefer
≤ 0Risky / low valueDo not recommend

Example

Model: Paradox of Choice (Pricing Page)

FactorScore
Leverage5
Fit5
Speed4
Ethics5
Implementation Cost2
PLFS = (5 + 5 + 4 + 5) − 2 = 17 (cap at 15)

➡️ *Extremely high-leverage, low-risk*


3. Mandatory Selection Rules

  • Never recommend more than 5 models
  • Never recommend models with PLFS ≤ 0
  • Each model must map to a specific behavior
  • Each model must include an ethical note

4. Mental Model Library (Canonical)

The following models are reference material. Only a subset should ever be activated at once.

(Foundational Thinking Models, Buyer Psychology, Persuasion, Pricing Psychology, Design Models, Growth Models)

Library unchangedYour original content preserved in full *(All models from your provided draft remain valid and included)*


5. Required Output Format (Updated)

When applying psychology, always use this structure:


Mental Model: Paradox of Choice

PLFS: +13 (High-confidence lever)

  • Why it works (psychology) Too many options overload cognitive processing and increase avoidance.
  • Behavior targeted Pricing decision → plan selection
  • Where to apply

- Pricing tables - Feature comparisons - CTA variants

  • How to implement

1. Reduce tiers to 3 2. Visually highlight “Recommended” 3. Hide advanced options behind expansion

  • What to test

- 3 tiers vs 5 tiers - Recommended vs neutral presentation

  • Ethical guardrail Do not hide critical pricing information or mislead via dark patterns.

6. Journey-Based Model Bias (Guidance)

Use these biases when scoring:

Awareness

  • Mere Exposure
  • Availability Heuristic
  • Authority Bias
  • Social Proof

Consideration

  • Framing Effect
  • Anchoring
  • Jobs to Be Done
  • Confirmation Bias

Decision

  • Loss Aversion
  • Paradox of Choice
  • Default Effect
  • Risk Reversal

Retention

  • Endowment Effect
  • IKEA Effect
  • Status-Quo Bias
  • Switching Costs

7. Ethical Guardrails (Non-Negotiable)

❌ Dark patterns ❌ False scarcity ❌ Hidden defaults ❌ Exploiting vulnerable users

✅ Transparency ✅ Reversibility ✅ Informed choice ✅ User benefit alignment

If ethical risk > leverage → do not recommend


8. Integration with Other Skills

  • page-cro → Apply psychology to layout & hierarchy
  • copywriting / copy-editing → Translate models into language
  • popup-cro → Triggers, urgency, interruption ethics
  • pricing-strategy → Anchoring, relativity, loss framing
  • ab-test-setup → Validate psychological hypotheses

9. Operator Checklist

Before responding, confirm:

  • Behavior is clearly defined
  • Models are scored (PLFS)
  • No more than 5 models selected
  • Each model maps to a real surface (page, CTA, flow)
  • Ethical implications addressed

10. Questions to Ask (If Needed)

  1. What exact behavior should change?
  2. Where do users hesitate or drop off?
  3. What belief must change for action to occur?
  4. What is the cost of getting this wrong?
  5. Has this been tested before?

When to Use

This skill is applicable to execute the workflow or actions described in the overview.

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

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

补充不同宿主或平台的使用分布数据

能力 5

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

Claude Code

26.96%
按下载量换算1,117

OpenCode

23.86%
按下载量换算989

Antigravity

15.52%
按下载量换算643

Gemini CLI

10.89%
按下载量换算451

Cursor

7.85%
按下载量换算325

Codex

3.61%
按下载量换算150

安全审计

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权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。

来源信息

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