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referral-program-designer推荐计划设计师

Agent Skill

referral-program-designer 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

12,470

周安装

309

GitHub Stars

公开资料未说明

下载量

2,284
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

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:referral-program-designer(推荐计划设计师)
来源仓库:https://github.com/eddiebe147/claude-settings
仓库路径:skills/referral-program-designer
安装命令:
npx skills add https://github.com/eddiebe147/claude-settings --skill 'Referral Program Designer'
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/eddiebe147/claude-settings --skill 'Referral Program Designer'

简介

referral-program-designer 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。

  • 适用于研究检索类任务,如信息搜集、资料筛选和知识整理,尤其适合多源数据聚合与初步分析。
  • 通过关键词、任务描述或来源仓库提供查询条件,返回结构化候选结果列表供进一步处理。
  • 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。
  • 可结合来源仓库、安装命令和原始 README 继续核验具体用法。

SKILL.md

Referral Program Designer

Create referral programs that turn happy customers into active promoters. This skill helps you design incentive structures, referral mechanics, and program experiences that motivate sharing and drive cost-effective customer acquisition.

Referrals are the gold standard of marketing - lower CAC, higher LTV, and built-in social proof. This skill provides frameworks for incentive design, program mechanics, viral loop optimization, and measurement. Learn from programs like Dropbox, Uber, and Airbnb to build referral engines that fuel growth.

Built for growth marketers, product managers, founders, and anyone looking to scale acquisition through word-of-mouth.

Core Workflows

Workflow 1: Referral Program Design

  1. Goal Setting - What you want the program to achieve
  2. Customer Motivation Analysis - Why would they refer?
  3. Incentive Structure - What to offer referrers and referees
  4. Reward Mechanics - When and how rewards are delivered
  5. Sharing Mechanics - How referrals are made
  6. Tracking Design - Attribution and fraud prevention
  7. Program Terms - Rules and limitations

Workflow 2: Incentive Optimization

  1. Incentive Type Selection - Cash, credit, product, status
  2. Two-Sided Incentives - Benefit for both parties
  3. Reward Timing - Instant vs delayed gratification
  4. Tiered Rewards - Increasing incentives for more referrals
  5. Milestone Bonuses - Extra rewards for achievement
  6. A/B Testing Plan - Test different incentive structures
  7. Economics Modeling - Ensure sustainable unit economics

Workflow 3: Program Launch

  1. MVP Program Design - Minimum viable referral program
  2. Technical Requirements - Tracking, attribution, rewards
  3. Communication Strategy - How to promote the program
  4. In-Product Integration - Where referral lives in experience
  5. Email Sequence - Referral program nurture
  6. Launch Metrics - Success indicators
  7. Optimization Roadmap - Post-launch improvements

Workflow 4: Viral Loop Enhancement

  1. Friction Audit - Where do people drop off?
  2. Share Flow Optimization - Make sharing effortless
  3. Message Customization - Personalized referral messaging
  4. Multi-Channel Sharing - Email, social, direct message
  5. Reminder Strategy - Re-engage with referral reminders
  6. Viral Coefficient Calculation - Measure program virality
  7. Loop Optimization - Improve K-factor over time

Quick Reference

ActionCommand/Trigger
Design program"Design referral program for [product/service]"
Incentive structure"Create incentive structure for referrals"
Viral loop analysis"Analyze viral loop for [program]"
Launch plan"Create referral program launch plan"
Optimize incentives"Improve referral incentives"
Email sequence"Write referral program email sequence"
Calculate K-factor"Calculate viral coefficient"
Fraud prevention"Design fraud prevention for referrals"

Best Practices

  • Make it easy - Fewer clicks = more referrals
  • Two-sided incentives - Benefit both parties
  • Relevant rewards - Match incentive to product value
  • Immediate gratification - Faster rewards drive behavior
  • Clear communication - Simple explanation of how it works
  • In-product placement - Referral should be discoverable
  • Timing matters - Ask after positive experiences
  • Personalization - Customizable referral messages
  • Social proof - Show others referring successfully
  • Multiple channels - Enable various sharing methods
  • Fraud prevention - Design to prevent gaming
  • Track everything - Attribution and conversion data
  • Test constantly - Optimize incentives and mechanics
  • Celebrate success - Recognize top referrers
  • Sustainable economics - CAC savings must exceed reward costs

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

29.86%
按下载量换算682

OpenCode

20.65%
按下载量换算472

Gemini CLI

15.56%
按下载量换算355

Antigravity

12.5%
按下载量换算286

Cursor

7.26%
按下载量换算166

Codex

3.26%
按下载量换算74

安全审计

Gen Agent Trust Hub

通过

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。来源字段存在多来源差异,先按来源优先级自动处理,无法消解时进入异常复核队列。

来源信息

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