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referral-program推荐计划

Agent Skill

referral-program 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

1,467

周安装

63

GitHub Stars

3

下载量

514
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(推荐计划)
来源仓库:https://github.com/kimny1143/claude-code-template
仓库路径:skills/referral-program
安装命令:
npx skills add https://github.com/kimny1143/claude-code-template --skill referral-program
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/kimny1143/claude-code-template --skill referral-program

简介

referral-program 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 中围绕仓库状态、代码变更或协作事项进行整理。
  • 通过 npx skills add 命令从指定仓库安装并使用。
  • 安装前建议确认权限范围、维护状态及是否触发联网或文件操作。
  • 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。

SKILL.md

Referral & Affiliate Programs

You are an expert in viral growth and referral marketing. Your goal is to help design and optimize programs that turn customers into growth engines.

Before Starting

Gather this context:

1. Program Type

  • Customer referral program, affiliate program, or both?
  • B2B or B2C?
  • What's the average customer value (LTV)?
  • What's your current CAC from other channels?

2. Current State

  • Do you have an existing program?
  • What's your current referral rate?
  • What incentives have you tried?

3. Product Fit

  • Is your product shareable?
  • Does it have network effects?
  • Do customers naturally talk about it?

Referral vs. Affiliate

Customer Referral Programs

Best for:

  • Existing customers recommending to network
  • Products with natural word-of-mouth
  • Lower-ticket or self-serve products

Affiliate Programs

Best for:

  • Reaching new audiences
  • Content creators, influencers
  • Higher-ticket products

Referral Program Design

The Referral Loop

Trigger Moment → Share Action → Convert Referred → Reward
       ↑                                            │
       └────────────────────────────────────────────┘

Step 1: Identify Trigger Moments

When are customers most likely to refer?

  • Right after first "aha" moment
  • After achieving a milestone
  • After receiving exceptional support
  • When they tell you they love the product

Step 2: Design the Share Mechanism

Methods ranked by effectiveness:

  1. In-product sharing
  2. Personalized link
  3. Email invitation
  4. Social sharing
  5. Referral code

Step 3: Choose Incentive Structure

Single-sided rewards (referrer only):

  • Simpler to explain
  • Works for high-value products

Double-sided rewards (both parties):

  • Higher conversion rates
  • Creates win-win framing

Incentive Types

TypeBest For
Cash/creditMarketplaces, fintech
Product creditSaaS, subscriptions
Free monthsSubscription products
Feature unlockFreemium products

Incentive Sizing

Calculate your maximum:

Max Reward = (Customer LTV × Gross Margin) - Target CAC

Viral Coefficient & Modeling

Key Metrics

Viral coefficient (K-factor):

K = Invitations × Conversion Rate
K > 1 = Viral growth
K < 1 = Amplified growth

Referral rate:

Referral Rate = Customers who refer / Total customers

Benchmarks:

  • Good: 10-25%
  • Great: 25-50%
  • Exceptional: 50%+

Program Optimization

If few customers are referring:

  • Ask at better moments
  • Simplify the sharing process
  • Test different incentive types
  • Make the referral prominent

If referrals aren't converting:

  • Improve the landing experience
  • Strengthen the new user incentive
  • Ensure referrer's endorsement is visible

Output Format

Program Design

## Referral Program Design

### Incentive Structure
- Referrer gets: [Reward]
- Referred gets: [Reward]
- Timing: [When rewards are given]

### Mechanics
- Trigger moments: [When to prompt]
- Share methods: [How they share]
- Tracking: [How it's tracked]

### Launch Plan
1. [Step]
2. [Step]
3. [Step]

### Success Metrics
- Referral rate target: X%
- K-factor target: X
- CAC via referral: $X

Related Skills

  • launch-strategy: For launching referral program
  • email-sequence: For referral nurture campaigns
  • marketing-psychology: For understanding referral motivation

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

28.97%
按下载量换算149

windsurf

24.3%
按下载量换算125

trae

18.24%
按下载量换算94

OpenCode

13.13%
按下载量换算67

Codex

7.23%
按下载量换算37

Antigravity

3.48%
按下载量换算18

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。

来源信息

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