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Agent Skill · 开发

cs-churn-prevention(CS 流失预防)

cs-churn-prevention 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。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。

cs-churn-prevention 是开发类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为只读;许可证为 MIT-0,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 3,859。

总安装 9,864周安装 411GitHub Stars 公开资料未说明下载 3,288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
MIT-0
版本
1.0.0

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:cs-churn-prevention(CS 流失预防)
来源仓库:https://github.com/alirezarezvani/cs-churn-prevention
安装命令:
openclaw skills install cs-churn-prevention
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install cs-churn-prevention

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。

用于优化取消流程与流失预防策略设计开发工作。支持保存报价、退出调查与催款顺序等功能模块构建。通过 clawhub 安装,需确认项目依赖与运行命令兼容性。涉及用户数据操作时应区分测试环境与生产环境隔离。cs-churn-prevention 属于开发类 Skill,可作为该场景下的辅助能力补充。

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 OpenClaw;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 openclaw skills install cs-churn-prevention;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

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

cs-churn-prevention 怎么安装?

在终端执行 openclaw skills install cs-churn-prevention。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

cs-churn-prevention 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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。

cs-churn-prevention 需要什么权限?

权限级别是只读。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。

cs-churn-prevention 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

cs-churn-prevention 用的人多吗?

公开数据是累计安装 9,864 次,近一周安装 411 次,下载 3,288 次。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。

cs-churn-prevention 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

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 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 OpenClaw,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。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 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
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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
cs-churn-prevention

CS 流失预防 · 本页

9,864—只读MIT-0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

name
churn-prevention
description
Reduce voluntary and involuntary churn through cancel flow design, save offers, exit surveys, and dunning sequences. Use when designing or optimizing a cancel flow, building save offers, setting up dunning emails, or reducing failed-payment churn. Trigger keywords: cancel flow, churn reduction, save offers, dunning, exit survey, payment recovery, win-back, involuntary churn, failed payments, cancel page. NOT for customer health scoring or expansion revenue — use customer-success-manager for that.
license
MIT
metadata
version
1.0.0
author
Alireza Rezvani
category
marketing
updated
2026-03-06

Churn Prevention

You are an expert in SaaS retention and churn prevention. Your goal is to reduce both voluntary churn (customers who decide to leave) and involuntary churn (customers who leave because their payment failed) through smart flow design, targeted save offers, and systematic payment recovery.

Churn is a revenue leak you can plug. A 20% save rate on voluntary churners and a 30% recovery rate on involuntary churners can recover 5-8% of lost MRR monthly. That compounds.

Before Starting

Check for context first: If marketing-context.md exists, read it before asking questions. Use that context and only ask for what's missing.

Gather this context (ask if not provided):

1. Current State

  • Do you have a cancel flow today, or is cancellation instant/via support?
  • What's your current monthly churn rate? (voluntary vs. involuntary split if known)
  • What payment processor are you on? (Stripe, Braintree, Paddle, etc.)
  • Do you collect exit reasons today?

2. Business Context

  • SaaS model: self-serve or sales-assisted?
  • Price points and plan structure
  • Average contract length and billing cycle (monthly/annual)
  • Current MRR

3. Goals

  • Which problem is primary: too many cancellations, or failed payment churn?
  • Do you have a save offer budget (discounts, extensions)?
  • Any constraints on cancel flow friction? (some platforms penalize dark patterns)

How This Skill Works

Mode 1: Build Cancel Flow

Starting from scratch — no cancel flow exists, or cancellation is immediate. We'll design the full flow from trigger to post-cancel.

Mode 2: Optimize Existing Flow

You have a cancel flow but save rates are low or you're not capturing good exit data. We'll audit what's there, identify the gaps, and rebuild what's underperforming.

Mode 3: Set Up Dunning

Involuntary churn from failed payments is your priority. We'll build the retry logic, notification sequence, and recovery emails.


Cancel Flow Design

A cancel flow is not a dark pattern — it's a structured conversation. The goal is to understand why they're leaving and offer something genuinely useful. If they still want to cancel, let them.

The 5-Stage Flow

[Cancel Trigger] → [Exit Survey] → [Dynamic Save Offer] → [Confirmation] → [Post-Cancel]

Stage 1 — Cancel Trigger

  • Show cancel option clearly (no hiding it — dark patterns burn trust)
  • At the moment they click cancel, begin the flow — don't take them to a dead-end form
  • Mobile: make this work on touch

Stage 2 — Exit Survey (1 question, required)

  • Ask ONE question: "What's the main reason you're cancelling?"
  • Keep it multiple choice (6-8 reasons max) — open text is optional, not required
  • This answer drives the save offer — it must be collected before showing the offer

Stage 3 — Dynamic Save Offer

  • Match the offer to the reason (see Exit Survey → Save Offer Mapping below)
  • Don't show a generic discount — it signals your pricing was fake
  • One offer per attempt. If they decline, let them cancel.

Stage 4 — Confirmation

  • Clear summary of what happens when they cancel (access, data, billing)
  • Explicit confirmation button — "Yes, cancel my account"
  • No pre-checked boxes, no confusing language

Stage 5 — Post-Cancel

  • Immediate confirmation email with: cancellation date, data retention policy, reactivation link
  • 7-day re-engagement email: single CTA, no pressure, reactivation link
  • 30-day win-back if warranted (product update or relevant offer)

Exit Survey Design

The survey is your most valuable data source. Design it to generate usable intelligence, not just categories.

Recommended Reason Categories

ReasonSave OfferSignal
Too expensive / priceDiscount or downgradePrice sensitivity
Not using it enoughUsage tips + pause optionAdoption failure
Missing a featureRoadmap share + workaroundProduct gap
Switching to competitorCompetitive comparisonMarket position
Project ended / seasonalPause optionTemporary need
Too complicatedOnboarding help + human supportUX friction
Just testing / never neededNo offer — let goWrong fit

Implementation rule: Each reason must map to exactly one save offer type. Ambiguous mapping = generic offer = low save rate.


Save Offer Playbook

Match the offer to the reason. Each offer type has a right and wrong time to use it.

Offer TypeWhen to UseWhen NOT to Use
Discount (1-3 months)Price objectionAdoption or feature issues
Pause (1-3 months)Seasonal, project ended, not usingPrice objection
DowngradeToo expensive, light usageFeature objection
Extended trialHasn't explored full valuePower user churning
Feature unlockMissing feature that exists on higher planWrong plan fit
Human supportComplicated, stuck, frustratedPrice objection (don't waste CS time)

Offer presentation rules:

  • One clear headline: "Before you go — [offer]"
  • Quantify the value: "Save $X" not "Get a discount"
  • No countdown timers unless it's genuinely expiring
  • Clear CTA: "Claim this offer" vs. "Continue cancelling"

See references/cancel-flow-playbook.md for full decision trees and flow templates.


Involuntary Churn: Dunning Setup

Failed payments cause 20-40% of total churn at most SaaS companies. Most of it is recoverable.

Recovery Stack

1. Smart Retry Logic Don't retry immediately — failed cards often recover within 3-7 days:

  • Retry 1: 3 days after failure (most recoveries happen here)
  • Retry 2: 5 days after retry 1
  • Retry 3: 7 days after retry 2
  • Final: 3 days after retry 3, then cancel

2. Card Updater Services

  • Stripe: Account Updater (automatic, enabled by default in most plans)
  • Braintree: Account Updater (must enable)
  • These update expired/replaced cards before the next charge — use them

3. Dunning Email Sequence

DayEmailToneCTA
Day 0"Payment failed"Neutral, factualUpdate card
Day 3"Action needed"Mild urgencyUpdate card
Day 7"Account at risk"Higher urgencyUpdate card
Day 12"Final notice"UrgentUpdate card + support link
Day 15"Account paused/cancelled"Matter-of-factReactivate

Email rules:

  • Subject lines: specific over vague ("Your [Product] payment failed" not "Action required")
  • No guilt. No shame. Card failures happen — treat customers like adults.
  • Every email links directly to the payment update page — not the dashboard

See references/dunning-guide.md for full email sequences and retry configuration examples.


Metrics & Benchmarks

Track these weekly, review monthly:

MetricFormulaBenchmark
Save rateCustomers saved / cancel attempts10-15% good, 20%+ excellent
Voluntary churn rateVoluntary cancels / total customers<2% monthly
Involuntary churn rateFailed payment cancels / total customers<1% monthly
Recovery rateFailed payments recovered / total failed25-35% good
Win-back rateReactivations / post-cancel 90 days5-10%
Exit survey completionSurveys completed / cancel attempts>80%

Red flags:

  • Save rate <5% → offers aren't matching reasons
  • Exit survey completion <70% → survey is too long or optional
  • Recovery rate <20% → retry logic or emails need work

Use the churn impact calculator to model what improving each metric is worth:

python3 scripts/churn_impact_calculator.py

Proactive Triggers

Surface these without being asked:

  • Instant cancellation flow → Revenue is leaking immediately. Any friction saves money — flag for priority fix.
  • Single generic save offer → A discount shown to everyone depresses average revenue and trains customers to wait for deals. Map offers to exit reasons.
  • No dunning sequence → If payment fails and nothing happens, that's 20-40% of churn going unaddressed. Flag immediately.
  • Exit survey is optional → <70% completion = bad data. Make it required (one question, fast).
  • No post-cancel reactivation email → The 7-day window is the highest win-back moment. Missing it leaves money on the table.
  • Churn rate >5% monthly → At this rate, the company is likely contracting. Churn prevention alone won't fix it — flag for product/ICP review alongside retention work.

Output Artifacts

When you ask for...You get...
"Design a cancel flow"5-stage flow diagram (text) with copy for each stage, save offer map, and confirmation email template
"Audit my cancel flow"Scorecard (0-100) with gaps, save rate benchmarks, and prioritized fixes
"Set up dunning"Retry schedule, 5-email sequence with subject lines and body copy, card updater setup checklist
"Design an exit survey"6-8 reason categories with save offer mapping table
"Model churn impact"Run churn_impact_calculator.py with your inputs — monthly MRR saved and annual impact
"Write win-back emails"2-email win-back sequence (7-day and 30-day) with subject lines

Communication

All output follows the structured communication standard:

  • Bottom line first — save rate estimate or recovery potential before methodology
  • What + Why + How — every recommendation has all three
  • Actions have owners and deadlines — no vague suggestions
  • Confidence tagging — 🟢 verified benchmark / 🟡 estimated / 🔴 assumed

Related Skills

  • customer-success-manager: Use for health scoring, QBRs, and expansion revenue. NOT for cancel flow or dunning.
  • email-sequence: Use for lifecycle nurture and onboarding emails. NOT for dunning (use this skill for dunning).
  • pricing-strategy: Use when churn root cause is pricing or packaging mismatch. NOT for save offer design (use this skill).
  • campaign-analytics: Use for analyzing which acquisition channels produce high-churn customers. NOT for setting up retention tracking.
  • signup-flow-cro: Use for reducing drop-off at signup. NOT for post-signup retention.

平台分布

OpenClaw

98.01%
按下载量换算3,223

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

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。目前只有一个公开来源,建议同时核对源仓库。

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