churn-prevention

churn-prevention is a skill for Claude Code, Codex from serejaris/kimi-skills. It costs 95 tokens per session (2,431 once invoked), scanned A, a copy of claude-skills-marketing-skill-churn-prevention-churn-prevention, MIT.

A customer-retention planning guide for reducing cancellations and failed-payment losses in subscription software. It covers cancellation flows, save offers, exit surveys, and payment-recovery email sequences.

In plain words
What is it for?
Use it to design or improve cancellation flows, offer alternatives to customers who want to leave, collect exit reasons, and recover failed subscription payments.
Why use it?
It helps separate two common causes of customer loss: people choosing to leave and payments failing. It also structures the information needed to design an appropriate retention process.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to design or improve cancellation flows, offer alternatives to customers who want to leave, collect exit reasons, and recover failed subscription payments.

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Install with agentmods
npx agentmods add skills/serejaris/kimi-skills/churn-prevention
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add serejaris/kimi-skills --skill churn-prevention
Clone the repo
git clone --depth 1 https://github.com/serejaris/kimi-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for churn-prevention

README.md
[![agentmods](https://agentmods.dev/badge/skills/serejaris/kimi-skills/churn-prevention/github.svg)](https://agentmods.dev/skills/serejaris/kimi-skills/churn-prevention)
Your own site
<a href="https://agentmods.dev/skills/serejaris/kimi-skills/churn-prevention"><img src="https://agentmods.dev/badge/skills/serejaris/kimi-skills/churn-prevention/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for churn-prevention

Your own site · 80×15
<a href="https://agentmods.dev/skills/serejaris/kimi-skills/churn-prevention"><img src="https://agentmods.dev/badge/skills/serejaris/kimi-skills/churn-prevention.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 95 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,431 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 94% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00095 $0.02431
Opus 5 $0.00048 $0.01215
Sonnet 5 $0.00019 $0.00486
Haiku 4.5 $0.00010 $0.00243

Measured 12d ago against content hash fc29b6e4d431, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

churn-prevention scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/churn_impact_calculator.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

94% identical to claude-skills-marketing-skill-churn-prevention-churn-prevention — 16 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/churn-prevention/SKILL.md · 233 lines

How it starts

The opening of the file, as written. The whole thing — 233 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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:

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.

Read the full file on GitHub · 233 lines

Files

What ships with it

6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 233 lines · 95 tokens per session scan A fc29b6e4d431

Subscribe to this mod's changes

churn-prevention is a skill published in the GitHub repository serejaris/kimi-skills (6 stars, last pushed 1mo ago), licensed MIT. It adds 95 tokens to every session and 2,431 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to claude-skills-marketing-skill-churn-prevention-churn-prevention, differing in 16 lines, and is treated as a copy.

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