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.
npx agentmods add skills/xyruscode/ai-sync/churn-preventionnpx skills add XyrusCode/ai-sync --skill churn-preventiongit clone --depth 1 https://github.com/XyrusCode/ai-syncWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00095 | $0.02431 |
| Opus 5 | $0.00048 | $0.01215 |
| Sonnet 5 | $0.00019 | $0.00486 |
| Haiku 4.5 | $0.00010 | $0.00243 |
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 yesterday.
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.
This is a copy
100% identical to churn-prevention — 0 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.
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.
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.
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.
- yesterday First seen · 233 lines · 95 tokens per session scan A fc29b6e4d431
churn-prevention is a skill published in the GitHub repository XyrusCode/ai-sync (2 stars, last pushed 2d 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 100% identical to churn-prevention, differing in 0 lines, and is treated as a copy.
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