retention

retention is a skill for Claude Code, Codex from cbrock84/headcount. It costs 77 tokens per session (565 once invoked), scanned A, original, MIT.

A customer-retention guide for finding why subscribers leave and designing ways to keep or win them back.

In plain words
What is it for?
Use it to improve cancellation flows, recover failed payments, identify at-risk accounts, and investigate product or service problems behind churn.
Why use it?
It separates failed-payment churn from customers choosing to leave, so teams can address the actual cause instead of treating every cancellation alike.

Skill for Claude CodeCodex

Part of the revenue plugin — 10 skills shipped together

About the project

headcount is an organization of independently installable Claude Code plugins, each grouping skills for a department such as finance, security, or demand generation. Claude Code users install the departments they need and invoke their skills for specialized work; the catalogue entries are skills and related agent tooling from that organization.

cbrock84/headcount · 1,247 stars · on GitHub · cbrock84.github.io

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.

agentmods
npx agentmods add skills/cbrock84/headcount/retention
Any agent
npx skills add cbrock84/headcount --skill retention
Clone the repo
git clone --depth 1 https://github.com/cbrock84/headcount

Made for: Claude Code, Codex.

Or install revenue, the plugin that ships this one along with the rest of its 10 skills.

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 retention

README.md
[![agentmods](https://agentmods.dev/badge/skills/cbrock84/headcount/retention.svg)](https://agentmods.dev/skills/cbrock84/headcount/retention)
Your own site
<a href="https://agentmods.dev/skills/cbrock84/headcount/retention"><img src="https://agentmods.dev/badge/skills/cbrock84/headcount/retention.svg" alt="Measured on agentmods" height="20"></a>
Per session 77 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 565 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found 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 $0.00077 $0.00565
Opus 5 $0.00039 $0.00282
Sonnet 5 $0.00015 $0.00113
Haiku 4.5 $0.00008 $0.00056

Measured yesterday against content hash eda4f20f763d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

retention 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.

plugins/revenue/skills/retention/SKILL.md · 58 lines

How it starts

The opening of the file, as written. The whole thing — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Retention

Separate the two churns first

They have nothing in common but the outcome, and conflating them wastes effort:

  • Involuntary — payment failed. Often a large share of total churn, entirely mechanical, and the cheapest thing to fix in the whole business.
  • Voluntary — they chose to leave.

Fix involuntary first. Card retries on a sensible schedule, dunning emails that reach a human, pre-expiry notification, and a grace period that does not immediately cut off access. This is recoverable revenue sitting untouched in most companies.

Diagnosing voluntary churn

Ask when the decision was actually made. It is almost never at cancellation — it is weeks earlier, at a failed expectation, an unresolved support issue, or a champion leaving.

Segment churn by tenure, plan, acquisition channel, and activation status. Concentrations tell you the cause:

  • Early churn — activation problem, not retention. Fix onboarding.
  • Churn at renewal — value not visible enough to justify the line item.
  • Churn after a specific event — find the event: a price change, an outage, a redesign, a champion departure.
  • Churn concentrated in one channel — an acquisition problem. You are buying the wrong customers, and no retention work fixes that.

Cancellation flow

Make canceling straightforward. Obstruction generates chargebacks, public complaints, and in a growing number of jurisdictions, regulatory exposure.

Do ask why, with specific options plus free text — this is the highest-quality product feedback you will ever receive, from people with no reason to be polite.

Offer a save only where it addresses the stated reason. A discount offered to someone leaving because a feature is missing confirms you were not listening. Pause is often the better offer and is rarely available.

At-risk detection

Build a simple signal from declining usage, a support escalation, a champion going quiet, or a seat count dropping. Then act on it while intervention is still possible — a health score nobody works is a dashboard, not a program.

Read the full file on GitHub · 58 lines

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. yesterday First seen · 58 lines · 77 tokens per session scan A eda4f20f763d

Subscribe to this mod's changes

retention is a skill published in the GitHub repository cbrock84/headcount (1,247 stars, last pushed 2d ago), licensed MIT. It adds 77 tokens to every session and 565 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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