retention-design

retention-design is a skill for Claude Code from RBraga01/builder-growth. It costs 45 tokens per session (1,792 once invoked), scanned A, original, MIT.

A product-planning method for encouraging users to return after their first use. It defines the first valuable action, the repeated habit, and the way to bring users back after they leave.

In plain words
What is it for?
Use it when planning a product, a major feature, or an AI tool that depends on repeated sessions. It also helps when improving a flow with poor return rates.
Why use it?
It prevents teams from launching features that users try once and then forget. It makes repeat use part of the design before development is finished.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the builder-growth plugin — 14 skills, 5 agents shipped together

Good fit Use it when planning a product, a major feature, or an AI tool that depends on repeated sessions. It also helps when improving a flow with poor return rates.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/rbraga01/builder-growth/retention-design
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 RBraga01/builder-growth --skill retention-design
Clone the repo
git clone --depth 1 https://github.com/RBraga01/builder-growth

Made for: Claude Code.

Or install builder-growth, the plugin that ships this one along with the rest of its 14 skills, 5 agents.

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-design

README.md
[![agentmods](https://agentmods.dev/badge/skills/rbraga01/builder-growth/retention-design/github.svg)](https://agentmods.dev/skills/rbraga01/builder-growth/retention-design)
Your own site
<a href="https://agentmods.dev/skills/rbraga01/builder-growth/retention-design"><img src="https://agentmods.dev/badge/skills/rbraga01/builder-growth/retention-design/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 retention-design

Your own site · 80×15
<a href="https://agentmods.dev/skills/rbraga01/builder-growth/retention-design"><img src="https://agentmods.dev/badge/skills/rbraga01/builder-growth/retention-design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,792 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 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 $0.00045 $0.01792
Opus 5 $0.00023 $0.00896
Sonnet 5 $0.00009 $0.00358
Haiku 4.5 $0.00005 $0.00179

Measured 10d ago against content hash 0df73c7885fb, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

retention-design 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 10d ago.

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.

skills/retention-design/SKILL.md · 168 lines

How it starts

The opening of the file, as written. The whole thing — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Retention Design

The Law

A FEATURE LAUNCHED WITHOUT A DESIGNED RETENTION LOOP IS A FEATURE DESIGNED TO CHURN.
"Users will come back if they like it" has no activation moment, no habit trigger, and no reactivation path — which describes every churned product, because users who liked it also forgot about it.
Activation moment + habit loop + reactivation path defined before launch IS retention design.

When to Use

Trigger before:

  • Launching any new product or significant new feature
  • Redesigning an existing flow where D7 or D30 retention is below target
  • Adding a feature whose primary value is realised over repeated sessions (not first use)
  • Building any AI assistant, tool, or agent that requires habit formation

When NOT to Use

  • One-time-use features where the user's goal is fully completed in a single session (e.g., a one-time document export — retention is not the right metric)
  • Features for internal tools where users are required to return (no voluntary retention decision being made)

The Three Retention Elements

1 — Activation Moment

The specific action a user takes that predicts they will return.

Activation is not the first session. It is the moment in the first session when the user understands what the product can do for them — the "aha moment."

How to find it:

  • Compare the behaviour of retained users (D30+) vs. churned users
  • Find the action that is significantly overrepresented in retained users in the first session
  • Verify causality vs. correlation: does encouraging new users to reach this action earlier improve D30?

What it looks like:

Slack: send your first message
Dropbox: put a file in a folder and access it from another device
GitHub Copilot: accept the first autocomplete suggestion

Required in the design:

  • Name the activation action
  • Measure how many new users reach it in the first session (baseline)
  • Design the first-session flow to lead users to this action

2 — Habit Loop

The cue → routine → reward cycle that brings users back.

Read the full file on GitHub · 168 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. 10d ago First seen · 168 lines · 45 tokens per session scan A 0df73c7885fb

Subscribe to this mod's changes

retention-design is a skill published in the GitHub repository RBraga01/builder-growth (2 stars, last pushed 2mo ago), licensed MIT. It adds 45 tokens to every session and 1,792 once invoked, about $0.0002 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 2026-08-31.

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