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 skills add fernando-bertholdo/4-successful-AI-life --skill retentiongit clone --depth 1 https://github.com/fernando-bertholdo/4-successful-AI-lifeWrote 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.
[](https://agentmods.dev/skills/fernando-bertholdo/4-successful-ai-life/retention)<a href="https://agentmods.dev/skills/fernando-bertholdo/4-successful-ai-life/retention"><img src="https://agentmods.dev/badge/skills/fernando-bertholdo/4-successful-ai-life/retention/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.
<a href="https://agentmods.dev/skills/fernando-bertholdo/4-successful-ai-life/retention"><img src="https://agentmods.dev/badge/skills/fernando-bertholdo/4-successful-ai-life/retention.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00127 | $0.04313 |
| Opus 5.5 | $0.00051 | $0.01725 |
| Sonnet 5.5 | $0.00025 | $0.00863 |
| Haiku 4.5 | $0.00013 | $0.00431 |
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 1mo 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.
This is a copy
91% identical to improve-retention — 29 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 — 292 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Behavior Design Framework
Framework for designing products that reliably change behavior. Based on a fundamental truth: behavior is not about willpower or motivation—it is a design problem with a predictable equation.
Core Principle
The Fogg Behavior Model = B=MAP. Behavior happens when Motivation, Ability, and a Prompt converge at the same moment.
HIGH ┃
┃ ★ Behavior happens
┃ (above the Action Line)
┃
Motivation ┃━━━━━━━━━━━━━━━━━━━━━━━ ← Action Line
┃
┃ ✗ Behavior fails
┃ (below the Action Line)
LOW ┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━
HARD EASY
Ability
The Action Line: When motivation and ability are sufficient, a prompt causes the behavior. Below the line, no prompt works. The line curves: high motivation compensates for low ability, and high ability compensates for low motivation. The reliable strategy is to make behaviors easier (move right), not to pump up motivation (move up).
Scoring
Goal: 10/10. When reviewing or creating product behavior design, rate them 0-10 based on adherence to the principles below. A 10/10 means full alignment with all guidelines; lower scores indicate gaps to address. Always provide the current score and specific improvements needed to reach 10/10.
The Three Elements
1. Motivation
Core concept: Motivation is the energy for action. It has three core motivators, each with two sides: Sensation (pleasure/pain), Anticipation (hope/fear), and Belonging (acceptance/rejection). Motivation is powerful but unreliable — it fluctuates like waves.
Why it works: Motivation explains why people want to act, but it is the least reliable element in behavior design. It spikes (New Year's resolutions, product launches) and crashes (day 3, week 2). Products that depend on high motivation fail when the wave recedes. The best designs work even when motivation is at a trough.
What ships with it
7 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.
- 1mo ago First seen · 292 lines · 127 tokens per session scan A 1bd6d43911b0
retention is a skill published in the GitHub repository fernando-bertholdo/4-successful-AI-life (2 stars, last pushed 10d ago), licensed MIT. It adds 127 tokens to every session and 4,313 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 91% identical to improve-retention, differing in 29 lines, and is treated as a copy.
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