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 pedrol-cmd/brain-drin --skill drin-customer-loyalty-enginegit clone --depth 1 https://github.com/pedrol-cmd/brain-drinWrote 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/pedrol-cmd/brain-drin/drin-customer-loyalty-engine)<a href="https://agentmods.dev/skills/pedrol-cmd/brain-drin/drin-customer-loyalty-engine"><img src="https://agentmods.dev/badge/skills/pedrol-cmd/brain-drin/drin-customer-loyalty-engine/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/pedrol-cmd/brain-drin/drin-customer-loyalty-engine"><img src="https://agentmods.dev/badge/skills/pedrol-cmd/brain-drin/drin-customer-loyalty-engine.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 | $0.00023 | $0.00171 |
| Opus 5 | $0.00012 | $0.00086 |
| Sonnet 5 | $0.00005 | $0.00034 |
| Haiku 4.5 | $0.00002 | $0.00017 |
Grade A, and why
drin-customer-loyalty-engine 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 6d 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.
What it actually says
Customer Loyalty Engine
Purpose
To maximize LTV by rewarding and engaging the product's most valuable users.
Components
- Detection: Identifying high-value/loyal users (Usage/Spend/Tenure).
- Rewards: Credits, early access, community status, or physical swags.
- Engagement: Exclusive content, AMAs, or beta-tester groups.
- Feedback: Direct line to the product team.
Rules
- Loyalty must be earned through value, not just bought with discounts.
- Make the program exclusive and aspirational.
subagents:
- customer-success
- growth-hacker
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.
- 6d ago First seen · 25 lines · 23 tokens per session scan A 75d54fde1a4f
drin-customer-loyalty-engine is a skill published in the GitHub repository pedrol-cmd/brain-drin (11 stars, last pushed 5mo ago), licensed MIT. It adds 23 tokens to every session and 171 once invoked, about $0.0001 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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