drin-customer-loyalty-engine

drin-customer-loyalty-engine is a skill for Claude Code from pedrol-cmd/brain-drin. It costs 23 tokens per session (171 once invoked), scanned A, original, MIT.

A workflow for designing and maintaining customer loyalty programmes that reward users based on their usage, spending, or relationship with a product.

In plain words
What is it for?
Use it to identify loyal customers, plan rewards such as credits or early access, organise exclusive engagement, and collect feedback.
Why use it?
It helps teams turn customer activity and feedback into a structured programme instead of handling rewards and engagement ad hoc.

Skill for Claude Code

Written for Claude Code: installed under .claude/. Also seen: mentions subagents.

Good fit Use it to identify loyal customers, plan rewards such as credits or early access, organise exclusive engagement, and collect feedback.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/pedrol-cmd/brain-drin/drin-customer-loyalty-engine
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 pedrol-cmd/brain-drin --skill drin-customer-loyalty-engine
Clone the repo
git clone --depth 1 https://github.com/pedrol-cmd/brain-drin

Made for: Claude Code.

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 drin-customer-loyalty-engine

README.md
[![agentmods](https://agentmods.dev/badge/skills/pedrol-cmd/brain-drin/drin-customer-loyalty-engine/github.svg)](https://agentmods.dev/skills/pedrol-cmd/brain-drin/drin-customer-loyalty-engine)
Your own site
<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.

agentmods 80×15 button for drin-customer-loyalty-engine

Your own site · 80×15
<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>
Per session 23 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 171 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 $0.00023 $0.00171
Opus 5 $0.00012 $0.00086
Sonnet 5 $0.00005 $0.00034
Haiku 4.5 $0.00002 $0.00017

Measured 6d ago against content hash 75d54fde1a4f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

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.

.claude/skills/drin-customer-loyalty-engine/SKILL.md · 25 lines

What it actually says

Customer Loyalty Engine

Purpose

To maximize LTV by rewarding and engaging the product's most valuable users.

Components

  1. Detection: Identifying high-value/loyal users (Usage/Spend/Tenure).
  2. Rewards: Credits, early access, community status, or physical swags.
  3. Engagement: Exclusive content, AMAs, or beta-tester groups.
  4. 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
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. 6d ago First seen · 25 lines · 23 tokens per session scan A 75d54fde1a4f

Subscribe to this mod's changes

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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