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 agentmods add skills/dokkabei97/forged-claude-code/referral-programnpx skills add Dokkabei97/forged-claude-code --skill referral-programgit clone --depth 1 https://github.com/Dokkabei97/forged-claude-codeWrote 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/dokkabei97/forged-claude-code/referral-program)<a href="https://agentmods.dev/skills/dokkabei97/forged-claude-code/referral-program"><img src="https://agentmods.dev/badge/skills/dokkabei97/forged-claude-code/referral-program.svg" alt="Measured on agentmods" 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 | $0.00035 | $0.00889 |
| Opus 5 | $0.00017 | $0.00445 |
| Sonnet 5 | $0.00007 | $0.00178 |
| Haiku 4.5 | $0.00003 | $0.00089 |
Grade A, and why
referral-program 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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Referral Program - Viral Growth Design
Overview
Designs referral programs that turn users into your best sales channel. Dropbox grew 3900% with referrals. The best growth is growth that pays for itself.
1. When to Apply
| Trigger | Behavior |
|---|---|
| Reducing CAC | Referral program design |
| "referral", "레퍼럴" | Full program setup guide |
| Users already sharing organically | Amplify existing behavior |
2. Referral Program Types
| Type | Mechanism | Best For | Example |
|---|---|---|---|
| Double-sided | Both referrer and referee get reward | SaaS, marketplace | Dropbox, Airbnb |
| One-sided (referrer) | Only referrer gets reward | Low-friction products | Cash referral bonus |
| One-sided (referee) | Only new user gets benefit | Trial/freemium | "Get 1 month free" |
| Tiered | Rewards increase with more referrals | Power users | Ambassador programs |
| Milestone | Reward at specific referral counts | Viral products | "Invite 5 → unlock feature" |
3. Program Design Template
# Referral Program: [Product Name]
## Incentive Structure
| Role | Reward | Trigger |
|------|--------|---------|
| Referrer | [e.g., 1 month free] | When referee [signs up / pays / activates] |
| Referee | [e.g., 20% off first month] | On signup via referral link |
## Sharing Mechanics
- **Unique referral link**: [user].product.com/ref/[code]
- **Share channels**: Copy link, Email, Twitter, WhatsApp
- **In-app placement**: Settings → "Invite Friends" + post-value moment
## Tracking
- Referral code in URL → cookie → attribution on signup
- Dashboard: referrals sent, signed up, converted, rewards earned
## Reward Fulfillment
- Automatic credit/discount application
- Email notification on successful referral
- Leaderboard for top referrers (optional)
## Anti-Fraud Rules
- Max [N] referrals per user per month
- Self-referral detection (same IP, email domain)
- Minimum activity threshold before reward unlock
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.
- 4d ago First seen · 132 lines · 35 tokens per session scan A 150ec609a947
referral-program is a skill published in the GitHub repository Dokkabei97/forged-claude-code (2 stars, last pushed 6mo ago), licensed MIT. It adds 35 tokens to every session and 889 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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