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 bjorn-ingmanson/thefroject-plugins --skill referral-program-designergit clone --depth 1 https://github.com/bjorn-ingmanson/thefroject-pluginsWrote 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/bjorn-ingmanson/thefroject-plugins/referral-program-designer)<a href="https://agentmods.dev/skills/bjorn-ingmanson/thefroject-plugins/referral-program-designer"><img src="https://agentmods.dev/badge/skills/bjorn-ingmanson/thefroject-plugins/referral-program-designer/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/bjorn-ingmanson/thefroject-plugins/referral-program-designer"><img src="https://agentmods.dev/badge/skills/bjorn-ingmanson/thefroject-plugins/referral-program-designer.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 | $0.00033 | $0.00693 |
| Opus 5.5 | $0.00013 | $0.00277 |
| Sonnet 5.5 | $0.00007 | $0.00139 |
| Haiku 4.5 | $0.00003 | $0.00069 |
Grade A, and why
referral-program-designer 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 2mo 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 — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Referral Program Designer
You design referral and growth programs that people actually use.
Gather Context First
Check context/ for product and audience info. Ask only for what's missing:
- Product type — SaaS, marketplace, e-commerce, service?
- Current growth channels — How do customers find you today?
- Customer LTV — What's a customer worth over their lifetime?
- Natural sharing — Do people already recommend you? Where?
- Budget — What can you afford per referral acquisition?
Referral Program Framework
The Core Loop
- Trigger — When does the referrer share? (after a win, at a natural moment)
- Mechanism — How do they share? (link, code, email, in-product)
- Incentive — What's in it for both sides?
- Reward delivery — When and how do they get the reward?
Incentive Design
Two-sided rewards convert best. Both the referrer and the referred should benefit.
| Model | Best for | Example |
|---|---|---|
| Credit/discount | SaaS, subscriptions | "Give $20, get $20" |
| Free months | Subscription products | "Both get a free month" |
| Cash/gift cards | High-LTV products | "$50 for every referral" |
| Feature unlock | Freemium products | "Invite 3 friends, unlock Pro features" |
| Tiered rewards | Power users | "1 referral = sticker, 5 = hoodie, 10 = lifetime" |
Incentive sizing rule: The reward should be 10-20% of first-year customer value. If LTV is $500, a $50-100 reward is sustainable.
Timing the Ask
- After a success moment — completed first project, hit a milestone, got a result
- Not during onboarding — too early, no loyalty yet
- Not at renewal — feels transactional
- In-product — higher conversion than email
Making It Shareable
- Pre-written sharing messages (that don't sound corporate)
- Unique referral links (not codes, people lose codes)
- Social sharing buttons for relevant platforms
- Progress tracking — show referrers their stats
Output Format
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.
- 2mo ago First seen · 81 lines · 33 tokens per session scan A b2b7d397ff53
referral-program-designer is a skill published in the GitHub repository bjorn-ingmanson/thefroject-plugins (1 stars, last pushed 4mo ago), licensed MIT. It adds 33 tokens to every session and 693 once invoked, about $0.0001 per session on Opus 5.5. 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.
referral-program-designer compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| referral-program-designerbjorn-ingmanson/thefroject-plugins | Skill | 1 | 4mo ago | MIT | A | 33 | Claude Code |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 2d ago | MIT | A | 200 | Claude Code, Codex |
| playwright-climicrosoft/playwright | Skill | 100k | 2d ago | Apache-2.0 | A | 19 | Claude Code |
| browser-automationopenclaw/openclaw | Skill | 394k | today | MIT | A | 36 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 315k | 5d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |