referral-programs

referral-programs is a skill for Claude Code, Codex from cbrock84/headcount. It costs 65 tokens per session (628 once invoked), scanned A, original, MIT.

A guide to referral, affiliate, and word-of-mouth programs, including their rewards, sharing process, timing, and fraud controls.

In plain words
What is it for?
Use it to design or improve referral and affiliate programs, choose incentives, place referral requests, and assess whether referrals suit the product.
Why use it?
It helps determine whether customers are likely to recommend a product and prevents programs from rewarding low-quality or fraudulent signups.

Skill for Claude CodeCodex

Part of the revenue plugin — 10 skills shipped together

About the project

headcount is an organization of independently installable Claude Code plugins, each grouping skills for a department such as finance, security, or demand generation. Claude Code users install the departments they need and invoke their skills for specialized work; the catalogue entries are skills and related agent tooling from that organization.

cbrock84/headcount · 1,247 stars · on GitHub

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.

agentmods
npx agentmods add skills/cbrock84/headcount/referral-programs
Any agent
npx skills add cbrock84/headcount --skill referral-programs
Clone the repo
git clone --depth 1 https://github.com/cbrock84/headcount

Made for: Claude Code, Codex.

Or install revenue, the plugin that ships this one along with the rest of its 10 skills.

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 referral-programs

README.md
[![agentmods](https://agentmods.dev/badge/skills/cbrock84/headcount/referral-programs.svg)](https://agentmods.dev/skills/cbrock84/headcount/referral-programs)
Your own site
<a href="https://agentmods.dev/skills/cbrock84/headcount/referral-programs"><img src="https://agentmods.dev/badge/skills/cbrock84/headcount/referral-programs.svg" alt="Measured on agentmods" height="20"></a>
Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 628 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00065 $0.00628
Opus 5 $0.00032 $0.00314
Sonnet 5 $0.00013 $0.00126
Haiku 4.5 $0.00006 $0.00063

Measured yesterday against content hash 482da7f81b9e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

referral-programs 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 yesterday.

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.

plugins/revenue/skills/referral-programs/SKILL.md · 63 lines

How it starts

The opening of the file, as written. The whole thing — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Referral programs

Qualify the channel first

Referral programs amplify existing word of mouth. They do not create it.

If customers are not already recommending you unprompted, a program will not produce them — it will produce incentive-motivated signups that churn. Check first: is anyone referring today, and what do they say when they do?

Incentive design

  • Two-sided beats one-sided in most cases. It gives the referrer something to offer rather than something to gain, which removes the awkwardness that stops most referrals.
  • Match the reward to the product's value, not to a round number. Account credit usually outperforms cash, and costs less.
  • Reward the outcome you want. Paying on signup buys signups; paying on a retained, activated customer buys customers.
  • Cash rewards attract fraud, and fraud scales faster than the program does. Budget for detection before launch, not after.

Mechanics

The referral has to be effortless at the moment of enthusiasm, which means the ask must appear right after a success moment — not in a settings page nobody visits.

  • One-click share with pre-written text the referrer can edit.
  • A link that works everywhere and survives being pasted into any app.
  • Visible status: who was invited, what stage they reached, what has been earned. Ambiguity kills repeat referrals.
  • The referred person's experience must be better than a normal signup. Landing them on the generic homepage wastes the introduction.

Fraud control

Self-referral, disposable accounts, and coordinated rings. Minimum viable controls: reward only on a qualifying event well past signup, hold a payout window, deduplicate on payment method and device, and cap per-referrer volume pending review.

Affiliates are a different program

Affiliates are a paid channel with commercial terms, not enthusiastic customers. They need attribution rules, cookie windows, prohibited-methods terms — brand bidding and coupon-site behavior in particular — and monitoring. Run without terms and you will pay commission on customers you already had.

Read the full file on GitHub · 63 lines

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. yesterday First seen · 63 lines · 65 tokens per session scan A 482da7f81b9e

Subscribe to this mod's changes

referral-programs is a skill published in the GitHub repository cbrock84/headcount (1,247 stars, last pushed 2d ago), licensed MIT. It adds 65 tokens to every session and 628 once invoked, about $0.0003 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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