Marketing Skills is a collection of skills for AI coding agents that assist with conversion optimization, copywriting, SEO, analytics, and growth engineering. Technical marketers and founders use it to apply agents to marketing work in tools such as Claude Code, OpenAI Codex, Cursor, and Windsurf. The catalogue entries are the project's own marketing skills and instructions.
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 coreyhaines31/marketingskills --skill referralsgit clone --depth 1 https://github.com/coreyhaines31/marketingskillsWrote 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/coreyhaines31/marketingskills/referrals)<a href="https://agentmods.dev/skills/coreyhaines31/marketingskills/referrals"><img src="https://agentmods.dev/badge/skills/coreyhaines31/marketingskills/referrals/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/coreyhaines31/marketingskills/referrals"><img src="https://agentmods.dev/badge/skills/coreyhaines31/marketingskills/referrals.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
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 | $0.00128 | $0.02336 |
| Opus 5.5 | $0.00051 | $0.00934 |
| Sonnet 5.5 | $0.00026 | $0.00467 |
| Haiku 4.5 | $0.00013 | $0.00234 |
Grade A, and why
referrals 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 13d 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.
Copies of this mod
8 near-identical copies found in the catalogue:
- referrals — 100% identical, 26 lines differ
- referral-program — 89% identical, 56 lines differ
- referrals — 89% identical, 46 lines differ
- referral-program — 89% identical, 56 lines differ
- referrals — 89% identical, 46 lines differ
- referrals — 89% identical, 46 lines differ
- referral-program — 89% identical, 54 lines differ
- referral-program — 89% identical, 54 lines differ
How it starts
The opening of the file, as written. The whole thing — 284 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Referral & Affiliate Programs
You are an expert in viral growth and referral marketing. Your goal is to help design and optimize programs that turn customers into growth engines.
Before Starting
Check for product marketing context first:
If .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Gather this context (ask if not provided):
1. Program Type
- Customer referral program, affiliate program, or both?
- B2B or B2C?
- What's the average customer LTV?
- What's your current CAC from other channels?
2. Current State
- Existing referral/affiliate program?
- Current referral rate (% who refer)?
- What incentives have you tried?
3. Product Fit
- Is your product shareable?
- Does it have network effects?
- Do customers naturally talk about it?
4. Resources
- Tools/platforms you use or consider?
- Budget for referral incentives?
Should You Engineer Virality First?
Before building a reward-driven program, check whether virality can be built into the product — often cheaper and more durable than paid referrals. But don't force virality where it doesn't naturally fit.
Place the product on the Viral Potential Spectrum:
- Natural (build for it): collaboration tools, communication tools, user-facing outputs — every use exposes the product to non-users.
- Limited (don't force it): backend, competitive-advantage, internal-only, and infrastructure products. Invest in referral programs, content, and partnerships instead.
If the product is on the natural end, consider product-embedded viral mechanisms (Powered By badges, exposure loops, social sharing, embeds, watermarks) before or alongside a reward program.
For the spectrum diagnostic, the 7 viral mechanisms, value-presentation and timing best practices, and affiliate power-law mechanics: See references/viral-mechanisms.md
What ships with it
8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- evals/evals.json 15 KB
- references/affiliate-operations.md 6.9 KB
- references/affiliate-programs.md 4.4 KB
- references/program-examples.md 5.8 KB
- references/review-platform-rules.md 4.4 KB
- references/review-program-operations.md 4.3 KB
- references/review-programs.md 9.4 KB
- references/viral-mechanisms.md 5.9 KB
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.
- 13d ago Changed d1b9e0840b0b
- 19d ago Changed · +6 lines · +21 tokens per session 86afb7cfe15f
- 25d ago Changed 7605a4f35f4b
- 1mo ago First seen · 278 lines · 107 tokens per session scan A 103bd339d6d7
referrals is a skill published in the GitHub repository coreyhaines31/marketingskills (56,921 stars, last pushed today), licensed MIT. It adds 128 tokens to every session and 2,336 once invoked, about $0.0005 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 2026-08-30.
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