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 uppifyagency/bettercallclaudegrowth --skill hormozi-offersgit clone --depth 1 https://github.com/uppifyagency/bettercallclaudegrowthWrote 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/uppifyagency/bettercallclaudegrowth/hormozi-offers)<a href="https://agentmods.dev/skills/uppifyagency/bettercallclaudegrowth/hormozi-offers"><img src="https://agentmods.dev/badge/skills/uppifyagency/bettercallclaudegrowth/hormozi-offers/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/uppifyagency/bettercallclaudegrowth/hormozi-offers"><img src="https://agentmods.dev/badge/skills/uppifyagency/bettercallclaudegrowth/hormozi-offers.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 | $0.00086 | $0.02563 |
| Opus 5 | $0.00043 | $0.01282 |
| Sonnet 5 | $0.00017 | $0.00513 |
| Haiku 4.5 | $0.00009 | $0.00256 |
Grade A, and why
hormozi-offers 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 12d 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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
$100M Offers — How to Make Offers So Good People Feel Stupid Saying No
Author: Alex Hormozi (Acquisition.com Vol. I) | Pages: ~200 | Chapters: 14 | Generated: 2026-06-06
How to Use This Skill
- Without arguments — load the Core Frameworks below for reference.
- With a topic — ask about
value equation,guarantees,pricing,scarcity, etc.; I find and read the relevant chapter. - With a chapter — ask for
ch05; I load that specific chapter file. - Browse — ask "what chapters do you have?" to see the full index.
When you ask about a topic not in the Core Frameworks below, I read the relevant chapter file (see Topic Index) before answering.
Core Frameworks & Mental Models
The thesis. A GRAND SLAM OFFER is an offer so good people feel stupid saying no — it combines pricing + value + guarantees + naming into something incomparable, so prospects stop shopping you against alternatives. You sell in a category of one. Same fulfillment work as a commodity offer, but it appears to be a totally different product → a value-driven (not price-driven) purchase. The opposite is the COMMODITY PROBLEM: a product available from many places, bought on price → race to the bottom. Differentiate or die.
MARKET FIRST — A STARVING CROWD. Order of importance: Market > Offer > Persuasion. A great offer in a bad market loses; pick the crowd first. The four indicators of a great market: ① massive Pain, ② Purchasing Power, ③ Easy to Target, ④ Growing. The three durable markets that never die: Health, Wealth, Relationships. "Riches in niches" — commit and go deeper, not broader.
PRICING — CHARGE WHAT IT'S WORTH. The Virtuous Cycle of Price: raising price creates a Price-to-Value Discrepancy, funds better delivery, and raises clients' emotional investment → better results → better testimonials → justifies higher price again. Premium pricing increases perceived value. Never compete on price; never discount (add bonuses instead).
What ships with it
17 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.
- chapters/ch01-grand-slam-offer.md 6.4 KB
- chapters/ch02-commodity-problem.md 7.2 KB
- chapters/ch03-starving-crowd.md 8.0 KB
- chapters/ch04-charge-what-its-worth.md 7.4 KB
- chapters/ch05-value-equation.md 7.5 KB
- chapters/ch06-thought-process.md 5.2 KB
- chapters/ch07-offer-problems-solutions.md 6.3 KB
- chapters/ch08-offer-trim-and-stack.md 7.5 KB
- chapters/ch09-enhance-scarcity.md 7.2 KB
- chapters/ch10-enhance-urgency.md 5.4 KB
- chapters/ch11-enhance-bonuses.md 8.5 KB
- chapters/ch12-enhance-guarantees.md 7.3 KB
- chapters/ch13-enhance-naming.md 7.8 KB
- chapters/ch14-your-first-100k.md 5.5 KB
- cheatsheet.md 4.2 KB
- glossary.md 7.6 KB
- patterns.md 12 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.
- 12d ago First seen · 128 lines · 86 tokens per session scan A f4af9205cdea
hormozi-offers is a skill published in the GitHub repository uppifyagency/bettercallclaudegrowth (5 stars, last pushed 3mo ago), licensed MIT. It adds 86 tokens to every session and 2,563 once invoked, about $0.0004 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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