100m-offers

100m-offers is a skill for Claude Code, Codex from getagentseal/founder-playbook. It costs 81 tokens per session (2,467 once invoked), scanned A, original, MIT.

A framework for designing sales offers by matching customer obstacles with solutions, setting prices, and packaging the result. It is based on Alex Hormozi's offer-design ideas.

In plain words
What is it for?
Use it to package products or services, improve conversion, design pricing and value bundles, and address obstacles for a clearly defined target audience.
Why use it?
It gives a structured way to examine why interested prospects do not buy. It helps identify whether the offer, rather than traffic or sales activity, is the main problem.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

not rated 570repo +25 1mo ago A scan Socket: passSnyk: passSkillSpector: pass 81 tokens original MIT

Good fit Use it to package products or services, improve conversion, design pricing and value bundles, and address obstacles for a clearly defined target audience.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/getagentseal/founder-playbook/100m-offers
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.

Any agent
npx skills add getagentseal/founder-playbook --skill 100m-offers
Clone the repo
git clone --depth 1 https://github.com/getagentseal/founder-playbook

Made for: Claude Code, Codex.

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 100m-offers

README.md
[![agentmods](https://agentmods.dev/badge/skills/getagentseal/founder-playbook/100m-offers/github.svg)](https://agentmods.dev/skills/getagentseal/founder-playbook/100m-offers)
Your own site
<a href="https://agentmods.dev/skills/getagentseal/founder-playbook/100m-offers"><img src="https://agentmods.dev/badge/skills/getagentseal/founder-playbook/100m-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.

agentmods 80×15 button for 100m-offers

Your own site · 80×15
<a href="https://agentmods.dev/skills/getagentseal/founder-playbook/100m-offers"><img src="https://agentmods.dev/badge/skills/getagentseal/founder-playbook/100m-offers.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 81 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,467 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 26 Apr 2026
  • Snyk pass 26 Apr 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 5.1 $0.00081 $0.02467
Opus 5 $0.00041 $0.01234
Sonnet 5 $0.00016 $0.00493
Haiku 4.5 $0.00008 $0.00247

Measured 12d ago against content hash 599a95f494b8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

100m-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.

100m-offers/SKILL.md · 257 lines

How it starts

The opening of the file, as written. The whole thing — 257 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Note: This skill is independent analysis and commentary, not a reproduction of the original text. It synthesizes the book's core ideas with modern startup practice, surfaces where frameworks are outdated or incomplete, and integrates perspectives from adjacent disciplines. For the full argument and context, read the original book.

$100M Offers

"Make offers so good people feel stupid saying NO" - Alex Hormozi

The Core Insight

"You don't have a sales problem or a marketing problem. You have an offer problem."

If qualified leads aren't buying, it's not your traffic - it's what you're offering them.

Decision Tree

Are you getting qualified leads?
├─ NO → Use 100m-leads
└─ YES → Are leads converting?
         ├─ NO → You have an offer problem (this skill)
         └─ YES → Are you charging premium?
                  ├─ NO → Stack value, raise prices
                  └─ YES → Scale ad spend
Building an offer?
├─ Pre-validation → Use mom-test FIRST
├─ Validated market → Use this skill
├─ Pricing question only → See monetizing-innovation
└─ Positioning unclear → See obviously-awesome

Step 0: Pick a Starving Crowd

Before any offer work: a great offer in a dead market fails. A mediocre offer in a ravenous market can still win.

The core principle: You want a market that is already hungry - people actively searching for a solution and willing to pay for it. Market selection is the multiplier on everything that follows.

3 criteria to test any market:

Criterion Question to ask Red flag
Pain Do they have an urgent, specific problem? Vague dissatisfaction, not a burning need
Purchasing power Can they actually pay for a solution? Market with desire but no budget
Targetability Can you reach them efficiently? Audience that is scattered or hard to identify

All three must be true. Two out of three is not enough.

How to pick:

  1. List markets where you have access or credibility.
  2. Run each through the 3-criteria test above.
  3. Pick the one with the highest pain score and a clear place to find them.

Read the full file on GitHub · 257 lines

Files

What ships with it

4 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.

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. 12d ago First seen · 257 lines · 81 tokens per session scan A 599a95f494b8

Subscribe to this mod's changes

100m-offers is a skill published in the GitHub repository getagentseal/founder-playbook (570 stars, last pushed 1mo ago), licensed MIT. It adds 81 tokens to every session and 2,467 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 2026-08-30.

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