Founder Offer

CommunityPopular

Jakeschincariol

founder-offer

Builds an offer too good to refuse. Lists every problem the buyer hits on the way to the result they want, turns each into a solution, trims to what is cheap to deliver and valuable to the buyer, and stacks it with honest bonuses, a guarantee the CFO can afford, real urgency and a clear name. Scores it on the value equation (outcome, likelihood, time, effort) and re-tests it on a quick buyer panel. Use when the user says "make my offer better", "why won't people buy", "what should I include", "guarantee", "bonuses", "grand slam offer", or after the panel shows people passing.

Overview

Publisher	Jakeschincariol
Repository	`founder-skill`
Skill name	`founder-offer`
Stars	1.5K
Forks	194
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by Jakeschincariol on GitHub. Read the source before you install it.

Installation

Install the Founder Offer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/Jakeschincariol/founder-skill/tree/main/skills/founder-offer
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/Jakeschincariol/founder-skill.git /tmp/founder-skill
mkdir -p .claude/skills
cp -r /tmp/founder-skill/skills/founder-offer .claude/skills/founder-offer

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Founder Offer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Founder Offer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Founder Offer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

founder-offer

Most businesses sell a product. Good ones sell an offer: the product plus everything that makes buying it an easy yes. This skill builds that, using the Offers lens in ../founder-board/lenses.md as the method (a summary of the framework in Alex Hormozi's $100M Offers; never present it as his words).

Step 1: read what is already known

founder/idea.md and founder/pitch.md: what is sold today.
founder/panel/results.md: why buyers pass, in their words. This is the raw material: every top objection should be answered by something in the offer.
founder/numbers.json: what each extra costs, so the stack stays profitable.
founder/board.md: the board's conditions.

Step 2: the problem list

Write every obstacle between the buyer and the result they want, in the buyer's words: before buying (doubt, price, effort to switch), during (waiting, learning, inconvenience), after (does it last, what if it fails). Aim for 15 to 30. Pull from the panel objections and the competitor complaints first.

Step 3: solutions, trimmed and stacked

Turn each problem into a solution (a feature, a service, a guarantee, a format). Score each on value to the buyer (1 to 5) and cost to deliver (1 to 5, from the CFO's numbers). Keep high value, low cost. Stack what is left into:

The core: the thing itself, described by the outcome, not the ingredients.
Bonuses: two or three, each killing one specific objection.
The guarantee: what happens if it does not deliver. Model what it costs at a realistic claim rate with the CFO's tool before promising it.
Urgency and scarcity: only if they are true (a launch week, a limited first batch). Never fake a countdown or a "only 3 left".
The name: a clear, specific name for the offer, not the company.

Step 4: score it

On the value equation, before and after, 1 to 10 each: dream outcome, perceived likelihood of getting it, time to the result, effort and sacrifice. Say which element of the stack moves which score.

Step 5: re-test it

Write the new offer into founder/pitch.md (keep the old one as founder/pitch-v1.md) and run /founder-consumer --quick with the same seed. Report the buy rate before and after and which objections dropped. If nothing moved, say so: the problem may be the market or the price, not the offer.

Rules

Every promise must be deliverable and affordable; check costs with the CFO.
No fake reviews, testimonials, scarcity, discounts or "as seen on".
Follow the advertising and consumer-protection rules of the user's market for guarantees and claims (health claims especially). Not legal advice.

Output

founder/offer.md (problem list, the stack, costs, the value-equation scores, the re-test result) and the updated founder/pitch.md. Next: /founder-cfo to re-run the numbers with the stack, then /founder-marketing.

Frequently asked questions

What does the Founder Offer AI skill do?

Why use Founder Offer on TypingMind?

Because you install it once and use it with any model. Founder Offer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Founder Offer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Jakeschincariol/founder-skill/tree/main/skills/founder-offer. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Founder Offer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Founder Offer?

As many as you like. As long as a model supports skills, you can use Founder Offer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Founder Offer AI skill free?

Yes. It is published on GitHub by Jakeschincariol under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

founder-offer

Step 1: read what is already known

Step 2: the problem list

Step 3: solutions, trimmed and stacked

Step 4: score it

Step 5: re-test it

Rules

Output

Frequently asked questions

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