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Offer Builder

Community
duncan-buildroom
offer-builder

Build a Hormozi-style "Grand Slam Offer" so good people feel stupid saying no — engineered around the Value Equation (bigger dream outcome, higher belief it'll work, less time, less effort). Use this when the user says "build my offer", "make my offer irresistible", "help me package what I sell", "I don't know how to price/pitch this", "grand slam offer", "I built a product but nobody's buying", or when they have a thing to sell but no compelling way to present it. Push to run this before they try to sell anything.

Overview

Publisherduncan-buildroom
Repositoryfreeskills
Skill nameoffer-builder
Stars
65
Forks
15
Bundled files
Instructions only
Links
  • 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 duncan-buildroom on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/duncan-buildroom/freeskills/tree/main/offer-builder
  4. 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.
2

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/duncan-buildroom/freeskills.git /tmp/freeskills
mkdir -p .claude/skills
cp -r /tmp/freeskills/offer-builder .claude/skills/offer-builder
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Offer Builder 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 Offer Builder 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 Offer Builder 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.

Offer Builder — engineer a Grand Slam Offer

Turn "here's my product" into an offer that's so stacked and de-risked the prospect feels dumb passing it up. You walk the user through the Value Equation, stack deliverables that each kill a specific obstacle, then name it and bolt on a guarantee, urgency, and bonuses. Output is a written, ready-to-pitch offer plus a one-line grand-slam statement they can say out loud.

Personalization

This skill works in your brand voice. Before running, load the brand profile at ~/.claude/brand-profile.md.

  • If it doesn't exist, run the personalize skill first (or just tell me your name, niche, offer, and audience — I'll create it).
  • If a field this skill needs is blank, I'll ask one or two quick questions and save the answers back to the profile so you only answer once.
  • Never invent facts or results about the user — use only what's in the profile, or ask.

The idea in one breath

People buy when the perceived value is high. Value goes UP when the dream outcome is bigger and the likelihood they'll actually achieve it feels higher. Value goes DOWN the more time it takes and the more effort and sacrifice it costs. So a great offer maximizes the top two and crushes the bottom two. Everything below is just doing that on purpose.

Steps

1. Anchor the dream outcome

Ask the user (or pull from the profile's Audience + Transformation): what does your buyer most want on the other side of this? Get it concrete and emotional — not "learn marketing" but "land your first paying client in 30 days without cold-calling." Write it down as the headline promise. This is the top of the Value Equation.

2. List the obstacles (this is the goldmine)

Ask: what stops your buyer from getting that result on their own? Get 4–8 real obstacles — the fears, the missing skills, the time it eats, the past failures, the "I don't know where to start." Each obstacle is a bump the offer will smooth out. Write them as a list.

3. Stack deliverables — one per obstacle

For every obstacle, invent a deliverable that removes it. This is the core move: the offer isn't one thing, it's a stack where each item visibly kills an objection.

  • Obstacle "I don't know where to start" -> a step-by-step roadmap or checklist.
  • Obstacle "no time" -> done-for-you templates / a done-with-you sprint.
  • Obstacle "what if it doesn't work for me" -> a live review or 1:1 call.
  • Obstacle "I've failed before" -> a proven framework + examples. Write each deliverable next to the obstacle it solves, and give each a tangible name and a rough standalone value.

4. Attack the bottom of the equation

Now cut time and effort explicitly:

  • Time delay: what's the fastest first win, and can you name a timeframe? ("first result in 7 days"). Front-load a quick win.
  • Effort & sacrifice: what can you make done-for-you, templated, or automated so they do less? Every "we do it for you" raises value.

5. Name the offer

Give the whole stack a name that implies the outcome (not the mechanism). "The 30-Day First-Client System" beats "My Coaching Package." Keep it short and outcome-loaded, in the user's tone.

6. De-risk it with a guarantee

Write a guarantee that reverses the risk onto you. Pick the strongest one the user is comfortable with: unconditional refund, conditional ("do the work, don't get X, full refund"), or a performance guarantee ("we keep working free until you get your first sale"). A specific guarantee beats a vague one.

7. Add real scarcity or urgency

Give a reason to act now that is TRUE — never fake a countdown. Legit forms: limited spots (you can only serve N people well), a cohort start date, a price that rises after launch, a bonus that expires. Write the exact line.

8. Sweeten with bonuses

Add 1–3 bonuses that handle the next objection after they say yes ("okay but how do I keep clients?"). Each bonus should feel like it could be sold on its own. Name each and give a value.

9. Write the finished offer + the grand-slam line

Assemble everything into a clean, pitch-ready offer, then distill it into ONE sentence they can say on a call or put on a page:

"You get [dream outcome] in [timeframe], with [core stack], backed by [guarantee] — for [price]. Only [scarcity]."

Output — save it

Write the finished offer to ~/offers/<offer-name>.md (create the ~/offers/ folder if needed; slugify the name, e.g. ~/offers/30-day-first-client-system.md). Confirm the path back to the user. The file must contain: the dream-outcome headline, the obstacle→deliverable stack table, the name, guarantee, scarcity, bonuses, total "value" vs price, and the one-line grand-slam statement.

Example (input → output)

Input: User sells a $500 "Notion setup" service to freelancers. Dream outcome: "stop losing track of clients and projects." Obstacles: don't know how to structure it, no time to build it, tried before and abandoned it, scared it won't fit their workflow.

Output (excerpt saved to ~/offers/freelancer-command-center.md):

  • Name: The Freelancer Command Center
  • Promise: Every client, project, and deadline in one dashboard within 5 days — without building anything yourself.
  • Stack: Done-for-you Notion build (kills "no time") + a 20-min personalization call (kills "won't fit me") + a 1-page daily operating checklist (kills "I'll abandon it") + a Loom walkthrough (kills "don't know how to run it").
  • Guarantee: If it's not saving you time in 14 days, I rebuild it or refund you.
  • Scarcity: 4 builds a month so each gets personalized.
  • Bonus: Client-onboarding template pack.
  • Grand-slam line: "Get your whole freelance business running from one dashboard in 5 days, done for you, guaranteed — 4 spots this month."

Notes / edge cases

  • If the user has no proof yet, lean the guarantee and quick-win harder — those substitute for a track record.
  • Keep pricing out of the deep end here; if they want help setting the number, hand off to the pricing-calculator skill.
  • Don't overstack — 3–5 deliverables that each kill a real obstacle beats 12 filler items.

Frequently asked questions

What does the Offer Builder AI skill do?

Build a Hormozi-style "Grand Slam Offer" so good people feel stupid saying no — engineered around the Value Equation (bigger dream outcome, higher belief it'll work, less time, less effort). Use this when the user says "build my offer", "make my offer irresistible", "help me package what I sell", "I don't know how to price/pitch this", "grand slam offer", "I built a product but nobody's buying", or when they have a thing to sell but no compelling way to present it. Push to run this before they try to sell anything.

Why use Offer Builder on TypingMind?

Because you install it once and use it with any model. Offer Builder 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 Offer Builder in TypingMind?

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

Which AI models can use Offer Builder?

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 Offer Builder?

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

Is the Offer Builder AI skill free?

It is published on GitHub by duncan-buildroom. Check the repository for licensing terms. 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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