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Prd V09 Offer Construction Hormozi

Community
mattgierhart
prd-v09-offer-construction-hormozi

Construct a high-conversion offer using Alex Hormozi's value equation and Grand Slam Offer mechanics during PRD v0.9 Go-to-Market. Triggers on requests to design the offer, set up the pitch, build bonuses or guarantees, or when user asks "how do we package this?", "what's the offer?", "build a grand slam offer", "Hormozi", "$100M offers", "guarantee", "bonus stack". Outputs GTM-* entries with Type=Offer / Type=Guarantee and BR-PRICING-* updates.

Overview

Publishermattgierhart
RepositoryPRD-driven-context-engineering
Skill nameprd-v09-offer-construction-hormozi
Stars
179
Forks
11
Bundled files
Instructions only
LicenseMIT
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 mattgierhart on GitHub. Read the source before you install it.

Installation

Install the Prd V09 Offer Construction Hormozi 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.
  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/mattgierhart/PRD-driven-context-engineering.git /tmp/PRD-driven-context-engineering
mkdir -p .claude/skills
cp -r /tmp/PRD-driven-context-engineering/plugins/prd-ce/skills/prd-v09-offer-construction-hormozi .claude/skills/prd-v09-offer-construction-hormozi
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Prd V09 Offer Construction Hormozi 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 Prd V09 Offer Construction Hormozi 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 Prd V09 Offer Construction Hormozi 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 Construction (Hormozi $100M Offers)

Position in workflow: v0.9 Positioning (Dunford) → v0.9 Offer Construction (Hormozi) → v0.9 Launch Channels (ORB)

Execution Mode

Default is standard. See .claude/rules/08-skill-execution-modes.md for selection logic.

ModeWhat this skill produces
quickOne offer; 1–2 named bonuses; one simple guarantee; price anchor
standardFull value equation calibrated; 3–5 bonuses with anchored values; one named guarantee; scarcity / urgency rule
deepMulti-tier offers (entry / mid / premium); guarantee experimentation plan; price anchor A/B; bonus value validation plan

Framework: Value Equation and Grand Slam Offer

From $100M Offers: How To Make Offers So Good People Feel Stupid Saying No (Alex Hormozi, 2021). An offer is the complete commercial proposition — what they get, what it costs, what's guaranteed, what's bundled, what's urgent — not just the product or the price.

The Value Equation

Perceived Value = (Dream Outcome × Perceived Likelihood of Achievement) / (Time Delay × Effort & Sacrifice)

Four levers — increase the numerator, decrease the denominator:

  1. Dream Outcome — What does the customer actually want? Express in their words. (Higher = better.)
  2. Perceived Likelihood of Achievement — How sure are they it will work? (Higher = better. Anchored by guarantees, social proof, case studies.)
  3. Time Delay — How long until they get the outcome? (Lower = better.)
  4. Effort & Sacrifice — How much work do they have to do? (Lower = better.)

If perceived value < price, the offer fails regardless of product quality.

Grand Slam Offer Components

A complete offer stacks five things:

  1. Core promise — the headline outcome (anchored in the value equation)
  2. Bonus stack — additional named items, each with anchored monetary value, that increase perceived value without proportionally increasing cost-to-deliver
  3. Guarantee — one of: unconditional refund, conditional ("if X doesn't happen, we Y"), anti-guarantee ("we don't refund — here's why we're so confident"), implied (case studies, results), or service-level
  4. Scarcity — limited supply (real: capacity, beta seats, custom service slots)
  5. Urgency — limited time (real: cohort start, price increase, bonus expiration)

Scarcity and urgency must be real. Manufactured scarcity erodes trust and is incompatible with Dunford's positioning (prd-v09-positioning-dunford).

Consumes

  • GTM-* positioning statement (from v0.9 Positioning) — Dream Outcome and Likelihood of Achievement language comes from the positioning's value claims; the offer cannot promise more than the positioning supports
  • BR-* pricing model (from v0.3 Pricing Model) — Existing price tiers; offer can stack on top but should not silently change the model
  • FEA-* features (from v0.3 Feature Value Planning) — Bonuses must be real product features or real services, not vapor
  • CFD-* value evidence (from v0.1–v0.4) — "Dream Outcome" wording comes from customer interviews; "Likelihood of Achievement" anchors come from case studies and usage data
  • PER-* best-fit segment (sharpened by Positioning) — Determines what "Dream Outcome" actually means to this buyer

This skill assumes Positioning is complete (positioning statement at confidence ≥ 3/5) and v0.3 Pricing Model is set.

Produces

  • GTM-* with Type=Offer — The full offer card: core promise, bonus stack with anchored values, guarantee reference, scarcity/urgency rule, price anchor
  • GTM-* with Type=Guarantee (separate ID) — The guarantee in standalone form so messaging can reference it directly
  • BR-PRICING-* updates — If the offer changes the pricing model (e.g., adds a one-time payment option, changes refund policy), update the BR- entries
  • CFD-* gaps surfaced — If the offer's Likelihood-of-Achievement claims can't be substantiated, log a CFD- research gap

Execution

Step 1: Calibrate the Value Equation

Write down each lever in the customer's words. Score each on a 1–5 scale:

LeverCurrentTargetGap
Dream Outcome
Likelihood of Achievement
Time Delay
Effort & Sacrifice

The largest gap = the lever to attack first.

Step 2: Design the core promise

State the headline outcome in one sentence: "You will [Dream Outcome] in [Time Delay] without [Effort & Sacrifice]." Test the sentence against the positioning statement — if they conflict, fix the offer, not the positioning.

Step 3: Build the bonus stack [standard+]

Aim for 3–5 bonuses. For each:

  • Name it concretely (not "additional support" — "1:1 setup call with founder, 30 min")
  • Assign an anchored value (what would this cost separately?)
  • Confirm it's deliverable at near-zero marginal cost (or factor cost into pricing)

Total stacked value should be ≥ 3× the price. If it isn't, the offer's perceived value is too low.

Step 4: Choose a guarantee

Pick the strongest guarantee you can deliver:

Guarantee TypeWhen to UseRisk
Unconditional refundConfident in product; low-touch saleRefund-fraud exposure
Conditional ("if X doesn't happen, we Y")Specific outcome promisedRequires clear measurement
Anti-guaranteePremium / high-status positioningLoses risk-averse buyers
Implied (case studies)Long sales cycle, B2BSlower trust-building
Service-levelOngoing relationshipOperational commitment

Write the guarantee in the customer's words. If you cannot stand behind it, choose a weaker one or fix the product.

Step 5: Add scarcity and urgency [standard+]

TypeExamples
Scarcity (supply)Beta seats (real cap), capacity-limited service tier, founding-member pricing
Urgency (time)Cohort start date, price increase scheduled, bonus expiration

Both must be real. Document the mechanism — what triggers the cap or deadline — in the GTM- entry. If you can't document the mechanism, drop the claim.

Step 6: Anchor the price [deep only]

Present the offer in this order: Dream Outcome → Stack value → Guarantee → Scarcity → Price. The price should feel inevitable given everything before it.

If running multiple offer tiers in deep mode, design the middle tier as the anchor (most buyers pick the option positioned next to the highest-priced option they almost-picked).

Output Template

GTM-XXX: Offer Card
Type: Offer
Owner: Founder / Sales
Status: Ready

Core promise: [One-sentence headline outcome]
Best-fit segment: PER-XXX
Linked positioning: GTM-YYY (Positioning Statement)

Value equation:
  Dream Outcome: [In customer words]
  Likelihood of Achievement: [What anchors this — case studies, guarantees]
  Time Delay: [Target]
  Effort & Sacrifice: [Target]

Bonus stack:
  1. [Bonus name] — anchored value: $X (real cost: ~$Y) — FEA-ZZZ or service
  2. [Bonus name] — ...
  3. ...

Total stacked value: $X (vs. price $Y — ratio ≥ 3:1)

Guarantee: GTM-ZZZ (separate entry)

Scarcity: [Real mechanism — beta cap, capacity limit, etc.]
Urgency: [Real deadline — cohort start, price change, etc.]

Price: $X (anchored against stacked value)
Payment terms: [One-time / monthly / annual / split]

Linked IDs: PER-XXX, GTM-YYY (positioning), FEA-ZZZ (bonus features), BR-PRICING-AAA, CFD-BBB (value evidence)
GTM-XXX: Guarantee
Type: Guarantee
Owner: Founder / Legal
Status: Approved

Guarantee type: [Unconditional refund | Conditional | Anti-guarantee | Implied | Service-level]
Stated in customer words: "[The exact wording]"
Eligibility: [Who, when, how]
Measurement: [How "did it work?" is determined]
Failure procedure: [What happens if invoked — refund process, etc.]

Linked IDs: GTM-YYY (Offer Card), BR-PRICING-ZZZ (if affects pricing model)

Anti-Patterns

PatternSignalFix
Manufactured scarcity"Only 7 spots left" reset every weekDrop the claim or make the cap real (e.g., one cohort per quarter)
Vapor bonusesBonus = "lifetime access" to a thing that costs you nothingReplace with something that has anchored value, even if cheap to deliver
Promise mismatchOffer promises more than positioning supportsFix the offer down; do not quietly upgrade positioning
Guarantee you can't honor"100% refund anytime" with 60% refund-fraud ratePick a stronger conditional guarantee instead
Stack ratio < 2:1Stacked value barely beats priceEither add more bonuses or drop the price; thin stacks don't convert
No best-fit segmentOffer designed for "everyone"Pull the PER- from positioning and design for them

Quality Gates

Before proceeding to Launch Channels:

  • Value equation calibrated with current vs. target per lever
  • Core promise written in one sentence
  • Stack value ≥ 3× price (standard+); ≥ 2× (quick)
  • Guarantee chosen and writable in customer's words
  • Scarcity and urgency mechanisms are real and documented
  • Offer does not contradict positioning statement
  • All bonuses trace to real FEA- or service deliverables

Downstream Connections

ConsumerWhat it usesExample
Launch Channels (ORB)Offer card = the unit being distributedOwned-channel emails sell the offer, not the product
Launch MetricsOffer becomes KPI- conversion targetKPI: offer page → purchase rate
Cold Outreach (Tactical)Tier 1/2/3 cold sequences end on the guaranteeGuarantee = reply-friction killer
v1.0 Crossing the Chasm (Moore)Offer shifts as adoption stage shiftsEarly-adopter offer ≠ early-majority offer

Detailed References

  • Alex Hormozi, $100M Offers (2021) — canonical source
  • Acquisition.com offer-construction resources
  • (No bundled references/ — read the book for depth)

Frequently asked questions

What does the Prd V09 Offer Construction Hormozi AI skill do?

Construct a high-conversion offer using Alex Hormozi's value equation and Grand Slam Offer mechanics during PRD v0.9 Go-to-Market. Triggers on requests to design the offer, set up the pitch, build bonuses or guarantees, or when user asks "how do we package this?", "what's the offer?", "build a grand slam offer", "Hormozi", "$100M offers", "guarantee", "bonus stack". Outputs GTM-* entries with Type=Offer / Type=Guarantee and BR-PRICING-* updates.

Why use Prd V09 Offer Construction Hormozi on TypingMind?

Because you install it once and use it with any model. Prd V09 Offer Construction Hormozi 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 Prd V09 Offer Construction Hormozi in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mattgierhart/PRD-driven-context-engineering/tree/main/plugins/prd-ce/skills/prd-v09-offer-construction-hormozi. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Prd V09 Offer Construction Hormozi?

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 Prd V09 Offer Construction Hormozi?

As many as you like. As long as a model supports skills, you can use Prd V09 Offer Construction Hormozi with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Prd V09 Offer Construction Hormozi AI skill free?

Yes. It is published on GitHub by mattgierhart 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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