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dealbreaker

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.

What is dealbreaker?

dealbreaker is a Claude Code agent skill that 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.

Works with✓Claude Code~Codex CLI~Cursor
npx skills add https://github.com/peaknr35/shark-Tank-proof/tree/main/skills/dealbreaker

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Documentation

What does dealbreaker do?

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 ${CLAUDE_SKILL_DIR}/../shark-board/lenses.md as the method (a summary of the framework in Alex Hormozi's $100M Offers; never present it as his words).

Read ${CLAUDE_SKILL_DIR}/../receipts/rules.md first. An offer is a set of promises. Every promise is PLANNED until it has been delivered and measured, and the offer must say it that way.

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 1b: the first yes

Before the full offer, design the first one: the smallest real commitment a stranger would make with no references. For a shop, a launch-day price or a founding-member card. For a business sold to businesses, a time-boxed pilot on their own numbers (two to eight weeks, one workflow, a success line written in advance, a clear end: roll into the standard price or remove it and owe nothing). Use the pilot offer shape in ${CLAUDE_SKILL_DIR}/../handshake/receivers.md. The full offer below is what the pilot rolls into.

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.

Be strict on likelihood: with no MEASURED results, a buyer has only the founder's word. Likelihood is low until there is a case, a quote or a demo on the buyer's kind of data, and a stack of bonuses does not change that.

Step 5: re-test it

Write the new offer into founder/pitch.md (keep the old one as founder/pitch-v1.md) and run /truth-serum --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. If it moved, say that too, and that it is still simulated: the real re-test is the first-yes offer put to real buyers.

Log every promise the offer makes ("results in 5 days", "3x faster", "zero data leaves the building") with ledger.py add as PLANNED, kind product, unless it is already MEASURED with evidence.

Rules

  • Every promise must be deliverable and affordable; check costs with the CFO.
  • A promise that has not been measured is written as a goal or a commitment ("we will measure", "if we miss it, you pay nothing"), never as a fact.
  • 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 (the hard truth first: the weakest part of the offer; then the first-yes offer, the problem list, the stack, costs, the value-equation scores, the re-test result) and the updated founder/pitch.md. Next: /burn-test to re-run the numbers with the stack, then /signal, or /handshake to send the first-yes offer to a real buyer.

Individual skills in this repo

This repo contains 5 individual skills — each has its own dedicated page.

burn-test

Your CFO. Builds the unit economics of a business before money is spent: what one unit earns after its direct costs, the real profit margin at the planned volume, the break-even point in units a day, year 1 month by month, the cash needed before it pays for itself, how long the startup spend takes to earn back, and what happens if the price drops, sales come in low or costs rise. Every number traces to an input the user can check. Use when the user says "find the profit margins", "do the numbers", "is this profitable", "break-even", "unit economics", "how much do I need to start", or "run the CFO".

handshake

Turns the founder folder into the thing that gets one real person to say yes to the next step: a one-page pilot offer for a customer, an NSF Project Pitch or grant answer for a funder, an investor or lender one-pager, a business case for a boss, or an invite for the people who will use it. Always writes the one-sentence, three-sentence and three-minute versions first. Builds only from claims in the evidence ledger that the audience may see, never from simulated buyers, and checks the finished pitch with the ledger before it goes out. Use when the user says "pitch this", "write a pilot offer", "one-pager", "grant pitch", "NSF pitch", "deck for", "email this customer", "business case", or "what do I send them".

kill-or-build

Your business planner. Compiles everything the other Shark Tank Proof skills wrote (the board's verdict, the competitors, the buyer panel, pricing, the offer, the CFO's numbers, marketing, brand, operations, the launch plan and the evidence ledger) into one business plan with a verdict at the top that is computed, never written by hand: Profitable (the numbers pass and a real buyer has paid, signed or booked), Unproven (works on paper, no real buyer yet), Not yet (with the failing numbers) or Incomplete. A simulated panel can fail a plan but never pass one. Adds an executive summary and a one-page version. Use when the user says "write my business plan", "put it all together", "is it profitable", "give me the plan", or at the end of the Shark Tank Proof pack.

shark-board

Your board of directors, built to disagree with you. Puts a business idea in front of a four-member board, each a sub-agent reading the idea through one published framework: the Offers lens (from Alex Hormozi's $100M Offers), the Monopoly lens (from Peter Thiel's Zero to One), the Product lens (from Walter Isaacson's biography of Steve Jobs) and the Evidence lens (from Rob Fitzpatrick's The Mom Test), which scores only what real people have done. Each member scores the idea, names what would kill it and the cheapest test that would prove it, and votes fund, fund with conditions, or pass. Use when the user says "test my business idea", "would this work", "pressure-test this", "what would a board say", "is this a good business", or starts the Shark Tank Proof pack on a new idea.

truth-serum

The consumer panel. Spins up a swarm of buyer sub-agents (default 100, --quick for 20) trained on the user's target customer, each with a different income, age, buying behaviour and objection, shows every one the same pitch, and runs the business through 100 buyer scenarios to see who buys, who doesn't, and why. Tallies the answers into buy rates by segment, the reasons people pass in their own words, what would flip a no, and price answers for litmus. Every result is labelled SIMULATED: it finds objections and the questions to ask real buyers, and never counts as demand. Use when the user says "would people buy this", "test it on customers", "run the consumer panel", "simulate buyers", "who is my customer", or "validate demand".

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