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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.

Install / Use

npx skills add Jakeschincariol/founder-skill --skill founder-offer

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

83/100

Supported Platforms

Universal

Tags

Our assessment of founder-offer

founder-offer scores 83/100 on our quality scale, 3097th of 4,619 Development & Engineering skills we index.

Its SKILL.md is 3.5 KB long, well organised into 8 sections and no code examples: a solid amount of guidance for an agent.

With 2,272 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
13/20
Description
15/15
Adoption
14/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 30 days ago, so founder-offer is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

founder-offer compared with similar skills

All 4 of these similar skills score higher than founder-offer; compare them before choosing.

SkillScoreStarsUpdatedFormat
founder-offer (this skill)by Jakeschincariol832.3k30d agoSKILL.md
taste-skillby Leonxlnx100111.2k1d agoCLAUDE.md
ai-job-searchby ai-job-search-dev10070.1k1d agoCLAUDE.md
claude-howtoby luongnv8910046.7k3d agoCLAUDE.md
lobehubby lobehub10084.2ktodayMCP Server

Frequently asked questions

How do I install founder-offer?
Run npx skills add Jakeschincariol/founder-skill --skill founder-offer. The install tabs above show the steps for each supported agent.
Which AI agents does founder-offer work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is founder-offer safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is founder-offer still maintained?
The repository was last updated 30 days ago, so founder-offer is actively maintained.

name: founder-offer description: >- 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. argument-hint: "[what you sell]"

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.

Related Skills

View on GitHub
GitHub Stars2.3k
CategoryDevelopment
Updated1mo ago
Forks299

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions