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Founder Cfo

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Jakeschincariol
founder-cfo

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".

Overview

PublisherJakeschincariol
Repositoryfounder-skill
Skill namefounder-cfo
Stars
1.5K
Forks
194
Bundled files
2
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.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Jakeschincariol on GitHub. Read the source before you install it.

Installation

Install the Founder Cfo 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/Jakeschincariol/founder-skill/tree/main/skills/founder-cfo
  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/Jakeschincariol/founder-skill.git /tmp/founder-skill
mkdir -p .claude/skills
cp -r /tmp/founder-skill/skills/founder-cfo .claude/skills/founder-cfo
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Founder Cfo 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 Cfo 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 Cfo 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-cfo

The person who asks "and what does that cost?" Margins decide whether a good idea is a business. This skill finds them, with every number traceable to an input.

Tool in this folder:

bash
python3 "${CLAUDE_SKILL_DIR}/unit_economics.py" founder/numbers.json --out founder/cfo.md

Step 1: gather the inputs

Write founder/numbers.json (shape: example.json in this folder, a walk-in matcha café). It needs:

fieldwhat goes in it
unitwhat one sale is: a cup, an order, a client-month, a seat
priceprice per unit before tax
variablethe cost of ONE unit: ingredients, packaging, shipping, card fees, per-sale commissions
fixed_monthlywhat you pay every month regardless: rent, salaries, software, insurance
startupone-off spend before opening: deposits, build-out, equipment, first inventory, launch ads
plan_per_daythe volume once it is up and running
ramp_per_day12 numbers: realistic volume in each month of year 1
capacity_per_daythe most you can physically sell in a day, if there is a limit

Where the numbers come from, in this order:

  1. The user's own quotes, invoices, leases and supplier price lists.
  2. Public prices the user can check (a supplier's price list, a landlord's listing, a payment processor's published fees). Write the source next to the number in founder/cfo-sources.md.
  3. Your estimate, clearly marked as an estimate, with the reasoning. Never present an estimate as a fact.

Ask the user for anything only they know (rent quoted, wages they will pay). Use the price from founder/pricing.md or founder/pitch.md if those exist.

The ramp is where plans lie. Month 1 is almost never the plan volume. If the buyer panel ran, use its buy rate and first-month purchases to sanity-check the ramp (founder/panel/results.md), and say how you did it.

Step 2: run it

bash
python3 "${CLAUDE_SKILL_DIR}/unit_economics.py" founder/numbers.json --out founder/cfo.md

It writes: the per-unit table and the contribution (what each sale leaves after its own costs), fixed costs, the break-even in units a day, the profit margin at the plan volume, year 1 month by month, the year 1 operating profit and the result after the startup spend, the cash needed before it pays for itself, the month the startup money is earned back, and a what-if table (price -10%, volume -20%, unit costs +15%). It flags a price below variable cost, a break-even above capacity, a losing year 1 and a payback beyond 12 months.

What-ifs without editing the file:

bash
python3 "${CLAUDE_SKILL_DIR}/unit_economics.py" founder/numbers.json --price 7.00
python3 "${CLAUDE_SKILL_DIR}/unit_economics.py" founder/numbers.json --volume 0.8

Step 3: the CFO's note

Add a short section at the top of founder/cfo.md, in plain words:

  • The margin: the profit margin at plan, and the contribution per unit.
  • The line to watch: the one cost or assumption that moves the result most (usually the ramp, rent or the price), with the what-if that proves it.
  • Cash: how much money the founder needs before it pays for itself.
  • Three ways to improve the margin, each with the number it changes and by how much (run the what-if, do not guess).
  • Whether the board's conditions about money (founder/board.md) are met.

Rules

  • Every number in your note comes from the tool's output or an input you can name.
  • Revenue is before tax; say if the user's market adds sales tax on top.
  • Not financial, tax or legal advice. Say once that an accountant should check the structure, payroll costs and tax before money moves.

Output

founder/numbers.json, founder/cfo.md, founder/cfo-sources.md. Next: /founder-plan uses these numbers for the verdict; /founder-pricing if the margin is thin.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Founder Cfo AI skill do?

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 t...

Why use Founder Cfo on TypingMind?

Because you install it once and use it with any model. Founder Cfo 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 Cfo in TypingMind?

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

Which AI models can use Founder Cfo?

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 Cfo?

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

Is the Founder Cfo 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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