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Unit Economics

CommunityPopular
cbrock84
unit-economics

Establishes whether the business makes money on each customer or unit — contribution margin, acquisition cost, payback period, lifetime value, and the cohort behavior underneath. Use this to assess whether growth is profitable, evaluate a channel or segment, support a pricing decision, judge how fast the business can afford to grow, or diagnose why revenue growth is not producing profit.

Overview

Publishercbrock84
Repositoryheadcount
Skill nameunit-economics
Stars
1.6K
Forks
237
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

    Published by cbrock84 on GitHub. Read the source before you install it.

Installation

Install the Unit Economics 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/cbrock84/headcount.git /tmp/headcount
mkdir -p .claude/skills
cp -r /tmp/headcount/plugins/finance/skills/unit-economics .claude/skills/unit-economics
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Unit Economics 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 Unit Economics 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 Unit Economics 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.

Unit economics

The question is simple and usually unanswered: does one more customer make the business better off, and how long does that take?

Build it in this order

  1. Define the unit. A customer, an account, a seat, an order. State it, because most disagreements about unit economics are disagreements about the unit.
  2. Contribution margin — revenue per unit minus the costs that vary with it. Include everything that actually varies: payment processing, hosting attributable to usage, support load, delivery, third-party fees. Understating variable cost is the single most common error and it flatters everything downstream.
  3. Acquisition cost — fully loaded. All sales and marketing spend, including salaries, divided by customers acquired in the same period. Excluding people costs is the second most common error and typically understates by half or more.
  4. Payback period — acquisition cost divided by monthly contribution. This is the number that governs how fast you can grow without financing it.
  5. Lifetime value — contribution × expected lifetime, from observed retention. Not from a churn-rate assumption chosen because it produces a good ratio.

Read it honestly

  • Ratios hide the constraint. A healthy lifetime-value ratio with a long payback still means growth consumes cash faster than it produces it. Payback governs the growth rate; the ratio governs whether it is worth doing at all.
  • Segment before concluding. Blended economics almost always conceal one segment subsidizing another. The average is the least useful number.
  • Use cohorts, not averages. Retention improves or decays over time, and blended figures mask which. If early cohorts retain better than recent ones, the business is deteriorating while the average looks stable.
  • Do not extrapolate lifetime beyond your data. A twelve-month-old company cannot observe a three-year lifetime, and assuming one is how unprofitable businesses appear profitable.

What it should change

Good unit economics by segment tell you where to spend. Bad ones tell you to fix the model before scaling — no acquisition efficiency rescues a negative contribution margin, it only reaches the loss faster.

Sources

references/sources.md in this skill lists the outside authorities that settle the questions here — what each one is authoritative for, and what you may do with it. Check them before answering on anything they cover, and cite what you used. Most are free to read and not free to reproduce; the use note on each is binding.

Never

  • Compare acquisition cost against revenue rather than contribution.
  • Report lifetime value without stating the retention data behind it and its observation window.
  • Treat improving ratios as progress without checking whether the mix simply shifted.

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 Unit Economics AI skill do?

Establishes whether the business makes money on each customer or unit — contribution margin, acquisition cost, payback period, lifetime value, and the cohort behavior underneath. Use this to assess whether growth is profitable, evaluate a channel or segment, support a pricing decision, judge how fast the business can afford to grow, or diagnose why revenue growth is not producing profit.

Why use Unit Economics on TypingMind?

Because you install it once and use it with any model. Unit Economics 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 Unit Economics in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cbrock84/headcount/tree/main/plugins/finance/skills/unit-economics. 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 Unit Economics?

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 Unit Economics?

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

Is the Unit Economics AI skill free?

Yes. It is published on GitHub by cbrock84 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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