Agent skill

Unit Economics

by mohitagw15856 in mohitagw15856/pm-claude-skills

Model the unit economics of a business — CAC, LTV, payback, contribution margin — from real inputs.

MITAuto-check passedBusiness, Finance & HR

Install Unit Economics

skills CLI
$ npx skills add mohitagw15856/pm-claude-skills --skill unit-economics -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mohitagw15856/pm-claude-skills unit-economics --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/unit-economics .claude/skills/unit-economics && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
unit-economics
GitHub stars
1.4k
Token cost
~844 tokens
SKILL.md length
381 words
Files
2 (incl. scripts)
Skills in repo
1,348
Repo updated
First seen
Licence
MIT

At a glance

Model the unit economics of a business — CAC, LTV, payback, contribution margin — from real inputs.

  • Asked to calculate unit economics
  • SKILL.md covers Required Inputs, Output Format, Programmatic Helper and Quality Checks, plus 3 more sections
  • Runs Python scripts from its folder; calls python3
  • Work out LTV:CAC

What it does

Unit Economics is an agent skill from mohitagw15856/pm-claude-skills. Model the unit economics of a business — CAC, LTV, payback, contribution margin — from real inputs. Use when asked to calculate unit economics, work out LTV:CAC, find the payback period, or check whether a business model is viable per customer. Produces a computed unit-economics summary (LTV, CAC, ratio, payback, contribution margin) with a verdict and the levers that move it most.

Its SKILL.md is about 840 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including scripts (for example `scripts/unit_econ.py`).

It sits in Business, Finance & HR, covering Financial modeling. The repository describes itself as: 1255 professional Agent Skills for Claude, ChatGPT, Gemini, Cursor & Codex — PRDs, postmortems, leases, medical bills, layoffs, go-bags, new countries. Plain markdown, MIT, in… The licence is MIT.

When your agent uses it

  • Asked to calculate unit economics
  • Work out LTV:CAC
  • Find the payback period
  • Check whether a business model is viable per customer

Example prompts

  • “/unit-economics”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit 1cbf1f0. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Unit Economics loads about 844 tokens when it runs. Until then it costs about 100 tokens; SKILL.md has 381 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~100
When it runs · the whole SKILL.md, loaded when a task matches
~844

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from mohitagw15856/pm-claude-skills at commit 1cbf1f0, republished under its MIT licence (© mohitagw15856). 381 words, ~844 tokens.

Download SKILL.mdSave it as .claude/skills/unit-economics/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
unit-economics
description
Model the unit economics of a business — CAC, LTV, payback, contribution margin — from real inputs. Use when asked to calculate unit economics, work out LTV:CAC, find the payback period, or check whether a business model is viable per customer. Produces a computed unit-economics summary (LTV, CAC, ratio, payback, contribution margin) with a verdict and the levers that move it most.

Unit Economics Skill

A business is only viable if each customer is worth more than it costs to acquire and serve. This skill computes the core unit economics — CAC, LTV, the LTV:CAC ratio, payback period, and contribution margin — from real numbers (not vibes), states a clear verdict against the rule-of-thumb benchmarks, and shows which lever moves the model most.

Required Inputs

Ask for these only if they aren't already provided:

  • ARPA — average revenue per account, per month (or per period).
  • Gross margin % — the share of revenue left after cost-to-serve.
  • Churn % — monthly customer (or revenue) churn — drives LTV.
  • CAC — fully-loaded cost to acquire a customer (sales + marketing ÷ new customers).

Output Format

Unit Economics: [business]

1. The numbers — computed, with the formula shown (use the helper script so they're consistent):

MetricValueBenchmark
Lifetime (1/churn)
LTV (ARPA × margin ÷ churn)
CAC
LTV : CAC≥ 3:1 healthy
Payback (months)< 12 healthy
Contribution margin

2. Verdict — healthy / borderline / underwater, in one line, against the benchmarks (LTV:CAC ≥ 3, payback < 12 months).

3. Biggest levers — which input, improved realistically, moves the model most (usually churn or CAC), with the rough effect.

4. Caveats — where the inputs are assumptions vs. measured, and what to validate before betting on this.

Programmatic Helper

scripts/unit_econ.py (stdlib only) computes the model so the numbers are calculated, not estimated:

bash
# in.json: {"arpa": 50, "gross_margin": 0.8, "monthly_churn": 0.03, "cac": 400}
python3 scripts/unit_econ.py in.json
python3 scripts/unit_econ.py in.json --json
Show full SKILL.md (166 more words)Show less

Quality Checks

  • LTV uses gross margin, not raw revenue (a common, model-breaking error)
  • The numbers are computed by the helper, not eyeballed
  • Verdict is stated against the standard benchmarks (LTV:CAC ≥ 3, payback < 12mo)
  • The biggest lever is identified with its rough effect
  • Assumed inputs are flagged separately from measured ones

Anti-Patterns

  • Do not compute LTV on revenue instead of gross margin — it inflates LTV and hides an unviable model
  • Do not ignore payback — a great LTV:CAC with a 30-month payback can still starve a business of cash
  • Do not treat blended CAC as paid CAC — separate organic from paid or the model lies
  • Do not present assumptions as facts — label estimated churn/CAC and validate them
  • Do not optimise the smallest lever — model which input actually moves the outcome

Based On

SaaS unit-economics practice (David Skok / for Entrepreneurs) — margin-based LTV, LTV:CAC ≥ 3, payback < 12 months.

Example Trigger Phrases

  • "Calculate unit economics."
  • "Work out LTV:CAC."
  • "Find the payback period."
  • "Check whether a business model is viable per customer."

© mohitagw15856, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (scripts) in skills/unit-economics of mohitagw15856/pm-claude-skills.

  • SKILL.md
  • scripts/unit_econ.py

Open the folder on GitHubat commit 1cbf1f0

Compare with similar skills

Unit Economics next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Unit Economics compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Unit Economics this skillmohitagw15856/pm-claude-skills1.4k—~844Automated safety check: PassMIT
Creating Financial ModelsChen-zexi/open-ptc-agent7293 repos~1.3kAutomated safety check: PassMIT
Equity ResearchrollingSirius/equity-research-skill453—~1.5kAutomated safety check: PassMIT
SaaS Metrics Coachrongxinzy/RongxinAI1542 repos~1.3kAutomated safety check: PassMIT
Startup Financial Modelingnicepkg/auto-company19511 repos~2.8kAutomated safety check: PassNone
Stock Value AnalyzerFunnyKun/stock-value-analyzer141—~3.3kAutomated safety check: PassNone

Similar skills

  • Creating Financial Models

    Chen-zexi/open-ptc-agent

    This skill provides an advanced financial modeling suite with DCF analysis, sensitivity testing, Monte Carlo simulations, and scenario planning for investment decisions

    729 GitHub starsUsed in 3 repos~1.3k tokens
    Business, Finance & HRAuto-check passed
  • Equity Research

    rollingSirius/equity-research-skill

    撰写机构级个股投资研究报告(二级市场深度研究)。Use whenever the user wants to research, analyze, or value a specific publicly-traded stock — e.g.

    453 GitHub stars~1.5k tokensUpdated 1 mo ago
    Business, Finance & HRAuto-check passed
  • SaaS Metrics Coach

    rongxinzy/RongxinAI

    SaaS financial health advisor. An agent skill from rongxinzy/RongxinAI.

    154 GitHub starsUsed in 2 repos~1.3k tokens
    Business, Finance & HRAuto-check passed
  • Startup Financial Modeling

    nicepkg/auto-company

    This skill should be used when the user asks to "create financial projections", "build a financial model", "forecast revenue", "calculate burn rate", "estimate runway", "model cash flow", or…

    195 GitHub starsUsed in 11 repos~2.8k tokens
    Business, Finance & HRAuto-check passed
  • Stock Value Analyzer

    FunnyKun/stock-value-analyzer

    基于邱国鹭《投资中最简单的事》方法论的股票价值分析器(v2.0 双层架构)。通过"三好原则"(好行业、好公司、好价格)系统评估一只股票是否值得投资。v2.0 在原定性框架之上注入一套可量化、可复现的硬模型层——反向 DCF 反解市场隐含增速、情景概率加权估值、EPV 盈利能力价值、分行业估值路由、杜邦三/五因子分解、ROIC vs WACC、Piotroski F-Score、Beneish…

    141 GitHub stars~3.3k tokensUpdated 3 mo ago
    Business, Finance & HRAuto-check passed
  • Dcf Valuation

    edinetdb/dexter-jp

    Performs discounted cash flow (DCF) valuation analysis to estimate intrinsic value per share for Japanese listed companies.

    312 GitHub stars~1.1k tokensUpdated 2 days ago
    Business, Finance & HRAuto-check passed

More from mohitagw15856/pm-claude-skills

All 1,348 skills in this repo
  • Car Tco

    mohitagw15856/pm-claude-skills

    Compare the total cost of car ownership across buy-new, buy-used, lease, and keep-your-current-car — depreciation, insurance, maintenance ramp, and fuel over a real horizon, not just the monthly…

    1.4k GitHub stars~1.1k tokensUpdated 2 days ago
    Auto-check passed
  • Cs Health Scorecard

    mohitagw15856/pm-claude-skills

    Build a customer health scorecard for a specific account. An agent skill from mohitagw15856/pm-claude-skills.

    1.4k GitHub stars~2.4k tokensUpdated 2 days ago
    Auto-check passed
  • Exit Waterfall

    mohitagw15856/pm-claude-skills

    Compute who gets what at each exit price from a cap table — liquidation preferences, conversion points, and where the founders' share collapses.

    1.4k GitHub stars~1.1k tokensUpdated 2 days ago
    Auto-check passed
  • Feature Prioritisation

    mohitagw15856/pm-claude-skills

    Apply prioritisation frameworks (RICE, MoSCoW, Kano, ICE, Opportunity Scoring) to rank features and backlog items.

    1.4k GitHub stars~2k tokensUpdated 2 days ago
    Auto-check passed
  • Fire Number

    mohitagw15856/pm-claude-skills

    Compute a financial-independence (FIRE) target and years-to-reach with every assumption labeled as an assumption — plus a sensitivity table instead of a single false-precision answer.

    1.4k GitHub stars~1.1k tokensUpdated 2 days ago
    Auto-check passed
  • Freelance Rate

    mohitagw15856/pm-claude-skills

    Derive a freelance day/hourly rate backwards from target income, honest billable utilization, overhead, and the self-employment tax premium — the arithmetic that proves a rate is not salary÷2000.

    1.4k GitHub stars~1.2k tokensUpdated 2 days ago
    Auto-check passed

Questions about Unit Economics

What does Unit Economics do?

Model the unit economics of a business — CAC, LTV, payback, contribution margin — from real inputs. Unit Economics is an agent skill from mohitagw15856/pm-claude-skills. Model the unit economics of a business — CAC, LTV, payback, contribution margin — from real inputs.

When should I use Unit Economics?

Unit Economics fits situations like: asked to calculate unit economics; work out LTV:CAC; find the payback period; check whether a business model is viable per customer.

How do I install Unit Economics in Claude Code?

Run `npx skills add mohitagw15856/pm-claude-skills --skill unit-economics -a claude-code`. Or copy the skill folder (skills/unit-economics in mohitagw15856/pm-claude-skills) into .claude/skills/unit-economics in your project. Claude Code loads it when a task matches its description.

How do I install Unit Economics in Codex?

Run `npx skills add mohitagw15856/pm-claude-skills --skill unit-economics -a codex`. Or copy the skill folder (skills/unit-economics in mohitagw15856/pm-claude-skills) into .agents/skills/unit-economics in your project. Codex loads it when a task matches its description.

Can I use Unit Economics in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mohitagw15856/pm-claude-skills --skill unit-economics -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/unit-economics, .gemini/skills/unit-economics, .github/skills/unit-economics and .opencode/skills/unit-economics in your project.

What does Unit Economics need to run?

Going by SKILL.md and its folder, Unit Economics needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Unit Economics access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Unit Economics safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Unit Economics use?

Unit Economics is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Unit Economics use?

About 844 tokens (SKILL.md is roughly 3.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Unit Economics?

Skills that share tags, products or a category with Unit Economics: Creating Financial Models (Chen-zexi/open-ptc-agent, 729 stars), Equity Research (rollingSirius/equity-research-skill, 453 stars), SaaS Metrics Coach (rongxinzy/RongxinAI, 154 stars) and Startup Financial Modeling (nicepkg/auto-company, 195 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Unit Economics?

mohitagw15856 (a GitHub user) maintains it in mohitagw15856/pm-claude-skills, which has 1,434 GitHub stars. The repository holds 1,348 skills in this directory. The repository was last updated on October 9, 2026.

Source: mohitagw15856/pm-claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.