Charlie logo

Charlie

Organization
EveryInc
charlie

Your AI CFO for bootstrapped startups, named after Charlie Munger who embodied the principle that capital discipline is a competitive advantage. Provides financial frameworks for cash management, runway calculations, unit economics (LTV:CAC), capital allocation, hiring ROI, burn rate analysis, working capital optimization, and forecasting. Use for questions like "should we make this hire?", "how much runway do we need?", "what metrics should I track?", "how do I forecast revenue?", or any strategic financial decision at a self-funded company.

Overview

PublisherEveryInc
Repositorycharlie-cfo-skill
Skill namecharlie
Stars
327
Forks
38
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 EveryInc on GitHub. Read the source before you install it.

Installation

Install the Charlie 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/EveryInc/charlie-cfo-skill/tree/main
  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/EveryInc/charlie-cfo-skill.git \
  .claude/skills/charlie
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Charlie 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 Charlie 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 Charlie 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.

Charlie CFO: Bootstrapped Financial Management

Your AI CFO for bootstrapped, profitable companies. Named after Charlie Munger, who embodied the principle that capital discipline is a competitive advantage.

Core Mental Models

Profit is a constraint, not a goal. Bootstrapped companies succeed because capital constraints force better decisions. Every dollar has three costs: direct expenditure, opportunity cost, and runway impact.

Unit economics are survival requirements:

  • LTV ≥ 3x CAC (best-in-class: 7-8x)
  • CAC payback < 12 months (high performers: 5-7 months)
  • Violating these creates a death spiral bootstrapped companies cannot survive

Revenue per employee is your efficiency scorecard:

  • $110-150K at $1-5M ARR
  • $200-250K at $10-50M ARR
  • $400K+ at maturity
  • Bootstrapped companies run 40-70% higher than VC-backed peers

Cash Management Rules

Runway targets:

  • Minimum: 24-36 months
  • Danger zone: <12 months (you've lost control)
  • Never fundraise your way out of a cash crisis

Reserve structure:

ReserveAmountPurpose
Operating3-6 months fixed costsPayroll, rent, essential software
Contingency1-2 months expensesEmergencies
GrowthExcessOpportunistic investments

Burn multiple = Net Burn ÷ Net New ARR

  • <1x: Excellent
  • 1-1.5x: Good
  • 2x: Concerning

  • Bootstrapped target: Zero or negative (profitable growth)

Capital Allocation Framework

Every investment question: What is the payback period? Target <12 months.

Rule of 40: Revenue Growth % + EBITDA Margin % ≥ 40%

  • High growth path: 40% + 0%
  • Balanced path: 20% + 20%
  • Profit path: 10% + 30%

Hiring decisions:

  1. Will this hire directly contribute to revenue?
  2. What's the time-to-productivity? (Factor into ROI)
  3. What else could this salary fund?
  4. Does this make existing team more productive?

Never grow a department >50% at once — productivity drops to zero during training.

Working Capital Optimization

Cash Conversion Cycle (CCC): DIO + DSO - DPO

  • SaaS target: Negative (-30 to -90 days)
  • Every 10-day reduction frees significant working capital

AR discipline: Target 30-45 days DSO

  • Reminder 7 days before due
  • Follow up Day 1, 7, 14, 30 past due

AP strategy: Pay on due date, not early, unless discount > cost of capital

  • 2% discount for 20 days early = 36.5% annualized return
  • Negotiate Net 45-60 terms after proving reliability

Annual prepay: Offer 15-20% discount

  • Produces 30% lower churn
  • 27-40% higher LTV
  • Customers finance your growth at 0% interest

Financial Review Rhythms

Weekly (60-90 min):

  • Cash position
  • AR aging
  • Pipeline movement
  • Revenue/bookings

Monthly:

  • Full close (target 5-7 business days)
  • Variance analysis
  • 12-18 month rolling forecast update

Quarterly:

  • Strategic recalibration
  • Scenario refresh (base/moderate/severe)
  • 18-24 month outlook

Key Metrics Dashboard

CategoryMetricsTargets
RevenueMRR/ARR, growth rate, NRRNRR >100%, growth 15-25% YoY
Unit economicsLTV:CAC, CAC payback, gross margin3:1+, <12 mo, 70-80%
CashBurn rate, runway, operating cash flowRunway 24-36 months
Customer healthChurn, concentrationMonthly churn <2%, no customer >10% revenue

Customer concentration warning: Any customer >10% revenue OR top 5 >25% revenue

Forecasting Approach

Use driver-based planning — models built on operational drivers (headcount, acquisition rate, churn), not static percentages.

MRR buildup model:

Starting MRR + New Bookings + Expansion - Churn = Ending MRR

13-week cash flow forecast:

  • Update every Monday
  • Compare actuals to forecast weekly
  • Cross-functional validation (sales confirms timing, ops verifies schedules)

Always maintain three scenarios:

  • Base case: Expected trajectory
  • Moderate downside: -15-20% revenue
  • Severe downside: -30-40% revenue

For each: Calculate runway, define action thresholds (hiring freeze, cost cuts).

Spending Benchmarks ($3-5M ARR)

  • Sales: 10-15% of ARR
  • Marketing: 8-10% of ARR
  • R&D: 25-30% of ARR
  • Customer Success: 8-12% of ARR
  • G&A: ~14% of ARR
  • Total: ~95% (vs. 107% for VC-backed)

References

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 Charlie AI skill do?

Your AI CFO for bootstrapped startups, named after Charlie Munger who embodied the principle that capital discipline is a competitive advantage. Provides financial frameworks for cash management, runway calculations, unit economics (LTV:CAC), capital allocation, hiring ROI, burn rate analysis, working capital optimization, and forecasting. Use for questions like "should we make this hire?", "how much runway do we need?", "what metrics should I track?", "how do I forecast revenue?", or any strategic financial decision at a self-funded company.

Why use Charlie on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/EveryInc/charlie-cfo-skill/tree/main. 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 Charlie?

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 Charlie?

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

Is the Charlie AI skill free?

Yes. It is published on GitHub by EveryInc 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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