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Financial Modeling

CommunityPopular
cbrock84
financial-modeling

Builds and stress-tests financial models for forecasting, scenario planning, and decision support — revenue build, cost structure, driver logic, and the sensitivities that show where a plan breaks. Use this to model a decision's financial consequence, build a forecast or long-range plan, evaluate an investment or hire, or pressure-test someone else's model before relying on it.

Overview

Publishercbrock84
Repositoryheadcount
Skill namefinancial-modeling
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 Financial Modeling 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/financial-modeling .claude/skills/financial-modeling
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Financial Modeling 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 Financial Modeling 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 Financial Modeling 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.

Financial modeling

A model is an argument about how the business works, expressed in arithmetic. Its value is the argument, not the output precision.

Structure

Three separated layers, always:

  1. Inputs — every assumption, in one place, each with a source and a date. An assumption buried inside a formula is invisible and therefore never challenged.
  2. Calculations — no hard-coded numbers. Ever. A constant inside a formula is an untraceable assumption.
  3. Outputs — the statements and the summary a decision-maker actually reads.

One row, one calculation, carried consistently across periods. Models become unauditable through inconsistent rows more than through complexity.

Build revenue from drivers

Never grow a top-line by a percentage. Build it: volume × price, or accounts × retention × expansion. Driver-based models can be argued with, and being argued with is the point — a growth rate cannot be wrong, only optimistic.

Cost structure separated into fixed, variable, and step-fixed. The step-fixed items are where plans break, because they move in jumps nobody modeled.

Sensitivities are the deliverable

A single-scenario model tells you nothing about risk. For every model, produce:

  • Which two or three assumptions actually move the answer. Usually far fewer than expected.
  • Breakeven on each — how wrong can this be before the decision reverses?
  • Downside case — not a haircut on the base case, but a coherent story where things go badly.

If a plan only works in the base case, that is the finding.

Reviewing someone else's model

The description of a model is not evidence about the model. Check these, in this order, because each one invalidates everything after it.

  • Trace one number end to end. Pick an output that matters and follow it back to inputs. If you cannot, nobody else has either, and the model has never actually been reviewed.
  • Find the hard-coded constants. Search the calculation area for typed numbers. Each one is an assumption that escaped the input sheet, and they are where overrides hide.
  • Check the row consistency. A formula that differs partway across a row is either a deliberate change nobody documented or an error, and the two look identical.
  • Test the extremes. Set a key driver to zero and to double. Models frequently break, go negative in impossible ways, or fail to respond at all — which tells you the driver is decorative.
  • Check that the statements tie. Cash flow reconciles to the balance sheet movement; the balance sheet balances in every period, not just the first.
  • Ask what is missing. Working capital, hiring lag, churn, price changes, tax, and the step costs that come with growth are the omissions that flatter a plan most.

Then find the assumption doing the work. Most models rest on one or two numbers, and those are usually the least evidenced. Ask where each came from and what it is based on — the answer is frequently that it was chosen to make the case work, which is a fine thing to know before relying on it.

Presenting

Lead with the answer, then the two assumptions it rests on most heavily, then what would change it. Never present a model without stating what it is most sensitive to — the recipient will assume robustness you did not claim.

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

  • Report a number to more precision than the assumptions support. Five significant figures from a guessed growth rate is false confidence.
  • Build a model whose logic you cannot explain in three sentences.
  • Change an assumption to reach a desired output without labeling it as a target case.

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 Financial Modeling AI skill do?

Builds and stress-tests financial models for forecasting, scenario planning, and decision support — revenue build, cost structure, driver logic, and the sensitivities that show where a plan breaks. Use this to model a decision's financial consequence, build a forecast or long-range plan, evaluate an investment or hire, or pressure-test someone else's model before relying on it.

Why use Financial Modeling on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cbrock84/headcount/tree/main/plugins/finance/skills/financial-modeling. 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 Financial Modeling?

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 Financial Modeling?

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

Is the Financial Modeling 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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