Cash Flow Forecaster logo

Cash Flow Forecaster

Organization
OneWave-AI
cash-flow-forecaster

Build a 13-week rolling cash flow forecast from bank exports, AR aging, AP bills, payroll, and recurring commitments -- the report that tells a small business whether it survives the quarter. Flags the crunch weeks early enough to act.

Overview

PublisherOneWave-AI
Repositoryclaude-skills
Skill namecash-flow-forecaster
Stars
293
Forks
49
Bundled files
Instructions only
LicenseMIT
Links
Skill sourceRepositoryHomepage
  • 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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by OneWave-AI on GitHub. Read the source before you install it.

Installation

Install the Cash Flow Forecaster 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/OneWave-AI/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/cash-flow-forecaster .claude/skills/cash-flow-forecaster
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cash Flow Forecaster 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 Cash Flow Forecaster 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 Cash Flow Forecaster 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.

Cash Flow Forecaster

Profitable businesses die of cash starvation; the 13-week forecast is the instrument that prevents it. Input: bank/transaction exports (.csv/.xlsx), open invoices (AR), upcoming bills (AP), payroll schedule, and known recurring items. Output: a week-by-week cash position with the crunch points circled.

Workflow

  1. Establish the baseline. Current cash across accounts (from the most recent export -- state the as-of date prominently). Reconstruct 8-12 weeks of history to learn the rhythm: payroll cadence, rent day, typical weekly card/vendor spend, revenue deposit patterns.
  2. Schedule the knowns. Inflows: open AR placed in the week each invoice is likely paid -- due date plus that customer's historical lateness, not the due date printed on the invoice. Outflows: payroll (with tax deposit timing), rent, loan payments, insurance, subscriptions, credit card due dates, quarterly estimated taxes -- the ambush everyone forgets.
  3. Model the unknowns. Recurring-but-variable spend from historical averages, labeled ESTIMATE. New revenue only if the user provides expected deals -- never invent pipeline.
  4. Build the forecast. cash-flow-13wk.csv + summary: weekly beginning cash, inflows, outflows, ending cash. Flag every week ending below the user's minimum comfort level (ask; default one payroll cycle) as CRUNCH, and the first crunch week is the headline.
  5. Scenario the levers. For each crunch: what closes the gap -- which specific AR to chase this week (pairs with cowork-invoice-chaser), which AP can slide two weeks without damage, where the line of credit covers, what the owner draw pause buys. Concrete moves with amounts, not advice-shaped sentences.

Rules

  • Payment behavior beats due dates: a net-30 customer who pays in 55 days forecasts at 55.
  • Never fabricate inflows. Hope is not a week-9 deposit; unconfirmed revenue stays out or sits in a clearly separated optimistic scenario.
  • Estimates are labeled and totaled separately so the user can see how much of the forecast is soft.
  • Weekly granularity, not monthly -- a month that nets positive can contain a week that bounces payroll.
  • The as-of date and data gaps are stated up front; a forecast built on a two-week-old balance says so.
  • Re-run weekly: roll the window, compare actuals to last week's forecast, and report the misses -- forecast accuracy is a metric.

Quick Commands

  • "Forecast from [files]" -- full workflow
  • "When's my next crunch?" -- the headline week and its gap
  • "What if [customer] pays late?" -- single-scenario rerun
  • "Roll the forecast" -- weekly update against actuals

Frequently asked questions

What does the Cash Flow Forecaster AI skill do?

Build a 13-week rolling cash flow forecast from bank exports, AR aging, AP bills, payroll, and recurring commitments -- the report that tells a small business whether it survives the quarter. Flags the crunch weeks early enough to act.

Why use Cash Flow Forecaster on TypingMind?

Because you install it once and use it with any model. Cash Flow Forecaster 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 Cash Flow Forecaster in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/OneWave-AI/claude-skills/tree/main/cash-flow-forecaster. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Cash Flow Forecaster?

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 Cash Flow Forecaster?

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

Is the Cash Flow Forecaster AI skill free?

Yes. It is published on GitHub by OneWave-AI 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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