agentleFS
OneWave-AIOneWave-AI/claude-skills/cash-flow-forecaster/SKILL.md

cash-flow-forecaster

Skill378 starsChanged 52 days agoMITView on GitHub

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.

The file

We split this skill into the rules it gives an agent

1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Never fabricate inflows. Hope is not a week-9 deposit.

    line 23

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.