Agent skill · business finance · anthropics
cash-flow-snapshot
Reads AR/AP, historical cash timing, and known fixed costs from QuickBooks, PayPal, Stripe, or Square — or a CSV upload — and produces a 30/60/90-day cash flow forecast with percentage-variance confidence bands and named risk flags. Delivers a chat summary and a downloadable XLSX. Use when the user asks "forecast my cash flow," "will I make payroll," mentions "runway," or says "cash crunch." Falls back to CSV upload when no connector is live.
Why this skill is useful
Adds a comprehensive cash flow forecasting script that integrates with multiple financial data sources and produces detailed outputs not covered in standard financial practices.
What it needs
Requires paypal, quickbooks, square, stripe account access. About 4k tokens when loaded. Last updated 2026-08-07. 23,345 stars on the source repository.
What this skill does
Cash Flow Snapshot Produces a 30/60/90-day cash flow forecast with percentage-variance confidence bands and named risk flags. Delivers a two-part output: a concise chat summary and a downloadable XLSX workbook. Quick start "Will I make payroll next month?" Claude pulls AR/AP and fixed costs from connected sources, calculates expected inflows and outflows across 30, 60, and 90-day windows, applies confidence bands based on each customer's historical payment variance, and flags specific risks by name. --- Workflow Step 1 — Identify available data sources Check which connectors are live. Try in this order: 1. QuickBooks — primary source for AR aging, AP, and fixed costs 2. PayPal — transaction history and settlement timing 3. Stripe — charge and payout history 4. Square — sales and payout history 5. CSV upload — fallback if no connector is connected If no connector is live and no file is attached, ask the user to either connect a source or upload a CSV (income/expense tabular data, any reasonable format). Note which sources were used in the output — this affects confidence band width. Step 2 — Pull the data From QuickBooks: AR aging report: customer name, invoice amount, invoice date, due date, days outstanding AP: vendor name, amount due, due date Recurring fixed costs: rent, payroll, subscriptions (look for recurring transactions) From PayPal / Stripe / Square: Settlement history: transaction date, amount, settlement date Use settlement lag (transaction date → payout date) to compute each source's average and variance payment delay From CSV upload: Parse as income/expense tabular data Required columns (flexible naming): date, amount, type (income or expense), description If columns are ambiguous, show the header row and ask the user to confirm mapping Step 3 — Compute historical payment timing For each AR customer (or income source from CSV), calculate: Mean payment lag — average days from invoice/transaction date to receipt Payment variance — standard deviation of p …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills anthropics/cash-flow-snapshot