ThinkWithPrompt by SynotticThinkWithPrompt

Categorize messy bank and card transactions to my chart of accounts

Sorts a raw transaction export into the right accounts, with confidence levels and a short list of items that need a human answer.

Finance & AccountingFew-ShotStandardFinanceBrainstormFill-in Template

The prompt

Help me categorize bank and credit card transactions for bookkeeping. Business type and what it sells: [e.g. "two-location dental practice", "Shopify apparel store"] Chart of accounts (expense and income accounts I use): [PASTE list] Transactions to categorize: [PASTE export - date, description, amount] Rules I already follow: [e.g. "software subscriptions under $500 go to Software", "owner's personal Amazon orders go to Owner Draws"] Accounting basis: [cash / accrual] For each transaction: - Suggest the account, a cleaned-up payee name, and a confidence level (high / medium / low). - Flag likely transfers between the business's own accounts, loan payments (split principal vs. interest as [NEED LOAN SCHEDULE]), owner draws or contributions, refunds, and sales tax collected - these are the usual miscategorizations. - Flag possible personal expenses, duplicates, and anything over [AMOUNT] that might need to be capitalized. - Do not guess on vague descriptions (e.g. "POS 4471", "Zelle J. Smith"). Mark them [ASK CLIENT]. Return: 1. A table: Date | Description | Cleaned payee | Suggested account | Confidence | Note. 2. A short list of questions for the business owner, grouped so they can answer in one pass. 3. Suggested bank rules I could set up in my accounting software for recurring payees.

Highlighted [brackets] are blanks to replace with your own details.

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What to fill in

  • e.g. "two-location dental practice", "Shopify apparel store"
  • PASTE list
  • PASTE export - date, description, amount
  • cash / accrual
  • NEED LOAN SCHEDULE
  • AMOUNT
  • ASK CLIENT

How this prompt is built

This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.

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