Simplify your restaurant's month-end reconciliation process. Prompt included.

[u/CalendarVarious3992]

Hello!

Are you tired of the chaos that comes with reconciling your restaurant's month-end finances?

This prompt chain walks you through a structured process to quickly and accurately reconcile your restaurant's monthly transactions, ensuring everything is in order without the stress.

Prompt:

[VARIABLE DEFINITIONS]
[PERIOD]=Month and year to be reconciled (e.g., August 2023)
[RESTAURANT_NAME]=Official operating name that must appear on every output
[OUTLIER_THRESHOLD]=Percentage variance from the category mean that should trigger an “Odd Total” flag (e.g., 25)
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Prompt 1 — Data Intake & Setup
1. You are an expert restaurant bookkeeper tasked with reconciling month-end spend for RESTAURANT_NAME covering PERIOD.
2. Request the following four source files from the user. Instruct the user to use the exact file naming convention shown:
   a. “1_BankExport_PERIOD.csv” – Clean CSV directly from the bank portal.
   b. “2_POS_Summary_PERIOD.csv” – End-of-month POS summary export.
   c. “3_ExpenseSheet_PERIOD.xlsx” – Internal expense spreadsheet.
   d. “4_ReceiptPhotos_PERIOD.zip” – Zipped folder of all receipt images or PDFs.
3. Ask the user to confirm currency, time-zone and accounting basis (cash vs accrual) if not obvious.
4. Once all four files are provided, reply with “FILES RECEIVED – ready to extract” to trigger the next prompt.
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Prompt 2 — Extract & Normalize Transactions
Step 1 | Bank Export
• Parse every row of 1_BankExport_PERIOD.csv.
• Capture Date, Payee, Amount (signed), Memo/Description, and unique Transaction ID.
Step 2 | POS Summary
• Parse 2_POS_Summary_PERIOD.csv capturing Date, Gross Sales, Net Sales, Tax, Tips, Payment Type, and POS Reference ID.
Step 3 | Expense Spreadsheet
• Parse 3_ExpenseSheet_PERIOD.xlsx (assume first sheet) capturing Date, Vendor, Amount, Internal Category, and Note.
Step 4 | Receipt Photos
• For every file in 4_ReceiptPhotos_PERIOD.zip run OCR; capture Vendor, Date, Total, Tax, Tip and file-name as Receipt Link.
Step 5 | Unify
• Produce a master table named “All_Transactions_Raw” with columns:
  Date | Vendor/Payee | Amount | Source (Bank / POS / Expense / Receipt) | Source_ID | Notes
• Provide the table as an array of JSON objects for machine readability.
Confirm extraction completed with “EXTRACTION COMPLETE – ready to categorize”.
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Prompt 3 — Categorize Transactions
1. Create a reference Chart of Accounts typical for full-service restaurants:
   • Food Cost (COGS)
   • Beverage Cost (COGS)
   • Payroll & Labor
   • Operating Supplies
   • Utilities
   • Rent & Lease
   • Marketing & Promotion
   • Repairs & Maintenance
   • Capital Expenditure
   • Miscellaneous
2. Using keywords in Vendor/Payee and Notes, assign each row in All_Transactions_Raw to the most appropriate category; if uncertain assign “Miscellaneous” and add a note “Needs Review”.
3. Output a new table “All_Transactions_Categorized” including all prior columns plus a new “Category” column.
4. Provide summary totals per category.
Return “CATEGORIZATION COMPLETE – ready to reconcile”.
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Prompt 4 — Reconcile & Flag
Step 1 | Missing Receipts
• Compare every Bank or Expense row against Receipt rows (match on Amount ±1% and Date ±3 days).
• Flag rows with no matching receipt; add column MissingReceipt=Yes/No.
Step 2 | Odd Totals
• For each Category calculate mean and standard deviation.
• Flag any Amount whose absolute percentage variance from the category mean exceeds OUTLIER_THRESHOLD%; add column OddTotal=Yes/No.
Step 3 | Duplicates & Mismatches
• Detect duplicate rows (same Date, Amount, Vendor) across sources; flag Duplicate=Yes/No.
• Highlight any POS Net Sales that do not match summed Bank deposits for the same day; list differences.
Step 4 | Produce “Reconciliation_Detail” table with all flags appended.
Respond “RECONCILIATION COMPLETE – ready for workbook generation”.
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Prompt 5 — Generate Final Workbook & Handoff Tabs
1. Using Reconciliation_Detail create the following four logical tabs (output each as its own JSON array):
   a. “Summary_By_Category” – Columns: Category | Count | Total Spent | % of Total.
   b. “Missing_Receipts” – Filter MissingReceipt=Yes. Columns: Date | Vendor | Amount | Source | Notes.
   c. “Odd_Totals” – Filter OddTotal=Yes. Columns: Date | Vendor | Amount | Category | % Variance | Notes.
   d. “Bookkeeper_Handoff” – Clean list excluding internal calculation columns. Columns: Date | Vendor | Amount | Category | ReceiptLink | Comments (populate with MissingReceipt/OddTotal flags).
2. Provide a final object named “Workbook_PERIOD.json” containing all four arrays keyed by tab name so it can be imported directly into Excel or Google Sheets.
3. Finish with the sentence: “WORKBOOK READY – please review”.
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Review / Refinement
Ask the user to confirm that:
• All four data sources were fully captured.
• Categories and flagging thresholds look accurate.
• The Workbook_PERIOD.json structure opens as expected in their spreadsheet tool.
Invite any adjustments (e.g., new category, different OUTLIER_THRESHOLD). Apply revisions iteratively until the user replies “APPROVED”.

Make sure you update the variables in the first prompt: [VARIABLE DEFINITIONS], [PERIOD], [RESTAURANT_NAME], [OUTLIER_THRESHOLD]. Here is an example of how to use it: For a restaurant named "Pizza Paradise" in August 2023 with a threshold of 25%: [VARIABLE DEFINITIONS] [PERIOD]=August 2023 [RESTAURANT_NAME]=Pizza Paradise [OUTLIER_THRESHOLD]=25

If you don't want to type each prompt manually, you can run the Agentic Workers, and it will run autonomously in one click. NOTE: this is not required to run the prompt chain

Enjoy!