Accounting Skill

Process accounting documents — invoices (hóa đơn GTGT), purchase orders, and bank statements. Extract structured data from PDF (digital and scanned), JPG, and PNG files using OCR. Output Excel tracking sheets and JSON backups. Classify unknown documents and route to the correct extractor. Supports Vietnamese and international formats. Use when asked to extract, process, classify, or track invoices, POs, bank statements, or accounting documents.

Extract structured data from accounting documents (invoices, POs, bank statements) into Excel tracking sheets with JSON backups. Handles digital PDFs, scanned PDFs, and images via automatic OCR.

Prerequisites

Install system OCR dependencies before first use. See {baseDir}/references/ocr-setup.md for full guide.

bash

# Ubuntu / Debian
sudo apt install tesseract-ocr tesseract-ocr-vie poppler-utils

# Verify
uv run {baseDir}/scripts/ocr_utils.py check

Quick Start

1. Classify an unknown document

bash

uv run {baseDir}/scripts/classify_document.py /path/to/document.pdf

Returns JSON with type (invoice / po / statement / other), confidence, and a ready-to-run extraction command.

2. Extract an invoice

bash

uv run {baseDir}/scripts/extract_invoice.py /path/to/invoice.pdf -o invoice_tracking.xlsx

Appends to the Excel tracking sheet. Use --dry-run to preview parsed data without writing.

3. Extract a bank statement

bash

uv run {baseDir}/scripts/extract_statement.py /path/to/statement.pdf

Creates statement_{bank}_{date}.xlsx with transactions. Use -o to specify output path.

4. Extract a purchase order

bash

uv run {baseDir}/scripts/extract_po.py /path/to/po.pdf -o po_tracking.xlsx

Tracks delivery dates and flags overdue/urgent POs.

5. Generate empty Excel templates

bash

uv run {baseDir}/scripts/generate_templates.py all -o ~/accounting/

Creates blank tracking sheets: invoice_tracking.xlsx, po_tracking.xlsx, statement_template.xlsx.

Common Options (all extractors)

Flag	Description
--format excel|json|both	Output format (default: both)
--dry-run	Parse and validate only, print JSON to stdout
--json-dir DIR	Directory for JSON backup files
-o FILE	Output Excel file path

Workflow

Single Document

text

File → classify_document.py → route → extract_*.py → Excel + JSON

Batch Processing

For a folder of mixed documents, classify first, then route:

bash

for f in /path/to/docs/*; do
  uv run {baseDir}/scripts/classify_document.py "$f" --output-dir ~/accounting/
done

Then run the suggested extraction commands from each classification result.

OCR Strategy

All scripts share {baseDir}/scripts/ocr_utils.py which auto-selects the best extraction method:

1. Digital PDFs → pdfplumber (fast, no OCR needed)
2. Scanned PDFs → pdf2image + pytesseract at 300 DPI (fallback when pdfplumber gets <50 chars/page)
3. Images (JPG/PNG/TIFF) → pytesseract with grayscale preprocessing

Each result includes ocr_confidence and extraction_confidence percentages. Documents below 85% are automatically flagged needs_review.

Validation Rules

• Invoices: Subtotal + VAT = Total (auto-checks math), duplicate detection by invoice number + vendor
• Bank statements: Opening balance + credits − debits = closing balance
• POs: Delivery date tracking with overdue/urgent alerts

Reference Documents

Read these for field schemas, Vietnamese format details, and validation logic:

• {baseDir}/references/invoice-fields.md — Vietnamese VAT invoice fields, tax rates, patterns
• {baseDir}/references/bank-formats.md — Vietnamese bank names, transaction formats, amount patterns
• {baseDir}/references/po-fields.md — PO fields, delivery status logic, payment terms
• {baseDir}/references/ocr-setup.md — OCR installation, troubleshooting, confidence scoring