Finance Skill

To parse transactions from a PDF bank statement, the Skill automatically extracts your financial data and stores it locally in a JSON file. This enables natural language queries for spending analysis and categorization without manual data entry.

Yes, you can track personal finance and budgeting using natural language queries. Once your transactions are stored locally, ask questions like "How much did I spend on food last month?" to query summaries, categories, date ranges, and merchant searches.

This personal finance tracker stores your financial data locally in a JSON file. This ensures your parsed PDF bank statements and manually added transactions remain private on your device.

To manually add a transaction to your spending tracker, use the finance skill and provide the specific JSON string containing the date, merchant, amount, and category. The script will then store this transaction locally for analysis.

You need the jq command-line JSON processor and the pypdf library to extract transactions from PDF statements. These dependencies support parsing PDF documents and processing the extracted financial data locally.

Yes, parsed bank statement transactions are automatically categorized into groups like groceries, transport, and entertainment. This allows you to immediately query your spending habits by category using natural language.