What problem does it solve? Manually reviewing credit card and bank statements to understand spending habits is tedious, and hidden costs like revolving debt interest or frequent small purchases often go unnoticed. This Skill automates the extraction, categorization, and analysis of financial documents to reveal spending patterns and concrete saving opportunities. ## Core Features & Use Cases - Transaction Extraction & Parsing: Extract transactions from PDF statements (via pymupdf), CSV exports, or screenshots, handling Japanese merchant names and payment types (one-time, installment, revolving). - Categorization & Summaries: Classify each transaction into categories like groceries, dining, transport, and utilities using curated Japanese merchant keyword lists, then compute totals and percentages. - Saving Opportunity Detection: Identify revolving debt interest costs, convenience store spending bleed, IC card top-up fragmentation, and unused subscriptions, with multi-month trend analysis. - Use Case: A user shares six months of EPOS card statements and asks where their money goes; the Skill parses each statement, categorizes every transaction, tracks the revolving balance trajectory, and produces a ranked list of saving tips. ## Quick Start Analyze the attached credit card statement PDF and show me a spending breakdown by category with personalized saving tips.
