update docs

CLAUDE.md

@@ -4,11 +4,14 @@ This file provides guidance to Claude Code (claude.ai/code) when working with co
 
 ## Project Overview
 
-Single-script Python tool that extracts credit card transactions from BAC Costa Rica statement PDFs. Parses sections B (purchases), D (other charges), and E (voluntary services) and outputs JSON.
+Python tools for BAC Costa Rica credit card statement processing:
+- `bac_extract.py`: Extracts transactions from statement PDFs to JSON
+- `bac_analyze.py`: Analyzes JSON output with categorization and graphs
 
 ## Dependencies
 
-- pdfplumber (>=0.10.0)
+- pdfplumber (>=0.10.0) - PDF extraction
+- matplotlib (>=3.5.0) - graphs (optional, only for bac_analyze.py --graph)
 
 ## Commands
 
@@ -16,22 +19,22 @@ Single-script Python tool that extracts credit card transactions from BAC Costa
 # Run tests
 python testStatements/run_tests.py
 
-# Run extractor
-python bac_extract.py <pdf_file> [options]
-
-# Examples
-python bac_extract.py EstadodeCuenta.pdf --pretty
+# Extract transactions from PDF
+python bac_extract.py statement.pdf --pretty
 python bac_extract.py statement.pdf -o output.json -v
-```
 
-Options:
-- `-o, --output`: Output JSON path (default: transactions.json)
-- `--pretty`: Pretty-print JSON
-- `-v, --verbose`: Enable debug logging
+# Analyze transactions (supports multiple JSON files)
+python bac_analyze.py transactions.json
+python bac_analyze.py *.json --graph all
+python bac_analyze.py *.json --graph bar -o spending.png
+python bac_analyze.py *.json --categories my_categories.json
+```
 
 ## Architecture
 
-The extraction pipeline:
+### bac_extract.py
+
+Extraction pipeline:
 1. Validates PDF is a BAC statement (`is_bac_statement`)
 2. Iterates pages line-by-line, detecting section boundaries via `SECTIONS` dict patterns
 3. Parses transactions matching `TRANSACTION_PATTERN` regex
@@ -41,7 +44,10 @@ Key data structures:
 - `SECTIONS`: Maps section IDs (B/D/E) to start/end regex patterns and output keys
 - `SPANISH_MONTHS`: Spanish month abbreviations for date parsing
 
-Key parsing functions:
-- `parse_spanish_date`: Converts "15-ENE-25" to "2025-01-15"
-- `parse_amount`: Handles "1,234.56" and trailing negatives "100.00-"
-- `matches_patterns`: Generic regex pattern matcher for section detection
+### bac_analyze.py
+
+Analysis pipeline:
+1. Loads transactions from one or more JSON files (purchases only)
+2. Categorizes by matching description against patterns in `categories.json`
+3. Aggregates by category and month, keeping CRC/USD separate
+4. Outputs text summary and optional graphs (bar/pie/timeline/all)