Personal Finance Tracker

A comprehensive expense tracking and budgeting skill that categorizes transactions from CSV bank exports, tracks spending against monthly budgets, and identifies patterns and trends. Supports multi-platform data import from Mint exports, YNAB, bank CSVs, and manual entry with export to Google Sheets, Notion, and Excel for complete financial visibility.

Supported Platforms & Integrations

Platform	Integration Type	Features
Bank CSV Exports	File Import	Parse transaction data from any major bank's CSV export
Mint (Legacy)	CSV Import	Import historical Mint export data for continuity
YNAB	CSV Import/Export	Compatible with YNAB transaction and budget formats
Google Sheets	CSV Export	Monthly budget dashboards with charts and formulas
Notion	Database Export	Transaction databases with category views and summaries
Excel	CSV Export	Pivot-table-ready transaction exports with category tags

When to Use This Skill

• Use this when you have bank CSV exports and want to see where your money is actually going

• Use this when building a monthly budget and need to categorize historical spending first

• Use this when comparing month-over-month spending to identify trends or problem areas

• Use this when Mint has been discontinued and you need an alternative categorization system

• Use this when preparing for tax season and need to categorize deductible expenses

• Use this when you want a simple budget check without subscribing to a paid finance app

• Consider alternatives when you need real-time bank account syncing and automatic transaction pulls

• Consider alternatives when you need investment portfolio management or retirement planning

• Consider alternatives when you need tax preparation software with filing capabilities

Quick Start

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# .claude/skills/personal-finance-tracker.yml
name: Personal Finance Tracker
trigger: "track finances"
context:
  currency: USD
  budget_period: monthly
  categories:
    - Housing: 1800
    - Food: 600
    - Transportation: 400
    - Entertainment: 200
    - Utilities: 250
    - Savings: 500
  csv_format: auto-detect

First Run Example:

User: Here are my transactions this month. Categorize them 
and show me where I stand against budget.
[Pastes or provides CSV file path]

Expected Output:

## March 2026 — Financial Summary

### Budget vs Actual
| Category | Budget | Spent | Remaining | Status |
|----------|--------|-------|-----------|--------|
| Housing | $1,800 | $1,800 | $0 | On Track |
| Food | $600 | $487 | $113 | On Track |
| Transport | $400 | $312 | $88 | On Track |
| Entertainment | $200 | $267 | -$67 | OVER |
| Utilities | $250 | $218 | $32 | On Track |
| Savings | $500 | $500 | $0 | On Track |
| Uncategorized | - | $145 | - | Review |

**Total Income:** $5,200
**Total Spending:** $3,729
**Net:** +$1,471

### Spending Insights
- Entertainment is 34% over budget ($67 over)
  - Top items: Concert tickets ($120), streaming ($45), 
    dining out categorized here ($102)
- Food spending is healthy at 81% of budget
- 3 transactions ($145) need manual categorization

### Uncategorized Transactions (Review)
| Date | Description | Amount |
|------|------------|--------|
| 03/05 | AMZN MKTP US | $67.42 |
| 03/12 | PAYPAL *TRANSFER | $45.00 |
| 03/18 | SQ *COFFEE SHOP | $32.58 |

Assign these to categories? [Food/Shopping/Entertainment]

Advanced Configuration

Platform-Specific Setup:

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# CSV parsing
csv_parsing:
  date_column: "Date"
  description_column: "Description"
  amount_column: "Amount"
  date_format: "MM/DD/YYYY"
  debit_negative: true

# Category rules
categorization:
  auto_rules:
    - pattern: "NETFLIX|HULU|SPOTIFY"
      category: Entertainment
    - pattern: "KROGER|TRADER|WHOLE FOODS"
      category: Food
    - pattern: "SHELL|EXXON|BP"
      category: Transportation
  learn_from_corrections: true

Parameter	Type	Default	Description
currency	string	USD	Currency symbol and format for display
budget_period	string	monthly	monthly, biweekly, weekly
categories	object	{}	Budget categories with allocated amounts
csv_format	string	auto-detect	auto-detect, chase, bofa, wells-fargo, amex, custom
date_format	string	MM/DD/YYYY	Transaction date format in CSV files
auto_categorize	bool	true	Automatically categorize known merchant patterns
merge_accounts	bool	false	Combine transactions from multiple bank accounts
exclude_transfers	bool	true	Exclude internal transfers between your own accounts
savings_goal	int	0	Monthly savings target to track alongside spending
trend_months	int	3	Number of months for spending trend comparison
output_format	string	markdown	markdown, csv, notion-db, google-sheets, ynab

Core Concepts

Concept	Description
Auto-Categorization	Matches transaction descriptions to spending categories using pattern rules
Budget Tracking	Compares actual spending against allocated budgets with remaining balance
Trend Analysis	Identifies month-over-month spending pattern changes and anomalies
Multi-Account Merge	Combines transactions from checking, credit cards, and other accounts
Transfer Exclusion	Filters out internal transfers to prevent double-counting between accounts

+------------------+     +------------------+     +------------------+
|  CSV Import      |---->|  Parser Engine   |---->|  Categorizer     |
|  (bank exports,  |     |  (date, amount,  |     |  (pattern match, |
|   Mint, manual)  |     |   description)   |     |   auto-assign)   |
+------------------+     +------------------+     +------------------+
                                                          |
                                                          v
+------------------+     +------------------+     +------------------+
|  Export Format   |<----|  Trend Analyzer  |<----|  Budget Tracker  |
|  (Sheets, Notion,|     |  (month vs month,|     |  (category totals|
|   CSV, YNAB)     |     |   anomaly detect)|     |   vs allocations)|
+------------------+     +------------------+     +------------------+

Workflow Examples

Scenario 1: Monthly Budget Review

Input: "Process my Chase checking CSV for March. 
Compare against my budget. Flag anything unusual."

Output:
## March 2026 — Chase Checking Analysis

**Processed:** 47 transactions totaling $3,842
**Auto-categorized:** 41 transactions (87%)
**Needs review:** 6 transactions

**Anomaly Detected:**
Grocery spending is 40% higher than February 
($487 vs $348). Top increase: Whole Foods visits 
went from 2 to 5 this month.

**Recommendation:** You are $67 over entertainment 
budget. Consider shifting $70 from transportation 
(which is $88 under) to cover it without guilt.

Scenario 2: Multi-Account Consolidation

Input: "Merge my Chase checking, Amex credit card, 
and Capital One card CSVs for a complete March picture."

Output:
## March 2026 — All Accounts Consolidated

**Chase Checking:** $2,450 spending
**Amex:** $890 spending (rewards card — groceries, gas)
**Capital One:** $502 spending (online shopping, subscriptions)

**Combined by Category:**
Food: $612 (Amex $340 + Chase $272)
Shopping: $445 (Capital One $380 + Amex $65)
[Complete unified view across all accounts]

**Transfers Excluded:** $1,200 (credit card payments 
from checking — not double-counted)

Scenario 3: Tax Preparation Expense Tracking

Input: "I'm self-employed. Categorize my 2025 expenses 
for Schedule C. Flag deductible expenses."

Output:
## 2025 Schedule C Expense Summary

**Deductible Categories:**
| Category | Total | Notes |
|----------|-------|-------|
| Home Office | $3,600 | 300 sq ft of 1500 ($300/mo) |
| Software/Tools | $1,840 | Adobe, GitHub, hosting |
| Professional Dev | $890 | Courses, conferences |
| Internet (50%) | $720 | Business portion deductible |
| Supplies | $456 | Equipment under $2,500 |

**Total Deductions:** $7,506
**Estimated Tax Savings:** $1,876 (at 25% bracket)

Note: Consult a tax professional to verify deduction 
eligibility. This is categorization, not tax advice.

Best Practices

• Download bank CSVs on the first of each month. Consistency makes trend analysis meaningful. Set a calendar reminder to export all account CSVs monthly. The skill builds better pattern recognition with consistent data.

• Correct miscategorized transactions to train the system. When you reassign a transaction from the wrong category, the auto-categorization rules learn from your corrections. After two to three months, accuracy reaches 95% or higher.

• Set budgets based on actual spending, not aspirational goals. Track two months of real spending before setting budget targets. Setting a $200 food budget when you actually spend $600 creates frustration rather than useful financial insight.

• Review uncategorized transactions weekly rather than monthly. Six uncategorized transactions are easy to remember and assign. Forty at month-end become a chore that gets skipped. Quick weekly reviews keep data clean.

• Separate fixed and variable expenses in your analysis. Rent, insurance, and subscriptions are fixed costs you cannot easily change. Focus your budget optimization energy on variable categories like food, entertainment, and shopping.

Common Issues

• CSV column names do not match expected format. Set csv_format to your specific bank, or use the custom configuration to map column names manually. Every bank uses different headers, and auto-detect handles most but not all.

• Internal transfers inflate spending totals. Enable exclude_transfers: true and ensure the skill can identify your own accounts. Credit card payments from checking should not appear as spending since they represent money already counted.

• Categories do not match my personal budget structure. Fully customize the categories object in configuration. The default categories are starting points. Your budget structure should reflect how you actually think about your money.

Privacy & Data Handling

• Local Processing: All financial data is processed locally in your Claude Code session. Transaction details, account information, and spending patterns are never transmitted to external servers or financial services.
• Data Retention: Processed transactions and reports exist only in your current session and exported files. No financial data persists between sessions unless you save files to your local filesystem.
• Export Options: Export as CSV spreadsheets, Notion databases, YNAB-compatible files, or Markdown reports. All files are written to your local storage with no cloud upload.
• No Account Access: The skill never connects to bank accounts, credit cards, or financial institutions directly. You provide CSV exports manually, maintaining full control over what financial data is shared with the tool.