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📈 Analytics

View statistics, spending breakdowns, top expenses, and financial summaries.

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get_statistics

Safe

Get spending and income statistics for a period. Shows totals, averages, and trends.

Parameters

Parameter Type Description
period? string today, week, month (default), year, or custom range
start_date? string Start date for custom range
end_date? string End date for custom range

Examples

User "How much did I spend this month?"
AI Statistics for January 2026:
• Expenses: $45,000
• Income: $80,000
• Balance: +$35,000
• Average daily expense: $2,250
User "Weekly statistics"
User "How much did I earn last year?"

get_spending_by_category

Safe

Get spending breakdown by category with percentages. Shows where your money goes.

Parameters

Parameter Type Description
period? string Time period. Default: month
limit? number Top N categories. Default: 10

Examples

User "What do I spend the most on?"
AI Spending by category (January):
1. Food: $15,000 (33%) ████████░░
2. Transport: $8,000 (18%) ████░░░░░░
3. Entertainment: $6,000 (13%) ███░░░░░░░
4. Subscriptions: $3,500 (8%) ██░░░░░░░░
5. Other: $12,500 (28%) ██████░░░░
User "Spending breakdown for the year"

get_top_expenses

Safe

Get the largest individual expenses for a period. Helps identify big spending.

Parameters

Parameter Type Description
period? string Time period. Default: month
limit? number Top N expenses. Default: 5

Examples

User "Top expenses for the month"
AI Top 5 expenses in January:
1. Rent: $50,000 (01/01)
2. iPhone Case: $3,500 (01/15)
3. Restaurant: $3,200 (01/12)
4. Groceries: $2,800 (01/08)
5. Taxi: $2,500 (01/18)
User "Biggest expenses this week"

compare_periods

Safe

Compare spending between two periods. Shows increase/decrease and percentage change.

Parameters

Parameter Type Description
period1? string First period (default: current month)
period2? string Second period (default: previous month)
category? string Compare specific category

Examples

User "Compare expenses with last month"
AI Comparison: January vs December

Expenses: $45,000 vs $52,000 (−13%)
Income: $80,000 vs $80,000 (0%)

By category:
• Food: +$2,000 (+15%)
• Transport: −$1,500 (−16%)
• Entertainment: −$7,500 (−56%)
User "Food expenses: this month vs last"

get_financial_summary

Safe

Get a complete financial overview: balances, debts, goals, budgets, and upcoming payments.

Examples

User "Financial summary"
AI Financial summary:

💰 Balance: $75,000
📊 Budgets: 3 active (2 on track, 1 exceeded)
🎯 Goals: 45% to Vacation, 30% to Car
🤝 Debts: owed to you $3,000, you owe $5,000
🔄 Next payments: Netflix (01/15), Gym (02/01)

This month: +$35,000 (income − expenses)
User "How are my finances doing?"

get_net_worth

Safe

Calculate your net worth: total assets minus liabilities. Includes all wallets, goals savings, and debts.

Parameters

Parameter Type Description
currency? string Convert all to this currency

Examples

User "My net worth"
AI Net worth: $123,000

Assets:
• Wallets: $75,000
• Goals (saved): $55,000
• Owed to you: $3,000
Total assets: $133,000

Liabilities:
• You owe: $10,000
Total liabilities: $10,000
User "Net worth in euros"

🔍 Data Quality

Find and fix data issues: uncategorized transactions, duplicates, and anomalies.

find_uncategorized

Safe

Find transactions without a category. Returns suggestions for bulk categorization or creating automation rules.

Parameters

Parameter Type Description
limit? number Max transactions to return. Default: 50

Examples

User "Find uncategorized transactions"
AI Found 15 uncategorized transactions (12% of total):

• Uber Eats - $1,200 (3 times)
• Yandex Go - $500 (5 times)
• ...

Suggestions:
1. Bulk assign category
2. Create rule "Uber Eats → Delivery"

find_duplicates

Safe

Find potential duplicate transactions based on amount, wallet, time proximity, and description similarity.

💡
Detection Criteria
  • Same amount and wallet
  • Within 5 minutes of each other
  • Similar description (>80% match)

Parameters

Parameter Type Description
days? number Days to analyze. Default: 30

Examples

User "Find duplicates"
AI Found 2 possible duplicates:

1. "Coffee" $2.50 (01/15 10:05 and 10:07) - 95% confidence
2. "Groceries" $15.00 (01/18 14:30 and 14:31) - 90% confidence

Delete duplicates?

detect_anomalies

Safe

Find unusual transactions that deviate significantly from your typical spending patterns. Uses statistical analysis (>2 standard deviations from mean).

Parameters

Parameter Type Description
category? string Analyze specific category only
months? number Months for baseline calculation. Default: 3

Examples

User "Find suspicious transactions"
AI Found 3 anomalous transactions:

1. "Restaurant" - $85.00 (usually ~$12.00, 7x average)
2. "Taxi" - $32.00 (usually ~$4.00, 8x average)
3. "Groceries" - $120.00 (usually ~$30.00, 4x average)

These may be errors or special cases.
User "Anomalies in Transportation category"

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