ledgr-savings-analysis

name	ledgr:savings-analysis
description	Calculate savings rate, identify top discretionary spending, and model what-if scenarios
version	1.0.0
tools	["get_income_vs_expense","get_spending_report","show_financial_dashboard"]

Savings Analysis

When to use

Use when the user asks about savings, savings rate, how to save more, or wants spending reduction scenarios. Trigger phrases: "savings rate", "how much am I saving", "how to save more", "what if I cut spending".

Steps

1. Get income vs expense history. Call get_income_vs_expense with the last 3 months:

   • dateFrom: 3 months ago, first day (YYYY-MM-01)
   • dateTo: today (YYYY-MM-DD)

2. Calculate savings rate for each month:

   • Savings = income - expenses (both in cents)
   • Rate = savings / income * 100
   • Average across the 3 months

3. Get current month's spending breakdown. Call get_spending_report for the current month.

4. Identify top discretionary categories. Discretionary = categories NOT in these groups: "Housing", "Utilities", "Insurance", "Debt Payments". Sort remaining by total descending.

5. Model what-if scenarios. For the top 3 discretionary categories:

   • "If you cut [category] by 20%: save [amountDisplay]/month, [annualDisplay]/year"
   • "If you cut [category] by 50%: save [amountDisplay]/month, [annualDisplay]/year"

6. Show the visual. Call show_financial_dashboard with view: "net-worth-trend" to show the income vs expense trend.

7. Present the summary. Structure:

   • Savings rate: [X%] average over 3 months (trending [up/down])
   • Monthly savings: [amountDisplay] average
   • Top 3 discretionary spending categories
   • What-if scenarios
   • Benchmark context: "A common target is saving 20% of income"

Important

• Always use amountDisplay fields for presenting money to the user.
• Do not store or cache any financial data beyond this conversation.
• The discretionary vs non-discretionary classification is approximate. Don't be dogmatic about it.