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Expense Tracker

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@aholake

npx machina-cli add skill @aholake/expense-tracker --openclaw
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SKILL.md
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Expense Tracker

Log and track daily expenses in markdown files organized by month.

Quick Start

Log an expense

python3 scripts/log_expense.py log <amount> <category> [--description "text"] [--tags "tag1,tag2"] [--date YYYY-MM-DD]

Examples:

# Simple expense
python3 scripts/log_expense.py log 45000 Coffee

# With description
python3 scripts/log_expense.py log 250000 Dining --description "Lunch with team"

# With tags
python3 scripts/log_expense.py log 500000 Shopping --tags "clothes,sale" --description "New shirt"

# Specify date (for backdating)
python3 scripts/log_expense.py log 1200000 Vehicle --description "Gas" --date 2026-02-15

View monthly summary

# Current month
python3 scripts/log_expense.py summary

# Specific month
python3 scripts/log_expense.py summary 2026-02

# JSON output (for parsing)
python3 scripts/log_expense.py summary 2026-02 --json

File Organization

Expenses are stored in expenses/ directory at workspace root:

expenses/
├── 2026-01.md
├── 2026-02.md
└── 2026-03.md

Each file contains a markdown table:

# Expenses - 2026-02

| Date | Category | Amount (VND) | Description | Tags |
|------|----------|-------------|-------------|------|
| 2026-02-17 | Coffee | 45,000 | | |
| 2026-02-17 | Dining | 250,000 | Lunch with team | |
| 2026-02-17 | Shopping | 500,000 | New shirt | clothes,sale |

Categories

See references/categories.md for common expense categories. Use existing categories or create custom ones as needed.

Common categories:

  • Housing - Rent, utilities, home expenses
  • Vehicle - Gas, maintenance, parking
  • Dining - Restaurants, food delivery
  • Coffee - Cafes, coffee shops
  • Shopping - Clothes, electronics, general purchases
  • Entertainment - Movies, games, hobbies
  • Healthcare - Medicine, doctor visits
  • Subscriptions - Netflix, Spotify, gym, apps
  • Savings - Investments, emergency fund
  • Debt Payment - Loans, credit cards
  • Miscellaneous - Other expenses

Workflow Examples

Log daily expenses from conversation

When the user mentions spending money:

# User: "Just paid 35k for coffee"
python3 scripts/log_expense.py log 35000 Coffee

# User: "Grabbed lunch for 120k at Phở 24"
python3 scripts/log_expense.py log 120000 Dining --description "Phở 24"

# User: "Filled up gas, 400k"
python3 scripts/log_expense.py log 400000 Vehicle --description "Gas"

Monthly review

# Get summary
python3 scripts/log_expense.py summary 2026-02

# Read the expense file to see details
cat expenses/2026-02.md

Analyze spending patterns

# Get JSON for analysis
python3 scripts/log_expense.py summary 2026-02 --json

# Compare multiple months
python3 scripts/log_expense.py summary 2026-01 --json > jan.json
python3 scripts/log_expense.py summary 2026-02 --json > feb.json

Tips

  • Batch logging: User can tell you multiple expenses at once, log them all
  • Category consistency: Use the same category names to enable accurate summaries
  • Tags for filtering: Use tags for subcategories (e.g., "work", "weekend", "urgent")
  • Descriptions: Add context that helps identify the expense later
  • Regular reviews: Suggest monthly summaries to track spending patterns

Integration with Financial Goals

When tracking expenses, consider:

  1. Budget tracking: Compare monthly totals to target budget
  2. Spending patterns: Identify high-spend categories
  3. Emergency fund: Track savings progress
  4. Debt reduction: Monitor debt payment progress
  5. Financial ratios: Calculate expenses as % of income

Script Reference

log_expense.py

Commands:

  • log - Add an expense entry
  • summary - View monthly summary

Arguments (log):

  • amount - Amount in VND (required)
  • category - Category name (required)
  • --description/-d - Optional description
  • --tags/-t - Optional comma-separated tags
  • --date - Optional date (YYYY-MM-DD, defaults to today)
  • --workspace - Optional workspace path (defaults to ~/.openclaw/workspace)

Arguments (summary):

  • year_month - Optional YYYY-MM (defaults to current month)
  • --json - Output as JSON
  • --workspace - Optional workspace path

Output:

  • Creates/updates markdown files in expenses/ directory
  • Prints confirmation with file location
  • Summary shows total, count, and breakdown by category

Source

git clone https://clawhub.ai/aholake/expense-trackerView on GitHub

Overview

Expense Tracker records daily spending into monthly markdown files under the expenses/ directory. It supports categories, tags, and optional descriptions, and can generate monthly summaries, including JSON output for analysis. This helps you log spending, review totals, and uncover patterns for personal finance management.

How This Skill Works

Use a Python CLI (log_expense.py) to append expenses to expenses/YYYY-MM.md. Each entry is stored in a Markdown table with Date, Category, Amount (VND), Description, and Tags; summaries are produced with the summary command, with an option to emit JSON (--json) for data-driven insights.

When to Use It

  • When you want to log a new purchase quickly via the CLI.
  • When you need a monthly spend summary for budgeting.
  • When you want to backdate an expense to reflect past purchases.
  • When filtering or comparing expenses by category or tag.
  • When exporting data for analytical workflows or reporting (JSON).

Quick Start

  1. Step 1: Log an expense with python3 scripts/log_expense.py log <amount> <category> --description text --tags tag1,tag2 --date YYYY-MM-DD
  2. Step 2: Review a summary with python3 scripts/log_expense.py summary [YYYY-MM] [--json]
  3. Step 3: Open expenses/YYYY-MM.md to see the monthly table or export data for tooling

Best Practices

  • Log expenses in batches to minimize context switching.
  • Maintain consistent category names to improve summary accuracy.
  • Include concise descriptions to add context for future reviews.
  • Use tags to filter or sub-categorize expenses (e.g., work, weekend).
  • Review monthly summaries regularly to spot patterns and adjust budgets.

Example Use Cases

  • python3 scripts/log_expense.py log 35000 Coffee
  • python3 scripts/log_expense.py log 120000 Dining --description Lunch with team --tags food,lunch --date 2026-02-17
  • python3 scripts/log_expense.py log 400000 Vehicle --description Gas --date 2026-02-18
  • python3 scripts/log_expense.py summary 2026-02
  • python3 scripts/log_expense.py summary 2026-02 --json

Frequently Asked Questions

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