aetherlang-strategy
Nobel-level strategic business intelligence with game theory, Monte Carlo simulations, market analysis, and implementation roadmaps.
Track daily expenses in structured markdown files organized by month. Use when the user wants to log spending, view expense summaries, analyze spending patterns, or manage personal finance tracking. Supports categories, tags, and monthly summaries.
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
SkillHub CLI
skillhub install aholake/expense-trackerInspect the source and compatibility requirements, then follow its installation steps.
Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.
Log and track daily expenses in markdown files organized by month.
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
# 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
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 |
See references/categories.md for common expense categories. Use existing categories or create custom ones as needed.
Common categories:
These signals come from indexed source analysis and may lag behind changes. Check the current source files.
# Expense Tracker Log and track daily expenses in markdown files organized by month. ## Quick Start ### Log an expense ```bash python3 scripts/log_expense.py log <amount> <category> [--description "text"] [--tags "tag1,tag2"] [--date YYYY-MM-DD] ``` Examples: ```bash # 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 ```bash # 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: ```markdown # 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,...
Nobel-level strategic business intelligence with game theory, Monte Carlo simulations, market analysis, and implementation roadmaps.
AI content from TrueSlazac Twitter account. Use when accessing AI-related prompts, templates, or discussions from social media sources.
AI content from TrueSlazac Twitter account. Use when accessing AI-related prompts, templates, or discussions from social media sources.
AI content from TrueSlazac Twitter account. Use when accessing AI-related prompts, templates, or discussions from social media sources.