Skills watch-my-money
Analyze bank transactions, categorize spending, track monthly budgets, detect overspending and anomalies. Outputs interactive HTML report.
git clone https://github.com/openclaw/skills
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/andreolf/watch-my-money" ~/.claude/skills/clawdbot-skills-watch-my-money && rm -rf "$T"
skills/andreolf/watch-my-money/SKILL.mdwatch-my-money
Analyze transactions, categorize spending, track budgets, flag overspending.
Workflow
1. Get Transactions
Ask user for bank/card CSV export OR pasted text.
Common sources:
- Download CSV from your bank's online portal
- Export from budgeting apps
- Copy/paste transactions from statements
Supported formats:
- Any CSV with date, description, amount columns
- Pasted text: "2026-01-03 Starbucks -5.40 CHF"
2. Parse & Normalize
Read input, normalize to standard format:
- Auto-detect delimiter (comma, semicolon, tab)
- Parse dates (YYYY-MM-DD, DD/MM/YYYY, MM/DD/YYYY)
- Normalize amounts (expenses negative, income positive)
- Extract merchant from description
- Detect recurring transactions (subscriptions)
3. Categorize Transactions
For each transaction, assign category:
Categories:
- rent, utilities, subscriptions, groceries, eating_out
- transport, travel, shopping, health
- income, transfers, other
Categorization order:
- Check saved merchant overrides
- Apply deterministic keyword rules (see common-merchants.md)
- Pattern matching (subscriptions, utilities)
- Heuristic fallback
For ambiguous merchants (batch of 5-10), ask user to confirm. Save overrides for future runs.
4. Check Budgets
Compare spending against user-defined budgets.
Alert thresholds:
- 80% - approaching limit (yellow)
- 100% - at limit (red)
- 120% - over budget (red, urgent)
See budget-templates.md for suggested budgets.
5. Detect Anomalies
Flag unusual spending:
- Category spike: spend > 1.5x baseline AND delta > 50
- Subscription growth: subscriptions up > 20%
- New expensive merchant: first appearance AND spend > 30
- Potential subscriptions: recurring same-amount charges
Baseline = previous 3 months average (or current month if no history).
6. Generate HTML Report
Create local HTML file with:
- Month summary (income, expenses, net)
- Category breakdown with budget status
- Top merchants
- Alerts section
- Recurring transactions detected
- Privacy toggle (blur amounts/merchants)
Copy template.html and inject data.
7. Save State
Persist to
~/.watch_my_money/:
- budgets, merchant overrides, historystate.json
- machine-readable monthly datareports/YYYY-MM.json
- interactive reportreports/YYYY-MM.html
CLI Commands
# Analyze CSV python -m watch_my_money analyze --csv path/to/file.csv --month 2026-01 # Analyze from stdin cat transactions.txt | python -m watch_my_money analyze --stdin --month 2026-01 --default-currency CHF # Compare months python -m watch_my_money compare --months 2026-01 2025-12 # Set budget python -m watch_my_money set-budget --category groceries --amount 500 --currency CHF # View budgets python -m watch_my_money budgets # Export month data python -m watch_my_money export --month 2026-01 --out summary.json # Reset all state python -m watch_my_money reset-state
Output Structure
Console shows:
- Month summary with income/expenses/net
- Category table with spend vs budget
- Recurring transactions detected
- Top 5 merchants
- Alerts as bullet points
Files written:
~/.watch_my_money/state.json~/.watch_my_money/reports/2026-01.json~/.watch_my_money/reports/2026-01.html
HTML Report Features
- Collapsible category sections
- Budget progress bars
- Recurring transaction list
- Month-over-month comparison
- Privacy toggle (blur sensitive data)
- Dark mode (respects system preference)
- Floating action button
- Screenshot-friendly layout
- Auto-hide empty sections
Privacy
All data stays local. No network calls. No external APIs. Transaction data is analyzed locally and stored only in
~/.watch_my_money/.