Watch My Money OpenClaw Skill - ClawHub
Do you want your AI agent to automate Watch My Money workflows? This free skill from ClawHub helps with web & frontend development tasks without building custom tools from scratch.
What this skill does
Analyze bank transactions, categorize spending, track monthly budgets, detect overspending and anomalies. Outputs interactive HTML report.
Install
npx clawhub@latest install watch-my-moneyFull SKILL.md
Open original| name | description |
|---|---|
| watch-my-money | Analyze bank transactions, categorize spending, track monthly budgets, detect overspending and anomalies. Outputs interactive HTML report. |
watch-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/:
state.json- budgets, merchant overrides, historyreports/YYYY-MM.json- machine-readable monthly datareports/YYYY-MM.html- interactive report
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/.