Agent skill
mail-expenses
Extract financial transactions, expenses, receipts, payments, and invoices from email. Summarize spending with amounts, merchants, and categories. Use when user asks about expenses, spending, receipts, payments, or financial transactions from email. Arguments: time range like "last 24 hours", "this month", "last week", or a specific date range.
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/mail-expenses
Metadata
Additional technical details for this skill
- openclaw
-
{ "requires": { "bins": [ "sqlite3", "python3" ] } }
SKILL.md
Mail Expenses — Financial Transaction Summary
Period: $ARGUMENTS (default: last 24 hours)
Step 1: Find financial emails
Use SQLite date functions — never compute Unix epochs manually (wrong year risk).
DB="$HOME/Library/Mail/V10/MailData/Envelope Index"
# Date range from $ARGUMENTS. Use SQLite date expressions directly:
# "yesterday" → dt >= date('now','-1 day','localtime') AND dt < date('now','localtime')
# "today" → dt >= date('now','localtime')
# "last 7 days" → dt >= date('now','-7 days','localtime')
# "this month" → dt >= date('now','start of month','localtime')
# Always print the range before querying so the period is visible in output.
sqlite3 "$DB" "
SELECT datetime(m.date_received,'unixepoch','localtime') as dt,
s.subject, a.address as sender, mb.url, m.ROWID
FROM messages m
JOIN subjects s ON m.subject = s.ROWID
JOIN addresses a ON m.sender = a.ROWID
JOIN mailboxes mb ON m.mailbox = mb.ROWID
WHERE datetime(m.date_received,'unixepoch','localtime') >= date('now','-1 day','localtime')
AND datetime(m.date_received,'unixepoch','localtime') < date('now','localtime')
AND m.deleted = 0
AND mb.url NOT LIKE '%Spam%' AND mb.url NOT LIKE '%Trash%'
AND mb.url NOT LIKE '%Sent%'
AND (
s.subject LIKE '%receipt%'
OR s.subject LIKE '%invoice%'
OR s.subject LIKE '%payment%'
OR s.subject LIKE '%order%'
OR s.subject LIKE '%purchase%'
OR s.subject LIKE '%charge%'
OR s.subject LIKE '%transaction%'
OR s.subject LIKE '%billing%'
OR s.subject LIKE '%renewal%'
OR s.subject LIKE '%subscription%'
OR s.subject LIKE '%paid%'
OR s.subject LIKE '%refund%'
OR s.subject LIKE '%transfer%'
OR s.subject LIKE '%successful%'
OR s.subject LIKE '%confirmation%'
-- Indonesian / multilingual
OR s.subject LIKE '%bukti%'
OR s.subject LIKE '%pembayaran%'
OR s.subject LIKE '%tagihan%'
OR s.subject LIKE '%transaksi%'
OR s.subject LIKE '%berhasil%'
-- Common financial senders
OR a.address LIKE '%bank%'
OR a.address LIKE '%paypal%'
OR a.address LIKE '%stripe%'
OR a.address LIKE '%xendit%'
OR a.address LIKE '%livin%'
OR a.address LIKE '%gopay%'
OR a.address LIKE '%ovo%'
OR a.address LIKE '%dana%'
OR a.address LIKE '%apple%'
OR a.address LIKE '%google%'
OR a.address LIKE '%amazon%'
OR a.address LIKE '%shopee%'
OR a.address LIKE '%tokopedia%'
OR a.address LIKE '%grab%'
)
ORDER BY m.date_received DESC;" 2>/dev/null
Step 2: Parse amounts from email bodies
python3 ~/.claude/skills/_mail-shared/parser.py <ROWID1> <ROWID2> ...
Step 3: Extract amounts with Python regex
From each parsed body, extract monetary amounts:
import re
patterns = [
r'(?:Rp|IDR)\s*[\d.,]+', # Indonesian Rupiah
r'(?:USD|US\$|\$)\s*[\d.,]+', # USD
r'(?:SGD|S\$)\s*[\d.,]+', # Singapore dollar
r'Total[:\s]+(?:Rp|IDR|USD|\$|€|£)[\d.,]+',
r'Amount[:\s]+(?:Rp|IDR|USD|\$|€|£)[\d.,]+',
r'(?:€|£|¥|₹|RM|THB|PHP|VND)\s*[\d.,]+',
]
Step 4: Categorize transactions
- Transfers (bank to bank, BI-Fast, QRIS, virtual account)
- Bills/Subscriptions (recurring charges, renewals)
- Shopping (e-commerce, marketplace)
- Food/Lifestyle (restaurants, delivery, groceries)
- Travel (flights, hotels, transport)
- Refunds (money coming back)
- Credit Card Payments (paying off balances — not new spending)
Output Format
Financial Activity — [PERIOD]
Line-by-line per account (no markdown tables — WhatsApp/Telegram render them as raw text):
💳 [Bank/Wallet Name]
HH:MM · [Merchant] · Rp X.XXX
Subtotals by category. Total: Rp X.XXX
Note refunds separately. Flag duplicates and unusually large transactions proactively.
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