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Scan bank statements to detect recurring charges, flag suspicious transactions, and draft refund requests with interactive HTML reports.
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 andreolf/refund-radarInspect 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.
Scan bank statements to detect recurring charges, flag suspicious transactions, identify duplicates and fees, draft refund request templates, and generate an interactive HTML audit report.
Ask user for bank/card CSV export or pasted text. Common sources:
Or accept pasted text format:
2026-01-03 Spotify -11.99 USD
2026-01-15 Salary +4500 USD
Run the parser on their data:
python -m refund_radar analyze --csv statement.csv --month 2026-01
Or for pasted text:
python -m refund_radar analyze --stdin --month 2026-01 --default-currency USD
The parser auto-detects:
Tool identifies recurring subscriptions by:
Output shows:
Tool automatically flags:
| Flag Type | Trigger | Severity |
|---|---|---|
| Duplicate | Same merchant + amount within 2 days | HIGH |
| Amount Spike | > 1.8x baseline, delta > $25 | HIGH |
| New Merchant | First time + amount > $30 | MEDIUM |
| Fee-like | Keywords (FEE, ATM, OVERDRAFT) + > $3 | LOW |
| Currency A... |
These signals come from indexed source analysis and may lag behind changes. Check the current source files.
# refund-radar Scan bank statements to detect recurring charges, flag suspicious transactions, identify duplicates and fees, draft refund request templates, and generate an interactive HTML audit report. ## Triggers - "scan my bank statement for refunds" - "analyze my credit card transactions" - "find recurring charges in my statement" - "check for duplicate or suspicious charges" - "help me dispute a charge" - "generate a refund request" - "audit my subscriptions" ## Workflow ### 1. Get Transaction Data Ask user for bank/card CSV export or pasted text. Common sources: - Apple Card: Wallet → Card Balance → Export - Chase: Accounts → Download activity → CSV - Mint: Transactions → Export - Any bank: Download as CSV from transaction history Or accept pasted text format: ``` 2026-01-03 Spotify -11.99 USD 2026-01-15 Salary +4500 USD ``` ### 2. Parse and Normalize Run the parser on their data: ```bash python -m refund_radar analyze --csv statement.csv --month 2026-01 ``` Or for pasted text: ```bash python -m refund_radar analyze --stdin --month 2026-01 --default-currency USD ``` The parser auto-detects: - Delimiter (comma, semicolon, tab) - Date format (YYYY-MM-DD, DD/MM/YYYY, MM/DD/YYYY) - Amount format (single column or debit/credit) - Currency ### 3. Review Recurring Charges Tool identifies recurring subscriptions by: - Same merchant >= 2 times in 90 days - Similar amounts (within 5% or $2) - Consistent cadence (weekly, monthly, yearly) - Known subscription keywords (Netflix, Spotify, etc.) Output shows: - Merchant name - Average amount and cadence - Last charge date - Next expected charge ### 4. Flag Suspicious Charges Tool automatically flags: | Flag Type | Trigger | Severity | |-----------|---------|----------| | Duplicate | Same merchant + amount within 2 days | HIGH | | Amount Spike | > 1.8x baseline, delta > $25 | HIGH | | New Merchant | First time + amount > $30 | MEDIUM | | Fee-like | Keywords (FEE, ATM, OVERDRAFT) + > $3 | LOW | | Currency A...
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