bambu-studio-ai
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Scan bank statements to detect recurring charges, flag suspicious transactions, and draft refund requests with interactive HTML reports.
Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.
SkillHub CLI
skillhub install andreolf/refund-radarExaminez la source et la compatibilité, puis suivez les étapes d’installation.
Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.
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... |
Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.
# 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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