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refund-radar

Scan bank statements to detect recurring charges, flag suspicious transactions, and draft refund requests with interactive HTML reports.

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Status

ACTIVE

Visibility

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安装方式

直接复制以下提示词,发送给你的 AI 助手即可完成安装。

请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 refund-radar 技能。 若已安装,则直接安装 refund-radar 技能。

Overview

Skill Key
andreolf/refund-radar
Author
andreolf
Source Repo
openclaw/skills
Version
-
Source Path
skills/andreolf/refund-radar
Latest Commit SHA
2685dbdb87e34ef3e8443354d96cdf875af5958f

Extracted Content

SKILL.md excerpt

# 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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