[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6CKY9A9DZXWD7F5CVM65HM3":3,"skill-same:01M6CKY9A9DZXWD7F5CVM65HM3":115},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":22,"publishedAt":31,"linkOnly":32,"markdownContent":33,"markdownBody":34,"frontMatter":35,"refName":36,"commitSha":37,"skillDirectory":38,"forksCount":39,"repositoryHtmlUrl":40,"repositoryHomepageUrl":6,"ownerHtmlUrl":41,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":42,"install":43,"resources":56},"01M6CKY9A9DZXWD7F5CVM65HM3","refund-radar",null,"Scan bank statements to detect recurring charges, flag suspicious transactions, and draft refund requests with interactive HTML reports.","kbarbel640-del\u002Fskills","kbarbel640-del","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F255315490?v=4","01M6CJPPQGCCESXMG3K7BBGQ5J","01M6CJPPX2PB2BCZERFVM2C2B3",1,"MIT","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fandreolf\u002Frefund-radar\u002FSKILL.md",[17],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000009","前端开发","SCENARIO","使用场景",[23,24,25,26,27,28,29,30],"refund radar","suspicious","transactions","interactive","recurring","html","reports","scan","2026-11-10 10:12:30",false,"---\nname: refund-radar\ndescription: Scan bank statements to detect recurring charges, flag suspicious transactions, and draft refund requests with interactive HTML reports.\n---\n\n# refund-radar\n\nScan bank statements to detect recurring charges, flag suspicious transactions, identify duplicates and fees, draft refund request templates, and generate an interactive HTML audit report.\n\n## Triggers\n\n- \"scan my bank statement for refunds\"\n- \"analyze my credit card transactions\"\n- \"find recurring charges in my statement\"\n- \"check for duplicate or suspicious charges\"\n- \"help me dispute a charge\"\n- \"generate a refund request\"\n- \"audit my subscriptions\"\n\n## Workflow\n\n### 1. Get Transaction Data\n\nAsk user for bank\u002Fcard CSV export or pasted text. Common sources:\n\n- Apple Card: Wallet → Card Balance → Export\n- Chase: Accounts → Download activity → CSV\n- Mint: Transactions → Export\n- Any bank: Download as CSV from transaction history\n\nOr accept pasted text format:\n```\n2026-01-03 Spotify -11.99 USD\n2026-01-15 Salary +4500 USD\n```\n\n### 2. Parse and Normalize\n\nRun the parser on their data:\n\n```bash\npython -m refund_radar analyze --csv statement.csv --month 2026-01\n```\n\nOr for pasted text:\n```bash\npython -m refund_radar analyze --stdin --month 2026-01 --default-currency USD\n```\n\nThe parser auto-detects:\n- Delimiter (comma, semicolon, tab)\n- Date format (YYYY-MM-DD, DD\u002FMM\u002FYYYY, MM\u002FDD\u002FYYYY)\n- Amount format (single column or debit\u002Fcredit)\n- Currency\n\n### 3. Review Recurring Charges\n\nTool identifies recurring subscriptions by:\n- Same merchant >= 2 times in 90 days\n- Similar amounts (within 5% or $2)\n- Consistent cadence (weekly, monthly, yearly)\n- Known subscription keywords (Netflix, Spotify, etc.)\n\nOutput shows:\n- Merchant name\n- Average amount and cadence\n- Last charge date\n- Next expected charge\n\n### 4. Flag Suspicious Charges\n\nTool automatically flags:\n\n| Flag Type | Trigger | Severity |\n|-----------|---------|----------|\n| Duplicate | Same merchant + amount within 2 days | HIGH |\n| Amount Spike | > 1.8x baseline, delta > $25 | HIGH |\n| New Merchant | First time + amount > $30 | MEDIUM |\n| Fee-like | Keywords (FEE, ATM, OVERDRAFT) + > $3 | LOW |\n| Currency Anomaly | Unusual currency or DCC | LOW |\n\n### 5. Clarify with User\n\nFor flagged items, ask in batches of 5-10:\n\n- Is this charge legitimate?\n- Should I mark this merchant as expected?\n- Do you want a refund template for this?\n\nUpdate state based on answers:\n```bash\npython -m refund_radar mark-expected --merchant \"Costco\"\npython -m refund_radar mark-recurring --merchant \"Netflix\"\n```\n\n### 6. Generate HTML Report\n\nReport saved to `~\u002F.refund_radar\u002Freports\u002FYYYY-MM.html`\n\nCopy [template.html](assets\u002Ftemplate.html) structure. Sections:\n- **Summary**: Transaction count, total spent, recurring count, flagged count\n- **Recurring Charges**: Table with merchant, amount, cadence, next expected\n- **Unexpected Charges**: Flagged items with severity and reason\n- **Duplicates**: Same-day duplicate charges\n- **Fee-like Charges**: ATM fees, FX fees, service charges\n- **Refund Templates**: Ready-to-copy email\u002Fchat\u002Fdispute messages\n\nFeatures:\n- Privacy toggle (blur merchant names)\n- Dark\u002Flight mode\n- Collapsible sections\n- Copy buttons on templates\n- Auto-hide empty sections\n\n### 7. Draft Refund Requests\n\nFor each flagged charge, generate three template types:\n- **Email**: Formal refund request\n- **Chat**: Quick message for live support\n- **Dispute**: Bank dispute form text\n\nThree tone variants each:\n- Concise (default)\n- Firm (assertive)\n- Friendly (polite)\n\nTemplates include:\n- Merchant name and date\n- Charge amount\n- Dispute reason based on flag type\n- Placeholders for card last 4, reference number\n\n**Important**: No apostrophes in any generated text.\n\n## CLI Reference\n\n```bash\n# Analyze statement\npython -m refund_radar analyze --csv file.csv --month 2026-01\n\n# Analyze from stdin\npython -m refund_radar analyze --stdin --month 2026-01 --default-currency CHF\n\n# Mark merchant as expected\npython -m refund_radar mark-expected --merchant \"Amazon\"\n\n# Mark merchant as recurring\npython -m refund_radar mark-recurring --merchant \"Netflix\"\n\n# List expected merchants\npython -m refund_radar expected\n\n# Reset learned state\npython -m refund_radar reset-state\n\n# Export month data\npython -m refund_radar export --month 2026-01 --out data.json\n```\n\n## Files Written\n\n| Path | Purpose |\n|------|---------|\n| `~\u002F.refund_radar\u002Fstate.json` | Learned preferences, merchant history |\n| `~\u002F.refund_radar\u002Freports\u002FYYYY-MM.html` | Interactive audit report |\n| `~\u002F.refund_radar\u002Freports\u002FYYYY-MM.json` | Raw analysis data |\n\n## Privacy\n\n- **No network calls.** Everything runs locally.\n- **No external APIs.** No Plaid, no cloud services.\n- **Your data stays on your machine.**\n- **Privacy toggle in reports.** Blur merchant names with one click.\n\n## Requirements\n\n- Python 3.9+\n- No external dependencies\n\n## Repository\n\nhttps:\u002F\u002Fgithub.com\u002Fandreolf\u002Frefund-radar\n","# refund-radar\n\nScan bank statements to detect recurring charges, flag suspicious transactions, identify duplicates and fees, draft refund request templates, and generate an interactive HTML audit report.\n\n## Triggers\n\n- \"scan my bank statement for refunds\"\n- \"analyze my credit card transactions\"\n- \"find recurring charges in my statement\"\n- \"check for duplicate or suspicious charges\"\n- \"help me dispute a charge\"\n- \"generate a refund request\"\n- \"audit my subscriptions\"\n\n## Workflow\n\n### 1. Get Transaction Data\n\nAsk user for bank\u002Fcard CSV export or pasted text. Common sources:\n\n- Apple Card: Wallet → Card Balance → Export\n- Chase: Accounts → Download activity → CSV\n- Mint: Transactions → Export\n- Any bank: Download as CSV from transaction history\n\nOr accept pasted text format:\n```\n2026-01-03 Spotify -11.99 USD\n2026-01-15 Salary +4500 USD\n```\n\n### 2. Parse and Normalize\n\nRun the parser on their data:\n\n```bash\npython -m refund_radar analyze --csv statement.csv --month 2026-01\n```\n\nOr for pasted text:\n```bash\npython -m refund_radar analyze --stdin --month 2026-01 --default-currency USD\n```\n\nThe parser auto-detects:\n- Delimiter (comma, semicolon, tab)\n- Date format (YYYY-MM-DD, DD\u002FMM\u002FYYYY, MM\u002FDD\u002FYYYY)\n- Amount format (single column or debit\u002Fcredit)\n- Currency\n\n### 3. Review Recurring Charges\n\nTool identifies recurring subscriptions by:\n- Same merchant >= 2 times in 90 days\n- Similar amounts (within 5% or $2)\n- Consistent cadence (weekly, monthly, yearly)\n- Known subscription keywords (Netflix, Spotify, etc.)\n\nOutput shows:\n- Merchant name\n- Average amount and cadence\n- Last charge date\n- Next expected charge\n\n### 4. Flag Suspicious Charges\n\nTool automatically flags:\n\n| Flag Type | Trigger | Severity |\n|-----------|---------|----------|\n| Duplicate | Same merchant + amount within 2 days | HIGH |\n| Amount Spike | > 1.8x baseline, delta > $25 | HIGH |\n| New Merchant | First time + amount > $30 | MEDIUM |\n| Fee-like | Keywords (FEE, ATM, OVERDRAFT) + > $3 | LOW |\n| Currency Anomaly | Unusual currency or DCC | LOW |\n\n### 5. Clarify with User\n\nFor flagged items, ask in batches of 5-10:\n\n- Is this charge legitimate?\n- Should I mark this merchant as expected?\n- Do you want a refund template for this?\n\nUpdate state based on answers:\n```bash\npython -m refund_radar mark-expected --merchant \"Costco\"\npython -m refund_radar mark-recurring --merchant \"Netflix\"\n```\n\n### 6. Generate HTML Report\n\nReport saved to `~\u002F.refund_radar\u002Freports\u002FYYYY-MM.html`\n\nCopy [template.html](assets\u002Ftemplate.html) structure. Sections:\n- **Summary**: Transaction count, total spent, recurring count, flagged count\n- **Recurring Charges**: Table with merchant, amount, cadence, next expected\n- **Unexpected Charges**: Flagged items with severity and reason\n- **Duplicates**: Same-day duplicate charges\n- **Fee-like Charges**: ATM fees, FX fees, service charges\n- **Refund Templates**: Ready-to-copy email\u002Fchat\u002Fdispute messages\n\nFeatures:\n- Privacy toggle (blur merchant names)\n- Dark\u002Flight mode\n- Collapsible sections\n- Copy buttons on templates\n- Auto-hide empty sections\n\n### 7. Draft Refund Requests\n\nFor each flagged charge, generate three template types:\n- **Email**: Formal refund request\n- **Chat**: Quick message for live support\n- **Dispute**: Bank dispute form text\n\nThree tone variants each:\n- Concise (default)\n- Firm (assertive)\n- Friendly (polite)\n\nTemplates include:\n- Merchant name and date\n- Charge amount\n- Dispute reason based on flag type\n- Placeholders for card last 4, reference number\n\n**Important**: No apostrophes in any generated text.\n\n## CLI Reference\n\n```bash\n# Analyze statement\npython -m refund_radar analyze --csv file.csv --month 2026-01\n\n# Analyze from stdin\npython -m refund_radar analyze --stdin --month 2026-01 --default-currency CHF\n\n# Mark merchant as expected\npython -m refund_radar mark-expected --merchant \"Amazon\"\n\n# Mark merchant as recurring\npython -m refund_radar mark-recurring --merchant \"Netflix\"\n\n# List expected merchants\npython -m refund_radar expected\n\n# Reset learned state\npython -m refund_radar reset-state\n\n# Export month data\npython -m refund_radar export --month 2026-01 --out data.json\n```\n\n## Files Written\n\n| Path | Purpose |\n|------|---------|\n| `~\u002F.refund_radar\u002Fstate.json` | Learned preferences, merchant history |\n| `~\u002F.refund_radar\u002Freports\u002FYYYY-MM.html` | Interactive audit report |\n| `~\u002F.refund_radar\u002Freports\u002FYYYY-MM.json` | Raw analysis data |\n\n## Privacy\n\n- **No network calls.** Everything runs locally.\n- **No external APIs.** No Plaid, no cloud services.\n- **Your data stays on your machine.**\n- **Privacy toggle in reports.** Blur merchant names with one click.\n\n## Requirements\n\n- Python 3.9+\n- No external dependencies\n\n## 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Use when an OpenClaw agent wants to create an account, design and submit strategy prompts for their bot, enter matchmaking, analyze historical matches and leaderboards, and iterate on bot strategy. Requires headless browser automation (no API available yet).","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzyori\u002Fdilemm-ai\u002FSKILL.md",[153],{"categoryNo":154,"categoryName":155,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发",[157,130,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,135,173],"dilemm ai","arena","analyze","browser","openclaw agent","create","automation","browser automation","bot","openclaw","design","strategy","headless","compete","submit","matchmaking","use",{"skillNo":175,"name":176,"nameZh":6,"description":177,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":178,"categories":179,"keywords":183,"publishedAt":31},"01M6G8HWAF3K9SW7NP3Z83CPJ6","arxiv-paper-reviews","Interact with arXiv Crawler API to fetch papers, read reviews, and submit comments. 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