Testing patterns for PHPUnit and Playwright E2E tests. Use when writing tests, debugging test failures, setting up test coverage, or implementing test patterns for ActivityPub features.
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Extract and analyze data from invoices, receipts, bank statements, and financial documents. Categorize expenses, track recurring charges, and generate expense reports. Use when user provides financial PDFs or images.
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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Extract structured data from financial documents with automatic categorization and analysis.
Activate when the user:
Identify Document Type
Extract Core Information
For Invoices:
For Receipts:
For Bank/Credit Card Statements:
Categorize Expenses
Identify Patterns
Generate Structured Output
# Financial Document Analysis
## Document Details
- **Type**: Invoice / Receipt / Statement
- **Date**: [Date]
- **Vendor/Merchant**: [Name]
- **Document Number**: [Number]
- **Total Amount**: $X,XXX.XX
## Line Items
| Description | Quantity | Unit Price | Total |
|-------------|----------|------------|-------|
| [Item] | X | $XX.XX | $XX.XX |
## Financial Summary
- **Subtotal**: $X,XXX.XX
- **Tax**: $XXX.XX
- **Total**: $X,XXX.XX
- **Payment Method**: [Method]
## Expense Categorization
| Category | Amount | Items |
|----------|--------|-------|
| Software | $XXX | Slack, GitHub |
| Office | $XX | Supplies |
## Insights
- ✓ Tax-deductible business expenses: $X,XXX
- ⚠ Recurring charges detected: 3 subscriptions ($XXX/month)
- ℹ Foreign transaction fees: $XX
## Flagged Items
- [ ] Large expense ($X,XXX) - verify approval
- [ ] Duplicate charge detected on [date]
## Export Data (CSV Format)
```csv
Date,Vendor,Description,Category,Amount,Tax Deductible
2025-01-15,Adobe,Creative Cloud,Software,52.99,Yes
## Examples
**User**: "Extract data from this invoice PDF"
**Response**: Parse PDF → Extract vendor info, line items, totals → Categorize as business expense → Format as structured data → Generate CSV export
**User**: "Analyze my bank statement and categorize expenses"
**Response**: Extract all transactions → Categorize each (dining, software, travel) → Identify recurring charges → Calculate totals by category → Flag unusual transactions → Generate spending report
**User**: "Parse these 10 receipts and create an expense report"
**Response**: Process each receipt → Extract merchant, date, amount, items → Categorize expenses → Calculate totals → Generate consolidated report → Create CSV for expense submission
## Best Practices
- Preserve exact amounts (don't round)
- Maintain currency symbols and formats
- Note when data is unclear or illegible
- Flag suspicious or duplicate transactions
- Provide tax-relevant categorization
- Use standard expense categories
- Generate export-ready formats (CSV, JSON)
- Protect sensitive info (mask account numbers)
- Identify missing information (no date, unclear vendor)
- Calculate totals and verify against document
- Note discrepancies or calculation errors
- Include exchange rates for foreign currency
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Testing patterns for PHPUnit and Playwright E2E tests. Use when writing tests, debugging test failures, setting up test coverage, or implementing test patterns for ActivityPub features.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
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Add unsigned integer (uint) type support to PyTorch operators by updating AT_DISPATCH macros. Use when adding support for uint16, uint32, uint64 types to operators, kernels, or when user mentions enabling unsigned types, barebones unsigned types, or uint support.
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This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.
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Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.