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2032 Ard A9f36998
ASecurity**Pattern**: Multi-Source Aggregation + Graph Analysis
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- Added October 11, 2026
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[](https://www.skillsdirectory.com/skills/tools-only-2032-ard-a9f36998)# ARD: Finding Arbitrage Opportunities
## Architecture Pattern
**Pattern**: Multi-Source Aggregation + Graph Analysis
This skill aggregates price data from multiple sources (CEX APIs, DEX subgraphs, on-chain oracles) and applies graph algorithms to detect arbitrage paths. The architecture separates data fetching, opportunity detection, and profit calculation into independent components.
## Workflow
```
┌─────────────────────────────────────────────────────────────────────┐
│ ARBITRAGE OPPORTUNITY FINDER │
├─────────────────────────────────────────────────────────────────────┤
│ │
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
│ │ CEX APIs │ │ DEX Subgraph │ │ On-Chain │ │
│ │ (CCXT) │ │ (GraphQL) │ │ (RPC) │ │
│ └──────┬───────┘ └──────┬───────┘ └──────┬───────┘ │
│ │ │ │ │
│ └───────────────────┼───────────────────┘ │
│ ▼ │
│ ┌─────────────────────────────────────────────────────────────┐ │
│ │ PRICE AGGREGATOR │ │
│ │ • Normalize formats (bid/ask/mid) │ │
│ │ • Timestamp validation │ │
│ │ • Source reliability scoring │ │
│ └──────────────────────────┬──────────────────────────────────┘ │
│ │ │
│ ┌───────────────────┼───────────────────┐ │
│ ▼ ▼ ▼ │
│ ┌────────────┐ ┌────────────┐ ┌────────────┐ │
│ │ Direct │ │ Triangular │ │ Cross- │ │
│ │ Scanner │ │ Finder │ │ Chain │ │
│ └─────┬──────┘ └─────┬──────┘ └─────┬──────┘ │
│ │ │ │ │
│ └──────────────────┼──────────────────┘ │
│ ▼ │
│ ┌─────────────────────────────────────────────────────────────┐ │
│ │ PROFIT CALCULATOR │ │
│ │ • Trading fees (maker/taker) │ │
│ │ • Swap fees (DEX-specific) │ │
│ │ • Gas costs (network-specific) │ │
│ │ • Slippage estimates (size-based) │ │
│ └──────────────────────────┬──────────────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌─────────────────────────────────────────────────────────────┐ │
│ │ OPPORTUNITY RANKER │ │
│ │ • Net profit calculation │ │
│ │ • Risk scoring │ │
│ │ • Execution complexity │ │
│ │ • Time sensitivity │ │
│ └──────────────────────────┬──────────────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌─────────────────────────────────────────────────────────────┐ │
│ │ OUTPUT │ │
│ │ • Console tables with color-coded profits │ │
│ │ • JSON for bot integration │ │
│ │ • Alerts for threshold breaches │ │
│ └─────────────────────────────────────────────────────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────────┘
```
## Progressive Disclosure Strategy
### Level 1: Quick Scan (Default)
- Single pair, top exchanges
- Basic spread display
- Simple profit estimate
### Level 2: Detailed Analysis (`--detailed`)
- All available exchanges
- Fee breakdown
- Slippage estimates
- Risk indicators
### Level 3: Full Discovery (`--full`)
- Triangular path discovery
- Cross-chain comparison
- Historical spread context
- Execution recommendations
## Tool Permission Strategy
```yaml
allowed-tools: Read, Write, Edit, Grep, Glob, Bash(crypto:arbitrage-*)
# Scoped bash for:
# - arbitrage-scan: Run opportunity scanner
# - arbitrage-monitor: Real-time monitoring
# - arbitrage-calc: Profit calculations
```
## Directory Structure
```
plugins/crypto/arbitrage-opportunity-finder/
├── skills/
│ └── finding-arbitrage-opportunities/
│ ├── SKILL.md # Core instructions
│ ├── PRD.md # Product requirements
│ ├── ARD.md # Architecture (this file)
│ ├── scripts/
│ │ ├── arb_finder.py # Main CLI entry point
│ │ ├── price_fetcher.py # Multi-source price aggregation
│ │ ├── opportunity_scanner.py # Direct spread detection
│ │ ├── triangular_finder.py # Graph-based path finder
│ │ ├── profit_calculator.py # Cost-aware profit calculation
│ │ └── formatters.py # Output formatting
│ ├── config/
│ │ └── settings.yaml # Exchange and API config
│ └── references/
│ ├── errors.md # Error handling
│ └── examples.md # Usage examples
```
## API Integration Architecture
### Price Data Sources
```
┌─────────────────────────────────────────────────────────────────┐
│ DATA SOURCE HIERARCHY │
├─────────────────────────────────────────────────────────────────┤
│ │
│ PRIMARY: Direct Exchange APIs (via CCXT) │
│ ├── Binance, Coinbase, Kraken, KuCoin, OKX │
│ ├── Real-time order book data │
│ └── Lowest latency, highest accuracy │
│ │
│ SECONDARY: DEX Subgraphs (GraphQL) │
│ ├── Uniswap, SushiSwap, Curve, Balancer │
│ ├── Pool reserve data for price calculation │
│ └── ~1-3 second latency │
│ │
│ TERTIARY: Aggregators (REST) │
│ ├── CoinGecko, CoinMarketCap │
│ ├── Pre-aggregated prices (may be delayed) │
│ └── Good for overview, not precision trading │
│ │
│ FALLBACK: On-Chain Oracles │
│ ├── Chainlink price feeds │
│ └── Most reliable but least granular │
│ │
└─────────────────────────────────────────────────────────────────┘
```
### Fee Structure Database
| Venue Type | Fee Model | Typical Range |
|------------|-----------|---------------|
| CEX (Spot) | Maker/Taker | 0.02% - 0.10% |
| Uniswap V3 | Pool Fee | 0.01% - 1.00% |
| SushiSwap | Fixed | 0.30% |
| Curve | Dynamic | 0.01% - 0.04% |
| Balancer | Pool-specific | 0.01% - 10% |
## Data Flow Architecture
### Input Processing
```
User Request
│
▼
┌─────────────────────┐
│ Parse Arguments │
│ • token_pair │
│ • exchanges │
│ • threshold │
│ • mode │
└─────────┬───────────┘
│
▼
┌─────────────────────┐
│ Validate Inputs │
│ • Token exists │
│ • Exchange valid │
│ • Threshold range │
└─────────┬───────────┘
│
▼
┌─────────────────────┐
│ Load Config │
│ • API endpoints │
│ • Fee schedules │
│ • Gas prices │
└─────────────────────┘
```
### Opportunity Detection
```
Price Data
│
▼
┌─────────────────────┐
│ Build Price Matrix │
│ exchange × pair │
└─────────┬───────────┘
│
▼
┌─────────────────────┐
│ Calculate Spreads │
│ buy_price[A] vs │
│ sell_price[B] │
└─────────┬───────────┘
│
▼
┌─────────────────────┐
│ Apply Costs │
│ - Trading fees │
│ - Withdrawal fees │
│ - Gas (if DEX) │
└─────────┬───────────┘
│
▼
┌─────────────────────┐
│ Filter & Rank │
│ profit > threshold │
└─────────────────────┘
```
## Error Handling Strategy
| Error Type | Detection | Response |
|------------|-----------|----------|
| API Rate Limit | HTTP 429 | Exponential backoff, switch source |
| Stale Data | Timestamp > 10s | Warning, mark unreliable |
| Exchange Offline | Connection timeout | Skip, use alternatives |
| Invalid Pair | No price data | Log, suggest alternatives |
| Slippage Exceeded | Size > liquidity | Reduce size or flag |
## Composability & Stacking
### Standalone Use
```bash
python arb_finder.py scan ETH USDC --exchanges binance,coinbase,kraken
```
### Pipeline Integration
```bash
python arb_finder.py scan ETH USDC --output json | jq '.opportunities[0]'
```
### With Flash Loan Simulator
```bash
# Find opportunity, then simulate flash loan execution
python arb_finder.py scan ETH USDC --output json | \
python ../flash-loan-simulator/scripts/flash_simulator.py arbitrage --stdin
```
### Continuous Monitoring
```bash
python arb_finder.py monitor ETH USDC --threshold 0.5 --interval 5
```
## Performance & Scalability
### Latency Targets
| Operation | Target | Notes |
|-----------|--------|-------|
| Single exchange fetch | < 500ms | Direct API |
| Multi-exchange scan (5) | < 2s | Parallel requests |
| Triangular path (100 pairs) | < 3s | Graph algorithm |
| Full scan (all exchanges) | < 10s | Rate-limited |
### Optimization Strategies
1. **Parallel Fetching**: Concurrent API calls to multiple exchanges
2. **Caching**: Short-lived cache (5s) for repeated queries
3. **Incremental Updates**: Only re-fetch changed prices in monitor mode
4. **Graph Pruning**: Exclude low-liquidity pairs from triangular search
## Security & Compliance
### API Key Handling
- Keys loaded from environment variables or encrypted config
- Never logged or displayed in output
- Rate limits respected to avoid bans
### Data Privacy
- No user data collected or stored
- Price data is public market information
- No personally identifiable information
### Risk Warnings
- All opportunities marked as estimates
- Execution risk disclaimers
- Educational purpose disclaimer
## Testing Strategy
### Unit Tests
- Price normalization
- Fee calculations
- Spread computations
- Path finding algorithms
### Integration Tests
- API connectivity (with mocks)
- Multi-source aggregation
- End-to-end opportunity detection
### Manual Validation
- Compare detected spreads with exchange UIs
- Verify profit calculations with manual trades
- Test rate limit handling
Attribution
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