548 Ard B3bf219c

ARD: Gas Fee Optimizer

Architecture Pattern

Analytics Pipeline Pattern - Python CLI that fetches gas data, analyzes patterns, and provides optimization recommendations.

Workflow

Data Collection → Analysis → Recommendation → Display
      ↓             ↓            ↓              ↓
  RPC + APIs    Historical   Timing/Price     Table/JSON

Data Flow

Input: User request (current gas, optimal time, estimate for operation)
          ↓
Fetch: Multiple gas oracles (RPC, Etherscan, Blocknative)
          ↓
Aggregate: Combine sources, calculate percentiles
          ↓
Analyze: Compare to historical patterns
          ↓
Recommend: Optimal timing, price recommendation
          ↓
Output: Formatted results with USD costs

Directory Structure

skills/optimizing-gas-fees/
├── PRD.md                    # This requirements doc
├── ARD.md                    # This architecture doc
├── SKILL.md                  # Agent instructions
├── scripts/
│   ├── gas_optimizer.py      # Main CLI entry point
│   ├── gas_fetcher.py        # Multi-source gas data
│   ├── pattern_analyzer.py   # Historical pattern detection
│   ├── cost_estimator.py     # Transaction cost estimation
│   └── formatters.py         # Output formatting
├── references/
│   ├── errors.md             # Error handling guide
│   └── examples.md           # Usage examples
└── config/
    └── settings.yaml         # Default configuration

API Integration

Ethereum RPC

• Method: eth_gasPrice, eth_feeHistory
• Data: Current gas price, base fee history

Etherscan Gas Tracker

• Endpoint: https://api.etherscan.io/api?module=gastracker
• Data: Safe/Proposed/Fast gas prices

Blocknative (Optional)

• Endpoint: https://api.blocknative.com/gasprices/blockprices
• Data: Confidence-based predictions

Component Design

gas_fetcher.py

class GasFetcher:
    def __init__(self, chain: str = "ethereum", rpc_url: str = None, api_key: str = None, verbose: bool = False)
    def get_current_gas(self) -> GasData
    def get_base_fee_history(self, blocks: int = 100) -> List[BaseFeeHistory]
    def get_gas_for_chain(self, chain: str) -> GasData  # For cross-chain comparison

pattern_analyzer.py

class PatternAnalyzer:
    def __init__(self, history_file: str = None, verbose: bool = False)
    def record_gas_data(self, gas_gwei: float) -> None
    def analyze_hourly_pattern(self) -> List[HourlyPattern]
    def analyze_daily_pattern(self) -> List[DailyPattern]
    def find_optimal_window(self, current_gas_gwei: float = None) -> TimeWindow
    def predict_gas(self, target_time: datetime) -> GasPrediction

cost_estimator.py

class CostEstimator:
    def __init__(self, native_symbol: str = "ETH", verbose: bool = False)
    def estimate_cost(self, operation: str, gas_price_gwei: float, tier: str = "standard", custom_gas_limit: int = None) -> CostEstimate
    def estimate_all_tiers(self, operation: str, gas_slow: float, gas_standard: float, gas_fast: float, gas_instant: float, custom_gas_limit: int = None) -> MultiTierEstimate
    def estimate_transfer(self, gas_price_gwei: float) -> CostEstimate
    def estimate_swap(self, gas_price_gwei: float, dex: str = "uniswap_v2") -> CostEstimate
    def estimate_nft_mint(self, gas_price_gwei: float) -> CostEstimate
    def estimate_custom(self, gas_price_gwei: float, gas_limit: int) -> CostEstimate

Gas Price Tiers

Historical Pattern Sources

1. Hourly patterns: Gas is typically lower during off-peak hours
2. Daily patterns: Weekends often have lower gas
3. Event patterns: NFT mints, token launches spike gas
4. Network upgrades: EIP implementations affect base fee

Error Handling Strategy

Multi-Chain Support

Performance Considerations

• Cache gas data for 10-15 seconds
• Batch RPC calls where possible
• Store historical data locally for pattern analysis
• Limit history fetch to needed window

Security

• No private keys required
• RPC URLs may contain API keys (handle securely)
• Read-only operations only