Trading Expert

If you're building algorithmic trading systems or need to implement quantitative strategies, this gives you the technical foundation without the fluff. It covers the practical stuff like backtesting frameworks with proper metrics (Sharpe ratio, max drawdown), execution algorithms including TWAP and VWAP, and order management with smart routing. The code examples are realistic, handling things like moving average crossovers, mean reversion with Bollinger Bands, and position sizing with risk controls. It's aimed at developers working on trading platforms or quant researchers prototyping strategies, not retail traders looking for get-rich-quick signals. The focus is clearly on infrastructure and systematic approaches rather than market prediction.

skills.sh installs: 966
GitHub stars: 44
last updated: Aug 21, 2026

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Install

$ npx -y skills add personamanagmentlayer/pcl --skill trading-expert --agent claude-code

Installs into .claude/skills of the current project.

Files

Trading Expert

Expert guidance for algorithmic trading systems, quantitative analysis, market data processing, and trading platform development.

Core Concepts

Trading Systems

Algorithmic trading strategies
High-frequency trading (HFT)
Market making
Arbitrage strategies
Portfolio optimization
Risk management

Market Data

Order book processing
Tick data analysis
Market microstructure
Real-time data feeds
Historical data analysis

Execution

Order routing
Smart order routing (SOR)
Execution algorithms (TWAP, VWAP)
Slippage minimization
Transaction cost analysis

Trading Strategy Implementation

import pandas as pd
import numpy as np
from typing import Optional

class TradingStrategy:
    def __init__(self, symbol: str, capital: float = 100000):
        self.symbol = symbol
        self.capital = capital
        self.position = 0
        self.cash = capital
        self.trades = []

SKILL.md on GitHub