quant-review

What problem does it solve?

Rigorous auditing of trading strategy code to ensure correctness, realism, and production-readiness, preventing silent mistakes from eroding P&L in live environments.

Core Features & Use Cases

• Architecture coherence: ensure backtests and live code share a single, unified signal/strategy module to avoid divergence.
• Data integrity checks: enforce point-in-time data handling, leakage prevention, and correct timestamp alignment across pipelines.
• Risk & cost realism: audit for proper slippage, costs, and risk controls to produce credible performance metrics.
• Use Case: review a strategy's signals, backtest-to-live code mapping, and data pipelines for a single cohesive system.

Quick Start

Ask Claude Code to review your trading strategy code for biases and production-readiness.