The problem

Traders often struggle to turn a vague strategy or "gut feeling" into a repeatable, rule-based system. Without a formal blueprint, execution remains inconsistent, risk management is neglected, and performance cannot be accurately measured or automated.

What it does

• Generates precise market selection criteria, including asset classes, timeframes, and liquidity filters.
• Defines concrete entry and exit signals using technical indicators, price action patterns, and multi-factor confirmation.
• Builds comprehensive risk management frameworks with position sizing formulas and drawdown circuit breakers.
• Outlines data logging requirements for systematic journaling and performance auditing.
• Provides technical specifications for automation, including data pipeline needs and API failsafes.

Why this beats prompting it yourself

General LLM prompts often produce generic advice rather than actionable code or rules. This skill enforces a professional structure that covers critical edges like walk-forward analysis, correlation limits, and execution slippage that DIY prompts usually miss.

Use cases

• Converting a manual discretionary strategy into a rule-based system for backtesting.
• Creating a detailed specification for a developer to build an automated trading bot.
• Auditing an existing strategy to identify gaps in risk management or journaling.
• Documenting a firm-wide trading manual for team consistency and compliance.

Known limitations

Requires the user to provide the initial core edge or strategy hypothesis. It does not provide financial advice or guaranteed profitable signals.