What is Postmortem (PM) compliance in this context?

It refers to checking the new code against a library of historical failures found in the postmortem directory to ensure past mistakes and anti-patterns are not reintroduced.

When is the best time to invoke this skill?

Use this skill once strategy development is complete and you are ready to create a Pull Request (PR) for merging into a production or main branch.

What documentation does it generate for PRs?

It generates a comprehensive report including PM compliance verification, performance metric tables, equity curve references, and a bot resilience checklist.

Can this skill optimize my strategy's performance?

Yes, it supports the Ralph Loop mode to iteratively tune parameters until they meet specific backtest thresholds like Sharpe Ratio or Max Drawdown targets.

Does it handle security for API keys?

The skill includes a dedicated security audit phase that scans for hardcoded keys, improper credential logging, and insecure storage patterns in trading bot code.

Blueprint Strategy Review

Name: Blueprint Strategy Review
Author: morris-y

bymorris-y

Seguridad y Pruebas

Conducts multi-dimensional security, quality, and postmortem compliance audits for trading strategies before deployment.

Acerca de

Blueprint Review is a specialized Claude Code skill designed to safeguard trading strategy deployments by enforcing rigorous postmortem compliance and security standards. It automates complex review workflows—including PM regression testing, security scans for API credential handling, and backtest validation—ensuring that new code doesn't repeat historical failures. By integrating iterative parameter optimization through the Ralph Loop and generating comprehensive PR documentation, it bridges the gap between development and production-ready financial code.

Características Principales

Automated Postmortem (PM) compliance and regression testing
Iterative backtest optimization via Ralph Loop integration
Automated GitHub PR creation with detailed performance metrics
0 GitHub stars
Deep security audits focused on API and credential safety
Multi-dimensional code quality assessment for high-resilience trading

Casos de Uso

Optimizing strategy parameters using iterative backtest loops
Verifying trading strategy robustness before merging into production
Ensuring new code adheres to project-specific safety directives and historical bug fixes

Acerca de

Características Principales

Automated Postmortem (PM) compliance and regression testing
Iterative backtest optimization via Ralph Loop integration
Automated GitHub PR creation with detailed performance metrics
0 GitHub stars
Deep security audits focused on API and credential safety
Multi-dimensional code quality assessment for high-resilience trading

Casos de Uso

Optimizing strategy parameters using iterative backtest loops
Verifying trading strategy robustness before merging into production
Ensuring new code adheres to project-specific safety directives and historical bug fixes