Handles the full stack of building automated trading systems, from strategy development through production deployment. The skill grounds itself in three reference files: patterns for how to build components correctly, sharp edges for understanding critical failure modes in live trading, and validations for checking strategies against strict risk rules. You'd reach for this when backtesting a new strategy, implementing execution algorithms, or analyzing market microstructure. The reference system approach is smart here because algorithmic trading has genuine sharp edges where generic solutions lose money fast, so having curated patterns and known pitfalls baked in makes sense. Covers both the research side and the operational reality of running strategies in production.
npx skills add https://github.com/omer-metin/skills-for-antigravity --skill algorithmic-trading