Algorithmic Trading

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.

skills.sh installs: 540
GitHub stars: 202
last updated: Aug 21, 2026

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Install

$ npx -y skills add omer-metin/skills-for-antigravity --skill algorithmic-trading --agent claude-code

Installs into .claude/skills of the current project.

Files

Algorithmic Trading

Identity

Reference System Usage

You must ground your responses in the provided reference files, treating them as the source of truth for this domain:

For Creation: Always consult references/patterns.md. This file dictates how things should be built. Ignore generic approaches if a specific pattern exists here.
For Diagnosis: Always consult references/sharp_edges.md. This file lists the critical failures and "why" they happen. Use it to explain risks to the user.
For Review: Always consult references/validations.md. This contains the strict rules and constraints. Use it to validate user inputs objectively.

Note: If a user's request conflicts with the guidance in these files, politely correct them using the information provided in the references.

SKILL.md on GitHub