Automate expert code reviews for the Relax reinforcement learning framework.
npx skills add https://github.com/EnkeZ/tgsopd --skill code-review-enkez
Please help me install this Agent Skill. Skill: code-review Source: https://github.com/EnkeZ/tgsopd/tree/main/skills/code-review Command: npx skills add https://github.com/EnkeZ/tgsopd --skill code-review-enkez
This Skill automates expert code reviews, detecting issues like SOLID violations, security risks, Python anti-patterns, and ML/distributed training issues, tailored for the Relax reinforcement learning framework.
Use the code-review skill to review the current git changes with a focus on SOLID principles, architecture, removal candidates, security risks, and Python-specific issues for the Relax project.
High-intent search queries and answers about installing and using this skill.
Automate code review for Python and reinforcement learning frameworks by scanning git changes for SOLID violations, security risks, and distributed training issues. This provides a senior engineer level analysis without manual line-by-line inspection.
Automated code review detects SOLID principle violations, architecture smells, security risks, and Python anti-patterns. It also identifies machine learning and distributed training issues specific to reinforcement learning projects.
Run a code review on your current git changes by executing the review workflow, which analyzes preflight context, architecture smells, removal candidates, security risks, and Python-specific quality issues tailored to your Relax framework project.
Yes, automated code review is explicitly tailored for machine learning and distributed training code. It executes a specialized ML and training-specific scan to detect issues within the Relax reinforcement learning framework.
The best way to enforce SOLID principles and check Python anti-patterns is using an automated review workflow that provides structured checklists and templates, systematically scanning for architectural and security issues.
Yes, this automated code review is specifically designed for the Relax reinforcement learning framework. It targets Python code within the Relax project to detect ML, distributed training, and architecture issues.
EnkeZAutomate development and debugging for Relax reinforcement learning on remote Ray clusters.
KaimingWanReview current git changes for SOLID violations, security risks, and performance issues.
jfrometaRun lint, type checks, and security audits on Node.js and Python projects.
cogikyoRefactor Go and TypeScript/React codebases for readability and organization.
