codex-review

Review source code with OpenAI Codex and apply targeted fixes.

Updated Feb 17, 2026
One-click install
npx skills add https://github.com/Objective-Arts/lens-dist --skill codex-review-objective-arts
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: codex-review
Source: https://github.com/Objective-Arts/lens-dist/tree/main/skills/codex-review
Command: npx skills add https://github.com/Objective-Arts/lens-dist --skill codex-review-objective-arts

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the process of reviewing code for production readiness and applying targeted fixes, ensuring code quality and security before deployment.

Core Features & Use Cases

  • Independent Code Review: Leverages OpenAI Codex to perform an objective code review.
  • Targeted Fixes: Automatically applies fixes for identified issues, prioritizing security and reliability.
  • Multi-Model Triangulation: Provides an additional layer of code quality assurance after other review phases.
  • Use Case: Integrate this Skill into your CI/CD pipeline to automatically catch and fix common coding errors, security vulnerabilities, and style issues, reducing the burden on human reviewers.

Quick Start

Use the codex-review skill to perform a production readiness review on the code in the current directory.

Frequently Asked Questions about codex-review

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate code review for production readiness in a CI/CD pipeline?

Automated code review analyzes source code against defined rubrics using OpenAI Codex to identify security and reliability issues. It integrates directly into CI/CD pipelines to continuously catch and fix common coding errors before deployment.

Can I automatically fix security vulnerabilities found during an automated code review?

Yes, automated code review applies targeted fixes for identified issues, prioritizing security and operational hygiene. It leverages OpenAI Codex to automatically resolve vulnerabilities and common coding errors, reducing the need for manual intervention.

What is multi-model triangulation for code quality assurance?

Multi-model triangulation provides an additional layer of code quality assurance by performing an independent review after other phases. It uses OpenAI Codex to objectively analyze source code and ensure production readiness against defined rubrics.

Does automated code review work without manual human reviewers?

Automated code review performs an independent, objective analysis of source code to catch style issues and vulnerabilities. While it reduces the burden on human reviewers by applying targeted fixes automatically, it serves as an assurance layer rather than a complete replacement.

How do I run a production readiness review on my current source code directory?

You can run a production readiness review by executing the codex-review skill against the code in your current directory. It analyzes the source code, identifies operational hygiene issues, and automatically applies targeted fixes.

What are the limitations of using AI for automated code review?

Automated code review focuses on defined rubrics for security, reliability, and operational hygiene. It applies targeted fixes for common errors but may require human oversight for complex architectural issues not covered by standard CI/CD quality checks.