What is the primary benefit of using Codex Review with Claude?

It provides a second, high-reasoning perspective from an external model (Codex) to catch architectural flaws, logic errors, and missing requirements that a single AI might overlook.

How is the feedback from Codex organized?

Feedback is structured into four clear sections: Blocking Issues (critical), Non-blocking Issues (suggestions), Outstanding Questions (clarifications), and Further Ideas (enhancements).

When is the best time to invoke a Codex Review?

It is most effective during early phases like brainstorming, requirements gathering, and design planning, as catching issues at these stages is significantly cheaper than after implementation.

How does the skill handle sensitive data like API keys?

The skill includes explicit instructions to strip sensitive data, credentials, and secrets from the content before it is sent to the external Codex environment for review.

Codex Architecture & Code Review

Name: Codex Architecture & Code Review
Author: williballenthin

bywilliballenthin

•

コラボレーションツール

Automates external design and code reviews by piping project context to OpenAI's Codex for high-reasoning feedback and risk assessment.

概要

Codex Review provides an automated 'second pair of eyes' by integrating OpenAI’s high-reasoning models directly into the Claude Code workflow. It excels at identifying logical gaps, architectural risks, and flawed assumptions during the early stages of development, such as brainstorming or design planning. By structuring output into blocking issues, non-blocking suggestions, and clarifying questions, it helps developers catch expensive mistakes before implementation begins, while also offering deep analysis of existing code and diffs to ensure production readiness.

主な機能

Integration with VCS tools to review diffs and implementations for logic errors
High-reasoning analysis using specialized models to identify complex architectural risks
Structured output format categorizing feedback into blocking and non-blocking issues
1 GitHub stars
Automated sensitivity instructions to ensure PII and credentials are removed before review
Context-aware review templates for brainstorming, requirements, and design docs

ユースケース

Cross-checking requirements documents for contradictions and missing edge cases
Getting an objective second opinion on complex code changes and pull requests
Validating system architecture and caching strategies during the design phase

概要

主な機能

Integration with VCS tools to review diffs and implementations for logic errors
High-reasoning analysis using specialized models to identify complex architectural risks
Structured output format categorizing feedback into blocking and non-blocking issues
1 GitHub stars
Automated sensitivity instructions to ensure PII and credentials are removed before review
Context-aware review templates for brainstorming, requirements, and design docs

ユースケース

Cross-checking requirements documents for contradictions and missing edge cases
Getting an objective second opinion on complex code changes and pull requests
Validating system architecture and caching strategies during the design phase