What is the benefit of a dual-model review?

Using two different models (Codex and Gemini) provides two distinct perspectives—logic/security vs. design/patterns—reducing the likelihood of missed bugs and improving code quality.

How does it handle overlapping issues?

The skill synthesizes findings from both models, deduplicates similar reports, and increases the severity level of issues that are flagged by both agents.

What roles do the models play during the review?

Codex acts as a 'code-reviewer' focusing on implementation logic and security, while Gemini acts as a 'designer' focusing on patterns and maintainability.

Can I run this review at any time?

Yes, the skill is designed to be triggered manually at any point in the development cycle, whether you are reviewing a git diff or a specific RPI state.

Dual-Model Cross-Review

Name: Dual-Model Cross-Review
Author: 1molchuan

by1molchuan

0•

协作工具

Conducts independent, parallel code reviews using Codex and Gemini to identify logic errors, security flaws, and architectural patterns.

The oh-my-ccg-review skill automates a sophisticated code review process by leveraging two distinct AI models simultaneously. It utilizes Codex for deep logic and security analysis while employing Gemini to evaluate design patterns and maintainability. By synthesizing findings from both 'code-reviewer' and 'designer' roles, it provides a comprehensive, cross-validated report that categorizes issues by severity. This dual-model approach helps developers catch critical bugs and architectural debt before deployment by cross-referencing insights from different AI architectures.

主要功能

01Parallel Dual-Model Analysis: Runs Codex and Gemini simultaneously for diverse perspectives.

02Cross-Model Validation: Automatically elevates the severity of issues identified by both models.

03Standardized Severity Reporting: Classifies findings into Critical, Warning, and Info categories.

04Interactive Decision Gate: Offers streamlined paths to fix, accept, or defer identified issues.

05Automated Artifact Collection: Pulls data from git diffs, RPI state, or manual selection.

060 GitHub stars

使用场景

01Cross-verifying bug fixes using independent reviewer and designer AI agents.

02Architectural pattern validation during major refactoring phases.

03Pre-commit logic and security auditing for complex pull requests.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add 1molchuan/oh-my-ccg oh-my-ccg-review

For use in Claude.ai and ChatGPT

主要功能

01Parallel Dual-Model Analysis: Runs Codex and Gemini simultaneously for diverse perspectives.

02Cross-Model Validation: Automatically elevates the severity of issues identified by both models.

03Standardized Severity Reporting: Classifies findings into Critical, Warning, and Info categories.

04Interactive Decision Gate: Offers streamlined paths to fix, accept, or defer identified issues.

05Automated Artifact Collection: Pulls data from git diffs, RPI state, or manual selection.

060 GitHub stars

使用场景

01Cross-verifying bug fixes using independent reviewer and designer AI agents.

02Architectural pattern validation during major refactoring phases.

03Pre-commit logic and security auditing for complex pull requests.