ce-code-review

Automate code review with tiered personas and automated fixes.

1|Updated Jun 2, 2026
One-click install
npx skills add https://github.com/FFCfelps1/SGPPF_Maua --skill ce-code-review-ffcfelps1
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ce-code-review
Source: https://github.com/FFCfelps1/SGPPF_Maua/tree/main/.gemini/skills/ce-code-review
Command: npx skills add https://github.com/FFCfelps1/SGPPF_Maua --skill ce-code-review-ffcfelps1

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pypdf, pdfplumber, pdf2image, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill streamlines the code review process by using tiered persona agents for analysis and automated fixes, providing a faster and more efficient review experience.

Core Features & Use Cases

  • Tiered Personas: Utilizes a structured set of reviewer personas for comprehensive code analysis.
  • Automated Fixes: Applies safe automated fixes to code issues.
  • Customizable Modes: Offers modes for interactive review, report-only, and headless execution.
  • Use Case: Before creating a pull request, run the ce-code-review Skill to automatically review and fix code issues, saving time and improving code quality.

Quick Start

Use the ce-code-review skill with the mode:autofix argument to review and automatically fix code changes in the current branch.

Frequently Asked Questions about ce-code-review

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

FAQPage Schema
How do I automate code review and apply fixes before creating a pull request?

Automated code review uses tiered persona agents to analyze your Python changes and apply safe fixes automatically. This streamlines software quality checks and resolves issues before you create a pull request.

What are reviewer personas and how do they improve software quality?

Reviewer personas are structured agent profiles that simulate different reviewer perspectives to provide comprehensive code analysis. They improve software quality by tiering multiple analytical viewpoints to catch issues a single review pass might miss.

Can I run automated code analysis in a headless execution mode?

Yes, automated code analysis supports headless execution mode. The process offers customizable modes including interactive review, report-only generation, and headless execution to fit different software development workflows.

Do I need Python libraries to parse and modify code during the review process?

Yes, specific Python libraries are required to parse, analyze, and modify code during the review process. These dependencies enable the scripts to function correctly and apply automated fixes.

What is the best way to integrate tiered code analysis into a software development workflow?

The best way to integrate tiered code analysis is to run it before creating a pull request. This allows the automated personas to review and fix code changes in the current branch, improving overall code quality efficiently.

Does the automated code review process work with PDF parsing libraries?

The automated code review process requires specific Python libraries including pypdf, pdfplumber, and pdf2image. These dependencies support the underlying parsing and analysis functions needed to modify code effectively.