githuman-skills

🥈Silver

Claude Code skill for GitHuman that enables AI-generated code review workflows, helping developers stage files, manage comments, and track follow-up work before committing changes.

700Updated 4mo ago

Intermediate30min to implementautomation

Saves ~135 min per use

Quick InstallView Source

git clone https://github.com/mcollina/githuman-skills.git

Works with:

Claude

Overview

About This Skill

GitHuman Skills integrate code review capabilities directly into Claude Code, allowing developers to systematically review AI-generated changes before committing. The skill teaches Claude how to start the GitHuman review interface, stage files for inspection, manage inline comments and suggestions, track todos for follow-up work, and export reviews for documentation. This workflow helps teams maintain code quality and catch issues in AI-assisted development. GitHuman Skills are particularly valuable for development teams using Claude Code who need structured review processes for automated code generation.

How to Use

Install GitHuman and the skill into Claude Code following the GitHuman documentation. The skill provides access to the GitHuman review interface where you can stage files, add comments and suggestions, manage todos, and export completed reviews.

Use Cases

Review AI-generated code changes before merging to main branch

Stage and inspect multiple files in a single review session

Track inline comments and suggestions on AI-generated code

Manage follow-up todos discovered during code review

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/mcollina/githuman-skills

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Review the following AI-generated code changes for a [COMPANY] project in the [INDUSTRY] sector. The changes are: [CODE_CHANGES]. Provide a detailed code review focusing on: 1) Potential security vulnerabilities, 2) Code efficiency, 3) Best practices adherence, and 4) Any industry-specific considerations. Use clear, actionable feedback.

Example Output

# Code Review for AI-Generated Changes

## Security Vulnerabilities
- **SQL Injection Risk**: The user input in `process_user_data()` is directly interpolated into the SQL query. This should use parameterized queries instead.
- **Authentication Bypass**: The `admin_check()` function doesn't verify session tokens, making it vulnerable to privilege escalation.

## Code Efficiency
- **Redundant Database Queries**: The `get_user_details()` function makes 3 separate queries that could be combined into one.
- **Inefficient Loop**: The `process_large_dataset()` function processes data row-by-row instead of using batch operations.

## Best Practices
- **Missing Error Handling**: Several functions lack try-catch blocks for database operations.
- **Inconsistent Naming**: Some variables use camelCase while others use snake_case (e.g., `userName` vs `user_email`).

## Industry-Specific Considerations
- **Compliance**: The data handling doesn't appear to comply with [INDUSTRY] regulations regarding data retention periods.
- **Audit Trail**: Missing logging for critical operations required by [INDUSTRY] standards.