Below you will find pages that utilize the taxonomy term “JNZader”
April 2, 2026
RepoForge AI
Version updated for https://github.com/JNZader/repoforge to version v0.5.0.
This action is used across all versions by ? repositories. Action Type This is a Composite action.
Go to the GitHub Marketplace to find the latest changes.
Action Summary RepoForge is an AI-powered GitHub Action designed to analyze codebases and automate the generation of technical documentation, AI agent skills, security scans, code graphs, and LLM-ready exports. It streamlines tasks such as creating comprehensive project documentation for various application types, enabling AI integrations, analyzing code dependencies, and improving code quality through advanced scanning capabilities.
April 1, 2026
GHAGGA Code Review
Version updated for https://github.com/JNZader/ghagga to version v2.8.1.
This action is used across all versions by 0 repositories. Action Type This is a Node action using Node version 20.
Go to the GitHub Marketplace to find the latest changes.
Action Summary GHAGGA is an AI-powered code review tool that combines static analysis and AI-driven insights to automate the review of pull requests. By integrating with 16 static analysis tools, leveraging project memory for learning from past reviews, and supporting multiple review modes (e.
March 24, 2026
RepoForge AI
Version updated for https://github.com/JNZader/repoforge to version v0.4.0.
This action is used across all versions by ? repositories. Action Type This is a Composite action.
Go to the GitHub Marketplace to find the latest changes.
Action Summary RepoForge is an AI-powered tool designed to analyze codebases and automate the generation of comprehensive technical documentation, AI agent skill files, security scans, dependency graphs, and large language model (LLM)-ready exports. It simplifies the process of creating project-specific documentation and AI integration assets, while also providing features like security analysis, code complexity scoring, and token optimization.
March 23, 2026
GHAGGA Code Review
Version updated for https://github.com/JNZader/ghagga to version v2.7.0.
This action is used across all versions by 0 repositories. Action Type This is a Node action using Node version 20.
Go to the GitHub Marketplace to find the latest changes.
Action Summary GHAGGA is an AI-powered code review tool that automates the review of pull requests by combining large language model (LLM) analysis, 16 static analysis tools, and a project memory system that learns from past reviews.
March 22, 2026
GHAGGA Code Review
Version updated for https://github.com/JNZader/ghagga to version v2.6.1.
This action is used across all versions by 0 repositories. Action Type This is a Node action using Node version 20.
Go to the GitHub Marketplace to find the latest changes.
Action Summary GHAGGA is an AI-powered code review tool designed to automate pull request reviews by combining large language model (LLM) analysis, static code analysis (using 16 tools), and project memory that learns from previous reviews.
March 18, 2026
RepoForge AI
Version updated for https://github.com/JNZader/repoforge to version v0.3.0.
This action is used across all versions by ? repositories. Action Type This is a Composite action.
Go to the GitHub Marketplace to find the latest changes.
Action Summary RepoForge is an AI-powered code analysis tool designed to automate the generation of comprehensive technical documentation, AI agent skill files, security scans, dependency graphs, and LLM-optimized exports for any codebase. It simplifies tasks such as creating project-specific documentation, preparing code for AI tools like GitHub Copilot and Claude, and performing code quality assessments and security checks.
March 16, 2026
RepoForge AI
Version updated for https://github.com/JNZader/repoforge to version v0.2.2.
This action is used across all versions by ? repositories. Action Type This is a Composite action.
Go to the GitHub Marketplace to find the latest changes.
Action Summary RepoForge is an AI-powered tool that automates codebase analysis to generate comprehensive technical documentation and AI agent skills. It creates Docsify-ready documentation tailored to various project types and produces AI skill definitions compatible with multiple agent frameworks, streamlining workflows for developers and teams.
March 9, 2026
GHAGGA Code Review
Version updated for https://github.com/JNZader/ghagga to version v2.5.0.
This action is used across all versions by 0 repositories. Action Type This is a Node action using Node version 20.
Go to the GitHub Marketplace to find the latest changes.
Action Summary GHAGGA is an AI-powered code review tool that automates the process of analyzing pull request (PR) changes by combining static analysis tools, project memory, and language models (LLMs). It detects issues, provides intelligent suggestions, and posts structured review comments directly on PRs, while continuously learning from past reviews to improve over time.
March 8, 2026
GHAGGA Code Review
Version updated for https://github.com/JNZader/ghagga to version v2.3.0.
This action is used across all versions by 0 repositories. Action Type This is a Node action using Node version 20.
Go to the GitHub Marketplace to find the latest changes.
Action Summary GHAGGA is an AI-powered code review tool designed to automate and enhance the process of reviewing pull requests. It combines static analysis tools (Semgrep, Trivy, CPD) with large language models (LLMs) and a project memory system to identify issues, suggest improvements, and provide structured feedback.
March 8, 2026
GHAGGA Code Review
Version updated for https://github.com/JNZader/ghagga to version v2.2.0.
This action is used across all versions by 0 repositories. Action Type This is a Node action using Node version 20.
Go to the GitHub Marketplace to find the latest changes.
Action Summary GHAGGA is an AI-powered code review tool that automates the analysis of pull requests by combining static analysis tools (Semgrep, Trivy, CPD), project memory, and intelligent multi-agent systems to provide structured review comments with findings, severity, and actionable suggestions.