repo-map generates LLM-enhanced summaries and analysis of software repositories, providing developers with valuable insights into project structures, file purposes, and potential considerations across various programming languages.
GitIntel is a robust GitHub OSINT tool crafted to reveal concealed insights from GitHub repositories and user profiles. Its capabilities make it an invaluable resource for ethical hacking, security assessments, and intelligence gathering in the realm of software development.
A powerful CLI tool for gathering and summarizing key information from Git repositories, enhancing developer productivity through automation and streamlined analysis.
🔍 Chrome extension that adds a convenient "Ingest" button to GitHub repository pages, enabling one-click access to view repositories on GitIngest.com for detailed analysis. Simple, lightweight, and seamlessly integrated with GitHub's interface.
🔍 git-author – Identify codebase authorship at a component level, beyond git blame, for better ownership insights.
A Git commit activity visualization tool with detailed repository insights
A collection of scripts for analyzing and visualizing Git repositories. Explore commit history, contributor activity, code changes, and more with easy-to-use tools designed to help you gain insights into your codebase.
Explore and analyze top GitHub repositories with TopGit, a web app built using HTML, CSS, JavaScript, and the GitHub API.
Calculate the popularity of words used in class names across GitHub Java Repositories
Complementary data package of the publication "On the Analysis of Non-Coding Roles in Open Source Development. An Empirical Study of NPM Package Projects"
RepoGenius aims to create a distributed system that, starting from a GitHub link or certain parameters, performs an analysis on the reference repository based on elements such as code, language or files
A comprehensive algorithm for evaluating and enhancing the quality of open-source software through metrics (NC, MU, MC, BP and IP).
AI-powered GitHub repository analyzer using Model Context Protocol (MCP) for structured repository insights and analysis
A Python tool employing a LightGBM-based Learning-to-Rank approach to predict and rank source code files by their bug likelihood.
Repository analysis tool that provides standardized metrics, visualizations, and insights for understanding code structure and project health.
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