Flattening for AI, Context for understanding, and Grading for quality.
RikaiCode is a sophisticated, browser-based tool designed to turn complex codebases into structured, actionable data. Whether you need to feed code into an LLM, audit a project's quality, or simply understand a new architecture, RikaiCode provides the insights you need in a beautiful, dark-themed interface.
Seamlessly analyze public GitHub or GitLab repositories, or upload local files and ZIP folders. It handles large repositories by automatically skipping binary files and non-text assets to ensure optimal performance.
RikaiCode assigns a unified grade (A++ to C) to every project. This isn't just a random score; it's calculated using a weighted algorithm based on industry standards for software health.
Integrated with the GLM-4.7-Flash model, RikaiCode acts as your personal code architect. It can summarize entire projects, explain complex functions, and generate onboarding guides.
Automatically scans code for potential vulnerabilities, including:
- Hardcoded AWS Access Keys.
- Generic API Keys/Secrets.
- Private SSH Keys (RSA, DSA, EC, OpenSSH).
Transforms raw git data into interactive visualizations:
- Treemaps: File extension distribution.
- Pie Charts: Code composition.
- Heatmaps: Commit activity by hour and day of the week.
Export your entire flattened codebase into a single file for LLM context. Supported formats: TXT, JSON, PDF, DOCX, HTML, Markdown, LaTeX.
- Select Source: Choose between GitHub URL, GitLab URL, or Upload Files.
- Analyze:
- If using a URL, click "Fetch Repository".
- If uploading, drag and drop your files.
- Explore: View the repository grade, architecture diagram, security alerts, and code statistics.
- AI Insights: Expand the "Rikai AI Analysis" section to generate architectural summaries.
- Export: Use the export buttons at the bottom to download the flattened context.
This project is licensed under the AGPL 3.0 License - see the LICENSE file for details.
Questions, feedback, or collaboration ideas? Reach out at pteroisvolitans12@gmail.com or open an issue on GitHub.
Contributions are always welcome!
Made with 🤍 by Aurumz
