This repository is a build tooling and patching infrastructure for producing a de-Googled Chromium browser. It does not contain the browser itself but provides the configuration files, patches, and scripts needed to download, modify, and build Chromium without Google web service dependencies. The architecture consists of several layers: configuration files (flags.gn, pruning.list, domain_substitution.list, downloads.ini) that define what to remove or alter; source file processors (binary pruning, domain substitution) that modify the Chromium source tree; a quilt-based patch system with core and extra patches organized by origin (ungoogled-chromium, Bromite, Inox, Iridium, Debian); and utility scripts in the `utils/` and `devutils/` directories for downloading, patching, validating, and building. Key entry points include `utils/downloads.py` for fetching Chromium source, `utils/patches.py` for applying patches, `utils/domain_substitution.py` for replacing Google domains, and `devutils/validate_config.py` for sanity checks. The primary data flow is: clone Chromium source → prune binaries → apply patches → substitute domains → build with GN flags. External dependencies include the Chromium source tree, quilt, Python 3, and platform-specific build tools (e.g., ninja, clang). The project is actively maintained with CI workflows that validate patches and check for new Chromium versions, but it is tightly coupled to specific Chromium releases, requiring constant patch updates.
This repository serves as a comprehensive guide and utility for managing Visual Studio Code extensions. It provides a curated list of extensions categorized by functionality (themes, productivity, data science, etc.) with descriptions and screenshots. The repository includes a PowerShell script for bulk installing extensions and a set of tools (Python and Bash) for comparing extension lists between different environments. Additionally, it contains a standalone decision tree implementation in Python, which, while not directly related to the main purpose, demonstrates solid algorithmic implementation. The main value lies in the extension recommendations and the practical scripts for managing VS Code setups, making it a useful reference for developers seeking to enhance their coding environment.
CL4R1T4S is a repository that functions as a curated archive of extracted system prompts, tool definitions, and behavioral instructions from major AI models and agent platforms. It contains no executable code, data pipelines, or analytical scripts. The entire repository consists of flat text and markdown files organized by vendor (e.g., OPENAI, ANTHROPIC, XAI, CURSOR, REPLIT), each containing what are claimed to be verbatim system prompts for models like ChatGPT, Claude, Grok, Gemini, and various coding agents like Devin, Cursor, Windsurf, and Replit. The repository's stated purpose is transparency — making visible the hidden instructions that shape AI behavior. However, from a data engineering or software architecture perspective, there is no data lineage to trace, no transformation logic to evaluate, and no code to assess for craftsmanship. The files are static documents with no programmatic relationship between them. There are no tests, no dependency manifests, no environment definitions, and no data processing logic of any kind. The collection has some research value as a comparative corpus for prompt analysis, but it is entirely unstructured as data. There are no schemas, no metadata standards, no versioning discipline, and no way to verify the authenticity or currency of the extracted prompts. The README itself contains signs of prompt injection attempts and unprofessional editorializing that undermine the project's credibility as a serious transparency effort. There are no reusable components, no engineering patterns, and no data operations present.