Jimmy is a command-line and terminal UI tool for converting notes from 50+ note-taking applications (Evernote, Obsidian, Joplin, Notion, Bear, etc.) into a unified Markdown format. It uses an intermediate representation (Notebook/Note/Resource/Tag objects) decoupled from input parsing and output writing, allowing clean extensibility. The architecture is a plugin-style converter framework with a rich set of format-specific parsers, markdown preprocessing libraries, and a resource deduplication system. The tool is distributed as standalone binaries bundling Pandoc and other dependencies. While the core abstractions are well-crafted, the vast majority of the codebase consists of tightly coupled format converters that are specific to each app's export schema, limiting general reuse. The project has extensive integration tests via a test data submodule, but many converters lack unit tests. Its requirement for Python 3.14 (a very recent version) and reliance on external binaries (Pandoc, one2html) introduce drift risks.
MDV (Markdown Data & Visualization) is a tool that extends CommonMark Markdown with front-matter, fenced code blocks for charts/tables/stats, `:::` container directives for layout and styled regions, and auto-generated table of contents. It parses `.mdv` files and renders them to self-contained HTML with inline SVG charts (bar, line, pie) and CSS themes, requiring no JavaScript runtime in the output. The project is a TypeScript monorepo with three packages: `@mdv/core` (parser and renderer library), `@mdv/cli` (CLI with render, preview, and PDF export commands), and `mdv-vscode` (VS Code extension providing live side-by-side preview). The parser uses `markdown-it` as a base with a fence-aware preprocessor that handles `:::` directives and HTML comments correctly within code blocks. The renderer is designed for robustness: errors never crash the document, invalid front-matter renders a fatal banner, and chart data validation produces inline error messages. Security measures include escaping raw HTML, sanitizing style values, and preventing path traversal in data file references. The CLI supports live preview with file watching and auto-reload, and PDF export via headless Chromium (Puppeteer). The VS Code extension provides a debounced live preview that also refreshes on data file changes.
This repository provides an agent skill for attaching before/after screenshots and screen recordings to GitHub pull request descriptions. The core product is `skill/SKILL.md`, which instructs AI agents (like Claude Code) on a workflow: capture media using `agent-browser`, format them with the bundled zero-dependency script `skill/scripts/format.mjs`, and publish via `gh --attach`. The formatter generates deterministic markdown tables with image or video comparisons, and performs idempotent replacement of a marked block (`<!-- before-and-after:start/end -->`) in PR bodies, preserving all unrelated prose. The repository also includes a comprehensive verification suite (unit tests, local browser smoke, live GitHub smoke, and an agent smoke test) and a Next.js landing page at `site/`. The architecture is minimal: one dependency-free script, one skill document, and verification infrastructure. It does not wrap browser automation, capture, or media hosting—those are delegated to `agent-browser` and GitHub CLI.
Docgeni is a documentation generator for Angular component libraries and markdown documentation. It operates as a CLI tool (serve, build, init) and a set of libraries that parse Angular component metadata, build navigation, render markdown with custom extensions (embed, code groups, tabs), and generate a static or server-side rendered Angular site. The architecture is a monorepo with packages: @docgeni/cli (entry point), @docgeni/core (orchestration, builders, plugins), @docgeni/template (Angular site components and services), @docgeni/ngdoc (TypeScript parser for Angular decorators), @docgeni/toolkit (utilities for file system, git, templates), and @docgeni/create-docgeni (scaffolding). Key data flows: user provides markdown docs and Angular component libraries; the core builders parse docs, extract component metadata via ngdoc, generate navigation trees, and produce an Angular application with live examples, API tables, and multi-language support. External dependencies include Angular CLI, TypeScript compiler API, marked (markdown parser), Prism (syntax highlighting), Handlebars (templates), cosmiconfig (configuration), and chokidar (file watching). The generated site supports CSR, SSR, and SSG render modes, theming, and i18n.
django-wiki is a full-featured wiki system built as a reusable Django application. It provides hierarchical wiki pages with URL slug paths, revision control, attachments, images, notifications, and granular permissions. The architecture is modular, with a plugin system that allows extensions like macros, image galleries, and notification digests. Content is authored in Markdown with custom extensions for wiki links, tables of contents, and code highlighting. The system integrates with Django's authentication, sites framework, and admin interface. It is designed for production use with caching, spam protection, and i18n support. The codebase is well-structured with clear separation of concerns, though it carries some technical debt from vendored frontend assets and deprecated patterns.
Mindolph is a desktop knowledge management application built with JavaFX. It provides integrated support for mind maps, markdown, PlantUML diagrams, and CSV files, along with AI-powered features such as text reframing, summarization, and chat via various LLM providers. The application features a modular architecture with core, base, FX, and domain-specific modules, an event-driven communication system, a plugin/extension system for mind map operations, and a preference management system. Users can manage workspaces, search within files, and use reusable snippets.
LapisCV is a collection of Markdown-based resume templates and styling assets designed for use with Obsidian, Typora, and VSCode. It provides a base CSS file (main.css) that defines the core resume styling using CSS variables for easy theming, along with platform-specific overrides to adapt to each editor's rendering engine. Users edit the provided Markdown templates to create their resumes and export to PDF using their editor's built-in or plugin-based PDF export functionality. The project includes a Makefile to build distribution packages for each supported platform.
Readme.so is a Next.js web application that provides an online editor for generating README.md files. Users can select from predefined sections, edit their content using a Monaco Editor (desktop) or textarea (mobile), reorder sections via drag-and-drop, and download the final markdown. The application state is managed in React and persisted to localStorage with debounced saving. The frontend uses TailwindCSS for styling and integrates libraries like dnd-kit for drag-and-drop and react-markdown for preview. The app is statically exported and deployed via GitHub Pages.
Dante is a static site generator theme for Astro.js, designed for single-author blogs and portfolios. It provides a complete, production-ready setup with dark/light mode, responsive design, SEO metadata, RSS feed, sitemap, pagination, and a subscription form. The theme is built with Tailwind CSS v4 and uses Astro's content collections for Markdown-based blog posts, pages, and projects. Configuration is centralized in a single TypeScript file. The architecture follows Astro's SSG model with view transitions for a SPA-like experience. The codebase is well-structured, with reusable components and utility functions. It is a hybrid of a theme and a starter template, not a library or service.
QMarkdownTextEdit is a mature C++ Qt library providing a feature-rich markdown text editor widget, QMarkdownTextEdit, which extends QPlainTextEdit with live markdown syntax highlighting, code block syntax highlighting (for dozens of languages via a large hand-curated keyword dataset), line numbers with bookmark indicators, block (rectangular) selection, clickable links, and an integrated search/replace widget. The library is designed to be embedded into larger Qt applications such as QOwnNotes, Notes, and CuteMarkEd-NG. It supports both widget-based (QWidget) and Qt Quick (QML) integration through a registered QML type. The architecture is a single-library module with optional demo and QML example applications. The core components include the main editor widget, the markdown highlighter (which can be used independently on any QTextDocument), a separate search/replace widget (QPlainTextEditSearchWidget), and a line number area (LineNumberArea). The language-specific syntax highlighting data is generated in a single massive C++ file (qownlanguagedata.cpp) using a consistent pattern of init/load functions grouped by language. The library is built and installed via qmake (.pro/.pri) and CMake, with continuous integration across multiple Qt versions (5.9 to 6.10) on Linux, macOS, and Windows. The codebase is well-organized and demonstrates solid engineering practices: clear separation of concerns (highlighter, search widget, editor), support for internationalization (translation files for German, Spanish, Urdu, Chinese), and compatibility with both widget and QML interfaces. While the library is primarily a UI component, it also includes utility patterns like debounced search and regex support. The main risk is the maintenance burden of the enormous hand-curated syntax data file, which contains some minor errors and duplicates, and the lack of automated tests for the highlighting logic. Overall, this is a practical, production-grade text editor component with broad applicability in Qt projects requiring markdown or code editing capabilities.
This repository is a Next.js static site that serves as the companion website for the 'Complete Intro to Web Dev v3' course by Brian Holt. It renders lesson content from Markdown files, provides interactive code editors via Klipse, and includes navigation between lessons. The architecture is a standard Next.js application with static generation at build time. The codebase is well-organized with clear separation of concerns: data loading logic in `data/lesson.js`, layout components in `components/`, and page routing in `pages/`. While the site is tailored to this specific course, the lesson loading module is a reusable pattern that could be extracted for other course sites. The project is actively maintained with recent commits and a CI/CD pipeline for deployment to GitHub Pages.
This repository provides a Python CLI tool and Makefile pipeline to scrape all essays from Paul Graham's website (paulgraham.com), convert them to Markdown, and produce an EPUB ebook. The core logic resides in a single script (`graham.py`) that uses `requests`, `BeautifulSoup`, `html2text`, and `htmldate` to download, parse, and date-stamp each essay. A `Makefile` orchestrates the full build: creating a virtual environment, fetching essays, merging them with `pandoc`, and generating the final EPUB with a custom CSS and an iBooks dark-mode patch. The CI workflow (GitHub Actions) runs daily, detects new essays by comparing article counts, and automatically creates a release with the updated EPUB and metadata CSV. The architecture is straightforward—no web server, database, or tests—but the pipeline is robust and well-documented for its single purpose. While the scraper is tightly coupled to Paul Graham's site structure, several components (the iBooks patcher, the footnote conversion function, and the EPUB stylesheet) are cleanly isolated and reusable in other EPUB generation projects.
CtxPort is a browser extension and companion documentation website that lets users copy AI conversations (from ChatGPT, Claude, Gemini, DeepSeek, Grok, Doubao, GitHub) as structured Markdown Context Bundles. It solves 'context rot' by enabling portable, lossless migration of conversations between AI tools without uploading data to third parties. The architecture is a modern monorepo using pnpm workspaces and Turborepo, with separate packages for schema validation (Zod), markdown serialization, plugin-based extraction, and shared UI components. The browser extension (Manifest V3, WXT, React 19, Tailwind CSS 4) injects copy buttons and sidebar list icons into supported platforms, while the documentation website (Next.js + Nextra) provides multilingual (en/zh) user guides and feature descriptions. All processing is client-side; no data is uploaded. The codebase demonstrates strong engineering practices including a plugin system for extensibility, a strategy pattern for content flatteners, clean separation of concerns, and comprehensive CI/CD pipelines. Some fragility exists in DOM selectors and platform APIs, but the architecture is well-structured for adaptation.
This repository is a collection of Agent Skills for AI coding assistants (Claude Code, Codex, OpenCode) that enables them to interact with Obsidian vaults. It contains six skill definitions: obsidian-markdown (creating Obsidian Flavored Markdown with wikilinks, embeds, callouts, properties), obsidian-bases (creating database-like .base files with views, filters, formulas), json-canvas (creating visual .canvas files with nodes and edges), obsidian-cli (interacting with Obsidian via CLI for note management and plugin development), defuddle (extracting clean markdown from web pages), and knap (rendering Markdown templates from structured data). Each skill is a self-contained markdown file following the Agent Skills specification, providing detailed syntax, examples, and validation steps. The repository is purely documentation with no executable code, serving as a knowledge base that AI agents use to perform Obsidian-related tasks on behalf of users.
WPFDevelopers is a comprehensive WPF custom control library (NuGet package `WPFDevelopers`) that provides ~50+ themed UI controls, styles, effects, window chrome customization, system tray integration, screen capture, charts, loading indicators, and utility helpers. It also includes a demo application showcasing each control. The library targets a wide range of .NET versions (4.0 through 10.0) and integrates Win32 interop for advanced shell features. While containing some vendored code (Microsoft Expression Blend SDK) and occasional duplication, the library demonstrates solid engineering practices with reusable controls, attached behaviors, and a consistent theming infrastructure. It is actively maintained with CI builds for multiple frameworks.
This is a Vue 3 Single-Page Application (SPA) that provides an interactive form-based interface for generating Markdown badges using the shields.io service. The application allows users to generate repo metadata badges, generic static badges, package version badges, dynamic data badges, image markdown/HTML, and a catalogue of pre-made badges. The code is written in TypeScript with a clean separation of concerns: core logic modules handle badge generation and URL construction, Vue components manage UI, and a simple store persists user preferences via localStorage. The architecture is monolithic with client-side routing via Vue Router. The project demonstrates solid software engineering practices with comprehensive unit tests, a Makefile for common tasks, and GitHub Actions CI/CD for linting, testing, and deployment. While the codebase is well-structured and maintainable, it relies on the deprecated Vue CLI and some packages are several major versions behind (e.g., TypeScript 4.6, ESLint 8), indicating moderate technical drift. The application is actively maintained with recent commits and a clear release process.
Koodo Reader is a cross-platform ebook reader application supporting a wide range of formats (EPUB, PDF, MOBI, AZW3, TXT, FB2, CBR/CBZ, MD, DOCX, HTML, etc.). It is built as an Electron desktop app with a React/TypeScript frontend and a separate Go HTTP server for OPDS catalog serving and KOReader sync. The application provides a full-featured reading experience including bookmarks, notes, highlights, text-to-speech (with multiple voice engines), translation and dictionary lookup (via built-in and custom plugins), OCR for scanned PDFs, and cloud sync/backup across many providers (WebDAV, S3, OneDrive, Google Drive, Dropbox, etc.). It also includes a library management system with shelves, tags, search, and import from local files, folders, URLs, and OPDS catalogs. The architecture is a monolith with a clear separation between the Electron main process (Node.js) and the renderer (React), plus an optional Go server for network-facing features. The codebase is large and feature-rich but shows signs of technical debt: widespread use of deprecated React lifecycle methods, heavy reliance on opaque minified libraries (kookit-extra), frequent `as any` type casts, and mixed Chinese/English comments. Despite these issues, the application is actively maintained and offers a robust set of features for ebook enthusiasts.
This repository provides a GitHub Action that wraps the lychee link checker to validate links in Markdown, HTML, and text files. The action downloads and installs a specified version of lychee, runs it with configurable arguments, and processes the output to set exit codes and generate reports. The core action is well-designed with robust version handling and error processing, but the associated workflow files show signs of technical drift due to outdated action versions (e.g., actions/checkout@v7 which doesn't exist). The action is actively maintained with recent commits and automated version update workflows.
This repository is a knowledge base and documentation collection rather than a software application or data pipeline. It contains 117+ markdown files with interview questions and answers focused on Large Language Models (LLMs), Transformers, RAG, and Prompt Engineering. The content is curated by a single author and serves as a study resource for AI/ML engineers preparing for technical interviews. There is no executable code, data processing logic, or model training scripts present. The repository structure is flat and consistent, grouping questions into logical batches (e.g., QA_1-3.md, QA_4-6.md). While it lacks engineering artifacts like tests or CI/CD pipelines, the documentation quality is high, with clear formatting, consistent answer structures, and cross-references to related repositories. It is best suited for learners seeking structured knowledge rather than engineers looking for reusable code components. The content is static and does not require environment setup or data ingestion, making it highly reproducible in terms of accessibility. However, as a documentation repo, it does not offer the architectural depth or component reusability typical of software engineering projects. The 'active' maintenance status is derived from the provided metadata timestamp, though the content itself is static text.
This repository is an awesome list (curated resource collection) for the Marp Markdown Presentation Ecosystem. It categorizes and links to official Marp projects, community tools, themes, plugins, and example deployments. There is no executable application code, data pipeline, or library; the entire content is a single README.md file with markdown formatting and a CI workflow (awesome-lint + Prettier) to enforce quality. The repo is actively maintained with recent commits and clean CI. It serves as a central discovery hub for the Marp community, but offers no reusable software components or data assets.