A complete AI agency at your fingertips - From frontend wizards to Reddit community ninjas, from whimsy injectors to reality checkers. Each agent is a specialized expert with personality, processes, and proven deliverables. 🎭 The Agency: AI Specialists Ready to Transform Your Workflow A complete AI agency at your fingertips - From frontend wizards to Reddit community ninjas, from whimsy injectors to reality checkers. Each agent is a specialized expert with personality, processes, and proven deliverables. 🆕 There's an app now Agency Agents is a native app for macOS, Linux & Windows that browses the entire roster and installs it into Claude Code, Cursor, Codex, Gemini, Osaurus, and more — with a click. No clone, no scripts, and it auto-updates. → Download the latest release · agencyagents.app 🚀 What Is This? Born from a Reddit thread and months of iteration, The Agency is a growing collection of meticulously crafted AI agent personalities. Each agent is: 🎯 Specialized : Deep expertise in their domain (not generic prompt templates) 🧠 Personality-Driven : Unique voice, communication style, and approach 📋 Deliverable-Focused : Real code, processes, and measurable outcomes ✅ Production-Ready : Battle-tested workflows and success metrics Think of it as : Assembling your dream team, except they're AI specialists who never sleep, never complain, and always deliver. ⚡ Quick Start Option 1: Install the app (Recommended) The fastest way in — no clone, no terminal. Agency Agents is a native desktop app (macOS · Linux · Windows) that browses the whole roster and installs agents into Claude Code, Cursor, Codex, Gemini CLI, OpenCode, Qwen, and Osaurus for you, then keeps them up to date. ⬇ Download the latest release — or on a Mac: brew install --cask msitarzewski/agency-agents/agency-agents Prefer the command line? The script-based options below install the same agents. Option 2: Use with Claude Code # Install all agents to your Claude Code directory ./scripts/install.sh --tool claude-code # Or manually copy a category if you only want one division cp engineering/*.md ~/.claude/agents/ # Then activate any agent in your Claude Code sessions: # "Hey Claude, activate Frontend Developer mode and help me build a React component" Option 3: Use as Reference Each agent file contains: Identity & personality traits Core mission & workflows Technical deliverables with code examples Success metrics & communication style Browse the agents below and copy/adapt the ones you need! Option 4: Use with Other Tools (GitHub Copilot, Antigravity, Gemini CLI, OpenCode, OpenClaw, Cursor, Aider, Windsurf, Kimi Code, Codex, Osaurus, Hermes, Mistral Vibe, DeepSeek Harness) # Step 1 -- generate integration files for all supported tools ./scripts/convert.sh # Step 2 -- install interac
Editorial diagram design for Claude Code, Codex, GitHub Copilot, Factory Droid, and Pi. 42 diagram types. Self-contained HTML + SVG. No shadows. No Mermaid slop. https://cathrynlavery.github.io/diagram-design/ New in 2.0 — the Loop: flywheels with a shared-memory hub. The dashed lines are the write-backs. New in 2.3: semantic system patterns and optional accessible motion, while static output stays the default. New in 2.5.10: ten more layout grammars — Sankey, fishbone, Wardley map, kanban, user journey, deployment, dependency graph, UML class, story map, and database schema. Editorial diagram types for Claude Code, Codex, Factory Droid, Pi, and Agent Skills-compatible hosts. Self-contained HTML + SVG. No shadows. No Mermaid slop. Semantic patterns describe behavior separately from layout, so a queue, policy trace, or trust boundary can use the nearest existing type without expanding the type count. Static HTML remains the default; optional motion is available for ordered explanations. The skill also redraws draw.io , Mermaid, or Excalidraw sources at a chosen format, size, and detail level. No Figma. No generic rounded boxes. No 30-minute color-picking sessions. Project site: diagramdesign.dev Why I built it I write at littlemight.com (and run BestSelf.co on the side). Every time I needed a diagram — an architecture sketch, a flowchart, a pyramid of what matters most — I'd ask Claude and get back a generic rounded-box thing that looked nothing like the rest of the site. I'd either fight with Figma for 30 minutes or just skip the diagram. So I built a Claude Code skill for it. Editorial-quality visual types, matched to your brand in 60 seconds by reading your website. The highest-quality move is usually deletion. Every node earns its place. The accent color is reserved for the 1–2 things the reader should look at first. Target density: 4/10. What it makes Every visual type ships in three static variants: minimal light, minimal dark, and full-editorial. Open any of them directly in a browser. There is no build step, JavaScript, or external image dependency. Architecture Components + connections IT current-state Legacy landscape + modernization Flowchart Decision logic Sequence Messages over time <a href="https://raw.githubusercontent.com/cathrynlavery/diagram
Next generation e2e testing framework for web and mobile apps. https://tester.army/e2e e2e e2e is an end-to-end testing framework for web and mobile apps. Describe a goal in natural language and an agent drives the app to reach it. Check the result with locators and assertions in the same test. // tests/checkout.e2e.ts import { test, expect } from 'e2e'; test('a member upgrades to Pro', async ({ app, agent, screen }) => { await app.open('/settings/billing'); await agent.act('upgrade the workspace to the Pro plan'); await agent.assert('the invoice preview shows a prorated amount'); await expect(screen.getByRole('status')).toContainText('Pro'); }); An agent step that a later assertion verifies records its actions, and the next run replays them with no model calls until the app changes. Tests without agent steps need no model. Bring your own subscription, API key, or local model. Quick start npx e2e init init asks for an engine, web or mobile, and a model provider, then writes a config and an example test. The quickstart covers the rest. Packages Package What it does e2e The SDK, runner, and CLI. @e2e-dev/web Browser engine: Chromium, Firefox, and WebKit through Playwright. @e2e-dev/mobile iOS and Android engine: simulators and emulators through agent-device. @e2e-dev/github Reporter that posts results as a pull request comment. @e2e-dev/kernel Kernel hosted browsers for the web engine. @e2e-dev/eas EAS Simulators hosted iOS simulators and Android emulators for the mobile engine. @e2e-dev/decision Decision-model executors for bounded semantic actions and assertions. Documentation e2e.tester.army/docs . The e2e package ships every page, so coding agents can read them offline in node_modules/e2e/docs . Contributing See CONTRIBUTING.md . Questions go to Discord . Security Please don't open public issues for security vulnerabilities. Follow SECURITY.md and report them to [email protected] . Telemetry The CLI sends anonymous usage data, such as which command
World's first open-source, agentic video production system. 12 production pipelines, 100+ tools, 700+ agent skill and production-knowledge files. Turn your AI coding assistant into a full video production studio. https://www.openmontage.video/ Monty the Clapper — the official mascot of OpenMontage OpenMontage The first open-source, agentic video production system. Paste A Video · Quick Start · Try These Prompts · Pipelines · How It Works · Sponsors · Providers · Review Guide · Agent Guide Follow The Build Sponsors Want to support OpenMontage? Sponsor the project . Click to collapse Bloome lets multiple AI agents (Claude, ChatGPT, DeepSeek, and more) collaborate in one conversation for agentic video pipelines. It has zero setup, runs in the cloud, works on web and mobile, and lets you share a configured agent with your whole team. Try Bloome . Atlas Cloud is a full-modal AI inference platform that gives developers a single AI API for video generation, image generation, and LLM APIs. Instead of managing multiple vendor integrations, you connect once and get unified access to 300+ curated models across all modalities. Check out Atlas Cloud's new coding plan promotion for more budget-friendly API access. Turn your AI coding assistant into a full video production studio. Describe what you want in plain language — your agent handles research, scripting, asset generation, editing, and final composition. Important distinction: OpenMontage can make image-based videos, but it can also make a real video video for free/open-source workflows: the agent builds a corpus from free stock footage and open archives, retrieves actual motion clips, edits them into a timeline, and renders a finished piece. That is not the usual "animate a handful of stills and call it video" trick. <p
The AI that really does things. Any OS. Any Platform. The lobster way. 🦞 https://openclaw.ai OpenClaw 🦞 — Your assistant, on your devices, in your chats OpenClaw is an open-source AI assistant that runs on your own computer and meets you in the channels you already use: Discord, iMessage, Slack, Teams, Telegram, WhatsApp, and 20+ more, plus native apps for macOS, iOS, Android, Windows, and Linux. One Gateway runs it as a personal assistant on a laptop or as a shared team deployment ; configuration is the only difference. Yours, with no catch. State, memory, and credentials live on your hardware. Models and agent harnesses (Claude, Codex, local models) are plugins you can swap without changing anything else. Your prompts go to the model provider and chat platforms you configure, plus any diagnostics export you enable yourself; by default OpenClaw itself phones home for nothing but a daily version check, anonymous feature statistics are opt-in, and update.checkOnStart: false disables both ( what OpenClaw sends ). OpenClaw is stewarded by the OpenClaw Foundation , an independent 501(c)(3), and has no paid tier, hosted service, or token. The architecture case — trusted gateway, untrusted execution, deterministic policy — is in Why OpenClaw . Website · Docs · Getting started · Why OpenClaw · FAQ · Vision · DeepWiki Install The installer supports macOS, Linux, and Windows. It provisions a supported Node.js runtime when needed. # macOS / Linux / WSL2 curl -fsSL https://openclaw.ai/install.sh | bash # Windows PowerShell iwr -useb https://openclaw.ai/install.ps1 | iex Already manage Node.js? Install the published package instead (Node 24.16+ or 26.1+; Node 26 recommended): npm install -g openclaw@latest --allow-scripts=openclaw That command is for npm 12 or npm 11.16+. On npm 11.15 and earlier, omit --allow-scripts=openclaw . See the installation guide for the lifecycle script contract, Docker, Nix, and other deployment paths. Quick start On a fresh install, the installer scripts start onboarding automatically. Complete the wizard they open. If you installed the package directly with npm, pnpm, or Bun, run: openclaw onboard --install-daemon After onboarding: openclaw gateway status openclaw dashboard Onboarding verifies model access, creates the workspace, and configures the Gateway. The last command opens the Control UI; send a message there to confirm the assistant is working. See the getting started guide for channel setup and troubleshooting. How it fits together The Gateway is the local control plane for sessions, tools, events, and channel connections. The <a href=
Skills for Real Engineers. Straight from my .agents directory. https://aihero.dev/skills Skills For Real Engineers My agent skills that I use every day to do real engineering - not vibe coding. Developing real applications is hard. Approaches like GSD, BMAD, and Spec-Kit try to help by owning the process. But while doing so, they take away your control and make bugs in the process hard to resolve. These skills are designed to be small, easy to adapt, and composable. They work with any model. They're based on decades of engineering experience. Hack around with them. Make them your own. Enjoy. If you want to keep up with changes to these skills, and any new ones I create, you can join ~60,000 other devs on my newsletter: Sign Up To The Newsletter Installation (30-second setup) Two ways in, two philosophies. The Claude Code plugin installs the whole set as a managed, read-only bundle that updates when I ship, so you subscribe rather than fork. skills.sh copies editable skill files into your project, so you can hack on them and make them your own. Pick one: installing both leaves you with every skill twice. 1. Get the skills Claude Code claude plugins install mattpocock-skills Or, from inside a session: /plugin install mattpocock-skills It's in Claude Code's official marketplace, so there's nothing to add first, and updates arrive automatically. Codex, and other agents npx skills@latest add mattpocock/skills Pick the skills you want, and which coding agents to install them on. The installer lets you choose which skills to take, so make sure setup-matt-pocock-skills is one of them. A native Codex plugin is on the roadmap (see .agents/adr/0002-ship-as-a-claude-code-plugin.md ). For tinkerers Use the same installer, on any agent, including Claude Code: npx skills@latest add mattpocock/skills It writes the skills into your repo as ordinary files you own and can edit. Nothing updates behind your back; pull my latest changes when you want them with npx skills update . 2. Run /setup-matt-pocock-skills In your agent, run it once per repo. It will: Ask you which issue tracker you want to use (GitHub, Linear, or local files) Ask you what labels you apply to tickets when you triage them ( /triage uses labels) Ask you where you want to save any docs we create 3. Bam - you're ready to go. Why These Skills Exist I built these skills as a way to fix common failure modes I see with Claude Code, Codex, and other coding agents. #1: The Agent Didn't Do What I Want "No-one knows exactly what they want" David Thomas & Andrew Hunt, The Pragmatic Programmer The Problem . The most common failure mode in software development is misalignment. You think the dev knows what you want. Then you see what they've built - and you realize it didn't understand you at all. This is just the same in the A
[ECCV 2026 Best Paper Award Candidate] LingBot-Map: Geometric Context Transformer for Streaming 3D Reconstruction LingBot-Map: Geometric Context Transformer for Streaming 3D Reconstruction Robbyant Team https://github.com/user-attachments/assets/fe39e095-af2c-4ec9-b68d-a8ba97e505ab 🗺️ Meet LingBot-Map! We've built a feed-forward 3D foundation model for streaming 3D reconstruction! 🏗️🌍 LingBot-Map has focused on: Geometric Context Transformer : Architecturally unifies coordinate grounding, dense geometric cues, and long-range drift correction within a single streaming framework through anchor context, pose-reference window, and trajectory memory. High-Efficiency Streaming Inference : A feed-forward architecture with paged KV cache attention, enabling stable inference at ~20 FPS on 518×378 resolution over long sequences exceeding 10,000 frames. State-of-the-Art Reconstruction : Superior performance on diverse benchmarks compared to both existing streaming and iterative optimization-based approaches. 📑 Table of Contents Click to expand 📰 News 📋 TODO ⚙️ Installation 📦 Model Download 🚀 Quick Start 🎬 Interactive Demo ( demo.py ) Try the Example Scenes Streaming with Keyframe Interval Windowed Inference (for long sequences, >3000 frames) Sky Masking Visualization Options Performance & Memory 🎥 Offline Rendering Pipeline ( demo_render/batch_demo.py ) 📜 License 📖 Citation ✨ Acknowledgments 📰 News 2026-06-28 — Fixed an SDPA KV cache bug. The SDPA backend now performs better on
ArtCraft is an intentional crafting engine for artists, designers, and filmmakers https://getartcraft.com ArtCraft The IDE for artists. https://github.com/user-attachments/assets/7339bd09-3e0d-44a7-a024-af9de64e4c11 Watch the two-minute ArtCraft demo on YouTube Download ArtCraft · GitHub releases · Build from source ArtCraft is the IDE for interactive AI image and video creation. Compose in 2D, stage scenes in 3D, and choose the models that fit your work. Turn prompting into crafting with visual tools for precise, repeatable results. Show, Don't Tell: Advanced Crafting Features Artists need control over composition, character identity, and camera placement. Build the scene before you generate it. Click any preview to view it at full size. Feature Preview Image to Location Place virtual actors in a consistent environment and plan multiple shots in the same room. 3D Image Compositing Layer backdrops, foregrounds, and props in 3D to build compositions with depth. 2D Image Compositing Compose a scene with image layers, background removal, and drawing tools. Image to 3D Mesh Turn an image into a 3D object you can position, rotate, and frame precisely. Character Posing Pose characters and set your camera before generating the final shot. Scene Blocking with Kitbashing Combine 3D asset kits to control camera angles, object placement, and depth. Character Identity Transfer Use a posed mannequin to guide the placement and pose of your character. Background Removal Isolate subjects to use as props, layers, or backdrops in 2D and 3D scenes. Mixed Asset Crafting Combine image cutouts, worlds, and 3D meshes in one scene. More previews are coming for scene blocking, canvas editing, and scene relighting.
VoiceStudio is the open-source, fully-local ElevenLabs alternative — voice cloning, voice design, video dubbing, dictation, transcription & audiobook creation in 646 languages. https://voicestudio.sh VoiceStudio Open-source voice cloning, voice design, video dubbing, dictation, transcription & audiobook creation in 646 languages. Website · Download · Get started · Docs · Discord · 简体中文 Your voice. Your workflow. Create Produce Connect Clone a voice or design your own Dub videos with timed speech Local API & MCP for agents Dictate with a floating widget Stories, audiobooks & batch jobs Optional remote workers Start with VoiceStudio (default, powered by k2-fsa/OmniVoice), or choose another engine. Features & engine catalog . Local workflows run on your hardware. Remote services are optional; usage analytics requires consent. Explore the workspaces · Clone, dub, design & models Voice cloning Video dubbing Voice design Local models Get started One-command install (macOS / Linux) # Latest Electron release curl -fsSL https://voicestudio.sh/install | sh # A specific published Electron release (replace X.Y.Z) curl -fsSL https://voicestudio.sh/install | sh -s -- --version X.Y.Z # Build current main and install the desktop app curl -fsSL https://voicestudio.sh/install | sh -s -- --main # Uninstall the app, keeping your data curl -fsSL https://voicestudio.sh/install | sh -s -- --uninstall Release downloads require curl and a SHA-256 tool. --main requires Git, Node.js 22+, Bun, Rust/Cargo, and platform build tools; see installer prerequisites and behavior . The installer preserves your settings, projects, and models. Older versions must contain Electron packages; it never falls back to archived Tauri builds. Download from Releases , then follow your platform guide: macOS · Windows · Linux<
Reverse engineer anything with agents, from app behavior down to native binaries. English · 简体中文 · 日本語 · 한국어 · العربية REA: Reverse Engineer Anything One MCP for reverse engineering across binaries, applications, and runtime behavior. See a feature you like. Understand how it works, down to the binary level. Quick start · Current status · Investigation model · Tool catalog · Roadmap · How it works npx rea-agents setup Join the Reverse Engineering Community Discord · Q&A · Show and Tell See a feature in an app that you want in your own product? Ask your agent to investigate it with REA. It can inspect the app without its source code, explain how the feature works, show the evidence, and build a version for your project. REA connects your agent to tools for inspecting native binaries, JavaScript and Electron apps, .NET assemblies, and websites. You can also use the same tools from your terminal. Analysis runs locally, and results include the evidence and limitations behind each conclusion. Setup registers REA with your agent and installs matching workflow instructions. Native analysis can use an existing Hopper or Ghidra installation; setup can optionally install Hopper with approval. Static JavaScript analysis needs neither engine. Quick start Run setup (recommended) Set up REA with your agent: npx rea-agents setup Choose which supported agents should use REA, then review the exact paths and changes before approving. Existing REA registrations are selected by default; newly detected agents are available to select, but detection alone does not select them. Setup adds MCP access and REA's guided workflow for selected agents. Hopper is a separate optional choice with its own consent. Setup can also record an existing Ghidra installation. Setup shows its changes before applying them and backs up existing configuration. See Installation and setup for requirements and setup options. AI Coding Assistants (optional) Add the skill to your AI coding assistant for richer context: npx skills add morluto/rea --skill reverse-engineer-anything The skill provides REA's investigation workflow. Run setup ab
Scale computer-use 2.0 with open-source drivers, cross-OS fleets, and benchmarks for training, evaluation, and data generation. https://cua.ai Give AI agents computers they can use. Cua Spaces gives your agents full desktops on your Mac and on machines you own. This repository also holds Cua Driver for desktop automation, Lume for local VMs, CUA-S1 decision models and Cua Bench for evaluating computer-use agents. Get Cua Spaces Choose your path Cua Spaces: Install the app and run your first Space . Cua Driver: Operate Calculator and verify its result . Lume: Create a Tahoe VM and connect over SSH . Cua SDK and CLI: Install cua and create a local sandbox . CUA-S1: Explore small, specialized models for computer-use decisions . Cua Bench: Create and verify a simulated task . Bring your own agent and model, or explore CUA-S1 for specialized decisions. Cua provides the computer and automation tools. Computer-Use 2.0 describes an agent moving between code, APIs, and graphical interfaces within the same task. Cua Spaces Cua Spaces is a desktop app that gives your agents full desktops. Each desktop is a Space: a macOS VM built locally on your Mac, or a Linux or Omarchy image. Spaces run on your Mac, on other machines you own, and in your own cloud account (AWS, Google Cloud or Modal), and the app keeps them in your menu bar and notch. Teleport. Move a signed-in app, such as Chrome or Slack, into a Space and it opens there still signed in. Your sessions stay in the Cua Keyvault, encrypted on your Mac, and reach a Space only after you approve. Multiplayer. You and your agents work on the same desktop, each with your own cursor. Step in to make a choice, then hand the desktop back. Agent-ready images. Spaces images ship with cua-spacesd , so agents get processes, files, screenshots and input as soon as a Space starts. https://github.com/user-attachments/assets/a2ccc86b-10d0-48c0-bee6-7ae652ba1c59 Install on macOS 26 or later curl -fsSL https://cua.ai/install.sh | sh On macOS the installer selects the Cua Spaces app b
The design language that makes your AI harness better at design. https://impeccable.style Impeccable Design guidance for AI coding agents. 1 skill, 24 commands, live browser iteration, and 61 deterministic detector rules for AI-generated frontend design. Quick start: From your project root, run npx impeccable install , then run /impeccable init inside your AI coding tool. Full docs: impeccable.style . Why Impeccable? Anthropic's frontend-design was the first widely-used design skill for Claude. Impeccable started from there. Every model trained on the same SaaS templates. Skip the guidance and you get the same handful of tells on every project: Inter for everything, purple-to-blue gradients, cards nested in cards, gray text on colored backgrounds, the rounded-square icon tile above every heading. Impeccable adds: One setup flow. /impeccable init records durable product truth in PRODUCT.md , so later commands know the audience, purpose, operating context, constraints, voice, and evidence without confusing those facts with surface-level visual direction. 24 commands. A shared design vocabulary with your AI: polish , audit , critique , distill , animate , bolder , quieter , and more. 61 deterministic detector rules plus LLM-only critique checks. The CLI and browser extension run the deterministic rules with no LLM and no API key. What's Included The Skill: impeccable The skill installs as one command: /impeccable <command> <target> Start every new project with: /impeccable init init inspects the project, asks only for material gaps in durable product truth, and writes PRODUCT.md . Visitor mode and visual direction are chosen later for each surface; incumbent or newly built visual systems are recorded separately in DESIGN.md . 24 Commands All commands are accessed through /impeccable : Command What it does /impeccable craft Full shape-then-build flow with visual iteration /impeccable init One-time setup: gather durable product context, write PRODUCT.md , configure live mode when applicable, recommend next steps /impeccable document Generate root DESIGN.md from existing project code /impeccable extract Pull reusable components and tokens into the design system /impeccable shape Plan UX/UI before writing code /impeccable critique UX design review: hierarchy, clarity, emotional resonance /impeccable audit Run technical quality checks (a11y, performance, responsive) /impeccable polish Final pass, design system alignment, and shipping readiness /impeccable bolder Amplify boring designs /impeccable quieter Tone down overly bold designs /impeccable distill<
Stremio - Freedom to Stream https://web.stremio.com Stremio Web Freedom to Stream — the official web UI of Stremio , a modern media center that's a one-stop solution for your video entertainment. 🌐 Open the Web App · Website · Report a bug ✨ Features 🧩 Addon-powered — discover movies, series and channels from catalogs provided by addons 🔄 Sync everywhere — your library and Continue Watching follow your Stremio account across devices 📺 Casting — play on the big screen via Chromecast 💬 Subtitles — addon-provided or local, with customizable styling ⌨️ Keyboard-first player — full playback control without touching the mouse 🌍 50+ languages — community-translated via stremio-translations 📱 Installable — runs as a standalone PWA 📸 Screenshots Discover Meta Details 🛠 How it works The UI (this repo) is a React app, but the brains live in stremio-core — Stremio's Rust engine compiled to WebAssembly and running in a Web Worker. The UI renders state, the core computes it. Playback goes through stremio-video , which picks the right player implementation for the environment. flowchart LR UI["React UI<br>(this repo)"] <--> Core["stremio-core<br>Rust → WASM, Web Worker"] Core <--> API["Stremio API"] Core <--> Addons["Addons"] UI --> Video["stremio-video"] 🚀 Getting started You'll need Node.js 22+ and pnpm 11+. pnpm install pnpm start The dev server runs at http://localhost:8080 . Command Description pnpm start Development server with hot reload pnpm run start-prod Development server in production mode pnpm run build Production build pnpm test Run tests pnpm run lint Lint the source pnpm run scan-translations Check for missing translation keys 🐳 Docker docker build -t stremio-web . docker run -p 8080:8080 stremio-web 🤝 Contributing Bug reports and pull requests are welcome — good first issue is a great place to start. Want Stremio in your language? Contribute to stremio-translations . Please read
跨平台 Xcode 替代方案。在 Linux、Windows、macOS 上使用 SwiftPM 构建并部署 iOS 应用。https://xtool.sh xtool 跨平台 Xcode 替代方案。在 Linux、Windows 和 macOS 上使用 SwiftPM 构建并部署 iOS 应用。概述 xtool 是一个跨平台（Linux/WSL/macOS）工具，采用开放标准复刻 Xcode 的功能。✅ 将 SwiftPM 包构建为 iOS 应用 ✅ 对 iOS 应用进行签名和安装 ✅ 以编程方式与 Apple Developer Services 交互 快速开始 按照指南安装 xtool 安装（Linux/Windows） 安装（macOS） 按照教程创建并运行你的第一个由 xtool 驱动的应用！示例 截图 命令行界面 $ xtool --help OVERVIEW: Cross-platform Xcode replacement USAGE: xtool <subcommand> OPTIONS: -h, --help Show help information. CONFIGURATION SUBCOMMANDS: setup Set up xtool for iOS development auth Manage Apple Developer Services authentication sdk Manage the Darwin Swift SDK DEVELOPMENT SUBCOMMANDS: new Create a new xtool SwiftPM project dev Build and run an xtool SwiftPM project ds Interact with Apple Developer Services DEVICE SUBCOMMANDS: devices List devices install Install an ipa file to your device uninstall Uninstall an installed app launch Launch an installed app See 'xtool help <subcommand>' for detailed help. 库 xtool 包含一个库，你可以在自己的应用中使用它与 Apple Developer Services、iOS 设备等进行交互。你可以通过将 XKit 添加为 SwiftPM 依赖来使用它。
阿波罗 11 号指令舱和登月舱所使用的原始 Apollo 11 Guidance Computer (AGC) 源代码。Apollo-11 🌐 Azerbaijani , bahasa Indonesia , Basa Jawa , Català , Čeština , Dansk , Deutsch , English , Español , Français , Galego , Italiano , Kurdî , Lietuvių , Mongolian , Nederlands , Norsk , Polski , Português , Română , Suomi , Svenska , tiếng Việt , Türkçe , Ελληνικά , Беларуская мова , Русский , Українська , العربية , فارسی , नेपाली भाषा <a href="https://raw.githubusercontent.com/chrislgarry/Apollo-11
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond. https://ecc.tools Language: English | Português (Brasil) | 简体中文 | 繁體中文 | 日本語 | 한국어 | Türkçe | Русский | Tiếng Việt | ไทย | Deutsch | Español | Українська | Polski Warning Official sources only. Install ECC only from verified channels: the GitHub repository github.com/affaan-m/ECC , the npm packages ecc-universal and ecc-agentshield , the GitHub App , the plugin slug ecc@ecc , and the project website ecc.tools . Third-party re-uploads and unofficial mirrors are not maintained or reviewed by the project and may contain malware. Install with Claude Code Use the guided setup or native plugin commands . Both install the same ecc@ecc plugin. Choose one and do not stack a full manual Claude install on top. ECC Pro + GitHub App Install free · Private repos from $19/seat/mo Sponsor ECC Fund the open-source project Community Discord · Q&A · Show and Tell
Tool for automatic PS5 executables porting to Linux and Windows https://discord.gg/BHFztBPUe About Tool for automatic executables porting to Linux and Windows. Includes a relinker that converts executable to the target system's native format and implementations of system prx libraries suitable for dynamic linking. No emulation or separate runtime process. Usage , Build instructions , Technical debt of the project , code style conventions , contributing Status * System libraries: percentage of the functions known to the project so far (declared in core/libs/prx ), not of every PS5 system function. The total grows as more functions are declared. List of verified games Dreaming Sarah (2D platformer) runs at a stable 60 fps on a GTX 1050 Ti / i5-7500 3.4GHz. Unsupported or unexpected states strictly throw std::runtime_error . what() is printed to stderr and the process terminates. The shader recompiler successfully produces SPIR-V (validated via Spirv-Tools when built with ANYPS5_ENABLE_SPIRV_TOOLS ). Compatibility See the game compatibility list for tested games and known issues. Input mapping SDL-mapped game controllers are supported, including analog sticks and triggers. Keyboard and mouse controls can be configured with an anyps5-input.ini file. See input mapping for the supported devices and configuration format. Disclaimer This project is intended for interoperability, research, preservation, and compatibility purposes. It does not include, distribute, or require copyrighted software, firmware, cryptographic keys, or proprietary libraries. Users are responsible for ensuring that any binaries used with this project are obtained and used in accordance with applicable laws and their respective license terms. License This project is licensed under the GNU General Public License version 2 only.
Use Garry Tan's exact Claude Code setup: 23 opinionated tools that serve as CEO, Designer, Eng Manager, Release Manager, Doc Engineer, and QA gstack "I don't think I've typed like a line of code probably since December, basically, which is an extremely large change." — Andrej Karpathy , No Priors podcast, March 2026 When I heard Karpathy say this, I wanted to find out how. How does one person ship like a team of twenty? Peter Steinberger built OpenClaw — 247K GitHub stars — essentially solo with AI agents. The revolution is here. A single builder with the right tooling can move faster than a traditional team. I'm Garry Tan , President & CEO of Y Combinator . I've worked with thousands of startups — Coinbase, Instacart, Rippling — when they were one or two people in a garage. Before YC, I was one of the first eng/PM/designers at Palantir, cofounded Posterous (sold to Twitter), and built Bookface, YC's internal social network. gstack is my answer. I've been building products for twenty years, and right now I'm shipping more products than I ever have. In the last 60 days: 3 production services, 40+ shipped features, part-time, while running YC full-time. On logical code change — not raw LOC, which AI inflates — my 2026 run rate is ~810× my 2013 pace (11,417 vs 14 logical lines/day). Year-to-date (through April 18), 2026 has already produced 240× the entire 2013 year . Measured across 40 public + private garrytan/* repos including Bookface, after excluding one demo repo. AI wrote most of it. The point isn't who typed it, it's what shipped. The LOC critics aren't wrong that raw line counts inflate with AI. They are wrong that normalized-for-inflation, I'm less productive. I'm more productive, by a lot. Full methodology, caveats, and reproduction script: On the LOC Controversy . 2026 — 1,237 contributions and counting: 2013 — when I built Bookface at YC (772 contributions): Same person. Different era. The difference is the tooling. gstack is how I do it. It turns Claude Code into a virtual engineering team — a CEO who rethinks the product, an eng manager who locks architecture, a designer who catches AI slop, a reviewer who finds production bugs, a QA lead who opens a real browser, a security officer who runs OWASP + STRIDE audits, and a release engineer who ships the PR. Twenty-three specialists and eight power tools, all slash commands, all Markdown, all free, MIT license. This is my open source software factory. I use it every day. I'm sharing it because these tools should be available to everyone. Fork it. Improve it. Make it yours. And if you want to hate on free open source software — you're welcome to, but I'd rather you just try it first. Who this is for: Founders and CEOs — especially technical ones who still want to ship First-time Claude Code users — structured roles instead of a blank prompt Tech leads and staff engineers — rigorous review, QA, and release automation on every PR Quick start Install gstack (about 30 seconds of setup — see below) Run /office-hours — describe what you're building Run /plan-ceo-review on any feature idea Run /review on any branch
The Office Harness for AI Agents — Spreadsheets, Docs, Slides, Canvas, Relational Tables, and PDF in one runtime. https://docs.univer.ai The Office Harness for AI Agents Spreadsheets · Documents · Presentations · Bases · Boards · PDFs High-performance, fully customizable Office SDK Build embeddable productivity experiences with a plugin architecture, Canvas-based rendering, a formula engine, and one Facade API that works in the browser and on Node.js. English | 简体中文 | 繁體中文 | 日本語 | 한국어 | Español 🌐 Website | 📖 Documentation | ✨ Showcase | 📘 API Reference | 📝 Blog ✨ What is Univer? Univer is an open-source SDK for creating office applications inside your own product. It gives you the building blocks for spreadsheet, document, and presentation experiences without forcing you into a hosted app or a fixed UI. Use Univer when you need to: Embed spreadsheet or document editing into a SaaS product, internal tool, BI workflow, or AI application. Run workbook/document processing on the server with the same architecture used in the browser. Compose only the features you need through plugins or start quickly with presets. Extend behavior through custom plugins, commands, services, UI components, and Facade APIs. Univer is not a spreadsheet file viewer only. It is a framework for building your own productivity surface. Across the Univer product family , Office tools share a runtime for storage and computation. Content can be composed and embedded across tools, with linked data and references updating together. People and AI agents can work in the same files. See the capability matrix for product coverage and Open Source and Pro for this repository's scope. Build a collaborative tool with Univer Office SDK Watch the demo Built with Univer Office SDK Featured example: Univer Workspace Univer Workspace is an open-source, self-hostable wo
Hindsight: Agent Memory That Learns https://hindsight.vectorize.io/ Documentation • Integrations • Cookbook • Benchmarks • Paper • Hindsight Cloud What is Hindsight? Hindsight™ is an agent memory system built to create smarter agents that learn over time. Most agent memory systems focus on recalling conversation history. Hindsight is focused on making agents that learn, not just remember. It eliminates the shortcomings of alternative techniques such as RAG and knowledge graph and delivers state-of-the-art performance on long term memory tasks. Contents Memory Performance & Accuracy Quick Start — server · clients · platforms · embedded Adding Hindsight to Your Agent — LLM Wrapper · integrations · coding agents · MCP Core Concepts — memory types · retain / recall / reflect · observations · mental models & knowledge pages · banks Use Cases Running in Production Resources Memory Performance & Accuracy Hindsight is the most accurate agent memory system ever tested according to benchmark performance. It has achieved state
Multi-agent harness that runs Claude Code and Codex together as one system https://openrig.dev OpenRig A harness wraps a model. A rig wraps your harnesses. Define your agent team in YAML, boot it with one command. Claude Code and Codex in the same rig, managed as one system. OpenRig turns AI coding agents from a pile of terminal sessions into a persistent, organized team. Talk to a lead agent about the outcome you want; it can coordinate specialists across teams and bring you results and decisions that need your attention. Start with a repository and one useful change, then keep the team's work and context at the same addresses. Install and first run Requires Node.js 22 or 24 and tmux, on macOS or Linux. On a Mac with Apple silicon, use Node.js 22 ( compatibility history ). Native Windows is not supported yet, and WSL2 has not been tested. Launching a rig writes provider hooks and workspace trust settings. Before running the commands below, read what OpenRig changes on your machine and back up the relevant files. npm install -g @openrig/cli rig setup --dry-run To install with Bun instead, run bun add -g @openrig/cli . OpenRig still runs on Node.js, so install Node.js 22 as well. Bun may block this package's postinstall script, in which case the Node.js and SQLite check described under what OpenRig changes on your machine does not run at install time. Review setup's plan before applying rig setup : it checks both native harnesses and cmux. This starter requires tmux and authenticated Codex; the other harness and terminal provider are optional for its repository task. Before launching, ask your agent to configure your chosen permissions : keep prompts, remember selected commands, or deliberately choose broader access. The agent handles setup and verification; OpenRig's shipped defaults stay unchanged. Check prerequisites in your launch shell: tmux -V codex --version codex login status Resolve missing tools or login before continuing. From your repository, inspect the plan before launching the two Codex seats, an owner and a checker: cd /path/to/your/repository rig up first-project --cwd . --plan rig up first-project --cwd . rig tui --shared The kernel provides separate operational support and the shared dashboard. To detach without stopping the dashboard, press Ctrl-b then d; rig tui --shared returns to that view. Plain rig tui opens an independent view. Closing a viewing terminal does not mean you should relaunch the team. Check project-seat readiness with rig ps --nodes --rig first-project and resolve any authentication, trust or permission prompt before assigning work. Then give the owner one bounded outcome from your repository: rig send dev-owner@first-project 'Implement <one useful change>. Track the task in the queue and return its ID. Keep it local, verify the behavior, ask dev-check@first-project to check the exact candidate, and record the result and how I can try it.' rig queue list --d
Self-hosted deployment platform https://openship.io Openship Open-source, self-hostable deployment platform with built-in CI/CD. Point it at a repo — it builds, ships, routes, and TLS-terminates your app. Drive it from a desktop app, web dashboard, or CLI. Quick Start · How It Works · Interfaces · Docs · Contributing Quick Start There's one decision to make first: how you run Openship itself (the control plane). Everything else is the same afterwards. If you're… Run Openship as Where your apps run Solo, one machine, no ops Desktop app A server you connect over SSH, or Openship Cloud A team — or you want push-to-deploy / to host apps on your own box Self-hosted server ( openship up ) On that box (Compose mode) — or out to another server / Cloud (bare mode) Not interested in running anything Openship Cloud Managed sandboxes, zero setup Tip Solo? Use the desktop app. It runs Openship's control plane on your own machine only while the app is open — nothing is left running on an always-on server, nothing is exposed publicly. You only need an always-on server install once you want push-to-deploy (CI/CD) , team access , or to host apps on that box — the things that need a public, always-on endpoint. Solo — desktop app The control plane runs locally and drives your servers over SSH. No login, no terminal, no public surface — download, open, done: Platform Download macOS (Apple Silicon) Openship-arm64.dmg macOS (Intel) <a h
The open-source CapCut alternative https://opencut.app OpenCut A free and open source video editor for web, desktop, and mobile. Status OpenCut is being rewritten from the ground up. What's coming: An Editor API First-class third party plugins (made possible by a plugin-first architecture) Desktop, mobile, and browser from one codebase (Rust core) MCP server (for AI agents) Headless mode (automation, batch rendering) A scripting tab directly in the editor You can still find the previous version at opencut-app/opencut-classic , which is the one to reach for today. opencut.app still runs the classic version. The rewrite will live at new.opencut.app until it's ready to take over. Development Install proto if you haven't already: Linux, macOS, WSL: bash <(curl -fsSL https://moonrepo.dev/install/proto.sh) Windows (PowerShell): irm https://moonrepo.dev/install/proto.ps1 | iex If shims fail to run, allow local scripts for your user: Set-ExecutionPolicy -Scope CurrentUser RemoteSigned From the repo root: proto use # installs the tools pinned in .prototools moon run web:dev # localhost:5173 moon run api:dev # localhost:8787 moon run desktop:dev # see apps/desktop/README.md Contributing We're not set up to take outside contributions yet while the architecture is being designed. If you want to follow along, ask questions, or just hang out, join the Discord or open an issue . Sponsors OpenCut is supported by companies that believe in open source creator tools. fal.ai : Generative image, video, and audio models all in one place. Want your logo here? Reach out at [email protected] . License MIT
Context window optimization for AI coding agents. Sandboxes tool output (98% reduction), persists session memory, and enforces routing across 17 platforms via MCP + hooks. https://context-mode.com Context Mode The other half of the context problem. Used across teams at The Problem Every MCP tool call dumps raw data into your context window. A Playwright snapshot costs 56 KB. Twenty GitHub issues cost 59 KB. One access log — 45 KB. After 30 minutes, 40% of your context is gone. And when the agent compacts the conversation to free space, it forgets which files it was editing, what tasks are in progress, and what you last asked for. On top of that, the agent wastes output tokens on filler, pleasantries, and verbose explanations — burning context from both sides. How Context Mode Solves It Context Mode is an MCP server that solves all four sides of this problem: Context Saving — Sandbox tools keep raw data out of the context window. 315 KB becomes 5.4 KB. 98% reduction. Session Continuity — Every file edit, git operation, task, error, and user decision is tracked in SQLite. When the conversation compacts, context-mode doesn't dump this data back into context — it indexes events into FTS5 and retrieves only what's relevant via BM25 search. The model picks up exactly where you left off. If you don't --continue , previous session data is deleted immediately — a fresh session means a clean slate. Think in Code — The LLM should program the analysis, not compute it. Instead of reading 50 files into context to count functions, the agent writes a script that does the counting and console.log() s only the result. One script replaces ten tool calls and saves 100x context. This is a mandatory paradigm across all 17 supported clients, plus the OpenClaw gateway integration: stop treating
Open source Ghostty-based macOS terminal with vertical tabs and notifications for AI coding agents. Built for multitasking, organization, and programmability. https://cmux.com cmux A Ghostty-based macOS terminal with vertical tabs and notifications for AI coding agents English | 日本語 | Tiếng Việt | 简体中文 | 繁體中文 | 한국어 | Deutsch | Español | Français | Italiano | Dansk | Polski | Русский | Bosanski | العربية | Norsk | Português (Brasil) | ไทย | Türkçe | ភាសាខ្មែរ | Українська ▶ Demo video · The Zen of cmux Docs · Blog · Changelog · Community Features Notification rings Panes get a blue ring and tabs light up when coding agents need your attention Notification panel See all pending notifications in one place, jump to the most recent unread In-app browser Split a browser alongside your terminal with a scriptable API ported from agent-browser Vertical + horizontal tabs Sidebar shows git branch, linked PR status/number, working directory, listening ports, and latest notification text. Split horizontally and vertically. SSH cmux ssh user@remote creates a workspace for a remote machine. Pass --command 'omp "investigate auth"' to run an initial command once in its first remote terminal. Browser panes route through the remote network so localhost just works. Drag an image into a remote session to upload via scp.
The Mother of AI Project Phase 1 RAG Systems: arXiv Paper Curator A Learner-Focused Journey into Production RAG Systems Learn to build modern AI systems from the ground up through hands-on implementation Master the most in-demand AI engineering skills: RAG (Retrieval-Augmented Generation) 📖 About This Course This is a learner-focused project where you'll build a complete research assistant system that automatically fetches academic papers, understands their content, and answers your research questions using advanced RAG techniques. The arXiv Paper Curator will teach you to build a production-grade RAG system using industry best practices . Unlike tutorials that jump straight to vector search, we follow the professional path : master keyword search foundations first, then enhance with vectors for hybrid retrieval. 🎯 The Professional Difference: We build RAG systems the way successful companies do - solid search foundations enhanced with AI, not AI-first approaches that ignore search fundamentals. By the end of this course, you'll have your own AI research assistant and the deep technical skills to build production RAG systems for any domain. 🎓 What You'll Build Week 1: Complete infrastructure with Docker, FastAPI, PostgreSQL, OpenSearch, and Airflow Week 2: Automated data pipeline fetching and parsing academic papers from arXiv Week 3: Production BM25 keyword search with filtering and relevance scoring Week 4: Intelligent chunking + hybrid search combining keywords with semantic understanding Week 5: Complete RAG pipeline with local LLM, streaming responses, and Gradio interface Week 6: Production monitoring with Langfuse tracing and Redis caching for optimized performance Week 7: Agentic RAG with LangGraph and Telegram Bot for mobile access 🏗️ System Architecture Evolution Week 7: Agentic RAG & Telegram Bot Integration Complete Week 7 architecture showing Telegram bot integration with the agentic RAG system LangGraph Agentic RAG Workflow Detailed LangGraph workflow showing decision nodes, document grading, and adaptive retrieval Week 7 Code walkthrough + blog: Agentic RAG with LangGraph and Telegram Key Innovations in Week 7: Intelligent Decision-Making : Agents evaluate and adapt retrieval strategies Document Grading : Automatic relevance assessment with semantic evaluation Query Rewriting : Adaptive query refinement when results are insufficient Guardrails : Out-of-domain detection prevents hallucination Mobile Access : Telegram bot for conversational AI on any device Transparency : Full reasoning step tracking for debugging and trust 🚀 Quick Start 📋 Prerequisites Docker Desktop (with Docker Compose) Python 3.12+ UV Package Manager ( Install Guide ) 8GB+ RAM and 20GB+ free disk space
Pi-hole-class DNS ad-blocker on a $2 ESP32-C3 (no PSRAM): 537k domains as 40-bit FNV-1a hashes in flash, binary-searched. UDP DNS sinkhole + web dashboard. https://youtube.com/shorts/RaxszOUMi8E?feature=share esp32-c3-adblock 日本語 README A Pi-hole-style DNS ad-blocker that runs on a $2 ESP32-C3 — no PSRAM required . 📰 Featured on Tom's Hardware , XDA Developers , and Korben . The trick everyone misses: you don't need to keep the blocklist in RAM. Store the domains as sorted 40-bit hashes in flash and binary-search them. 140,000+ domains fit in ~0.7 MB of flash and are matched in ~10 ms, using ~50 KB of RAM . query in ──▶ extract domain ──▶ FNV-1a hash (+ parent suffixes) ──▶ binary-search the flash hash table ├─ hit ──▶ answer 0.0.0.0 (sinkholed) └─ miss ──▶ forward to upstream resolver, relay the reply Why this is interesting Most ESP32 DNS sinkholes load the blocklist (domain strings ) into RAM, so they demand PSRAM. This project stores fixed 5-byte (40-bit) hashes in flash instead: string-in-RAM approach this (hash-in-flash) Hardware ESP32 + PSRAM (~$8) ESP32-C3, no PSRAM (~$2) 141k domains ~2.5 MB of RAM 0.67 MB of flash RAM used most of it ~50 KB Lookup string compare ~18 flash reads (~10 ms incl. WiFi RTT) Collisions n/a 0 at 141k (1 at 537k) Why 40 bits? It's the sweet spot for this flash budget. Collisions follow the birthday bound — at 141k domains you get ~0, at 537k about 1 (i.e. one unlucky domain gets over-blocked). Dropping to 32 bits would save 20% of the flash but cost ~7 collisions at 250k; going to 64 bits wastes 3 bytes per domain to solve a problem you don't have. The same trick works on bigger chips — it isn't a C3 workaround. On a 16 MB ESP32-S3 these hashes hold ~2.7M domains vs ~466k for strings in 8 MB of PSRAM. Hashes in flash beat strings in PSRAM basically everywhere; the C3 just makes it undeniable. Hardware Any ESP32-C3 board (tested on a C3 SuperMini), 4 MB flash, no PSRAM needed Classic ESP32 (DevKit / WROOM, 4 MB) also builds: pio run -e esp32dev -t upload (community-contributed, compile-tested; the C3 is the tested target) Power it from a stable USB source (a phone charger or your router's USB port). Cheap/loose USB-C→A adapters can brown out the radio during WiFi transmit. A USB-A → USB-C dongle lets it plug straight into the spare USB port on the back of most routers — no power supply, no extra box. Enclosure A printable case for the C3 SuperMini: hardware/esp32-
Persistent Context Across Sessions for Every Agent – Captures everything your agent does during sessions, compresses it with AI, and injects relevant context back into future sessions. Works with Claude Code, OpenClaw, Codex, Gemini, Hermes, Copilot, OpenCode + More https://claude-mem.ai 🇨🇳 中文 • 🇹🇼 繁體中文 • 🇯🇵 日本語 • 🇵🇹 Português • 🇧🇷 Português • 🇰🇷 한국어 • 🇪🇸 Español • 🇩🇪 Deutsch • 🇫🇷 Français • 🇮🇱 עברית • 🇸🇦 العربية • 🇷🇺 Русский • 🇵🇱 Polski • 🇨🇿 Čeština • 🇳🇱 Nederlands • 🇹🇷 Türkçe • 🇺🇦 Українська • 🇻🇳 Tiếng Việt • 🇵🇭 Tagalog • 🇮🇩 Indonesia • 🇹🇭 ไทย • 🇮🇳 हिन्दी • 🇧🇩 বাংলা • 🇵🇰 اردو • 🇷🇴 Română • 🇸🇪 Svenska • 🇮🇹 Italiano • 🇬🇷 Ελληνικά • 🇭🇺 Magyar • 🇫🇮 Suomi • 🇩🇰 Dansk • <a href="https://raw.githubusercontent.com/thedotmack/claude-mem/main/docs/i18n/README
Open Multi-Agent Interactive Classroom — Get an immersive, multi-agent learning experience in just one click Get an immersive, multi-agent learning experience in just one click English | Simplified Chinese Live Demo · Quick Start · Lemonade · FunASR · Features · Use Cases · OpenClaw 🗞️ News 2026-10-29 — v1.3.0 : knowledge base and Pro workbench upgrade. Every upload is kept in its owner's knowledge base until deleted, organized in folders and parsed once for every conversation; the composer offers it through @ , and the agent can read, search and organize it. In the Pro workbench, a request shows a preview of the agent's work before the first page exists, and classroom tabs switch between Learn and Edit. The upgrade has release conditions (stop all old instances first; no rollback below 1.3.0), so read the changelog before upgrading. 2026-10-18 — v1.2.1 : web research. Kimi, DeepSeek and Firecrawl join as web-search providers, and a new webFetch slot lets the agent read pages through a hosted reader (DeepSeek, Kimi or Firecrawl) instead of the built-in one; each is opt-in. Classroom chat can offer suggested replies, and retired models are removed from the built-in catalogs. Classroom chat now always runs on Pi and needs a classroom model with tool calling; read the release's Breaking Changes before upgrading. 2026-10-16 — v1.2.0 : server-first is stable. Generation runs on the server and survives closed tabs and restarts, models are configured once in openmaic.yml (defaults, locks, and an option to forbid user keys), materials are parsed as soon as they are attached, and the web app and the API share one pipeline. New: classroom export , as a PPTX that keeps every scene or as one offline HTML file that plays the lesson. It needs PostgreSQL and a long-running server; V
Open Source Introductory Systems Programming Textbook for the University of Illinois https://cs341.cs.illinois.edu/coursebook Coursebook Welcome to the systems programming coursebook! This repository houses a high-quality, open-source introductory systems programming textbook used by the CS 341: System Programming course at the University of Illinois Urbana-Champaign The book assumes that you have taken a programming language course and are familiar with assembly instructions. All of the code and instruction will be in C, as it is the de-facto language of the Linux Kernel. The Coursebook is an aim to standardize and build upon Angrave's original wikibook experiment . The most recent version of the coursebook as a single pdf is here: main.pdf . Overview Goals Improve the quality and rigour of the original wikibook while maintaining openness. Improve the factualness by including citations, footnotes, extended reading, and a glossary. Have exports in the form of pdf, markdown, and html. Automagically build so writers can focus on writing. Contributing, Building, and Structure Read CONTRIBUTING.md Credit Where Credit is Due Title Page Idea Inspiration - https://tex.stackexchange.com/questions/85904/showcase-of-beautiful-title-page-done-in-tex Duck Image Inspiration - https://pixabay.com/photos/toy-bath-rubber-duck-studio-1474138/ Chapter Style Inspiration - https://texblog.org/2012/07/03/fancy-latex-chapter-styles/ PDF Image Inspiration - https://pixabay.com/illustrations/pdf-miniature-file-icon-2127829/
Fast and extensible multi-platform HTTP/1-2-3 web server with automatic HTTPS https://caddyserver.com a project Every site on HTTPS Caddy is an extensible server platform that uses TLS by default. Releases · Documentation · Get Help Powered by Special thanks to: Warp, built for coding with multiple AI agents Available for MacOS, Linux, & Windows Menu Features Install Build from source For development With version information and/or plugins Quick start Overview Full documentation Getting help About Features Easy configuration with the Caddyfile Powerful configuration with its native JSON config Dynamic configuration with the JSON API Config adapters if you don't like JSON Automatic HTTPS by default ZeroSSL and Let's Encrypt for public names Fully-managed local CA for internal names & IPs Can coordinate with other Caddy instances in a cluster Multi-issuer fallback Encrypted ClientHello (ECH) support Stays up when other servers go down due to TLS/OCSP/certificate-related issues Production-ready after serving trillions of requests and managing millions of TLS certificates Scales to hundreds of thousands of sites as proven in production HTTP/1.1, HTTP/2, and HTTP/3
A skill to stop your coding agent from burying the answer. ADHD-friendly output. ADHD-friendly outputs. No ADHD diagnosis needed! 🇬🇧 · 🇨🇳 · 🇪🇸 · 🇧🇷 · 🇯🇵 · 🇻🇳 · 🇰🇷 · 🇮🇷 · 🇹🇭 · 🇸🇦 Install Copy/paste into your CLI prompt: Install the i-have-adhd skill/plugin from https://github.com/ayghri/i-have-adhd, refer to the repo's AGENTS.md for instructions. Or 🔗 check the installation instructions . What it does A skill for your coding assistant that stops it from burying the answer. Action first. Steps numbered. No "Hope this helps!" Kacper Rutkiewicz | AI Made Simple has made a good breakdown of an earlier version of the skill. What changes Before Great question! Let me think about this. Your auth flow has a few moving pieces: the middleware, the token verification, and the cookie handling. Looking at src/auth.ts , the verifyToken function (around lines 42-58) seems to be using an older jsonwebtoken API. One approach would be to update the package and rewrite that function. After making the change, you'd want to run the auth tests to confirm nothing breaks. By the way, you might also want to look at your dependency versions overall. Hope this helps! Let me know if you want to dig deeper. After Edit src/auth.ts:42 to update the token validation. Open src/auth.ts Replace verifyToken (lines 42–58) with the snippet below Run npm test -- auth.spec.ts Next: paste the first failing line if any test fails. The rules 10 rules. Full text in SKILL.md . Lead with the next action. Number multi-step tasks. End with one concrete next step. Suppress tangents. Restate state every turn. Specific time estimates (minutes, not "a bit"). Make wins visible. Matter-of-fact errors. Cap lists to 5 items. No preamble. No recap. No closers. Tune it Fork, edit skills/i-have-adhd/SKILL.md , then swap your copy in: claude plugin uninstall i-have-adhd # drop the upstream copy first: claude plugin marketplace remove i-have-adhd # fork and upstream share both names claude plugin marketplace add <your-username>/i-have-adhd claude plugin install i-
A native, user-mode, multi-process, graphical debugger. The RAD Debugger Project NOTE: This README does not document usage instructions and tips for the debugger itself, and is intended as a technical overview of the project. The debugger's README, which includes usage instructions and tips, can be found packaged along with debugger releases, or within the build folder after a local copy has been built. You can find pre-built release binaries here . The RAD Debugger is a native, user-mode, multi-process, graphical debugger. It currently only supports local-machine Windows x64 debugging with PDBs, with plans to expand and port in the future. In the future we'll expand to also support native Linux debugging and DWARF debug info. The debugger is currently in ALPHA . In order to get the debugger bullet-proof, it'd greatly help out if you submitted the issues you find here , along with any information you can gather, like dump files (along with the build you used), instructions to reproduce, test executables, and so on. In addition to the debugger, we aim to further improve the toolchain with two additional related technologies: (1) the RAD Debug Info (RDI) format, and (2) the RAD Linker. The RAD Debug Info (RDI) Format The RAD Debug Info (RDI) format is our custom debug information format, which the debugger parses and uses, rather than the debug information natively produced by toolchains, like PDB or DWARF. To work with these existing toolchains, we convert PDB (and eventually PE/ELF files with embedded DWARF) into the RDI format on-demand. The RDI format is currently specified in code, in the files within the src/lib_rdi folder. In rdi.h and rdi.c , the types and functions which define the format itself are specified. In rdi_parse.h and rdi_parse.c , helpers for parsing the format are included. We also have an in-progress library for constructing and serializing RDI data, located within the src/lib_rdi_make folder. Our radbin utility (accessible through the debugger too, via the --bin command line argument) is capable of converting native debug information formats to RDI, and of producing textual dumps of contents stored within RDI files. The RAD Linker The RAD Linker is a new performance linker for generating x64 PE/COFF binaries. It is designed to be very fast when creating gigantic executables. It generates standard PDB files for debugging, but it can also (optionally) natively create RAD Debug Info too, which is useful both to eliminate on-demand conversion time when debugging, but also for huge executables that otherwise create broken PDBs that overflow internal 32-bit tables. The RAD Linker is primarily optimized to handle huge linking projects. In our test cases (where debug info is multiple gigabytes), we see 50% faster link times. The command line syntax is fully compatible with MSVC; you can get a full list of implemented switches from /help . Our current designed-for use case for the linker is to help with the compile-debug cycle of huge projects. We don't yet have support for link-time-optimizations, but this feature is on the road map. By default, the linker spawns as many threads as there
HTTP load generator, ApacheBench (ab) replacement hey is a tiny program that sends some load to a web application. hey was originally called boom and was influenced from Tarek Ziade's tool at tarekziade/boom . Using the same name was a mistake as it resulted in cases where binary name conflicts created confusion. To preserve the name for its original owner, we renamed this project to hey. Installation Linux (amd64): https://storage.googleapis.com/hey-releases/hey_linux_amd64 macOS (amd64): https://storage.googleapis.com/hey-releases/hey_darwin_amd64 Windows (amd64): https://storage.googleapis.com/hey-releases/hey_windows_amd64 Package Managers macOS: Homebrew users can use brew install hey . Usage hey runs provided number of requests in the provided concurrency level and prints stats. It also supports HTTP2 endpoints. Usage: hey [options...] <url> Options: -n Number of requests to run. Default is 200. -c Number of workers to run concurrently. Total number of requests cannot be smaller than the concurrency level. Default is 50. -q Rate limit, in queries per second (QPS) per worker. Default is no rate limit. -z Duration of application to send requests. When duration is reached, application stops and exits. If duration is specified, n is ignored. Examples: -z 10s -z 3m. -o Output type. If none provided, a summary is printed. "csv" is the only supported alternative. Dumps the response metrics in comma-separated values format. -m HTTP method, one of GET, POST, PUT, DELETE, HEAD, OPTIONS. -H Custom HTTP header. You can specify as many as needed by repeating the flag. For example, -H "Accept: text/html" -H "Content-Type: application/xml" . -t Timeout for each request in seconds. Default is 20, use 0 for infinite. -A HTTP Accept header. -d HTTP request body. -D HTTP request body from file. For example, /home/user/file.txt or ./file.txt. -T Content-type, defaults to "text/html". -a Basic authentication, username:password. -x HTTP Proxy address as host:port. -h2 Enable HTTP/2. -host HTTP Host header. -disable-compression Disable compression. -disable-keepalive Disable keep-alive, prevents re-use of TCP connections between different HTTP requests. -disable-redirects Disable following of HTTP redirects -cpus Number of used cpu cores. (default for current machine is 8 cores) Examples Make requests with default settings: hey https://google.com Make 1000 requests with 100 concurrent workers: hey -n 1000 -c 100 https://google.com Run load test for 30 seconds: hey -z 30s https://google.com Make POST request with custom body: hey \ -m POST \ -d "param1=value1&param2=value2" \ https://google.com Add custom headers: hey \ -H "Accept: application/json" \ -H "Authorization: Bearer token" \ https://google.com Test with HTTP/2: hey -h2 https://google.com Rate limit to 10 queries per second per worker: hey -q 10 -c 5 -z 30s https://google.com
Write HTML. Render video. Built for agents. Write HTML. Render video. Built for agents. Quickstart | Showcase | Playground | Catalog | Docs | Discord HyperFrames is an open-source framework for turning HTML, CSS, media, and seekable animations into deterministic MP4 videos. Use it locally with the CLI, from AI coding agents with skills, or as the rendering core behind hosted authoring workflows. Quick Start With an AI coding agent For Claude Code, install the versioned plugin: claude plugin marketplace add heygen-com/hyperframes claude plugin install hyperframes@hyperframes Enable auto-update for the hyperframes marketplace in /plugin → Marketplaces , then use /hyperframes:hyperframes . See the plugin guide for Copilot, VS Code, Cursor, Gemini CLI, updates, and migration. For standalone skills (including OpenCode), use: npx skills add heygen-com/hyperframes The picker opens with nothing pre-selected — the Core Skills group is all you need: the /hyperframes router installs each creation workflow on demand. Agents and non-interactive runs should use npx hyperframes skills update instead — it installs exactly the core set, whereas skills add --all installs all 21 published skills. The six repo-internal skills under .claude/skills / .agents/skills are excluded by default. For the full published set use npx hyperframes skills . skills add resolves the skills.sh registry blob, which can lag main by hours. npx hyperframes skills update installs from the current main , so reach for it when you need the newest copy of a skill. Try a prompt like: Using /hyperframes , create a 10-second product intro with a fade-in title, a background video, and subtle background music. The skills teach agents the HyperFrames production loop: plan the video, write valid HTML, wire seekable animations, add media, lint, preview, and render. They work with Claude Code, Codex, Cursor, Gemini CLI, IBM Bob, and other coding agents that support skills. Skills HyperFrames ships 21 skills agents load on demand. Read /hyperframes first — it's the router and capability map; it picks a workflow for any "make me a…" request — video, deck, or composition port — and points to the domain skills below. For standalone installation, default to the core set — the router installs each creation workflow on demand. npx hyperframes skills update installs exactly that from anywhere; the interactive picker ( npx skills add heygen-com/hyperframes ) lists it as the "Core Skills" group, nothing pre-selected. The picker is interactive-only — a non-interactive or agent run without --skill installs all 21. Use npx skills add heygen-com/hyperframes --all to install the com
AI agent toolkit: unified LLM API, agent loop, TUI, coding agent CLI New issues and PRs from new contributors are auto-closed by default. Maintainers review auto-closed issues daily. See CONTRIBUTING.md . Pi Pi is a minimal, extensible agent harness that you can make your own. Adapt Pi to your workflows, not the other way around. Customize Pi with extensions , skills , prompt templates , and themes . Bundle them as Pi packages and share via npm or git. Pi ships with powerful defaults but skips features like sub-agents and plan mode. Ask Pi to build what you want, or install a package that does it your way. Use Pi interactively , automate it in print or JSON mode , control it over RPC , or build apps with the Pi TypeScript SDK . See OpenClaw for a real-world integration. Getting started Install the command-line interface: curl -fsSL https://pi.dev/install.sh | sh On Windows: powershell -c "irm https://pi.dev/install.ps1 | iex" The installer pins all dependencies and updates Pi with pi update . Alternatively, install directly with npm, which does not pin transitive dependencies: npm install -g --ignore-scripts @earendil-works/pi-coding-agent Pi requires Node.js 22.19 or newer. The macOS, Linux, and Windows installers can install it if needed. Pi does not require dependency lifecycle scripts for a normal npm installation. Start Pi in the directory where you want it to work: cd /path/to/project pi For a built-in AI provider, run /login inside Pi to connect a subscription or API key. Then give Pi a task. See the documentation for full setup and usage instructions, or visit pi.dev for demos. Run with Nix nix run github:earendil-works/pi/stable stable points at the latest release. Install it with nix profile add github:earendil-works/pi/stable and update with nix profile upgrade pi . Use a release tag such as github:earendil-works/pi/v1.0.0 to pin a version, or github:earendil-works/pi for unreleased changes on main . Nix builds Pi from source. Supports ARM64 and x86-64 on Linux and macOS. Use nix build . or nix run . to build or run your checkout. Nix builds are offline, so the bundled model data comes from a pi.dev model catalog revision pinned in nix/model-catalog.js
Model Context Protocol Servers https://modelcontextprotocol.io Model Context Protocol servers This repository is a collection of reference implementations for the Model Context Protocol (MCP), as well as references to community-built servers and additional resources. Important If you are looking for a list of MCP servers, you can browse published servers on the MCP Registry . The repository served by this README is dedicated to housing just the small number of reference servers maintained by the MCP steering group. Warning The servers in this repository are intended as reference implementations to demonstrate MCP features and SDK usage. They are meant to serve as educational examples for developers building their own MCP servers, not as production-ready solutions. Developers should evaluate their own security requirements and implement appropriate safeguards based on their specific threat model and use case. The servers in this repository showcase the versatility and extensibility of MCP, demonstrating how it can be used to give Large Language Models (LLMs) secure, controlled access to tools and data sources. Typically, each MCP server is implemented with an MCP SDK: C# MCP SDK Go MCP SDK Java MCP SDK Kotlin MCP SDK PHP MCP SDK Python MCP SDK Ruby MCP SDK Rust MCP SDK Swift MCP SDK TypeScript MCP SDK 🌟 Reference Servers These servers aim to demonstrate MCP features and the official SDKs. Everything - Reference / test server with prompts, resources, and tools. Fetch - Web content fetching and conversion for efficient LLM usage. Filesystem - Secure file operations with configurable access controls. Git - Tools to read, search, and manipulate Git repositories. Memory - Knowledge graph-based persistent memory system. Sequential Thinking - Dynamic and reflective problem-solving through thought sequences. Time - Time and timezone conversion capabilities. Archived The following reference servers are now archived and can be found at servers-archived . <l
Production-grade engineering skills for AI coding agents. https://skills.addy.ie Agent Skills Production-grade engineering skills for AI coding agents. Skills encode the workflows, quality gates, and best practices that senior engineers use when building software. These ones are packaged so AI agents follow them consistently across every phase of development. DEFINE PLAN BUILD VERIFY REVIEW SHIP ┌──────┐ ┌──────┐ ┌──────┐ ┌──────┐ ┌──────┐ ┌──────┐ │ Idea │ ───▶ │ Spec │ ───▶ │ Code │ ───▶ │ Test │ ───▶ │ QA │ ───▶ │ Go │ │Refine│ │ PRD │ │ Impl │ │Debug │ │ Gate │ │ Live │ └──────┘ └──────┘ └──────┘ └──────┘ └──────┘ └──────┘ /spec /plan /build /test /review /ship Commands 9 slash commands that map to the development lifecycle. Each one activates the right skills automatically. What you're doing Command Key principle Define what to build /spec Spec before code Plan how to build it /plan Small, atomic tasks Build incrementally /build One slice at a time Prove it works /test Tests are proof Set the quality bar /constraints Decide it once, enforce it everywhere Review before merge /review Improve code health Audit web performance /webperf Measure before you optimize Simplify the code /code-simplify Clarity over cleverness Ship to production /ship Faster is safer Want fewer manual steps once the spec exists? /build auto generates the plan and implements every task in a single approved pass — you approve the plan once, then it runs autonomously. It removes the human stepping between tasks, not the verification: every task is still test-driven and committed individually, and it pauses on failures or risky steps. Skills also activate automatically based on what you're doing — designing an API triggers api-and-interface-design , building UI triggers frontend-ui-engineering , and so on. Quick Start Fastest path — any agent, one command. The open skills CLI installs into 70+ agents (Claude Code, Cursor, Codex, Copilot, Cline, and more): npx skills add addyosmani/agent-skills # install all 25 skills npx skills add addyosmani/agent-skills --list # browse before installing Or grab individual skills: npx skills add addyosmani/agent-skills --skill code-review-and-quality # five-axis review before merge npx skills add addyosmani/agent-skills --skill interview-me # requirements interrogation, one question at a time npx skills add addyosmani/agent-skills --skill test-driven-development # red-green-refactor, enforced Installing one skill? A per-skill npx install copies only skills/<name>/ , not the repo-level refere
Hyprland is an independent, highly customizable, dynamic tiling Wayland compositor that doesn't sacrifice on its looks. https://hypr.land Hyprland is a 100% independent, dynamic tiling Wayland compositor that doesn't sacrifice on its looks. It provides the latest Wayland features, is highly customizable, has all the eyecandy, the most powerful plugins, easy IPC, much more QoL stuff than other compositors and more... Install Quick Start Configure Contribute Features All of the eyecandy: gradient borders, many types of blur, animations, glow, shadows and much more A lot of customization 100% independent, no wlroots, no libweston, no kwin, no mutter. Custom bezier and spring curves for the best animations Powerful plugin support Built-in plugin manager Tearing support for better gaming performance Easily expandable and readable codebase Fast and active development Not afraid to provide bleeding-edge features Config reloaded instantly upon saving Global keybinds passed to your apps of choice Tiling/pseudotiling/floating/fullscreen windows Special workspaces (scratchpads) Window groups (tabbed mode) Powerful window/monitor/layer rules Socket-based IPC Native IME and Input Panels Support Fully dynamic workspaces Extensive layout support Dwindle Scrolling Master Monocle Custom layout with Lua Custom layouts with plugins Per Workspace Layouts and much more... Gallery Special Thanks wlroots - For powering Hyprland in the past tinywl - For showing how 2 do stuff Sway - For showing how 2 do stuff the overkill way Vivarium - For showing how 2 do stuff the simple way dwl - For showing how 2 do stuff the hacky way Wayfire - For showing how 2 do some graphics stuff
Claude Code is an agentic coding tool that lives in your terminal, understands your codebase, and helps you code faster by executing routine tasks, explaining complex code, and handling git workflows - all through natural language commands. https://code.claude.com/docs/en/overview Claude Code Claude Code is an agentic coding tool that lives in your terminal, understands your codebase, and helps you code faster by executing routine tasks, explaining complex code, and handling git workflows -- all through natural language commands. Use it in your terminal, IDE, or tag @claude on Github. Learn more in the official documentation . Get started Note Installation via npm is deprecated. Use one of the recommended methods below. For more installation options, uninstall steps, and troubleshooting, see the setup documentation . Install Claude Code: MacOS/Linux (Recommended): curl -fsSL https://claude.ai/install.sh | bash Homebrew (MacOS/Linux): brew install --cask claude-code Windows (Recommended): irm https://claude.ai/install.ps1 | iex WinGet (Windows): winget install Anthropic.ClaudeCode NPM (Deprecated): npm install -g @anthropic-ai/claude-code Navigate to your project directory and run claude . Plugins This repository includes several Claude Code plugins that extend functionality with custom commands and agents. See the plugins directory for detailed documentation on available plugins. Reporting Bugs We welcome your feedback. Use the /bug command to report issues directly within Claude Code, or file a GitHub issue . Connect on Discord Join the Claude Developers Discord to connect with other developers using Claude Code. Get help, share feedback, and discuss your projects with the community. Data collection, usage, and retention When you use Claude Code, we collect feedback, which includes usage data (such as code acceptance or rejections), associated conversation data, and user feedback submitted via the /bug command. How we use your data See our data usage policies . Privacy safeguards We have implemented several safeguards to protect your data, including limited retention periods for sensitive information, restricted access to user session data, and clear policies against using feedback for model training. For full details, please review our Commercial Terms of Service and Privacy Policy .
Open source repository of plugins primarily intended for knowledge workers to use in Claude Cowork Knowledge Work Plugins Plugins that turn Claude into a specialist for your role, team, and company. Built for Claude Cowork , also compatible with Claude Code . Why Plugins Cowork lets you set the goal and Claude delivers finished, professional work. Plugins let you go further: tell Claude how you like work done, which tools and data to pull from, how to handle critical workflows, and what slash commands to expose — so your team gets better and more consistent outcomes. Each plugin bundles the skills, connectors, slash commands, and sub-agents for a specific job function. Out of the box, they give Claude a strong starting point for helping anyone in that role. The real power comes when you customize them for your company — your tools, your terminology, your processes — so Claude works like it was built for your team. Plugin Marketplace We're open-sourcing 11 plugins built and inspired by our own work: Plugin How it helps Connectors productivity Manage tasks, calendars, daily workflows, and personal context so you spend less time repeating yourself. Slack, Notion, Asana, Linear, Jira, Monday, ClickUp, Microsoft 365 sales Research prospects, prep for calls, review your pipeline, draft outreach, and build competitive battlecards. Slack, HubSpot, Close, Clay, ZoomInfo, Notion, Jira, Fireflies, Microsoft 365 customer-support Triage tickets, draft responses, package escalations, research customer context, and turn resolved issues into knowledge base articles. Slack, Intercom, HubSpot, Guru, Jira, Notion, Microsoft 365 product-management Write specs, plan roadmaps, synthesize user research, keep stakeholders updated, and track the competitive landscape. Slack, Linear, Asana, Monday, ClickUp, Jira, Notion, Figma, Amplitude, Pendo, Intercom, Fireflies marketing Draft content, plan campaigns, enforce brand voice, brief on competitors, and report on performance across channels. Slack, Canva, Figma, HubSpot, Amplitude, Notion, Ahrefs, SimilarWeb, Klaviyo legal Review contracts, triage NDAs, navigate compliance, assess risk, prep for meetings, and draft templated responses. Slack, Box, Egnyte, Jira, Microsoft 365 finance Prep journal entries, reconcile accounts, generate financial statements, analyze variances, manage close, and support audits. Snowflake, Databricks, BigQuery, Slack, Microsoft 365 data</
Build production-ready applications in TypeScript https://effect.website Effect Effect is a library for building robust, maintainable, type-safe, and production grade applications in TypeScript. It helps you handle the hard problems at scale: typed errors, dependency injection, structured concurrency, scheduling, tracing, and unified schema validation. Effect 4.x is a long-term support (LTS) release. If you are upgrading from Effect 3.x, follow the migration guide . Installation npm install effect Requirements TypeScript 5.9 or newer. TypeScript 7 is recommended for the best performance and compatibility with Effect's TypeScript tooling . Node.js 18 or newer is the general minimum for running Effect on Node.js. Some integration packages require newer runtimes; for example, @effect/sql-sqlite-node requires Node.js 22.16 or newer. Strict type-checking: the strict flag must be enabled in your tsconfig.json . Links Website : documentation, guides, and news Discord : ask questions, share what you're building, and talk to the core team Community : meetups and events, or bring Effect to your own Issues : bug reports and feature requests Jobs : companies hiring Effect developers Follow us on X , Bluesky , and LinkedIn Let's talk Whether your team is considering Effect, rolling it out, or already running it in production, we'd love to hear from you: what you're building, what works, and what you need from Effect next. Talk to the maintainers. Introduce your team on Discord or email [email protected] . We're happy to connect privately on Slack or Discord for feedback and help with adoption. Production support. We're exploring how to better support teams running Effect in production. If your organization has specific support needs, let's discuss them. Adoption help. Our adoption partners offer implementation, consulting, team extension, training, and commercial support. Feedback from teams using and evaluating Effect directly shapes what we stabilize and build next. Long-term support Teams depend on Effect for systems they expect to run for years. Effect 4.x is a long-term support (LTS) release with the following guarantees: At least three years of support, including bug and security fixes. Bug fixes for one year after the next major version is released. Security fixes for two years after the next major version is released. Stable APIs reserve breaking changes for major releases. APIs marked unstable may change in minor releases, and experimental APIs may change in patch releases. Effect v3 The Effect v3 source code is available on the v3 branch, which is also where
25 MB lightweight cross-platform database client for 100+ databases, including MySQL, PostgreSQL, SQLite, Redis, MongoDB, DuckDB, SQL Server, and Dameng. Built-in AI, MCP Server, CLI, desktop and Docker. | 轻量级跨平台数据库管理工具，支持 MySQL、PostgreSQL、SQLite、Redis、MongoDB、达梦等 100+ 数据库，提供桌面端、Docker、CLI、内置 AI 助手和 MCP。 https://dbxio.com 100+ databases in 25 MB. Desktop, Docker, CLI, built-in AI assistant, and MCP Server. English | 前往中文版本 ❤️ Sponsors RainYun is a cloud service provider offering cloud servers, physical servers, game hosting, and developer-friendly infrastructure services. Visit RainYun TrustAsia provides cloud-based code signing service for DBX, enabling trusted software through automated CI/CD builds. Visit TrustAsia Jalapeño Cloud is an AI infrastructure and token compute platform, with an exclusive DBX entry offering free credits and top-up bonuses. Visit Jalapeño Cloud Special thanks to AICodeMirror for sponsoring this project! AICodeMirror provides a high-stability official relay service for Claude Code / Codex / Gemini CLI, with enterprise-grade concurrency, fast invoicing, and 7×24 dedicated support. Official-channel pricing for Claude Code / Codex / Gemini is as low as 38% / 2% / 9% of list price, with extra discounts on top-ups! AICodeMirror offers a special benefit for DBX users: register through this link to enjoy 20% off your first top-up, and enterprise customers up to 25% off. Visit AICodeMirror HuaLongAI is a model API relay built for heavy AI developers, offering 100% official-source Codex and Claude models with transparent token-level billing, enterprise contracts, and invoicing. Visit HuaLongAI <a href="https://www.ucloud.cn/site/active/kuaijiesale.html?ytag=geo_waituo_gith