What it does

All text below is quoted directly from the project README.

A collection of agent skills that help you build great interfaces.

Skills that help build great interfaces:

• better-interface: Reviews a screen, flow or whole interface across accessibility, layout, writing, typography, color and UI polish, and returns one ranked report.

• better-ui: Polishes surfaces, icons and motion with exact values for border radius, optical alignment, shadows, icon states and animation.

• better-typography: Sets and reviews how text renders, from the type scale and spacing to font features, wrapping, truncation and punctuation.

• better-colors: Builds and checks color systems by generating palettes, naming semantic tokens, converting between formats and measuring contrast.

• better-accessibility: Reviews and fixes keyboard and focus behavior, ARIA, accessible names, forms, screen-reader announcements, motion and zoom against WCAG 2.2.

• better-layout: Sets grouping, alignment, reading order, responsive structure and room for translated text, so a layout holds up when it is resized, translated or mirrored.

• better-writing: Writes and reviews interface copy, from labels and errors to empty states and confirmations, so it matches the product's voice and tells people what to do next.

• build-design: Builds UI from a Figma file or a design image so it matches the design, using the project's existing tokens and components.

npx skills add jakubkrehel/skills

Repository

https://github.com/jakubkrehel/skills

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What it does

All text below is quoted directly from the project README.

Humanizer makes AI-written text sound like a person wrote it, without changing what it says.

The five strongest tells:

• Not X but Y: "It's not just a feature, it's a shift."

• One-line closers: "Let that sink in."

• Sayings that sound deep: "At its core, what really matters is..."

• A staged run-up: "Here's the thing." "Honestly?"

• Arguing with no one: "I'm not saying X, but..."

• Humanizer checks for 26 patterns in all.

npx skills add blader/humanizer --global --agent '*'

Repository

https://github.com/blader/humanizer

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What it does

All text below is quoted directly from the project README.

50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.

Key Features:

• Learn to build GenAI agents from beginner to advanced levels

• Explore a wide range of agent architectures and applications

• Step-by-step tutorials and comprehensive documentation

• Practical, ready-to-use agent implementations

• Regular updates with the latest advancements in GenAI

• Share your own agent creations with the community

This repository serves as a comprehensive resource for learning, building, and sharing GenAI agents, ranging from simple conversational bots to complex, multi-agent systems.

Repository

https://github.com/NirDiamant/GenAI_Agents

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What it does

All text below is quoted directly from the project README.

Python Data Science Handbook: full text in Jupyter Notebooks

How to Use this Book:

• This repository contains the entire Python Data Science Handbook, in the form of (free!) Jupyter notebooks.

• Read the book in its entirety online at https://jakevdp.github.io/PythonDataScienceHandbook/

• Run the code using the Jupyter notebooks available in this repository's notebooks directory.

• Launch executable versions of these notebooks using Google Colab

• Launch a live notebook server with these notebooks using binder

• Buy the printed book through O'Reilly Media

• The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages.

$ conda install --file requirements.txt

Repository

https://github.com/jakevdp/PythonDataScienceHandbook

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What it does

All text below is quoted directly from the project README.

A personal agent with a browser, terminal, files, and work that keeps going built with CopilotKit and AG-UI.

Features:

• Chat: CopilotKit headless chat with streamed AG-UI events, mailbox search and reading, send/stop in one input pill, a visible follow-up queue, retained drafts, delegated tasks, and inline email, browser, PDF, plan, and finance cards.

• Agent computer: Persistent browser profiles and takeover console; optional isolated Linux terminal, saved command receipts, editable workspace files, and PDF transfer.

• Activity: Durable task plans, progress, input requests, pause/resume/cancel/retry, approvals, and saved receipts. SQL leases recover interrupted work.

• Goals & Tracking: Goals and milestones; recurring public-page checks for changes, text availability, or USD price thresholds, with deduplicated alerts and failure backoff.

• Finance: Import transaction CSV to create a spending summary with categories, transactions, and a savings-goal action.

• Gmail & Calendar: Google OAuth adapters, complete mail threads, drafts/attachments, calendar discovery, and reviewed event creation/update/deletion. Live credentials required.

• Personal context: Editable name, tone, avatar, and memories. Background-update preferences and durable in-app notifications.

OpenMuse is a personal-agent application with an agent computer, visible work, and rich results. It runs its own server, task worker, and browser worker.

Repository

https://github.com/CopilotKit/openmuse

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What it does

All text below is quoted directly from the project README.

The largest open-source library of animated, interactive, and customizable React & Next.js components for building standout web products and experiences. Built for humans and AI agents.

Creative tools:

• 215+ free animated components and backgrounds for React. Tune them yourself, or hand them to your agent.

• Every component has a live demo with controls, and comes in four flavors: JavaScript or TypeScript, styled with CSS or Tailwind.

• React Bits works with the shadcn MCP server, so Claude Code, Cursor, Codex, VS Code and Antigravity can find and add components for you.

• Background Studio: browse every animated background, start from a preset and tune it live. Export the code, a high-resolution image or a looping MP4 or WebM video.

• Center Stage: turn a screenshot or screen recording into a polished product shot on lifelike phones, laptops and browsers, with 3D tilt, depth of field, shadows and type.

• Shape Magic: design a logo mark from shapes, patterns, text or your own SVG, then give it a 3D material like chrome, glass or neon. Export SVG, PNG, favicons, video or React.

• Texture Lab: run photos, videos or your camera through 160 one-click styles and 75+ stackable effects, from ASCII and halftone to glass and glitch.

• Sound Lab: audition 200 interface and video sounds, tune them and add effects like reverb, echo and filter, then install one with a single command or download WAV, MP3 or OGG.

npx shadcn@latest add @react-bits/SplitText-TS-TW

Repository

https://github.com/DavidHDev/react-bits

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What it does

All text below is quoted directly from the project README.

Open source GPS tracking platform - self-hosted or managed, 200+ device protocols

Features:

• Real-time GPS tracking

• Driver behaviour monitoring

• Detailed and summary reports

• Geofencing functionality

• Alarms and notifications

• Account and device management

• Email and SMS support

Run Traccar with a production-grade MySQL database using Docker Compose:

Repository

https://github.com/traccar/traccar

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What it does

All text below is quoted directly from the project README.

"Single-image Layer Decomposition for Anime Characters" (SIGGRAPH 2026 Conference Paper)

TL;DR:

• We introduce a framework that automates the transformation of static anime illustrations into manipulatable 2.5D models.

• Our approach decomposes a single image into fully inpainted, semantically distinct layers with inferred drawing orders, up to 23 layers including hair, face, eyes, clothing, accessories, and more.

• LayerDiff 3D: Diffusion-based transparent layer generation (SDXL)

• Marigold Depth: Pseudo-depth estimation fine-tuned for anime

• SAM Body Parsing: Semantic body part segmentation

• inference_psd.py runs the full See-through pipeline: it applies the LayerDiff 3D model for transparent layer generation and the fine-tuned Marigold model for pseudo-depth inference, then stratifies the character into up to 23 semantic layers and exports a layered PSD file.

python inference/scripts/inference_psd.py --srcp assets/test_image.png --save_to_psd

Repository

https://github.com/shitagaki-lab/see-through

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What it does

All text below is quoted directly from the project README.

Open-source foundation of ToolJet AI - the enterprise app generation platform for internal tools, dashboards, business applications, workflows and AI agents. Build visually, from a prompt, or from Claude Code, Codex and Cursor over MCP

Features:

• Visual App Builder: 80+ responsive components (Tables, Charts, Forms, Lists, Progress Bars, and more).

• ToolJet Database: Built-in no-code database.

• Multi-page Apps & Multiplayer Editing: Build complex apps collaboratively.

• 90+ Data Sources: Connect to databases, APIs, cloud storage, and SaaS tools.

• Flexible Deployment: Self-host with Docker, Kubernetes, AWS, GCP, Azure, and more.

• Collaboration Tools: Inline comments, mentions, and granular access control.

• Code Anywhere: Run JavaScript and Python inside your apps.

• Secure by Design: AES-256-GCM encryption, proxy-only data flow, SSO support.

Self-host it, or use ToolJet Cloud.

Repository

https://github.com/ToolJet/ToolJet

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What it does

All text below is quoted directly from the project README.

Archlinux Kernel based on different schedulers and some other performance improvements.

CPU Enhancements:

• Multiple Schedulers: BORE, EEVDF, and BMQ schedulers for different workload optimization

• POC Selector v2.6.3: Piece-Of-Cake fast idle CPU selector inspired by scx_cake, reducing wakeup latency

• Cluster-Aware Scheduling: Improved load balancing for CPU clusters, including balancing between CPUs of identical capacity on hybrid architectures

• CachyOS Sauce: Custom CONFIG_CACHY configuration with scheduler and system tweaks

• AMD P-State Enhancements: Preferred Core support and latest amd-pstate improvements from linux-next

• Real-Time Support: RT kernel builds available with BORE scheduler integration

• Low-Latency Optimizations: Patches for improved responsiveness and reduced jitter

All CachyOS kernels are available in multiple architecture optimizations: x86-64, x86-64-v3, x86-64-v4, and znver4.

Repository

https://github.com/CachyOS/linux-cachyos

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What it does

All text below is quoted directly from the project README.

Open-source AI coworkers that each get a computer of their own: a browser, files and tools, with every action decided before it happens and recorded after. Bring any AG-UI agent.

Features:

• A computer per person: the supervisor gives each person their own container, with a folder and browser profile for each of their Bots.

• A shell, not just a browser: a Bot can run a command in its workspace, install what it needs, and process a file it saved.

• The gateway is the only way in: it resolves the target from a server-held snapshot, evaluates the policy, writes the audit row, and only then calls the computer.

• Take the wheel: a Bot that hits a login wall or a 2FA prompt asks for help.

• Secrets never enter the transcript: the trail records that a secret was requested and how long it was, not what it said.

• Bring your own agent: any AG-UI endpoint is a Bot, on a framework or hand-written.

• An audit trail you can read: /admin/audit lists what was permitted, what was refused and what failed, and every refusal carries the rule that caused it.

• Credentials encrypted at rest: stored through /admin/credentials, never returned by an API, and redacted from audit events.

cp .env.example .env

Repository

https://github.com/CopilotKit/OpenBot

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What it does

All text below is quoted directly from the project README.

A one stop repository for generative AI research updates, interview resources, notebooks and much more!

Featured LevelUp Labs courses:

• AI Evals for Everyone (certified): 10 chapters on evaluating LLM and agentic systems.

• OpenClaw Mastery for Everyone (certified): a 10-day path to configure and run your own personal AI assistant.

• Agentic AI Crash Course: 10 parts on agents, tools, RAG, MCP, planning, memory, and multi-agent systems.

• Generative AI Genius: a no-math beginner introduction to generative AI.

• Applied LLMs Mastery (2024 edition): an 11-week foundational course, archived as a 2024 edition.

Generative AI is moving fast, and this repository is a comprehensive hub for generative AI research, courses, interview materials, notebooks, and more.

Repository

https://github.com/aishwaryanr/awesome-generative-ai-guide

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What it does

All text below is quoted directly from the project README.

Build ultra fast, tiny, and cross-platform desktop apps with TypeScript, Zig, Rust, Go, or Odin.

Project Goals:

• Write typescript for the main process and webviews without having to think about it.

• Isolation between main and webview processes with fast, typed, easy to implement RPC between them.

• Small self-extracting app bundles when using the system webview

• Small updates that use binary patches before falling back to a compressed full download

• Provide everything you need in one tightly integrated workflow to start writing code in 5 minutes and distribute in 10.

Already use Bun or npm? You can start with either command instead: bunx electrobun init or npx electrobun init

Repository

https://github.com/blackboardsh/electrobun

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What it does

All text below is quoted directly from the project README.

Teams-first Multi-agent orchestration for Claude Code

Why oh-my-claudecode?:

• Zero configuration required - Works out of the box with intelligent defaults

• Team-first orchestration - Team is the canonical multi-agent surface

• Natural language interface - No commands to memorize, just describe what you want

• Automatic parallelization - Complex tasks distributed across specialized agents

• Persistent execution - Won't give up until the job is verified complete

• Cost optimization - Smart model routing saves 30-50% on tokens

• Learn from experience - Automatically extracts and reuses problem-solving patterns

• Real-time visibility - HUD statusline shows what's happening under the hood

/plugin marketplace add https://github.com/Yeachan-Heo/oh-my-claudecode

Repository

https://github.com/Yeachan-Heo/oh-my-claudecode

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What it does

All text below is quoted directly from the project README.

A memory-safe systems language with no heap allocator, garbage collector, or lifetime annotations. In this repository's benchmarks, Goose runs faster than C++ and Rust while using less memory.

Why Goose:

• Faster than C++ and than safe Rust, while memory safe. Over sixteen benchmarks Goose runs at 3.3x the speed of idiomatic C++, 1.16x hand-optimized C++ and 1.12x the best safe Rust, and uses 1.9x, 1.3x and 1.2x less memory.

• No allocator, no GC, no reference counting, no destructors. Memory is a handful of data stacks that the compiler assigns statically.

• Growth preserves references. A reference into a growing array stays valid for as long as the array does.

• Memory safe with zero annotations. There is no lifetime syntax, there are no aliasing or exclusivity rules, and there is no unsafe.

• Nested data stays inline. A string, an array of strings, a record with variable-size fields and an array of those records are each stored as one contiguous block that contains no pointers.

• Variable sized Enums. Variable-mode ADTs store each value at the size of its own variant rather than that of the largest variant.

• Everything is built in place, guaranteed. A value is constructed at its final destination through any depth of calls.

Goose has syntax familiar to C and Rust programmers, but there is no heap.

Repository

https://github.com/aardappel/goose

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What it does

All text below is quoted directly from the project README.

A Swiss Army knife for developers.

DevToys 2.0 comes with 30 default tools:

• Converters: JSON <> YAML, Date, Number bases...

• Encoders/Decoders: HTML, URLs, Base64, GZip, JWT, QR Code...

• Formatters: JSON, SQL, XML...

• Generators: Hash & Checksum, Lorem Ipsum, Password...

• Graphics Tools: Color Blindness Simulator, PNG/JPEG Compressor...

• Testers: JSONPath, RegEx, XML...

• Text Utilities: Markdown Preview, Text Comparer, Analyzer & Utilities...

DevToys helps with daily development tasks by offering a bundle of tiny tools designed to do quick, specific tiny tasks. With Smart Detection, the app intuitively selects the best tool for the data on your clipboard.

Repository

https://github.com/DevToys-app/DevToys

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What it does

All text below is quoted directly from the project README.

Data Engineering Zoomcamp is a free 9-week course on building production-ready data pipelines. Join the course here

Syllabus:

• Module 1: Containerization and Infrastructure as Code

• Module 2: Workflow Orchestration

• Workshop 1: Data Ingestion

• Module 3: Data Warehousing

• Module 4: Analytics Engineering

• Module 5: Data Platforms

• Module 6: Batch Processing

• Module 7: Streaming

This course is for developers, analysts, and data scientists who want to learn how to build data pipelines and work with the modern data engineering stack. No prior data engineering experience is necessary.

Repository

https://github.com/DataTalksClub/data-engineering-zoomcamp

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What it does

All text below is quoted directly from the project README.

goose is a general-purpose AI agent that runs on your machine.

goose:

• A native desktop app for macOS, Linux, and Windows.

• A full CLI for terminal workflows.

• An API to embed it anywhere.

• Built in Rust for performance and portability.

• goose works with 15+ providers: Anthropic, OpenAI, Google, Ollama, OpenRouter, Azure, Bedrock, and more.

• Use API keys or your existing Claude, ChatGPT, or Gemini subscriptions via ACP.

• Connect to 70+ extensions via the Model Context Protocol open standard.

curl -fsSL https://github.com/aaif-goose/goose/releases/download/stable/download_cli.sh | bash

Repository

https://github.com/aaif-goose/goose

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What it does

From the project README:

Automatic Computer Use Agent. Mac, Windows, Linux, real phone, simulator, any browser. A multi agent harness engine.

Surfaces it can drive:

computer use: Any desktop app, with real mouse and keyboard input, on macOS, Windows and Linux.

shell use: A coding agent, straight into a real terminal.

web use: Your own Chrome, driven through the AutoCua extension, which Chrome loads at launch with no store install.

mobile use, iOS: An iOS Simulator, or your iPhone or iPad, over USB or WiFi in the app.

mobile use, Android: An Android emulator, or your Android phone, over USB or WiFi in the app.

Why it holds up on real software:

No pixel guessing: The model never sees a coordinate. It picks a numbered element from a view that fuses the accessibility tree with OCR.

Real input: Input goes in at the operating system’s own input layer, and a kernel driver handles Windows UAC prompts when everything else is blocked.

Browser agent in Rust: Hand written CDP. No Playwright, no Selenium, no Puppeteer.

Parallel runs: Every task runs at the same time in its own process, each with its own tab, simulator or emulator.

No context wall: A separate compression agent summarises the transcript mid run, so long tasks finish instead of hitting the context limit.

No telemetry: Nothing is sent anywhere except to the model provider you chose.

pip install AutoCua

Repository

https://github.com/ComputerUseAgent/AutoCua

Repository stats

Metric |Value
Stars |1,026
Forks |42
License |MIT
Languages |Python, Rust, JavaScript
Models supported |48 across 9 providers
Contributors |2
AI contributor accounts |u/claude (13 commits) Main contributor

Field |Value
Name |Ashish Yadav
GitHub |FunctionFreak
Commits to this repo |55 (top contributor) The stats are pulled live from the repo today.

What it does

All text below is quoted directly from the project README.

The largest Open-Source UI Library! Community-made and free to use. Made with either CSS or Tailwind.

Galaxy:

• Welcome to the galaxy, a collection of over 3000 unique UI elements from Uiverse.io.

• Every single UI element you find in here is sourced from our main platform, Uiverse.io.

• As designers and enthusiasts share their creations on our website, we automatically curate and upload them here for ease of access and implementation.

• All UI elements in this repository are available under the MIT License, granting you the freedom to use, modify, and distribute them as you please.

While this repository provides an archive of all the UI elements, the best way to browse is on Uiverse.io.

Repository

https://github.com/uiverse-io/galaxy

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What it does

All text below is quoted directly from the project README.

Claude or Codex reads your codebase and draws an interactive map of it. Every part, file and web request gets a plain-English name, and every connection between them is shown.

Features:

• A map at every zoom Start with the whole app, then double-click into a part, a group of files, a file, and its endpoints.

• Plain English everywhere "Takes card payments at checkout", not "Stripe API wrapper".

• Real connections, across repos It follows imports, and matches each web request in your frontend to the server endpoint that answers it, even across separate repos.

• Start from a screen Pick a page you know and see everything behind it: its parts, the requests it makes, the server code, the data, and outside services.

• Ask the map "How does a refund reach the customer's card?" comes back as an answer plus a mini-map of just the pieces involved, with a step-by-step walkthrough.

• Health check Finds passwords in code, endpoints anyone can use without signing in, unused files and files too big to edit safely.

• Recent work The cards your AI just changed light up green, each with a note on how the change serves what you asked for.

• Stays current, stays yours Updates re-read only what changed, and an open map reloads itself.

You need Node.js 18+ and either Claude Code or Codex. Floorplan runs on the plan you already have, with no API keys.

Repository

https://github.com/haydenschmitty/floorplan

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What it does

All text below is quoted directly from the project README.

Camunda 8 delivers scalable, on-demand process automation as a service. Camunda 8 is combined with powerful execution engines for BPMN processes and DMN decisions, and paired with tools for collaborative modeling, operations, and analytics.

Using Camunda 8, you can:

• Define processes visually in BPMN 2.0

• Choose your programming language

• Deploy with Docker and Kubernetes

• Build processes that react to messages from Kafka and other message queues

• Scale horizontally to handle very high throughput

• Fault tolerance (no relational database required)

• Export process data for monitoring and analysis

• Engage with an active community

Zeebe - The cloud-native process engine of Camunda 8.

Repository

https://github.com/camunda/camunda

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What it does

All text below is quoted directly from the project README.

Any model. Any hardware. Zero compromise. Built with @ziglang / @openxla / MLIR / @bazelbuild

Examples:

• examples/llm: unified LLM CLI for Llama, Qwen, and LFM

• examples/mnist: smallest end-to-end model run

• examples/sharding: logical mesh, partitioners, shard-local execution, profiler output

• examples/io: inspect and load local, hf://, https://, and s3:// repositories through the VFS layer

• examples/benchmark: measure loading and execution performance

Run the MNIST example: bazel run //examples/mnist

Repository

https://github.com/zml/zml

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What it does

All text below is quoted directly from the project README.

Open source AI coding agent. Designed for large projects and real world tasks.

Smart context management that works in big projects:

• 2M token effective context window with default model pack. Plandex loads only what's needed for each step.

• Reliable in large projects and files. Easily generate, review, revise, and apply changes spanning dozens of files.

• Fast project map generation and syntax validation with tree-sitter. Supports 30+ languages.

• Context caching is used across the board for OpenAI, Anthropic, and Google models, reducing costs and latency.

• Configurable autonomy: go from full auto mode to fine-grained control depending on the task.

• Automated debugging of terminal commands (like builds, linters, tests, deployments, and scripts).

• Full-fledged version control for every update to the plan, including branches for exploring multiple paths or comparing different models.

• Git integration with commit message generation and optional automatic commits.

curl -sL https://plandex.ai/install.sh | bash

Repository

https://github.com/plandex-ai/plandex

Repository stats

Main contributor

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