Agentic Quality Engineering Fleet (Agentic QE) is a comprehensive tool designed for quality engineering tasks. It offers a Domain-Driven Design architecture with 13 bounded contexts and 60 specialized QE agents. The tool includes features like TinyDancer intelligent model routing, ReasoningBank learning with Dream cycles, HNSW vector search, Coherence Verification, and integration with other tools like Claude Flow and Agentic Flow. It provides capabilities for test generation, coverage analysis, quality assessment, defect intelligence, requirements validation, code intelligence, security compliance, contract testing, visual accessibility, chaos resilience, learning optimization, and enterprise integration. The tool supports various protocols, LLM providers, and offers a vast library of QE skills for different testing scenarios.

PAIML MCP Agent Toolkit (PMAT) is a zero-configuration AI context generation system with extreme quality enforcement and Toyota Way standards. It allows users to analyze any codebase instantly through CLI, MCP, or HTTP interfaces. The toolkit provides features such as technical debt analysis, advanced monitoring, metrics aggregation, performance profiling, bottleneck detection, alert system, multi-format export, storage flexibility, and more. It also offers AI-powered intelligence for smart recommendations, polyglot analysis, repository showcase, and integration points. PMAT enforces quality standards like complexity ≤20, zero SATD comments, test coverage >80%, no lint warnings, and synchronized documentation with commits. The toolkit follows Toyota Way development principles for iterative improvement, direct AST traversal, automated quality gates, and zero SATD policy.

Agentic InfraOps is a multi-agent orchestration system for Azure infrastructure development that transforms how you build Azure infrastructure with AI agents. It provides a structured 7-step workflow that coordinates specialized AI agents through a complete infrastructure development cycle: Requirements → Architecture → Design → Plan → Code → Deploy → Documentation. The system enforces Azure Well-Architected Framework (WAF) alignment and Azure Verified Modules (AVM) at every phase, combining the speed of AI coding with best practices in cloud engineering.

PAI-OpenCode is a complete port of Daniel Miessler's Personal AI Infrastructure (PAI) to OpenCode, an open-source, provider-agnostic AI coding assistant. It brings modular capabilities, dynamic multi-agent orchestration, session history, and lifecycle automation to personalize AI assistants for users. With support for 75+ AI providers, PAI-OpenCode offers dynamic per-task model routing, full PAI infrastructure, real-time session sharing, and multiple client options. The tool optimizes cost and quality with a 3-tier model strategy and a 3-tier research system, allowing users to switch presets for different routing strategies. PAI-OpenCode's architecture preserves PAI's design while adapting to OpenCode, documented through Architecture Decision Records (ADRs).

sf-skills is a collection of reusable skills for Agentic Salesforce Development, enabling AI-powered code generation, validation, testing, debugging, and deployment. It includes skills for development, quality, foundation, integration, AI & automation, DevOps & tooling. The installation process is newbie-friendly and includes an installer script for various CLIs. The skills are compatible with platforms like Claude Code, OpenCode, Codex, Gemini, Amp, Droid, Cursor, and Agentforce Vibes. The repository is community-driven and aims to strengthen the Salesforce ecosystem.

AReaL (Ant Reasoning RL) is an open-source reinforcement learning system developed at the RL Lab, Ant Research. It is designed for training Large Reasoning Models (LRMs) in a fully open and inclusive manner. AReaL provides reproducible experiments for 1.5B and 7B LRMs, showcasing its scalability and performance across diverse computational budgets. The system follows an iterative training process to enhance model performance, with a focus on mathematical reasoning tasks. AReaL is equipped to adapt to different computational resource settings, enabling users to easily configure and launch training trials. Future plans include support for advanced models, optimizations for distributed training, and exploring research topics to enhance LRMs' reasoning capabilities.

AxonHub is an all-in-one AI development platform that serves as an AI gateway allowing users to switch between model providers without changing any code. It provides features like vendor lock-in prevention, integration simplification, observability enhancement, and cost control. Users can access any model using any SDK with zero code changes. The platform offers full request tracing, enterprise RBAC, smart load balancing, and real-time cost tracking. AxonHub supports multiple databases, provides a unified API gateway, and offers flexible model management and API key creation for authentication. It also integrates with various AI coding tools and SDKs for seamless usage.

Motia is an AI agent framework designed for software engineers to create, test, and deploy production-ready AI agents quickly. It provides a code-first approach, allowing developers to write agent logic in familiar languages and visualize execution in real-time. With Motia, developers can focus on business logic rather than infrastructure, offering zero infrastructure headaches, multi-language support, composable steps, built-in observability, instant APIs, and full control over AI logic. Ideal for building sophisticated agents and intelligent automations, Motia's event-driven architecture and modular steps enable the creation of GenAI-powered workflows, decision-making systems, and data processing pipelines.

New API is a next-generation large model gateway and AI asset management system that provides a wide range of features, including a new UI interface, multi-language support, online recharge function, key query for usage quota, compatibility with the original One API database, model charging by usage count, channel weighted randomization, data dashboard, token grouping and model restrictions, support for various authorization login methods, support for Rerank models, OpenAI Realtime API, Claude Messages format, reasoning effort setting, content reasoning, user-specific model rate limiting, request format conversion, cache billing support, and various model support such as gpts, Midjourney-Proxy, Suno API, custom channels, Rerank models, Claude Messages format, Dify, and more.

RAG Web UI is an intelligent dialogue system based on RAG (Retrieval-Augmented Generation) technology. It helps enterprises and individuals build intelligent Q&A systems based on their own knowledge bases. By combining document retrieval and large language models, it delivers accurate and reliable knowledge-based question-answering services. The system is designed with features like intelligent document management, advanced dialogue engine, and a robust architecture. It supports multiple document formats, async document processing, multi-turn contextual dialogue, and reference citations in conversations. The architecture includes a backend stack with Python FastAPI, MySQL + ChromaDB, MinIO, Langchain, JWT + OAuth2 for authentication, and a frontend stack with Next.js, TypeScript, Tailwind CSS, Shadcn/UI, and Vercel AI SDK for AI integration. Performance optimization includes incremental document processing, streaming responses, vector database performance tuning, and distributed task processing. The project is licensed under the Apache-2.0 License and is intended for learning and sharing RAG knowledge only, not for commercial purposes.

TS-Bench is a performance benchmarking tool for TypeScript projects. It provides detailed insights into the performance of TypeScript code, helping developers optimize their projects. With TS-Bench, users can measure and compare the execution time of different code snippets, functions, or modules. The tool offers a user-friendly interface for running benchmarks and analyzing the results. TS-Bench is a valuable asset for developers looking to enhance the performance of their TypeScript applications.

NeMo Curator is a Python library designed for fast and scalable data processing and curation for generative AI use cases. It accelerates data processing by leveraging GPUs with Dask and RAPIDS, providing customizable pipelines for text and image curation. The library offers pre-built pipelines for synthetic data generation, enabling users to train and customize generative AI models such as LLMs, VLMs, and WFMs.

Uni-CoT is a unified reasoning framework that extends Chain-of-Thought (CoT) principles to the multimodal domain, enabling Multimodal Large Language Models (MLLMs) to perform interpretable, step-by-step reasoning across both text and vision. It decomposes complex multimodal tasks into structured, manageable steps that can be executed sequentially or in parallel, allowing for more scalable and systematic reasoning.

CIA is a powerful open-source tool designed for data analysis and visualization. It provides a user-friendly interface for processing large datasets and generating insightful reports. With CIA, users can easily explore data, perform statistical analysis, and create interactive visualizations to communicate findings effectively. Whether you are a data scientist, analyst, or researcher, CIA offers a comprehensive set of features to streamline your data analysis workflow and uncover valuable insights.

AutoDev Xiuper is an AI-native, multi-agent development platform built on Kotlin Multiplatform. It covers all seven phases of the software development lifecycle and runs on 8+ platforms. The platform provides a unified architecture for writing code once and running it anywhere, with specialized agents for each phase of development. It supports various devices including IntelliJ IDEA, VS Code, CLI, Web, Desktop, Android, iOS, and Server. The platform also offers features like Multi-LLM support, DevIns language for workflow automation, MCP Protocol for extensible tool ecosystem, and code intelligence for multiple programming languages.

Agentic Quality Engineering Fleet (Agentic QE) is a comprehensive tool designed for quality engineering tasks. It offers a Domain-Driven Design architecture with 13 bounded contexts and 60 specialized QE agents. The tool includes features like TinyDancer intelligent model routing, ReasoningBank learning with Dream cycles, HNSW vector search, Coherence Verification, and integration with other tools like Claude Flow and Agentic Flow. It provides capabilities for test generation, coverage analysis, quality assessment, defect intelligence, requirements validation, code intelligence, security compliance, contract testing, visual accessibility, chaos resilience, learning optimization, and enterprise integration. The tool supports various protocols, LLM providers, and offers a vast library of QE skills for different testing scenarios.

AiScript is a lightweight scripting language that runs on JavaScript. It supports arrays, objects, and functions as first-class citizens, and is easy to write without the need for semicolons or commas. AiScript runs in a secure sandbox environment, preventing infinite loops from freezing the host. It also allows for easy provision of variables and functions from the host.

AskUI is a reliable, automated end-to-end automation tool that only depends on what is shown on your screen instead of the technology or platform you are running on.

The 'bots' repository is a collection of guides, tools, and example bots for programming bots to play video games. It provides resources on running bots live, installing the BotLab client, debugging bots, testing bots in simulated environments, and more. The repository also includes example bots for games like EVE Online, Tribal Wars 2, and Elvenar. Users can learn about developing bots for specific games, syntax of the Elm programming language, and tools for memory reading development. Additionally, there are guides on bot programming, contributing to BotLab, and exploring Elm syntax and core library.

Ain is a terminal HTTP API client designed for scripting input and processing output via pipes. It allows flexible organization of APIs using files and folders, supports shell-scripts and executables for common tasks, handles url-encoding, and enables sharing the resulting curl, wget, or httpie command-line. Users can put things that change in environment variables or .env-files, and pipe the API output for further processing. Ain targets users who work with many APIs using a simple file format and uses curl, wget, or httpie to make the actual calls.

LaVague is an open-source Large Action Model framework that uses advanced AI techniques to compile natural language instructions into browser automation code. It leverages Selenium or Playwright for browser actions. Users can interact with LaVague through an interactive Gradio interface to automate web interactions. The tool requires an OpenAI API key for default examples and offers a Playwright integration guide. Contributors can help by working on outlined tasks, submitting PRs, and engaging with the community on Discord. The project roadmap is available to track progress, but users should exercise caution when executing LLM-generated code using 'exec'.

Robocorp is a platform that allows users to create, deploy, and operate Python automations and AI actions. It provides an easy way to extend the capabilities of AI agents, assistants, and copilots with custom actions written in Python. Users can create and deploy tools, skills, loaders, and plugins that securely connect any AI Assistant platform to their data and applications. The Robocorp Action Server makes Python scripts compatible with ChatGPT and LangChain by automatically creating and exposing an API based on function declaration, type hints, and docstrings. It simplifies the process of developing and deploying AI actions, enabling users to interact with AI frameworks effortlessly.

Open Interface is a self-driving software that automates computer tasks by sending user requests to a language model backend (e.g., GPT-4V) and simulating keyboard and mouse inputs to execute the steps. It course-corrects by sending current screenshots to the language models. The tool supports MacOS, Linux, and Windows, and requires setting up the OpenAI API key for access to GPT-4V. It can automate tasks like creating meal plans, setting up custom language model backends, and more. Open Interface is currently not efficient in accurate spatial reasoning, tracking itself in tabular contexts, and navigating complex GUI-rich applications. Future improvements aim to enhance the tool's capabilities with better models trained on video walkthroughs. The tool is cost-effective, with user requests priced between $0.05 - $0.20, and offers features like interrupting the app and primary display visibility in multi-monitor setups.

AI-Case-Sorter-CS7.1 is a project focused on building a case sorter using machine vision and machine learning AI to sort cases by headstamp. The repository includes Arduino code and 3D models necessary for the project.