Projects sharing features with Skills

Azure PowerShell is a collection of scriptable commands and a management tool used for the administration, configuration, and automation of Microsoft Azure cloud resources and infrastructure. It serves as a command line interface for deploying and monitoring cloud services. The project provides capabilities for cloud resource orchestration and infrastructure automation, allowing for the execution of programmable scripts to handle repetitive administrative tasks. It includes tools for managing identity and access across multiple Azure tenants and subscriptions. The system covers authenticatio

The Azure Cloud Command-Line Interface is a terminal-based utility used for creating, managing, and automating infrastructure and services within the Azure cloud ecosystem. It serves as a programmatic interface for handling cloud environment setup and resource lifecycles by interacting with Azure APIs. The tool facilitates cloud infrastructure automation through the use of scripts and standardized exit codes. It provides a command-line workflow that includes tab-completion for commands and parameters and a flexible query syntax for filtering results and extracting specific data fields from cl

Letta is a framework for building, deploying, and managing autonomous AI agents that maintain persistent state across long-term interactions. It provides a comprehensive suite of primitives for defining agents with configurable personas, modular memory blocks, and tool-use capabilities, enabling them to retain user preferences and conversation history over extended sessions. The platform distinguishes itself through its advanced memory management and orchestration capabilities. It allows agents to autonomously update their own memory, perform retrieval-augmented generation, and coordinate com

Phidata is an LLM agent framework and agentic workflow orchestrator used to build autonomous agents that integrate custom data, tools, and memory. It provides a production environment for serving these agents as services via APIs, utilizing server-sent events and websockets for real-time communication. The system distinguishes itself through a human-in-the-loop control layer that requires manual approval and administrative sign-off for specific tool executions. It also implements a multi-tenant AI infrastructure that uses token-based roles to ensure data isolation between different tenants.

Rig is a framework for building large language model applications, featuring a multi-provider client and a workflow builder for retrieval-augmented generation systems. It serves as an orchestrator for creating autonomous agents that can maintain conversation state and execute complex tasks through custom prompting and plugins. The project provides standardized interfaces for both completion and embedding model providers, allowing for unified request and response patterns across different engines. It also includes a vector database integration layer that defines a common interface for indexing

TaskingAI is an AI agent orchestrator and application platform used to build, deploy, and scale AI-native applications. It functions as a multi-tenant backend as a service, providing the infrastructure to host and manage independent AI agent instances across multiple users or organizations on a shared architecture. The platform features a visual workflow builder and project management console, allowing users to configure agent logic and test conversation workflows through a graphical interface before moving them to a production environment. The system orchestrates large language models by st

Vocode-core is a framework for building real-time conversational AI voice agents. It serves as a conversational orchestrator and pipeline that integrates speech-to-text, large language models, and text-to-speech services to enable low-latency voice interactions. The project features a provider-agnostic interface that allows for swappable speech and language model providers, including support for both cloud APIs and local binaries. It distinguishes itself through a specialized telephony integration layer that enables agents to be deployed across phone lines, WebRTC, and virtual meeting platfor

Skills is a command-line tool for managing reusable instruction sets, called skills, that configure the behavior of AI coding agents. It provides a versioned registry of agent prompts that can be discovered, installed, updated, and removed through a CLI interface, with skills stored as declarative configuration files injected directly into a project's file system. The tool supports the full lifecycle of agent skill management, including searching a public registry by keyword, browsing a leaderboard of community-contributed skills, inspecting remote repositories before installation, and genera

This project is a Terraform provider that enables the management of Azure cloud resources through an infrastructure as code workflow. It serves as a programmatic interface for creating and configuring services via the Azure Resource Manager API, functioning as a declarative system for provisioning virtual infrastructure. The tool orchestrates the lifecycle of Azure virtual machines, networks, and storage. It replaces manual portal configuration with version-controlled scripts to automate the deployment of cloud services and scale environments across development, staging, and production stages

Mastra is an orchestration framework designed for building, deploying, and managing autonomous AI agents and multi-agent systems. It provides a comprehensive suite of primitives for creating resilient AI applications, including durable workflow orchestration, event-driven agent loops, and semantic memory management. By integrating these core components, the platform enables developers to build complex, multi-step processes that can reason about goals and execute tasks without manual intervention. The framework distinguishes itself through its focus on observability and secure, isolated execut

This project is a framework for integrating Large Language Models into the Feishu messaging platform to create automated assistants. It functions as a self-hosted AI assistant and a chatbot gateway that routes messages between chat platforms and remote AI cloud providers. The system features a multi-channel messaging bridge and provider-agnostic model routing, allowing for orchestration between different AI models with automatic failover management. It includes a browser automation agent capable of programmatically controlling web browsers and capturing page snapshots to extend the assistant'

This project is a framework for packaging and installing standardized capabilities, scripts, and instructions that LLM agents execute to perform complex tasks. It functions as a tool orchestrator and skill framework, bundling instructions and resources into portable formats that agents discover and use for repeatable workflows. The system distinguishes itself through a manifest-driven discovery process, allowing agents to identify available capabilities and their execution parameters. It supports the deployment of these modular capability sets into isolated runtime environments using remote U

Spring AI is an application framework for Java that provides a portable, fluent API for integrating AI models, tools, and vector stores into applications. It wraps multiple AI providers behind a common interface, allowing developers to switch between chat, embedding, image, and speech models without changing application code. The framework includes a chainable chat client API similar to WebClient or RestClient, supports both synchronous and streaming interactions, and offers structured output conversion that transforms unstructured AI responses into strongly-typed Java objects. The framework

Quarkus is a Kubernetes-native Java framework designed for building high-performance, memory-efficient applications. It utilizes ahead-of-time native compilation to transform Java code into standalone, optimized binaries that eliminate the need for a virtual machine, enabling rapid startup and reduced memory consumption. By performing code augmentation during the build phase, it shifts heavy processing tasks away from runtime, ensuring that applications are optimized for cloud-native environments. The framework distinguishes itself through a unified approach to reactive and imperative program

This project serves as a comprehensive educational repository and technical reference collection, documenting a wide range of software engineering practices and modern development technologies. It provides a structured learning path for developers, curating tutorials and practical examples that cover the full lifecycle of application development, from initial project scaffolding to deployment and maintenance. The repository distinguishes itself by offering deep technical insights into complex architectural patterns, including actor-based concurrency models for managing parallel tasks and cont

an ambient intelligence library

Klavis is a platform for managing Model Context Protocol (MCP) servers and providing sandboxed environments where AI agents can safely interact with external tools and services. It functions as an integration framework that orchestrates MCP server instances, exposes tools and resources for AI agents, and isolates agent interactions from production data through horizontally scalable sandbox environments. The platform distinguishes itself through its ability to generate long-horizon agentic tasks that simulate realistic tool-use workflows with live SaaS applications and production MCP servers.

Kiln is an LLM development workbench and evaluation framework designed for designing, testing, and optimizing prompts and AI agents. It functions as a multi-agent orchestrator and a RAG optimization tool, providing a visual interface for the iterative development of AI systems. The project distinguishes itself through a comprehensive fine-tuning pipeline that supports zero-code model training and reasoning distillation. It enables the creation of hierarchical multi-agent systems where specialized actors coordinate via tool calling, and it implements a Model Context Protocol server to expose t

Lucida is a multimodal AI assistant framework and containerized microservice orchestrator. It provides a platform for building agents that process and integrate speech, vision, and text inputs to perform intelligent tasks, supported by a retrieval-augmented generation system for storing and querying factual data from texts, URLs, and images. The framework features a state-graph workflow engine to route user requests through a sequence of microservices using a predefined state machine. It also includes an extensible plugin interface that allows for the integration of custom functional modules

SuperduperDB is an AI agent orchestrator and database-integrated machine learning platform. It serves as a framework for building stateful AI agents and retrieval-augmented generation applications by integrating large language models directly with database backends. The project enables the deployment of self-hosted AI infrastructure and the management of language models on private hardware using local checkpoints. It distinguishes itself by allowing users to attach AI components directly to data fields, triggering model execution and automated transformations based on database insertions and

This project provides a collection of reference implementations, architectural patterns, and SDK samples for building autonomous agents using large language models. It serves as a multi-language framework for implementing and deploying specialized AI agents across diverse programming environments. The system centers on an orchestration framework that combines deterministic code with adaptive reasoning through structured graph workflows. It utilizes schema-driven integration to connect agents with third-party applications and diverse AI models. The development lifecycle is supported by toolki

The Azure SDK for Python is a collection of libraries that enables programmatic management of Azure cloud resources and services directly from Python code. It provides a credential-based authentication pipeline for secure access, along with an async-first client design that supports concurrent I/O operations without blocking the event loop. The SDK is built on AutoRest-generated client code from OpenAPI specifications, offering both synchronous and asynchronous service clients. It includes a long-running operation poller abstraction for managing operations that require status checks and retry

This project is a structured educational resource and technical guide for designing and implementing autonomous systems using large language models. It provides a comprehensive curriculum and code samples focused on agentic design patterns, autonomous development, and the creation of systems capable of planning and executing multi-step tasks. The resource details the implementation of agentic retrieval-augmented generation, where models autonomously plan and refine data searches. It covers a wide array of orchestrators and design patterns, including metacognitive reflection for self-correctin

n8n-skills is a collection of technical guides and architectural frameworks for designing, building, and deploying automation workflows and AI agents within n8n. It provides a structured approach to creating autonomous agents by combining large language model chains with memory systems and custom toolsets. The project focuses on extending AI capabilities through the development of custom tool functions using structured input schemas and the integration of Model Context Protocol servers. It emphasizes the use of specific architectural patterns to manage webhooks, APIs, and binary data handling

This project is a library of pre-configured n8n workflow templates and structural blueprints designed for automating business processes and AI tasks. It provides a collection of JSON files that can be imported into a workflow engine to deploy automation sequences, including specialized configurations for integrating vector databases and large language models. The collection focuses on the development of context-aware AI agents, utilizing memory buffers and retrieval systems to create intelligent data generation and retrieval pipelines. It includes dedicated blueprints for retrieval augmented

This project serves as a comprehensive, curated directory of resources, tools, and platforms dedicated to the generative artificial intelligence ecosystem. It functions as a central hub for developers and researchers to discover the frameworks, models, and services necessary for building, deploying, and managing intelligent software applications. The directory distinguishes itself by providing a structured index of specialized tooling across several technical domains. It covers the full lifecycle of generative AI, including the development of autonomous agent systems, the implementation of re

Eigent is a comprehensive platform for developing, configuring, and orchestrating autonomous AI agents. It functions as an agent development environment and workflow automation engine, enabling users to build modular agents equipped with custom toolsets, domain-specific skill packages, and external API connections to perform targeted operational tasks. The framework distinguishes itself through a robust multi-agent orchestration layer that coordinates teams of specialized agents to execute complex workflows. By utilizing hierarchical task decomposition, the system breaks high-level goals into