AI agent skills

MetaGPT is an agentic workflow orchestrator and multi-agent framework designed to transform natural language requirements into complete software deliverables. It functions as an AI software engineering suite that automates the creation of technical documentation, data structures, and source code by treating natural language as a programming environment. The system distinguishes itself by assigning professional roles to large language models, creating specialized agent teams that collaborate through a shared communication structure. It utilizes standard operating procedures to convert organiza

MetaGPT is an agentic workflow engine and multi-agent orchestration framework designed to automate complex software engineering and data analysis tasks. It functions as an automated software factory that transforms high-level natural language requirements into functional web applications, technical documentation, and production-ready code. By utilizing a runtime environment that manages the lifecycle of specialized agents, the platform bridges the gap between user intent and finished software components. The system distinguishes itself through role-based agent orchestration and dynamic task d

This project is a comprehensive framework for building and managing autonomous agent systems. It provides a unified architecture for orchestrating multi-agent societies, where specialized agents collaborate through roleplay to decompose and solve complex tasks. The system integrates language models with external environments, enabling agents to perform real-world actions through a standardized tool-calling abstraction layer. The framework distinguishes itself through its focus on iterative reasoning and data reliability. It employs automated feedback loops to refine agent outputs and self-eva

Langroid is a multi-agent orchestration framework and tool integration suite designed for building complex AI applications. It serves as a multi-modal integration layer that connects diverse local and remote language models with an agentic retrieval-augmented generation system. The project distinguishes itself through a collaborative message-exchange paradigm, allowing specialized agents to delegate tasks hierarchically and coordinate via structured communication. It features an advanced state management system for conversational AI, including the ability to rewind and prune conversation hist

Eino is an AI agent development kit and LLM application framework designed for building autonomous agents and orchestrating complex language model workflows. It serves as a multi-agent orchestration engine and workflow orchestrator, providing a graph-based execution model to route data between models, tools, and retrievers. The framework distinguishes itself through a robust set of multi-agent coordination patterns, including supervisor-led management, sequential flows, and autonomous reasoning loops like ReAct. It features advanced agent execution controls such as active turn preemption, che

CrewAI is a multi-agent orchestration framework designed for building autonomous systems that execute complex, multi-step workflows. It provides a development platform where specialized agents are defined with specific roles, goals, and tool sets to perform tasks collaboratively. By leveraging a declarative workflow engine, the system manages task dependencies, state transitions, and execution logic, allowing for the creation of structured, stateful sequences of operations. The framework distinguishes itself through its hierarchical management capabilities, which utilize manager agents to coo

This project is a comprehensive framework for building AI-powered applications, providing a unified toolkit for orchestrating language models, autonomous agents, and interactive user interfaces. It serves as a central library for managing the entire lifecycle of AI interactions, from initial prompt generation and model provider abstraction to complex, multi-step reasoning and tool execution. The framework distinguishes itself through its deep integration with frontend development, specifically by enabling generative user interfaces that render dynamic components directly from model outputs. I

This framework provides a development environment for building collaborative systems where autonomous agents interact to solve complex tasks through conversational workflows. It functions as a conversational workflow engine and event-driven runtime, coordinating multi-step processes by translating high-level goals into structured dialogue sequences between specialized agents. The system distinguishes itself through its message-passing orchestration, which manages state transitions and task delegation between independent participants. It supports dynamic conversation state management to provid

LlamaIndex is a comprehensive development framework designed to connect private or external data sources to large language models. It functions as a data-centric toolkit that enables the construction of retrieval-augmented generation systems, allowing developers to build applications that provide context-aware answers based on specific organizational information. The project distinguishes itself through a robust agentic orchestration engine that supports the creation of autonomous agents capable of multi-step reasoning, memory management, and complex tool execution. Beyond simple retrieval, i

LangChain is an orchestration framework designed for building, managing, and deploying applications powered by large language models. It provides a unified integration layer that normalizes disparate model provider APIs into a consistent set of primitives, enabling developers to build complex, multi-step AI workflows that manage state, memory, and tool execution. The project distinguishes itself through a durable execution runtime that maintains persistent state across long-running processes by checkpointing progress to external storage. It models agent workflows as directed graphs, allowing

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

GenAI_Agents is a development framework and orchestration engine designed for building autonomous, multi-agent systems. It provides the infrastructure to construct complex, state-managed workflows where specialized agents collaborate to execute multi-step tasks, manage long-term memory, and perform iterative reasoning. The platform distinguishes itself through its graph-based orchestration model, which allows developers to define intricate agentic processes with explicit state transitions. It supports advanced control mechanisms such as human-in-the-loop intervention for manual oversight and

OpenHands is an autonomous agent framework designed for software engineering workflows. It provides a modular platform for orchestrating AI agents that reason, plan, and execute tasks within isolated, containerized development environments. By integrating with standard version control and development tools, the system enables agents to autonomously navigate codebases, implement features, and resolve issues through iterative reasoning and tool execution. The platform distinguishes itself through a model-agnostic orchestrator that connects diverse language models to a unified tool registry. It

Agent Zero is an LLM agent framework and multi-agent orchestrator that provides an AI-powered interface for operating system tasks. It functions as a containerized AI workspace, allowing large language models to interact with a filesystem and terminal within an isolated Linux environment. The system distinguishes itself through a hierarchical orchestration model that decomposes complex goals by spawning specialized sub-agents to collaborate and consolidate results. It features a plugin-based architecture for extending capabilities via a community plugin hub, a custom skills system, and extern

GenericAgent is an LLM agent framework and autonomous system controller designed to manage local systems, web browsers, and hardware interfaces through action and observation loops. It functions as a tool orchestrator that routes model calls to local executors, enabling the automation of complex tasks on a host machine. The project is distinguished by its self-evolving AI agent capabilities, which convert successful execution paths into reusable procedural scripts and skill trees to reduce future reasoning overhead. It employs a context optimization engine that utilizes layered memory hierarc

OpenCode is a framework for orchestrating autonomous AI agents within development environments. It provides a multi-tiered architecture where primary assistants manage user interaction while specialized subagents handle specific tasks like planning, research, and code generation. The system includes a comprehensive command-line interface for managing these workflows, configuring agent behavior, and defining custom tools or commands through metadata-rich files. The platform features a modular plugin system and extensive integration support, including standardized protocols for connecting local

This project is a Python framework for building autonomous, event-driven agent systems. It provides a unified runtime for orchestrating multi-agent workflows, managing persistent conversation state, and executing code within secure, isolated sandbox environments. The framework is designed to handle complex task delegation, allowing agents to invoke other agents as tools while maintaining context across multi-turn interactions. The framework distinguishes itself through its deep integration with the Model Context Protocol, enabling agents to connect to external data sources and remote services

LobeHub is a comprehensive multi-agent orchestration platform designed for building, configuring, and deploying specialized AI agents. It provides a unified chat-based gateway that allows users to manage autonomous agent teams across web, desktop, and mobile environments. By utilizing a framework that supports persistent memory and granular tool integration, the platform enables the execution of complex, multi-step workflows and domain-specific tasks. The platform distinguishes itself through an interactive artifact renderer that injects dynamic, visual UI elements directly into the chat stre

This project provides a command-line interface for managing autonomous agent workflows, task orchestration, and system-level automation. It includes a comprehensive framework for defining agent skills, managing persistent memory, and delegating tasks to specialized subagents. Users can configure complex planning modes, execute shell commands with safety constraints, and integrate external tools through standardized protocols. The platform supports non-interactive execution via a headless mode and provides an event-driven hook framework for custom lifecycle automation. It features centralized

This framework provides a development toolkit for building autonomous agents that utilize language models to solve complex, non-deterministic tasks. Its core design centers on a code-executing architecture where agents generate and run Python code snippets to perform logic, data manipulation, and tool interactions. By moving beyond structured data formats, the system enables agents to manage program flow and object state through iterative reasoning cycles. The project distinguishes itself through its focus on code-based agent implementation and secure execution environments. Developers can ch

AIOS is an LLM agent operating system and orchestration kernel designed to manage memory, resource scheduling, and tool execution for multiple autonomous AI agents. It serves as a comprehensive framework for developing and deploying agents, featuring a dedicated resource manager that coordinates model backends, GPU memory, and isolated kernel instances. The system distinguishes itself through a semantic memory engine that uses vector search and autonomous clustering for long-term knowledge management, and a semantic file system that allows users to control computer files and system operations

LibreChat is an artificial intelligence orchestration platform that provides a unified interface for interacting with multiple language models. It functions as a centralized workspace where users can switch between different intelligence engines, manage complex conversational workflows, and maintain persistent memory across sessions through a vector-database-backed storage system. The platform distinguishes itself through an extensible agent framework that supports autonomous task execution and the integration of external tools. It features a secure, containerized environment for executing co

Acontext is an LLM orchestration backend and agent memory framework designed to manage session state and knowledge for AI agents. It functions as a context manager and orchestration layer that integrates model providers with a secure code sandbox and a zero-knowledge data store. The project is distinguished by its approach to knowledge distillation, capturing agent learnings as reusable Markdown skills and structured memory files. It provides a secure execution environment where shell commands and scripts run in isolated containers with the ability to mount these persistent skill files direct

Agentscope is a comprehensive toolkit for developing and orchestrating autonomous multi-agent systems. It provides a unified framework for building agents that can reason, execute tools, and manage memory, enabling the creation of complex, collaborative workflows where multiple specialized agents interact to solve multi-step objectives. The platform distinguishes itself through a robust orchestration engine that supports both sequential and concurrent agent pipelines. It utilizes a centralized event bus for real-time telemetry, allowing developers to track agent reasoning, tool usage, and sys

This project is an autonomous agent framework designed to integrate large language models with popular messaging platforms. It functions as a middleware platform that enables automated, multimodal interactions by decomposing complex user goals into sequential plans, executing them through external tools, and maintaining persistent context across sessions. The framework distinguishes itself through a modular skill architecture and a hybrid memory system. Users can extend system capabilities by installing custom logic modules from community hubs or generating them through natural language. The

Pipecat is a framework and software development kit for building real-time multimodal AI agents and speech-to-speech systems. It utilizes a frame-based data pipeline to route audio, video, and text through a modular sequence of processors, enabling the orchestration of low-latency conversational AI. The project is distinguished by its ability to coordinate complex multimodal services, including speech-to-text, language models, and text-to-speech, within a single pipeline. It features semantic voice activity detection for natural turn-taking, state-machine conversation flows for dialogue manag

This project provides a standardized framework for extending the functional range of artificial intelligence agents through a registry of modular, declarative instructions. It enables agentic workflow automation by allowing developers to define task-specific behaviors and operational constraints that guide how agents interact with external tools and execute multi-step processes. The system distinguishes itself through a directory-based discovery model and a plugin-registry architecture that facilitates the distribution of specialized workflows. By utilizing a schema-driven specification that

OpenManus is an autonomous agent framework designed to build intelligent software entities capable of executing complex, multi-step tasks through independent decision-making. It functions as a workflow orchestration engine that uses a central language model to interpret user goals, break them down into actionable steps, and manage the execution flow of agents. The system maintains coherence across tasks through a stateful execution context that tracks progress and intermediate data. The platform distinguishes itself through a dynamic capability discovery mechanism that inspects tool definitio

Oh-my-agent is a vendor-agnostic orchestration framework designed to manage autonomous agent teams and automate complex engineering workflows. It functions as a multi-agent development tool that synchronizes agent behavior, skills, and project-specific rules across diverse development environments and command-line interfaces. The platform distinguishes itself through configuration-based projection, which maintains a single source of truth for agent definitions that are mapped into various vendor-specific runtime formats. By utilizing cross-platform symlink bridging and a vendor-agnostic skill

Goose is an extensible agentic AI platform designed for autonomous task orchestration and developer-centric assistance. It provides a workflow engine that manages complex, multi-step objectives by delegating tasks to specialized subagents, all while maintaining stateful session continuity. The system is built to integrate directly into terminal and coding environments, allowing for automated file manipulation and context-aware interaction. The platform distinguishes itself through a secure, sandboxed runtime environment that enforces granular permission controls and policy-driven guardrails.

IntentKit is an open-source platform for deploying and managing a collaborative team of AI agents that can work together to complete complex tasks. It provides a self-hosted agent orchestrator that coordinates multiple agents through a modular pipeline of entrypoints, orchestration, and storage, all running as containerized services using Docker Compose or Swarm for production-grade deployment. The platform distinguishes itself by offering a plugin-based system for extending agent capabilities without modifying the core codebase, along with built-in integrations for connecting agents to socia

Agent Skills is a framework for bundling executable scripts and metadata to extend the capabilities and tool-use of language model agents. It provides a standardized directory structure for packaging specialized workflows, technical instructions, and portable agent capabilities for distribution across different AI platforms. The project features a tool optimization suite used to refine skill triggers and evaluate the reliability of agent-activated capabilities. It includes a context-aware knowledge manager that organizes technical references into a hierarchy, loading them on demand to reduce

Cipher is an AI agent orchestration framework and LLM context memory layer. It provides a collaborative AI knowledge base and a context synchronization service that allows AI agents and CLI tools to maintain a persistent, structured memory of project decisions and codebase patterns across different sessions and machines. The system distinguishes itself through a version-controlled context model, using branches and commits to track how project knowledge evolves. It features a hierarchical knowledge store where information is organized as markdown files and can be synchronized between local env

Composio is an integration platform designed to connect autonomous agents with external software services and APIs. It functions as a tool orchestration framework and a middleware hub, providing a unified interface for managing the lifecycle, authentication, and execution of external tool definitions within agentic workflows. The platform distinguishes itself by utilizing the Model Context Protocol to standardize communication between artificial intelligence models and external data sources. It employs a provider-agnostic adapter pattern to decouple core logic from specific model providers an

Everything Claude Code is an agentic framework designed to orchestrate complex software development workflows through specialized subagent delegation. It functions as a control plane that manages agent behavior, tool access, and context window efficiency, allowing developers to break down large tasks into focused, scoped sub-processes that prevent system overload. The framework distinguishes itself through a robust security and automation layer that includes automated static analysis and adversarial red-teaming to audit agent configurations. It enables the creation of reusable behavioral patt

AutoGPT is an orchestration platform designed for building, managing, and deploying autonomous agents. It provides a visual canvas-based environment where users can assemble agents by connecting modular blocks that represent actions, data flows, and conditional logic. The platform supports the entire agent lifecycle, including task scheduling, execution monitoring, and configuration management, while offering a marketplace for discovering and sharing community-built workflows. The project includes a legacy framework for command-line agent execution and an extensible component system for devel

Langchain-Chatchat is a system for building retrieval-augmented generation applications and autonomous AI agents. It integrates a knowledge base management system and an agent framework to enable language models to interact with private documents and execute multi-step tasks through external tools. The platform supports local deployment of language models on private infrastructure to operate without an internet connection. It includes a multimodal AI platform that combines vision models for image analysis with text-to-image generation capabilities. The system provides a web-based conversatio

This is a framework for building autonomous agents that use large language models to plan, execute, and refine their own tasks. It functions as an autonomous task orchestrator and agent framework, utilizing a function registry to manage the code-based tools and plugins the agents use to achieve complex goals. The system is distinguished by its ability to perform autonomous code generation, where the agent analyzes requirements to write new reusable functions on the fly. It employs a recursive loop-based planning model to continuously update its goal list and refine its performance based on ex

This project is an AI software engineering tool and framework for building autonomous coding agents. It provides a system for automating program synthesis and bug fixing by integrating large language models with codebase analysis and iterative refinement loops. The framework features an agentic development server that exposes task execution interfaces to remote agents through a structured protocol. This allows for the remote execution of development tasks and the embedding of autonomous program synthesis capabilities into external software projects. The toolset covers AI-driven project scaff

E2B is a cloud-based infrastructure platform designed to provide secure, isolated execution environments for code and shell commands. It functions as an ephemeral orchestrator that provisions lightweight virtual machines, allowing developers and autonomous agents to run untrusted processes within a sandbox that is completely separated from the host system. The platform distinguishes itself through its focus on programmable, serverless workspaces that support the full lifecycle of cloud-based development. By utilizing hardware-level isolation and snapshot-based resumption, it enables the near-

Griptape is a Python framework for building generative AI applications, autonomous agents, and complex AI workflows. It functions as both an AI agent orchestrator and a workflow engine, capable of managing sequential pipelines and directed acyclic graphs to ensure predictable execution of AI tasks. The framework distinguishes itself through a focus on security and governance, utilizing a Docker-based environment to execute model-generated code and shell commands in isolation. It employs a driver-based abstraction layer that allows developers to swap language model providers and vector stores

Agent Skills is a centralized registry and management system designed for the discovery, auditing, and integration of reusable procedural modules into automated agent workflows. It provides a structured environment for sourcing verified capabilities that extend the functional range of AI agents, enabling the development and scaling of complex, multi-step automated processes. The platform distinguishes itself through a security-first approach to module integration, utilizing audit-verified data to ensure that capabilities meet safety requirements before they are deployed. It incorporates a dec

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

FastMCP is a Python framework designed for building servers that expose functions, resources, and prompts to AI models using the Model Context Protocol. It simplifies the development process by automatically deriving tool metadata, input schemas, and documentation directly from Python function signatures and type hints. The framework provides a unified container for managing these components, allowing developers to build modular applications that integrate seamlessly with AI assistants. The project distinguishes itself through its support for interactive, server-defined user interface compone

Anthropic's terminal-native AI coding agent.

OpenSkills is an agent capability orchestrator and skill manager designed to sync, version, and distribute standardized skill definitions across autonomous agent environments. It functions as a system for installing domain-specific instruction sets and specialized knowledge into large language model agents, acting as a context injector to load task-oriented prompts and technical documentation into an agent's active operational window. The project distinguishes itself through a git-based distribution framework, allowing agent capabilities to be fetched and updated from remote version control s

This project is a container-native runtime designed for building, orchestrating, and executing autonomous AI agents. It provides a framework for managing multi-agent teams and complex workflows by packaging agent configurations as portable container images. By leveraging declarative configuration files, the system allows users to define agent personas, model routing, and tool access without requiring changes to application code. The platform distinguishes itself through its deep integration with container infrastructure, ensuring that agent tasks and external tools run within isolated environ

Agent skills for Claude Code and other agentskills.io-compatible agents. See https://developertoolkit.ai for more information about skills in general.

A2A is a standardized framework designed to enable interoperability, discovery, and orchestration among independent artificial intelligence agents. It provides a common communication protocol that allows heterogeneous agents to exchange data, verify identities, and collaborate across diverse programming languages and computing environments. By establishing a unified messaging standard, the project facilitates the creation of complex, multi-agent workflows where tasks are routed and managed between specialized services. The project distinguishes itself through a capability-based architecture t

This project is a framework for developing and orchestrating autonomous software agents within JVM-based applications. It provides a toolkit for embedding artificial intelligence directly into business logic, enabling agents to perform complex tasks through dynamic, goal-oriented planning rather than rigid state machines. By leveraging declarative annotations, the framework allows developers to define agent capabilities and integrate them into existing object-oriented domain models. The framework distinguishes itself through a vendor-neutral abstraction layer that allows for the seamless swap