Projects sharing features with AgentGym

AgentOps is an observability platform and developer toolkit for monitoring the execution, performance, and reliability of autonomous agents powered by large language models. It serves as a system for tracking AI agent behavior, debugging complex workflows, and benchmarking model performance. The platform is distinguished by its ability to visualize multi-agent workflows through execution path graphing and session replays. It provides specific tools for calculating financial spend across various language model providers and supports a self-hosted observability stack for users who require full

Agenta is a Prompt Ops lifecycle manager and prompt management platform that decouples prompt engineering from application code. It serves as a centralized system for developing, versioning, and deploying prompt templates and model configurations across different environments. The platform functions as an AI agent orchestrator with a visual interface for building agent workflows and connecting models to external tools. It further acts as an evaluation framework and observability tool, utilizing OpenTelemetry to capture execution traces, monitor latency, and track token costs. The system cove

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

Agents.md is a configuration framework designed to standardize how AI coding assistants interact with a repository. It provides a structured format for defining project context, behavioral guidelines, and operational instructions, ensuring that AI tools maintain consistency and adhere to project-specific standards throughout the development process. The system distinguishes itself through a hierarchical configuration approach, allowing developers to define settings that inherit and override instructions across different subdirectories. By utilizing markdown-based files, it enables the injecti

The AI Agent Workforce Platform. Run a hundred AI coding agents across your own machines — schedule, isolate, and steer them all from one console.

Knowledge work automation with AI agents

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

Agno is an agent operating system designed to manage the lifecycle, tool execution, and persistent state of autonomous agents across distributed infrastructure. It provides a unified runtime environment that wraps diverse agent frameworks into a consistent, interoperable protocol, allowing developers to build and deploy complex multi-agent systems that coordinate tasks and delegate sub-processes. The platform distinguishes itself through a robust governance and orchestration layer that includes human-in-the-loop approval gates, role-based access control, and a centralized API gateway. It feat

The fastest way to bring multi-agent workflows to production.

FinRobot is an AI-powered financial analysis framework that coordinates multiple specialized agents to automate equity research, financial analysis, and investment risk assessment. At its core, it functions as a multi-agent orchestration system where a director and task manager allocate financial tasks to the most suitable large language models based on performance metrics and task requirements. The framework distinguishes itself through its ability to execute complex multi-step financial workflows by routing tasks through perception, reasoning, and action modules. It generates professional e

This is an LLM agent framework and symbolic learning system designed for building self-evolving autonomous agents. It functions as a computational graph orchestrator that organizes agent interactions and tool sequences as a trainable graph of nodes. The framework focuses on data-centric agent optimization, allowing agent pipelines and prompts to be upgraded through data-driven training rather than manual engineering. It utilizes a symbolic learning process that applies language-based loss and textual reflections to refine the operational logic and symbolic components of an agent. The system

Agent techniques to augment your LLM and push it beyong its limits

OpenHands is an autonomous AI software engineer and coding assistant designed to execute software engineering tasks by interacting directly with codebases and development environments. It functions as a platform for running AI agents that can write code and manage files to automate complex development workflows. The system distinguishes itself through a container-based execution environment that isolates agent actions within a sandboxed Linux environment. It employs an autonomous agent loop of observation, planning, and action, supported by a standardized communication protocol that allows it

This project is a curated directory and educational resource focused on the development and implementation of autonomous AI agents. It serves as a comprehensive knowledge repository that organizes practical use cases and open-source projects into a structured taxonomy, helping developers explore how intelligent systems can be applied across diverse industry sectors. The repository distinguishes itself through a community-driven approach that maps diverse agentic workflows to a common schema, facilitating cross-framework evaluation. By providing modular educational scaffolding, it guides users

Zero-configuration MCP server that unifies multiple AI coding assistants (Codex, Claude Code, Cursor, Gemini) through intelligent auto-discovery and standardized interface

GPT Researcher is an autonomous agent framework designed to automate the process of gathering, synthesizing, and documenting information from diverse web and local sources. It functions as a research-oriented execution environment that orchestrates specialized agents to perform complex, multi-branch research tasks, transforming raw data into structured, factual, and cited reports. The project distinguishes itself through a graph-based orchestration layer that manages state transitions and information flow between specialized agents. It employs recursive tree-search execution to explore comple

Minimal typescript agent framework that keeps it simple and gives you control - no BS

Painter & SegGPT Series: Vision Foundation Models from BAAI

ClaraVerse is a self-hosted orchestration platform for deploying and managing local language models, autonomous agents, and automated workflows on private infrastructure. It functions as a containerized backend manager that orchestrates services, databases, and model providers within local containers to maintain data sovereignty. The platform features a visual workflow builder with a drag-and-drop interface for designing complex parallel task sequences. It utilizes a multi-model abstraction layer to normalize interactions across diverse local and remote AI endpoints and includes a retrieval a