Agent-S: Open Agentic Framework for Human-Like Computer Use
Agent-S is an open-source Python framework by Simular AI designed to enable AI agents to interact with computers in a human-like manner. The project has accumulated 11,388 GitHub stars with modest daily growth of 29 stars. It represents an entry in the growing space of computer-use agent frameworks targeting GUI and desktop automation tasks.
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Microsoft agent-framework: open-source library for building and orchestrating AI agents
Microsoft has published an open-source framework on GitHub for building, orchestrating, and deploying AI agents and multi-agent workflows, with support for both Python and .NET. The repository has accumulated 11,061 stars. It represents Microsoft's entry into the agent harness tooling space alongside existing frameworks like LangChain and AutoGen.
AgentScope: Open-Source Multi-Agent Framework for Transparent, Trustworthy Agents
AgentScope is an open-source Python framework for building and running AI agents with an emphasis on observability and trustworthiness. The repository has accumulated 25,755 total GitHub stars with 95 new stars today, indicating sustained community interest. It targets developers building multi-agent systems and positions itself around interpretability and reliability of agent behavior.
K-Dense-AI/scientific-agent-skills: Ready-to-Use Agent Skills Library for Research and Engineering
A Python repository providing a collection of pre-built agent skills targeting research, science, engineering, analysis, finance, and writing tasks. The project has accumulated 24,087 stars with a notable single-day gain of 762 stars, indicating significant community traction. No detailed technical documentation is available from the snippet, but the scope suggests a modular agent tooling library.
PentestAgent: AI Agent Framework for Black-Box Security Testing
PentestAgent is an open-source Python framework that applies AI agent techniques to penetration testing, bug bounty, and red-team workflows. The project has accumulated 2,497 GitHub stars with modest daily traction (+30). It represents a practical deployment of autonomous agent architectures in offensive security contexts.
AstrBot: multi-platform AI agent framework with IM integration trending on GitHub
AstrBot is an open-source Python framework for building AI agent assistants that integrates multiple instant messaging platforms, LLMs, and plugins. The project has accumulated over 34,000 GitHub stars with 110 new stars today, indicating active community interest. It positions itself as an alternative to OpenClaw-style agent orchestration tools.
Agent-Reach: open-source CLI tool giving AI agents multi-platform web access without API fees
Agent-Reach is an open-source Python CLI tool that enables AI agents to read and search across Twitter, Reddit, YouTube, GitHub, Bilibili, and XiaoHongShu without requiring API keys or fees. The project has accumulated over 21,000 GitHub stars with 127 added today, indicating significant community traction. It addresses a common friction point in agent development: accessing real-time web content across multiple platforms.
Anthropic Publishes 'Agent Skills' Public Repository
Anthropic has made a public GitHub repository called 'skills' available, described as a public repository for Agent Skills. The repository has accumulated 136,679 total stars with 514 added today, suggesting significant community interest. The project appears to be a Python-based resource related to agent capabilities, though specific technical details are sparse from the available description.
Andrew Ng introduces OpenCoworker, an open-source desktop AI agent harness
Andrew Ng and collaborators Rohit Prasad and Devika Verma have released OpenCoworker, a free open-source desktop agent built by extending the aisuite library to support agent harnesses. The tool allows users to connect frontier LLMs (OpenAI, Anthropic, Google) or local models via Ollama to desktop tasks including file access, messaging, and workflow automation, with privacy as a design priority. Ng frames this as a response to data-retention concerns with commercial desktop agents, citing Anthropic's Fable release as a recent example of policy opacity. The post also provides a concise overview of the current desktop agent landscape and the shift toward LLM-driven agentic loops.