wshobson/agents: Multi-harness agentic plugin marketplace for major AI coding tools
A GitHub repository called 'agents' by wshobson provides a multi-harness agentic plugin marketplace targeting Claude Code, Codex CLI, Cursor, OpenCode, GitHub Copilot, and Gemini CLI. The project has accumulated 37,134 stars with modest daily momentum (+43 today). It represents a cross-platform approach to agent tooling that spans multiple competing AI coding environments.
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claude-skills: 313+ Skill/Plugin Collection for Claude Code and Multi-Agent Coding Tools
A GitHub repository providing 313+ reusable skills, agent plugins, and workflow templates targeting Claude Code, Codex, Gemini CLI, Cursor, and eight other coding agents. Coverage spans engineering, marketing, compliance, C-level advisory, finance, and productivity domains. The project has accumulated 15,476 stars with 157 added today, indicating strong community traction. It represents a growing ecosystem of structured prompt/skill libraries designed to extend AI coding agents beyond pure code generation.
Awesome Harness Engineering: Curated List for AI Agent Infrastructure
A GitHub repository aggregating resources on AI agent harness engineering, covering tools, patterns, evaluations, memory systems, MCP (Model Context Protocol), permissions, observability, and orchestration. The list has accumulated 1,318 stars with 39 added today, indicating moderate community traction. It serves as a reference index rather than original research or tooling.
shareAI-lab/learn-claude-code: Minimal Claude Code-style Agent Harness in Python
A GitHub repository implementing a minimal 'nano' version of a Claude Code-style agent harness built from scratch in Python, using Bash as the primary tool interface. The project has accumulated 62,802 stars with 262 added today, indicating significant community interest. It serves as an educational resource for understanding how agentic coding assistants like Claude Code are structured at a low level.
anthropics/claude-code: Agentic Terminal Coding Tool Trending on GitHub
Claude Code is an agentic coding tool developed by Anthropic that operates in the terminal, enabling natural language interaction with codebases for tasks like code execution, explanation, and git workflow management. The repository has accumulated 127,316 stars with 323 added today, indicating sustained community interest. It represents Anthropic's direct entry into the developer tooling space with an agent-oriented product.
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.
agent-skills: Secure Validated Skill Registry for AI Coding Agents
A TypeScript-based open-source skill registry designed to extend AI coding agents including Claude Code, Cursor, GitHub Copilot, and Antigravity with validated, reusable capabilities. The project provides a structured way to add skills to multiple coding agent platforms with a focus on security and validation. It is gaining notable traction with 3,767 total stars and 225 stars added today.
agent-teams-ai: multi-agent orchestration framework with kanban-style oversight
A TypeScript open-source project on GitHub implements a multi-agent system where autonomous agents handle tasks, communicate with each other, and review each other's work, while the user supervises via a kanban board. The framework supports 200+ models across 75+ LLM providers including Codex, Claude, and OpenCode. It has accumulated 1,189 stars with 56 added today, suggesting growing community interest.
Code as Agent Harness: A Survey of Code as Operational Substrate for Agentic AI Systems
This survey paper introduces the concept of 'code as agent harness,' framing code not merely as output but as the operational infrastructure for LLM-based agents—covering reasoning, action, environment modeling, and execution-based verification. The authors organize the analysis across three layers: harness interface, harness mechanisms (planning, memory, tool use, feedback control), and scaling to multi-agent systems. Applications span coding assistants, GUI/OS automation, embodied agents, scientific discovery, and enterprise workflows. Open challenges include evaluation beyond task success, verification under incomplete feedback, and human oversight for safety-critical actions.