🤯 LobeHub is your Chief Agent Operator, organizing your agents into 7×24 operations by hiring, scheduling, and reporting on your entire AI team.
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Updated
May 26, 2026 - TypeScript
🤯 LobeHub is your Chief Agent Operator, organizing your agents into 7×24 operations by hiring, scheduling, and reporting on your entire AI team.
Turn repeat work into running AI work-streams.
Agent harness to make your slop code well-engineered and beautiful.
AI content workspace for Chinese creators: desktop writing, research, prompt library, knowledge base, and multi-model workflows.
Autonomous Agents (LLMs) research papers. Updated Daily.
Awesome list for AI agent harness engineering: tools, patterns, evals, memory, MCP, permissions, observability, and orchestration.
Open-source agent harness platform. Native Rust, multi-provider, runs on your own machine. Sovereign by design.
Portable, vendor-agnostic agent harness for project-specific skills, workflows, and agent teams aligned with your codebase, conventions, and engineering standards.
The Agent Harness for AI-Human Collaboration, inspired by the AI-DLC (AI-Driven Development Lifecycle)
An awesome list of Agent Harness engineering resources, including GitHub projects, tools, benchmarks, and practical guides.
A social platform for humans and AI agents, built and maintained by its own AI team. Connect any agent via HTTP.
🤖 MateClaw — Your second brain with Multi-Agent Orchestration, MCP Protocol, Skills & Memory, Dream, and Multi-Channel Support. Built on Spring AI Alibaba.
Deterministic safety solutions for probabilistic AI agents
Self-hosted OpenClaw gateway + agent runtime in .NET (NativeAOT-friendly)
The production-ready agent harness framework for Python
Control-plane-grade agent harness for Claude, Codex & Hermes: policy gates, verification/evidence loops, memory, and auditable execution.
Open Python agent harness for production AI apps: tools, MCP, memory, workspace, telemetry, subagents, background tasks, and OmniServe APIs.
Agent Harness for Large Language Model Agents: A Survey. Survey on LLM agentharnessengineering with a taxonomy. 110+papers, 23 systems analyzed.
Portable CC-inspired skills for memory, verification, multi-agent coordination, context compression, and proactive coding-agent workflows.
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